ВЕ ЕТ У БАЊ О УЦ •УНИ ИТ ЈЛ РЗ И• 1975 UNIVERSITY OF BANJA LUKA FACULTY OF MECHANICAL ENGINEERING Gordana Globočki Lakić Davorin Kramar Janez Kopač METAL CUTTING THEORY AND APPLICATIONS Cutting forces F t Fc Ff Fp Surface quality Chip shape Ra t UNIVERSITY OF LJUBLJANA FACULTY OF MECHANICAL ENGINEERING 19 71 UNIVERSITY OF BANJA LUKA FACULTY OF MECHANICAL ENGINEERING UNIVERSITY OF LJUBLJANA FACULTY OF MECHANICAL ENGINEERING Gordana Globočki Lakić Davorin Kramar Janez Kopač METAL CUTTING THEORY AND APPLICATIONS Banja Luka and Ljubljana, 2014 METAL CUTTING – THEORY AND APPLICATIONOS Authors: PhD Gordana Globočki Lakić, Associate Professor, University of Banja Luka, Faculty of Mechanical Engineering PhD Davorin Kramar, Assistant Professor, University of Ljubljana, Faculty of Mechanical Engineering PhD Janez Kopač, Full Professor, University of Ljubljana, Faculty of Mechanical Engineering Reviewers: PhD Franci Čuš, Full Professor, University of Maribor, Faculty of Mechanical Engineering PhD Pavel Kovač, Full Professor, University of Novi Sad, Faculty of Technical Sciences Publisher: University of Banja Luka, Faculty of Mechanical Engineering 78000 Banja Luka, Vojvode Stepe Stepanovića, 71 University of Ljubljana, Faculty of Mechanical Engineering 1000 Ljubljana, Aškerčeva 6 For publisher: PhD Darko Knežević, Associate Professor, Dean PhD Branko Širok , Full Professor, Dean Lector: Božana Bugarski DTP Milivoj Stipanović Print: Vilux, Banja Luka Number of copies: 120 Banja Luka and Ljubljana, 2014 ISBN: ISBN: 978-961-6536-85-1 Copyright © Faculty of Mechanical Engineering, Banja Luka, 2014 Copyright © Faculty of Mechanical Engineering, Ljubljana, 2014 By the decision No...... of......... 2014, the Teaching and Research Council of the Faculty of Mechanical Engineering, University of Banja Luka, approved the publishing of this book as a university textbook PREFACE Dear readers, More than 5% of the world GDP is related to machining processes as part of manufacturing technologies. This proves that knowledge about machining processes is strategically important and has to be further improved. With this in mind, the idea is to have a book that gives us an opportunity to open it at any time and provide us with theoretical or/and technological information about machining processes. Therefore, this book covers the most important processes, such as turning, milling, drilling, etc. Besides conventional, this book also describes cutting-edge technologies. The basic cutting theory is similar or practically the same for all the processes, while for further development, we must be familiar with the mechanisms occurring in the cutting zone and improve this understanding. In the cutting zone takes place the transformation of material, where material is separated from the workpiece, producing chips, and what is most valuable – the final shaped workpiece (product). However, technicians and engineers must also become familiar, besides conventional, with the latest sound developments in this field, and make a step further in the real production environment. Therefore, we still have to improve our knowledge and fully comprehend cutting processes and focus on mechanisms and reasons for successful or less successful cutting. This can be achieved through a careful and precise analysis of the cutting process behaviour. Machining problems such as bad surface roughness, unpredictable tool-wear and vibration occurrence (chatter), are directly related to the machining parameters. Usually, when these problems occur, they have to be minimised. This will however lead to lower productivity, while trends require the opposite. The solution lies in careful analyses and the development of predictive performance models that can predict the process behaviour as well as the mentioned problems. The fact is that in order to prevent bad machining scenarios, one must predict them. These are the reasons why further analysis, research, and studies of the cutting theory, processes and technologies, are inevitable. Ideally, improved knowledge would offer the possibility of finding the best/optimal solution for any specific/unique problem. Nevertheless, this cannot be done without the strong support of a theoretical background. What is the difference between a technician and an engineer? The technician is an operator responsible for the realization of the machining production (by using modern machine tools, of course). On the other side, the engineer is a person who has to take care of the preparation of technology and definition of optimal cutting/machining parameters. And the fact is that there can be no single optimal solution in machining. This depends on specific objectives that we have, and they are case-based. In general, these objectives pertain to three main areas: cost optimization, time optimization and quality optimization. All the objectives are in fact opposite in nature. It is therefore important for process planning to consider all the conditions and choose the right viewpoint for optimization. Moreover, recent trends are directed towards a sustainable production, sustainable machining, etc. In order to reach the goal of this idea, the book is encouraging engineers to act in a manner where they can significantly contribute to saving energy, reducing consumption of cooling/lubrication fluids, minimizing waste, etc. Banja Luka and Ljubljana, November, 2014 iii Acknowledgements This book is the result of many years of successful cooperation between the Laboratory for cutting technology and machining systems of the Faculty of Mechanical Engineering, University of Banja Luka, and the Laboratory for cutting of the Faculty of Mechanical Engineering, University of Ljubljana, and personal cooperation between the authors. We would like to use this opportunity to thank the reviewers of the book, professor Franci Čuš, PhD, and professor Pavel Kovač, PhD, for their helpful suggestions and advice that have certainly contributed to the best possible content of the book. We also thank Branislav Sredanovic, MSc, mechanical engineer and senior assistant at the Faculty of Mechanical Engineering in Banja Luka, for assisting with the technical preparation of this book. Also, thanks go to the sponsors who financially supported the publication of this book. Last but not least, many thanks to our families for their support and understanding. Banja Luka and Ljubljana, November 2014 Gordana Globočki Lakić Davorin Kramar Janez Kopač v Symbols and Abbreviations Capital Letters A Ach Aα A'α Aγ AΦ BBD BUE C CAD CAM CAPP CBN CCD CI CIM CLF CNC CMM Co D DFM E EDM F Fa Fc FD Ff FΦ FΦN FN Fp FT G HB HRC HSC HSS HV KB KM KT MQL Mo mm2 mm2 mm2 mm2 mm2 mm2 mm N N N N N N N N N N mm mm mm Nm Cross section Chip cross section Major flank face Minor flank face Rake face Shear plane cross section Box Behnken design Built up edge Taylor equation constant Computer Aided Design Computer Aided Manufacturing Computer Aided Process Planning Cubic Boron Nitride Central Composite Design Statistical confidence interval Computer Aided Manufacturing Cooling and Lubrication Fluid Computer Numerical Control Coordinate Measuring Machine Piezo Crystal Capacitivity Tool diameter Design for Manufacturing Young’s modulus Electric Discharge Machining Resultant cutting force Active force Main cutting force Thrust force Feed force Shear force Normal force on shear plane Normal force on rake face Passive force Tangential force on rake face Shear modulus Brinell hardness Rockwell hardness High Speed Cutting High Speed Steel Vickers hardness Crater width Crater centre distance Crater depth Minimum Quantity Lubrication Torque vii METAL CUTTING – Theory and Applications NC OVAT P Pf Pn Po Pr Ps PCD Qe Q R Ra REM RSm RSM Rm Rp0,2 Rmax (Rt) Rz S S' T T Tch Tm Tr U V VB VBmax VC Vch VCmax VNmax VS W kW V J μm mm N/mm2 N/mm2 μm μm min °C °C °C °C V mm3 mm mm mm mm3 mm mm mm J Numerical Control One-Variable-At-a-Time Power Assumed working plane Tool cutting edge normal plane Tool orthogonal plane Tool reference plane Cutting edge plane Polycrystalline Diamond Electric charge Heat generated in cutting zone Electrical resistance Average roughness (Arithmetic mean roughness) Scanning electron microscope (SEM) Average ridge width of roughness profile Response Surface Methodologies Tensile strength 0.2%–yield strength Profile total height Ten-point mean roughness (Average surface roughness) Major cutting edge Minor cutting edge Tool life Temperature Chip temperature Mean cutting temperature Room temperature Voltage Volume of removed layer of material before cutting Width of flank wear Maximum width of flank wear Average width of wear on chamfered or rounded cutting edge Volume of cut chips Maximum width of wear on chamfered or rounded cutting edge Notch length on main flank face at maximum depth of cut or rounded cutting edge Width of average wear on minor cutting edge Mechanical work Small Letters ae ap apmax b bch c cch dch dW/dt viii mm mm mm mm mm mm m/min Width of cut Depth of cut Maximum depth of cut Undeformed chip width Chip width Thermal conductivity Specific heat of workpiece material (chip) Curve diameter Growth of wear Symbols and Abbreviations emf f fa fmax fmin fr fz h hch hcu,max hm hmin kc1.1 kf1.1 ki kp1.1 kq l lch ln lm lf m mch mc n pch rε r rß sd t tg te vc vch vsh vf vfax ve z q mV mm mm mm mm mm mm mm mm mm mm mm N/mm2 N/mm2 N/mm2 N/mm2 m mm m m m kg kg rev/min mm mm mm min min min m/min m/min m/min m/min m/min m/min % Electromotive force Feed Axial feed Maximum feed Minimum feed Radial feed Feed per tooth/cutting edge Undeformed chip thickness Chip thickness Maximum chip thickness Geometric mean chip thickness Minimum chip thickness Specific cutting force, b = h = 1 mm Specific feed force, b = h = 1 mm Specific resultant force Specific passive force, b = h = 1 mm Crystal constant Length of material (length of the tool path) Chip length Tool-overhang Machining length Feed path Mass of removed layer of material before cutting Chip mass Exponent of specific cutting force Spindle speed Pitch of curve Corner radius (tool nose radius) Correlation coefficient Rounded cutting edge radius Coating thickness Cutting time Basic time Time per unit Cutting velocity Chip velocity Velocity in shear plane direction Feed velocity Axial feed velocity Effective cutting speed Number of teeth Percentage of heat dissipated by the chip Greek Letters α αL αk β ° ° ° ° Tool clearance angle Coefficient of linear expansion Kinematic values of tool clearance angle Wedge angle ix METAL CUTTING – Theory and Applications γ γk ε εk εr θ κr λs λch ψ μ ϕ ϕf φ φc ρ ρm σ τ ω x ° ° ° °C ° ° ° ° ° ° ° ° kg/m3 N/mm2 N/mm2 rad/s Tool rake angle Kinematic values of tool rake angle Strain Critical strain Tool included angle Temperature Major tool cutting edge angle Tool cutting edge inclination angle Chip compression ratio Angle of texture Friction coefficient Shear angle Slide angle Feed motion angle Engagement feed angle Friction angle Density (specific mass) Normal stress Tangential stress (shear stress) Angular speed Contents CHAPTER I INTRODUCTION ..............................................................................................................................1 1.1 Importance of processing technology with chip removal in modern manufacturing ..............1 1.2 General information on machining technology .......................................................................6 1.3 Types of machining with chip removal ...................................................................................6 1.4 Model of the cutting process ...................................................................................................8 1.5 Machinability of materials ......................................................................................................9 Literature .....................................................................................................................................11 CHAPTER II MEASUREMENT AND CONTROL IN MACHINING PROCESSES ..........................................13 2.1 The importance of measurement and quality of products .....................................................13 2.2 Process of measurement ........................................................................................................16 2.3 Basic principles of measurement ..........................................................................................16 2.4 Accuracy of machining – dimensions, tolerances and related attributes ..............................17 2.5 Length measurement .............................................................................................................22 2.5.1 Single purpose measuring tools ...................................................................................22 2.5.2 Multipurpose indicating measuring instruments ..........................................................26 2.6 Angles and cones measurement ............................................................................................29 2.7 Laboratory exercise – cutting wedge angles measurement ...................................................31 2.7.1 Geometry of the cutting tool ........................................................................................32 2.7.2 Description of the experimental exercise .....................................................................34 Literature .....................................................................................................................................37 CHAPTER III CHIP SHAPES AND TYPES ..........................................................................................................39 3.1 Chip shaping and forming process ........................................................................................39 3.2 Rating of chip forms; favourable and unfavourable chip forms ...........................................45 3.3 Experimental chip shape determination ................................................................................47 3.4 Main conclusions regarding the creation of favourable chip forms ......................................50 3.5 Laboratory exercise – Determination of shape and type of the chips ...................................50 Literature .....................................................................................................................................55 CHAPTER IV CHIP COMPRESSION RATIO .......................................................................................................57 4.1 Theoretical considerations ....................................................................................................57 4.2 Influence of the cutting regime on the chip compression ratio .............................................59 4.3 Experimental determination of the chip compression ratio ..................................................60 4.4 Laboratory exercise – Determination of the chip compression ratio ....................................61 Literature .....................................................................................................................................67 CHAPTER V CUTTING FORCES ........................................................................................................................69 5.1 Theoretical considerations ....................................................................................................69 5.2. Determination of specific cutting forces ..............................................................................75 5.3 Determination of the resultant cutting force components .....................................................77 5.3.1 Components of resultant cutting force in turning ........................................................78 xi METAL CUTTING – Theory and Applications 5.3.2 Components of resultant cutting force in drilling ........................................................78 5.3.3 Components of resultant cutting force in milling ........................................................80 5.4 Statistical evaluation of experimental results ........................................................................82 5.5 The cutting force components measuring system .................................................................83 5.6 Laboratory exercise – Measurements of cutting force components ......................................88 5.6.1 Software for cutting force measurement and analysis .................................................92 5.6.2 Measurements of feed force and torque in drilling ......................................................95 5.7 Final conclusions ...................................................................................................................98 Literature ...................................................................................................................................100 CHAPTER VI THERMAL PHENOMENA IN MACHINING PROCESSES ......................................................101 6.1 Theoretical considerations ..................................................................................................101 6.2 Temperature field of the cutting zone .................................................................................103 6.3 Methods for determining temperatures in cutting ...............................................................105 6.3.1 Caloric heat measurements ........................................................................................106 6.3.2 Measurement with thermo-colours ............................................................................107 6.3.3 Thermoelectric measurement methods ......................................................................108 6.3.4 Radiation measurement ..............................................................................................111 6.4 Laboratory exercise .............................................................................................................112 6.4.1 Calorimetric method for mean chip temperature measurement .................................112 6.4.2 Cutting temperature measurements with thermocouple .............................................116 Literature ...................................................................................................................................119 CHAPTER VII TOOL WEAR ................................................................................................................................121 7.1 Theoretical considerations ..................................................................................................121 7.2 Determination of tool wear .................................................................................................128 7.3 Tool life line determination .................................................................................................129 7.4 Final conclusions .................................................................................................................133 7.5 Experimental measurement of tool wear .............................................................................135 7.6 Laboratory exercises ...........................................................................................................138 Literature ...................................................................................................................................144 CHAPTER VIII SURFACE ROUGHNESS .............................................................................................................145 8.1 Theoretical considerations ..................................................................................................145 8.2 Basic definitions of surface roughness ................................................................................147 8.3 Surface roughness in machining .........................................................................................149 8.4 Surface roughness measurements .......................................................................................151 8.5 Laboratory exercises – Surface roughness measurements ..................................................153 Literature ...................................................................................................................................159 CHAPTER IX MANUFACTURABILITY AND MACHINABILITY .................................................................161 9.1 Theoretical considerations ..................................................................................................161 9.2 Manufacturability ................................................................................................................164 9.3 Machinability ......................................................................................................................171 9.4 Case studies ..........................................................................................................................178 Literature ...................................................................................................................................191 xii Contents CHAPTER X PROCESS MODELLING USING DESIGN OF EXPERIMENTS ..............................................193 10.1 Introduction .......................................................................................................................193 10.2 Process modelling .............................................................................................................195 10.3 Methodology for Design of Experiments ..........................................................................199 10.3.1 Selecting an appropriate design for the experiment ................................................203 10.3.2 Analytical tools of DOE ..........................................................................................206 10.4 Laboratory exercise ...........................................................................................................208 Literature ...................................................................................................................................215 xiii CHAPTER I INTRODUCTION Contents 1.1 1.2 1.3 1.4 1.5 Importance of processing technology with chip removal in modern manufacturing General information on machining technology Types of machining with chip removal Model of the cutting process Machinability of materials 1.1 Importance of processing technology with chip removal in modern manufacturing Manufacturing is the initiator of development in any industrialized country. The main rule for any country is: the higher the level of manufacturing, the higher the standard of living. Modern manufacturing includes product design and documentation, material selection, process planning, production, quality assurance, management and product marketing. These activities should be integrated in order to produce viable and competitive products. Today, the manufacturing processes are extremely complex owing to the latest technological advances. The status of modern manufacturing processes is extremely complex and technologically sophisticated. The machining of materials, especially the cutting technology, is of great importance in the industry of each country today. An explanation for this lies in the fact that the requirements for the accuracy and quality of processing are constantly increasing. The accuracy of processing is the most important output parameter of processing and is directly related to the costs of processing. We should not aspire for perfection, but the accuracy of machining should be minimal in order to achieve the functionality of the workpiece. In many companies, the strategy to increase productivity often includes high capital investment in the plant, and to amortize such costs i.e. pay-back. This strategy can create ‘bottlenecks’ and disrupt the harmonious flow of production at later stages of manufacturing. Another approach might be to maximize the number of components per hour, or alternatively, reduce costs at the expense of shorter tool life, which would increase the non-productive idle time for the production set-up. Solutions for these problems related to the tools, in any company, should be resolved systematically through three related areas: rationalization, consolidation and optimization [1]. For the rationalization of the use of tools within the current production in a company, it is essential to conduct a thorough appraisal of all the tools and associated equipment with the company. Tool rationalization (Figure 1.1) consists of looking at the results of the previous tooling survey and significantly reducing the number of tooling suppliers for particular types of tools and inserts. The rationalization of cutting inserts can have a very good effect on reducing the tooling and work holding inventory [1]. By grouping inserts by their respective sizes, shapes, nose radius, etc., it is possible to eliminate many of the lessutilized inserts. In this case one should create conditions for tool costs reduction. By 1 METAL CUTTING – Theory and Applications consolidating the tooling, one allows for productivity to be boosted by the optimization of the cutting insert grades [2]. The optimization of the cutting process is very complex because it involves three key factors: tool life, speed, feed rate, being in certain relationships, Figure 1.2 [1]. The rationalisation includes: shape geometry size grade coatings application data VERY IMPORTANT: Reduction of inventory is possible from 60 to 90% Figure 1.1 Effects of the rationalisation of cutting inserts [1, 3] If one parameter changes, it will affect the others, and therefore a compromise has to be reached to obtain optimum performance from a cutting tool. For example, if the cutting speed is increased rather than the feed, a point is reached where any increase in the cutting speed will result in a decrease in productivity. In other words, if cutting is too fast, it will result in spending more time on tools replacement than on parts production. On the other hand, if cutting is too slow, the tool will last much longer, however this will affect the final number of produced machined parts. What is the ‘right’ cutting speed? Generally, an answer to this lies in each specific production, i.e. each individual manufacturing plant (or each factory) will have to determine its own particular manufacturing objectives – where considering both cutting speeds and tool life. One must keep in mind that the key requirement in the production is not perfection, but the overall output increase. 2 INTRODUCTION Complex relationship between: speed, feed and tool life. Other factors are constant: depth of cut workpiece material insert grade insert geometry nose radius coolant lead angle entering angle Figure 1.2 Complex relationship between influential factors in optimization of the cutting process Not only cutting parameters but also tool geometry affects the tool life, especially the entering and lead angle, see Figures 1.3 and 1.4. Figure 1.3 Plan approach angle for a typical insert [1] The lead angle and the entering angle have a very important role in the definition of cutting forces. Influences of both angles are present on Figure 1.4. The impact of the entering angle on the cutting speed is important, because at the same chips cross-section different active lengths of the cutting occur. For larger values of the major cutting edge angle, the length of the cutting edge is less active. Then a higher specific heat and mechanical load on the tool appear. For different values of the entering angle and the lead angle, different values of the axial and radial cutting forces appear, Figure 1.4. 3 METAL CUTTING – Theory and Applications Figure 1.4 Insert approach angles geometry for turning operations [1] For example, the ideal cutting tool should have superior performance in five distinct areas (Figure 1.5): Hot hardness - it is necessary to keep a sharp and consistent cutting edge at the elevated temperatures that are present in the cutting process. Resistance to thermal shock - this is necessary in the cutting conditions with periodical cycles of heating and cooling (for example, in milling operation). If the resistance to thermal shock is too low, than the wear is rapidly increasing. Resistance to oxidation - the oxidation resistance of the cutting tool is necessary in case of machining at high temperatures, Toughness - it is very important for the cutting conditions where unwanted vibrations are induced, and Lack of affinity - any degree of affinity between the tool and the workpiece will lead to the formation of a built up edge (BUE). Figure 1.5 Main factors affecting cutting tool life [1] 4 INTRODUCTION Cutting tool manufacturers will produce an "ideal cutting tool" by carefully balancing these five factors. Tool manufacturers have produced a wide range of workpiece-cutting ability ranging from fewer types of inserts to a diverse range of speeds and feeds. Metal cutting process is the most complex part of the technological process of production, machining and assembling parts of different configurations. In modern production conditions, there is a constant increasing demand for quality and assortment of products. These requirements are possible to achieve in the conditions of flexible automation, Figure 1.6. Figure 1.6 Area of application of different systems of automated manufacturing [4] Increasing the effectiveness of the automation process is connected with the application of new workpiece materials, tools and a cutting regime in specific production conditions. The solution is the introduction of a system of monitoring (diagnostics) of both the cutting process and the state of the cutting tool. The main task of the theory and practice of metal cutting is to increase the productivity of the machining system. It is achieved by increasing the cutting regime and reducing the auxiliary and preparatory processing time. The increasing of the cutting regime is achieved by increasing the total cross-section of the chip and the cutting regime (cutting speed, feed and speed of auxiliary movements). The shortening of the auxiliary and preparatory time is achieved by using flexible manufacturing systems and computer aided design, technology and management of process (CAD, CAM, CAPP, CIM). Figure 1.7 Influence of the cutting speed and feed on the cost of processing [5] 5 METAL CUTTING – Theory and Applications 1.2 General information on machining technology In production, using different manufacturing processes, the base material - preform is transformed into the final product. The geometric shape of a semi-finished or finished part can be achieved in two ways: with removal of excess material (with chip removal) - machining of metal cutting and unconventional processing, and without removal of excess material (without chip removal) - processing by casting, plastic deformation and by joining. The main task of the metal cutting technology is how to make a particular part (product) to achieve its geometrical and functional specifications in the fastest and most cost-effective way with the application of knowledge from this technology. In the metal cutting technology, the process starts from the base material (preform) which can be raw material of different shapes and dimensions, or can be semifinished product obtained by casting, forging, welding, Figure 1.8. Figure 1.8 Illustration of metal cutting process [5] By applying technological knowledge and available equipment in a factory, one can define the machining operations, which will allow to obtain the finished machine parts predetermined geometry, accuracy and quality. Both of the above mentioned components (available technological knowledge and available equipment) have a great impact on the technology of metal cutting. In the modern industrial world, however, the technological knowledge ("know-how") has more importance. The level of the technology planning in one facility depends on the technological knowledge of engineers as well as on the available contemporary equipment. This rule still remains: "A good technologist can always produce better quality parts working on older equipment than a bad technologist on modern equipment." [6]. 1.3 Types of machining with chip removal Machining with chip removal includes methods in which the design of workpieces is achieved by removing excess of materials. Depending on the mechanisms of the excess material removal, there are two types of processes, Figure 1.9: 6 INTRODUCTION 1. A machining processes that use a tool to create chips and remove metal from a workpiece, and 2. Unconventional machining processes. In the machining processes, the excess of material is removed mechanically with tools whose hardness is much higher than the hardness of the material of the workpiece. These processes include: turning, milling, drilling, planning, broaching, sawing, grinding, threading cutting, gear cutting. The methods of thread cutting and gear cutting are specific by the kinematics of cutting and by tools. The methods of machining differ mutually by the geometry of the tool and kinematics of the machining, while the mechanism of removing excess of material is the same for all processes. The machining processes are much more developed compared to the non-conventional processes, as expected, as they have been developed for many years. Figure 1.9 Classification of metal cutting processes [5] In unconventional machining processes, the modification of the shape and dimensions, as well as the material structure of parts are realized by removing excess of material by means of different physical-chemical mechanisms which are entirely different. In these processes different forms of energy are applied: electrical, chemical, light, electro-thermal, magnetic, etc. The unconventional machining processes include: 1. Ultrasonic machining, 2. Water jet machining, 3. Electrical discharge machining (EDM), 4. Electron beam machining, 5. Laser machining, 6. Plasma arc machining, 7. Electrochemical machining, 8. Chemical machining, 9. Ion beam machining and 10. Combined machining processes. The unconventional machining processes are a recent phenomenon. According to estimates by many authors in this field, the metal cutting processes represent approximately 70-80% of the processing technology with chip removal. The rest of 20-30% is related to the unconventional machining processes. Although this percentage is much lower, these processes are irreplaceable in some branches of industry: nuclear and rocket technology, 7 METAL CUTTING – Theory and Applications airline industry, the production of spacecraft, the production of electronic micro components, the production of special tools for different machining technology, etc. The expansion of the field of application of these machining processes has been more and more present today. Based on the foregoing, it can be concluded that the technology of cutting, as well as nonconventional technologies, have a very important place in the modern production today. This importance will become even greater in the future because this is the only production method that can comply with the increasing demands in terms of the accuracy and quality of processing. 1.4 Model of the cutting process Metal cutting is an interdisciplinary and multidisciplinary science that uses the knowledge of mechanics of solid bodies, applied mechanics, materials science, thermodynamics, tribology, physics and chemistry, Figure 1.10. Figure 1.10 Model of metal cutting [5] Machining process is a very complex physicochemical process. The sizes in the cutting process are as follows, Figure 1.11: input (primary, controls and disturbance), functional, and output. The basic sizes are: workpiece material, method of machining, required accuracy and surface roughness. The control sizes are: tool materials, construction and tool geometry, type of machine tool, regime of machining, CLF. The disturbance sizes can be systemic and random. The systemic sizes are related to the principle of change of speed and depth of cut, tool geometry, etc. Mainly, they are the consequence of cutting kinematics. The random sizes are stochastic (uncontrolled) and represent the result of changes in the structure of the workpiece or tool material, and the static and dynamic behavior of the machining system, etc. The functional sizes are the quantitative indicators of physicochemical mechanisms of the process. They describe the processes in the cutting zone. The functional state of the technological cutting system can be evaluated by identifying and measuring cutting forces, tool wear, acoustic emission, vibration signals, etc. The output sizes of the cutting process are: surface quality, productivity and efficiency, reliability of the process and characteristics of the surface layer. 8 INTRODUCTION Figure 1.11 Structural model of the cutting process [5] 1.5 Machinability of materials The concept of the machinability of materials is generally understood as the ability of the materials to be processed. The concept of the machinability, in its broadest sense, refers to all the mechanical machining and, therefore, covers the processes of cutting. In many examples, the metal cutting process is referred to machinability. Such a definition seems perfectly clear, but it is difficult to specify a particular measure. Nevertheless, machinability is a very important property of materials that should be considered by designers if one wants to ensure that products meet quality requirements and are as costeffective as possible. In a narrow sense, one material has a better machinability if: it can be processed, where the tool life is longer, where smaller cutting forces occur, where better surface quality occurs, where favorable chip shape occurs, where better precision of processing occurs. Each of these positions represents an important factor in determining the machinability of a specific material. A number of attempts have been made to get a numeric value or to set parameters that could be established when it comes to the machinability of individual materials. But it has not been possible yet to determine the legality of the interactions of the tool material, the workpiece and the tool wear. The machinability of materials, for most technologists, is a combination of different characteristics. If we wish to express it numerically, we can use the following criteria, Figure 1.12: tool wear, tool life, shape of chip, surface quality and accuracy of machining, size of the cutting forces. In addition to these four basic criteria, some auxiliary ones should be added, such аs: temperature of the chip, temperature of the tool, energy consumption for cutting, total cost of machining, etc. 9 METAL CUTTING – Theory and Applications Figure 1.12 Basic criteria and objectives to determine the machinability [7] When determining the machinability of materials, problems occur because not all the criteria for each process are equally important. Therefore, the most important criterion for the rough turning is tool life, for the fine turning is the surface quality, while for processing on machines, it is the shape of the chip. Therefore, one can only talk about characteristics according to individual criteria, and moreover, they can only be compared. When specifying and standardizing the values of the cutting parameters for a particular cutting process, we should start from the meaning of machining (Figure 1.13) [8, 9]. The aim of the processing is to make parts that must meet the defined criteria. At the same time, it is important to achieve the accuracy of shape and dimensions as well as the surface quality. Also, one must take into account the cost of the production, the processing time and the utilization of production resources that are used in the production. In sharp regimes of the processing, the quantity of cut material per time unit is high, and the result is a shorter technological processing time. Such regimes of the processing cause rapid tool wear and short tool life, and thus result in more frequent tool change. This increases significantly the cost of tools in total costs per product. The values of the cutting parameters should be selected so that all the costs (costs of tools, processing, equipment and personal income of workers) are in a reasonable relation. This can only be achieved if we know the impact of processing conditions on the tool wear and the tool life. 10 INTRODUCTION Figure 1.13 Influential factors in determining the value of cutting parameters [3, 7] The selection of the cutting parameters is necessary in order to determine the tool life that can be achieved in specific processing conditions in adhering to the criteria of the tool wear. Using these data, one can determine the cutting parameters to be used when calculating the optimal parameters of cutting in the production on conventional machine tools, as well as on modern machines that support the NC technology. Literature: [1] Smith G.T.: Cutting Tool Technology, Industrial Handbook, Springer, Southampton Solent University, Southampton, U. K., ISBN 978-1-84800-204-3, Springer-Verlag London, 2008 [2] Çalşkan, H., Kurbanoğlu, C., Panjan, P., Kramar, D.: Investigation of the performance of carbide cutting tools with hard coatings in hard milling based on the response surface methodology. The international journal of advanced manufacturing technology, 2013, vol. 66, no. 5-8, 883-893 [3] Sandvik Coromant: Metal Cutting Technology, Technical Guide, 2010 [4] Globočki-Lakić G.: Metal cutting process – theory, modeling and simulation, Faculty of Mechanical Engineering, Banja Luka, 2010 (in Serbian) [5] Lazić M.: Metal cutting process, Faculty of Mechanical Engineering, Kragujevac, 2002 (in Serbian) [6] Milikić D., Gostimirović M., Sekulić M.: Basics of machining technology, Faculty of Technical Science, Novi Sad, 2008 (in Serbian) [7] Cedilnik M., Rotar V., Kopač J.: Cutting 1, supplementary material for lectures and exercises, script, Ljubljana, 2006 (in Slovenian) [8] Sredanović, B., Globočki-Lakić, G., Cica, Dj., Kramar, D.: Influence of different cooling and lubrication techniques on material machinability in machining, Journal of Mechanical Engineering, 2013, vol. 59, No. 12, 748-754 [9] Kramar, D., Sredanović, B., Globočki - Lakić, G., Kopač, J.: Contribution to Material Machinability Definition, Journal of production engineering, 2012, vol. 15, No. 2, 27 - 32 11 CHAPTER II MEASUREMENT AND CONTROL IN MACHINING PROCESSES Contents 2.1 2.2 2.3 2.4 2.5 2.6 2.7 Importance of measurement and quality of products Process of measurement Basic principles of measurement Accuracy of machining - dimensions, tolerances and related attributes Length measurement Angles and cones measurement Laboratory work – cutting wedge angles measurement The science of measurement is called metrology. Metrology is in fact a specialized part of the individual sciences and engineering, which deals with the methods of measurement of physical quantities, development and production of measuring devices, reproduction and storage of measuring units, and all other activities that allow measurement and improvement of measurement procedures [1]. Measurement plays a very important role in all fields of science and technological development of each national economy. In highly developed countries, 6% of gross domestic product is spent on the process of measurement [1]. For quality and objective measurement, in addition to the educated and professional staff, it is necessary to dispose of appropriate measuring equipment. The foundation of modern highly automated production is based on measurement and industrial quality control, since measurement and control facilitate the development of new technologies, modernization and automation of production processes, quality assurance of products and their placement on the market. Measurement costs in the production are significant and sometimes amount up to 15% of the total production costs. Technical measurements are applied in all areas, from the procurement of raw materials, production and development of parts and products to the sale of the finished product on the market. Monitoring, control and management of industrial processes would be impossible without modern measuring equipment. On the other hand, there can be no development of science, nor any scientific research and testing of phenomena and processes without measurement and modern equipment. 2.1 The importance of measurement and quality of products Generally, there are two types of measurement: measurement in the production and measurement in the laboratory. If product development includes all phases from concept to finished product on the market, we can then say that measurement is present in all phases. Production measurements contribute to increasing the level of automation and the level of product quality and reduce production operations, Figure 2.1. The following products can be tested, measured and controlled in the production: machining system-machine tool, tool, workpiece or instrument to be checked [1]. 13 METAL CUTTING – Theory and Applications Figure 2.1 The main tasks of production measurements [1] The control of machine tools is performed periodically, and the process parameters that affect the product stability and characteristics are measured. Product quality directly depends on the condition and accuracy of the machining systems and devices used in its production. The measurement and control of the tool is performed during its production and during its exploitation. Tool accuracy directly affects product quality. The measurement and control of the workpiece refers to its geometric characteristics, material and functional purpose. The purpose of the measuring tool control and testing is to establish confidence in measurement results according to the international standards, as well as to establish trust between the manufacturer and the buyer of the product. In this way, control time is reduced, significant savings in material resources are achieved, and the product reaches the market faster. The product parameters that are measurable and include dimensions, colour, weight, material, mechanical properties, as well as the quality of the machined surface, describe the condition of the product and define its quality. The control of the product parameters is related to: testing and control of material properties, testing of product functionality and control of geometric characteristics, Table 2.1. Table 2.1 Measurement of product characteristics [1] Material testing - Young's modulus (E), - Shear modulus (G), - Hardness - Microstructure - Cracks Testing of functionality - Static tests - Dynamic tests - Vibration characteristics - Measurement of noise Control of geometric characteristics - Shape - Dimensions - Position - Surface integrity The control of geometric characteristics forms the basis of production measurements. These measurements are performed during the preparation and processing of the workpiece and creation of the finished product. The highest percentage of measurements is performed directly on the workpiece and 80-90% of all measurements involve the measurement of the geometric characteristics of the product. More specifically, 85% relate to the measurement of the dimensions and shape of the product (macrostructure-size, shape, location, angle, microstructure-roughness and waviness). Approximately 10% of the total measurement refers to the measurement and control of materials and structures (hardness, chemical composition, crystal structure, elastic modulus), and approximately 5% refers to the surface characteristics (hardness, cracks, residual stresses, ...). 14 MEASUREMENT AND CONTROL IN MACHINING PROCESSES Considering the fact that we live in a time of the globalization of markets and in conditions of highly automated production of parts and products, measurement procedures must also be automated as it will reduce the time necessary for the finished product to be put on the market. At present, complex products are usually assembled in one place from parts manufactured worldwide. Products made at various machining systems and controlled with different equipment must form a functional unit, and to be able to achieve this goal basic requirements for products interchangeability must be met, Figure 2.2. Apart from the prescribed control, additional controls are sometimes conducted in order to ensure prevention and avoid mistakes. Today, error ranges in ppm (parts per million) are considered to be acceptable. The establishment of methods for complete quality management makes it possible for a product of desired quality to be put on the market in the shortest possible time. This can be achieved by control throughout the process, by minimizing the level of errors in the process and by the establishment of automatic control in the process wherever possible. Figure 2.2 Basic requirements for interchangeability of products [1] Mistakes that mainly result from the measuring tool errors or errors made by the measurer occur throughout all measurements. Ideal conditions for laboratory measurements include air conditioned room with temperature of 20°C and at 55% relative humidity, where most accurate and state-of-the-art equipment and devices for accurate measurements are available. If measurements are made beyond this temperature, the coefficient of linear expansion αL must be taken into account (for steel αLSt 12·10-6 K-1, and for aluminium αLAl 23·10-6 K-1). The first measuring tools in the form of movable scales originate from the ninth century. With the industrial revolution begins the mass production of measuring tools, especially the control gauges for direct comparison of the gauge and the workpiece. During this period, machines for mechanical measurements and gauges for calibration were developed, and the set of calibration gauges was made in Sweden. In the twenties and thirties of the past century began the development of optical and pneumatic methods. The development of electronic measuring devices for production measurements originates from the early seventies of the past century, and since the eighties, the development of the means of coordinate metrology that use electronic and optical components has rapidly expanded, Figure 2.3. 15 METAL CUTTING – Theory and Applications Figure 2.3 Development of measuring tools for production measurements [1] 2.2 Process of measurement In order to carry out the process of measurement correctly, whether it is production measurements in a factory or precise measurements, it is necessary to proceed in a particular order: 1. Clearly define measurement task, position to be measured, measurement error, confidence interval for the measured value, probability of the measured value being in the confidence interval, start and end of measurement, etc. 2. Define units of the SI system to be used to express the measurement results. 3. For each individual measurement define the best combination of boundary conditions in order to get reliable results. 4. Select a measuring instrument and define a measurement system. Form a measurement plan or an experimental plan. 5. Calibration of the measuring system or instrument to ensure measurement accuracy. 6. Perform the measurements (defining the conditions and criteria for the measurement set, the choice of the measuring equipment, type of sensor signals, etc.) and determine the results. 7. Consider influences on the measurement, eliminate errors, define measurement uncertainty. 8. Determination of the actual measurement results. 9. Evaluation and analysis of the measurement results. 2.3 Basic principles of measurement The accuracy of measurement depends on a number of factors, but also on the basic principles that underlie the design and construction of the measurement and control tools. The basic principles are: Abbe's (comparator principle of measurement) Taylor's principle of measurement 16 MEASUREMENT AND CONTROL IN MACHINING PROCESSES The Abbe's principle uses optical indicating elements and works by using very precise rulers. It applies to measuring instruments and reads as follows: the most accurate measure can only be achieved when the measured size is in a straight line extension of the scale. Otherwise an additional error will take place (e.g. Δl by callipers), Figure 2.4. Figure 2.4 Comparator or Abbe's principle of measurement [1] The Taylor's principle applies to limit gauges and reads as follows: the ‘Go side’ of a limit gauge should be constructed in a way that it ensures the interchangeability of parts, while the ‘No go side’ is supposed to be constructed in a way to ensure the verification of only one parameter. So the task of the ‘No go side’ is to detect deviations from the controlled measures, and therefore has a barrel form. The principle is applied to limit gauges for assembly elements control (e.g., shaft - sliding or ball bearing, piston ring - cylinder liner, etc.), Figure 2.5. Figure 2.5 Taylor's principle of control 2.4 Accuracy of machining – dimensions, tolerances and related attributes Machining accuracy is a degree of concurrency of processed parts with predetermined standards and is conditioned by the requirements of constructive documentation (class of accuracy, deviations, etc.). The main objective of a cost-effective production is to produce parts of only necessary and sufficient accuracy, not of highest one. In this way, the costs of the production are reduced to a minimum. The accuracy depends on the development of machining errors that can be: Pre-processing, Processing, Post-processing. 17 METAL CUTTING – Theory and Applications Machining errors are random and cannot be predicted, but with a proper choice of parameters and processing conditions can be minimized and set within the allowable margin of error. Pre-processing errors are methodological errors (wrong choice of processing method), basing errors, clamping, tool setting, and faults in machine tool, tools, and equipment. Processing errors result from the elastic and temperature dilatations of technological system elements, tool wear and internal (residual) stresses. Post-processing errors result from measurement and control errors. In the cutting process, geometric processing errors and errors in the microstructure are present. Geometric machining errors can be divided into: macro-geometric and microgeometric, Figure 2.6. Shape error MACRO GEOMETRIC ERRORS MICRO GEOMETRIC ERRORS Measure error Roughness Position error Figure 2.6 Geometric errors of machining Micro-geometric errors are related to the surface roughness (see Chapter VIII), and macrogeometric errors are related to: 1. Shape errors, 2. Dimension errors (measure), and 3. Position errors. Shape errors are the deviations of the actual profile from the ideal one. Shape tolerances are straightness, flatness, roundness, cylindricity, line form and surface shape, Table 2.2. Shape errors should be smaller than the acceptable shape deviation indicated in the drawing. Examples of marking shape deviations are shown in Figure 2.7 [1]. Dimension errors - measures (width, length, height, cylindrical surface diameter, hole depth, cone angle, ...) represent deviations from the dimensional tolerances prescribed in the documentation. Tolerances are prescribed by ISO standards. ISO tolerance class and ISO roughness class must be reconciled, Table 2.3. Position errors represent the deviations of relative position from the ideal one as defined by the documentation (part drawings). Surface position tolerances are presented in Table 2.4 and Figure 2.8 and are classified into three categories: direction deviations, deviations of the place and deviations of the rotation accuracy. Direction deviations include: deviations from parallelism, deviations from perpendicularity and the angle of inclination. Deviations of the place are: location, concentricity, coaxiality and symmetry. Deviations of rotation accuracy are: accuracy, roundness and rotation straightness [1]. 18 MEASUREMENT AND CONTROL IN MACHINING PROCESSES Table 2.2 Definitions of the geometric attributes of parts Name of geometric attribute Angularity Definition The extent to which a part feature such as a surface or axis is at a specified angle relative to a reference surface. If the angle = 90°, then the attribute is called perpendicularity or squareness. Circularity For a surface of revolution such as a cylinder, circular hole, or cone, circularity is the degree to which all points on the intersection of the surface and a plane perpendicular to the axis of revolution are equidistant from the axis. For a sphere, circularity is the degree to which all points on the intersection of the surface and a plane passing through the centre are equidistant from the centre. Concentricity The degree to which any two (or more) part features such as a cylindrical surface and a circular hole have a common axis. Cylindricity The degree to which all points on a surface of revolution such as a cylinder are equidistant from the axis of revolution. Flatness The extent to which all points on a surface lie in a single plane. Parallelism The degree to which all points on a part feature such as a surface, line, or axis are equidistant from a reference plane or line or axis. Perpendicularity The degree to which all points on a part feature such as a surface, line, or axis are 90 from a reference plane or line or axis. Roundness Same as circularity Squareness Same as perpendicularity. Straightness Same as perpendicularity. Figure 2.7 Examples of marking deviations of the shape Figure 2.8 Examples of marking deviations of the position 19 METAL CUTTING – Theory and Applications Table 2.3 Connection between ISO tolerance class and class of roughness [2] Classes of roughness and values of roughness parameters Normal value, mm to 3 over 3 to 18 over 18 to 80 over 80 to 250 over 250 Class of Ra, Class of Ra, Class of Ra, Class of Ra, Class of Ra, roughness μm roughness μm roughness μm roughness μm roughness μm IT5 N3 0.1 N4 0.2 N5 0.4 N5 0.4 N6 0.8 IT6 N4 0.2 N5 0.4 N5 0.4 N6 0.8 N6 0.8 IT7 N5 0.4 N5 0.4 N6 0.8 N7 1.6 N7 1.6 IT8 N5 0.4 N6 0.8 N7 1.6 N7 1.6 N8 3.2 IT9 N6 0.8 N6 0.8 N7 1.6 N8 3.2 N9 6.3 IT10 N7 1.6 N7 1.6 N8 3.2 N9 6.3 N9 6.3 IT11 N7 1.6 N8 1.6 N9 6.3 N9 6.3 N10 12.5 IT12 N8 3.2 N8 3.2 N9 6.3 N10 12.5 N11 25 IT13 N9 6.3 N9 6.3 N10 12.5 N11 25 N11 25 IT14 N10 12.5 N10 12.5 N11 25 N11 25 N12 50 IT15 N10 12.5 N10 12.5 N11 25 N12 50 100* IT16 N11 25 N11 25 N12 50 100* 100* *) extremely rough surface quality Mark of ISO tolerance class Table 2.4 Surface shape and position tolerances The basic parameters used by design engineers to specify sizes of geometric features on a part drawing are: dimensions, tolerances, flatness, roundness and angularity. ANSI [3, 4] defines a dimension as “a numerical value expressed in appropriate units of measure and indicate on a drawing and in other documents along with lines, symbols and notes to define size or geometric characteristic, or both, of a part or part feature“. Dimensions on part drawings represent nominal or basic sizes of the part and its features. These are the values that the designer would like the part size to be, if the part could be made to an exact size with no errors or variations in the fabrication process. However, there are variations in the manufacturing process, which are manifested as variations in the part size. 20 MEASUREMENT AND CONTROL IN MACHINING PROCESSES Tolerances are used to define the limits of the allowed variation. ANSI standard [3, 4] defines a tolerance as “the total amount by which a specific dimension is permitted to vary. The tolerance is the difference between the maximum and minimum limits.” Tolerances can be specified in several ways, illustrated in Figure 2.9 [3]. Probably most common is the bilateral tolerance, in which the variation is permitted in both positive and negative directions from the nominal dimension. For example, shown in Figure 2.9 (a), the nominal dimension = 2.500 linear units (e.g., mm, in), with an allowable variation of 0.005 units in either direction. Parts outside these limits are unacceptable. It is possible for a bilateral tolerance to be unbalanced; for example, 2.500 +0.010, -0.005 dimensional units. A unilateral tolerance is one in which the variation from the specified dimension is permitted in only one direction, either positive or negative, as in Figure 2.9 (b). Limit dimensions are an alternative method to specify the permissible variation in a part feature size; they consist of the maximum and minimum dimensions allowed, as in Figure 2.9 (c). Dimensions and tolerances are normally expressed as linear (length) values. There are other geometric attributes of parts that are also important, such as flatness of a surface, roundness of a shaft or hole, parallelism between two surfaces, and so on. Definitions of these terms are listed in Table 2.2 [3]. Figure 2.9 Three ways to specify tolerance limits for a nominal dimension of 2.500: (a) bilateral, (b) unilateral, and (c) limit dimensions [2] Measurement is a procedure in which an unknown quantity is compared with a known standard, using an accepted and consistent system of units. Two systems of units have evolved in the world: (1) the U.S. customary system (U.S.C.S.), and (2) the International System of Units (or SI, for Système internationale d’unités), more popularly known as the metric system. The metric system is used throughout this book. The metric system is widely accepted in nearly every part of the industrialized world except the United States, even though the US has also been adopting SI System lately. Measurement provides a numerical value of the quantity of interest, within certain limits of accuracy and precision. Accuracy is the degree to which the measured value agrees with the true value of the quantity of interest. A measurement procedure is accurate when it has no systematic errors, which are positive or negative deviations from the true value that are consistent from one measurement to the next. Precision is the degree of repeatability in the measurement process. Good precision means that random errors in the measurement procedure are minimized. Random errors are usually associated with human participation in the measurement process. Gauging is a term closely related to measurement. Gauging determines simply whether a part characteristic meets or does not meet the design specification. 21 METAL CUTTING – Theory and Applications 2.5 Length measurement Following their principle of operation, the length measuring tools can be divided into: mechanical, pneumatic, optical, and electronic. The following mechanical gauges for length measurement will be particularly analyzed: Ones not showing the measured quantities (single purpose), which include: gauge blocks, limit gauges, rulers without scales, measuring boards, and other gauges. Ones showing the measured quantities (multipurpose), which include: callipers, micrometers and comparators. Single purpose measuring tools measure only one particular quantity, while multipurpose measuring tools measure a range of quantities. 2.5.1 Single purpose measuring tools Precision gauges are the reference standard for other dimensional measuring instruments and gauges. In the technique of length measurement, different gauges are used: Parallel gauges in which the distance between two flat and parallel surfaces constitute a longitudinal measure. Stepwise gauges that have more than two flat and parallel surfaces. Angular gauges with flat but non-parallel measuring surfaces. These measuring tools represent angular measure and are classified as the length embodied measuring tool. Globe (Ball) gauges – have two measurement surfaces which belong to the common sphere. Cylindrical gauges and rings are also classified in this group and are used to measure the size of circular cylinder. Precision gauge blocks Gauge blocks are usually square or rectangular. The measuring surfaces are finished to be dimensionally accurate and parallel within several millionths of an inch and are polished to a mirror finish. The highest grade is made to a tolerance of ±0.0003 mm. Depending on the degree of desired hardness and price the user is willing to pay, gauge blocks can be made of any of several hard materials, including tool steel, chrome-plated steel, chromium carbide, or tungsten carbide [3]. Precision gauge blocks are available in certain standard sizes or in sets, the latter containing a variety of different-sized blocks. The sizes in a set are systematically determined so they can be stacked to achieve virtually any desired dimension within 0.0025 mm. For best results, gauge blocks must be used on a flat reference surface, such as a surface plate. A surface plate is a large solid block whose top surface is finished to a flat plane. Most surface plates today are made of granite. Granite has the advantage of being hard, nonrusting, nonmagnetic, long wearing, thermally stable, and easy to maintain. Gauge blocks and other high-precision measuring instruments must be used under standard conditions of temperature and other factors that might affect the measurement. By international agreement, 20°C (293 K) has been established as the standard temperature. Metrology labs operate at this standard. If gauge blocks or other measuring instruments are used in a factory environment in which the temperature differs from this standard, corrections for thermal expansion or contraction may be required, see Chapter 2.1. Also, working gauge blocks used for inspection in the shop are subject to wear and must be calibrated periodically against more precise laboratory gauge blocks [3]. 22 MEASUREMENT AND CONTROL IN MACHINING PROCESSES Figure 2.10 Parallel gauge blocks set (Source: Mahr) Accuracy of gauge blocks: 1. The most accurate (according to ISO 3650 Class K and 0): 2. Less accurate (Class 1 and 2): 1,0 where M is a nominal measure given in mm. 0,1 µm µm Figure 2.11 Stepwise gauges (Source: etalon QFM, Erlangen) Figure 2.12 Cylindrical gauges set Embodied measuring tools are also cylindrical gauges (control-measuring pins) according to DIN-2269, having the largest nominal diameter of 20 mm. The cylindrical gauges 23 METAL CUTTING – Theory and Applications embody external measure of the circular cylinder diameter. They are used for testing cylindrical holes, balls, spacing, threads, gear teeth, branch, etc., Figure 2.12. They are often used as standards for setting the measuring devices. Control rings embody the size of the inner cylinder, and also represent an element of circular cylinder forms in very narrow tolerances. They are in addition to the parallel gauge blocks classified as the most important reference standards, Figure 2.13. Figure 2.13 Control ring gauges Limit gauges For finished product control, especially in serial and mass production of the same parts, single purpose limit gauges are used as control tools, which allow an immediate control of measures and shapes of the product features by the comparison method. Thus, comparative limit gauges do not provide a direct measure, but allow determining whether a delegated lengths measure is or is not in the tolerance planned in the drawings. Limit gauges are produced in two basic forms: Snap gauge for control of external linear measures, and Plug shaped gauge for control of internal linear measures. Limit gauges (test gauges) are used to determine whether a controlled size lies within its allowed tolerances but they do not determine the controlled size value nor measurement deviation. They are fixed gauges with the “GO” side and the “NO GO” side. They are therefore used for controlling only one type of object, or to be more precise only one size (nominal size) and its tolerance zone. Single (fixed) gauges are primarily used as control tools in serial production. The main types of single (fixed) gauges are: parallel limit gauges, tolerance gauges for checking shafts and holes, single profiled gauges for specific purposes. Compared to multiple gauges with direct reading, single gauges are simple and allow a much faster control of object measures. Their main weakness is that they can only be used for one control type and one nominal size. Limit gauges can be fixed and adjustable, single and double-sided and are used to control the extent and form of shafts, holes, internal and external threads, taper. They are primarily used in the mass production of products with the specified tolerance. The characteristic of fixed, single purpose gauges is that each of them can be used to control a single nominal dimension or the tolerance field related to the measure. Therefore, these gauges must be made in a high accuracy class. 24 MEASUREMENT AND CONTROL IN MACHINING PROCESSES a) b) Figure 2.14 Limit snap gauges for shafts: a) different shapes of gauges, b) two-sided snap gauge a) b) Figure 2.15 Limit plug gauges for holes: a) different shapes of plug gauges b) two-sided plug gauge Other single purpose measuring tools (gauges) Other single purpose measuring tools include: 1. Taper plug gauge, Figure 2.16 (1). 2. Spline gauge, Figure 2.16 (2). 3. Tread gauges. 4. Thread plug gauges, Figure 2.17 a). 5. Snap thread gauges, Figure 2.17 b). 6. Templates and calibres, Figure 2.18. 7. Angle gauges for cutting tool angle measurements, Figure 2.19. Figure 2.16 Taper plug gauge (1) and spline gauge (2) 25 METAL CUTTING – Theory and Applications a) b) Figure 2.17 a) Thread plug gauges and b) snap thread gauge Templates and calibres are made of sheets in kits, have a certain shape and dimensions, and are used for the rapid control of a specific object shape in case of which measurement with the usual means of measurement tools is difficult or impossible. This group of measuring tools include: feeler gauges for gaps ("spies"), gauges for the inner and outer radii, taper gauges for the angles (casting and forging) and "combs" thread pitch gauge for control of the threads. a) b) c) Figure 2.18 a) Feeler gauge, b) radius gauges, b) thread pitch gauge Figure 2.19 Angle gauges for cutting tool angle measurements 2.5.2 Multipurpose indicating measuring instruments These instruments are universal and provide us with any measures or deviations in a certain range of measures. Depending on the accuracy that can be achieved when measuring, the following measuring instruments differ: rulers, measuring tools with vernier or calliper scale – callipers, micrometers, comparators, and the combined instruments and 26 MEASUREMENT AND CONTROL IN MACHINING PROCESSES devices for length measurements. Rulers are the easiest measuring tools to be used in the production and are used for the roughest measurements in castings, forgings, welded structures and the like, especially when measuring objects of great dimensions. Instruments with mechanical converters They belong to a group of multiple indicating measuring instruments that are the oldest but also the most commonly used. This group of measuring instruments includes: callipers, micrometers and comparators. These measuring instruments are used when it is necessary to provide significantly greater accuracy of measurement compared to measuring rulers. They are used in a single production in workshops, including: callipers, depth measuring instruments for depth of holes or stack height measuring, etc., and height gauges for marking of castings and forgings. Figure 2.20 Calliper with digital display Micrometers These instruments are used for more precise measurements compared to callipers. They work by means of precision-made ball screw with a pitch of 0.5 mm or 1/40". Measuring range of micrometers as a rule is 25 mm, regardless of the size of the openings of its body. The limit of 25 mm is therefore taken to avoid any error in the preparation of the micrometer mechanism, and thus avoiding the inaccuracies of the measurement. Micrometers achieve the accuracy of measurement of 1/100 mm within the measuring range of 25 mm. They differ in micrometers for: external, internal and depth measurements, Figure 2.21. Figure 2.21 Micrometer for external measurements 27 METAL CUTTING – Theory and Applications Figure 2.22 Micrometer for internal measurements with adjustable ring Comparators These measuring instruments are used for accurate measurement of smaller dimensions, up to 10 mm. They are often used to measure the deviations from the nominal measure, in which case the comparator must be previously set to correct nominal measure, and the measurement obtained in this case is a positive or negative deviation from the nominal measure. Figure 2.23 Comparator with an analogue measurement scale (dial) and with a digital display a) b) Figure 2.24 a) Comparative measuring instrument with integrated dial comparator for external measures, b) Comparative measuring instrument for inner measurements (bore gauge) 28 MEASUREMENT AND CONTROL IN MACHINING PROCESSES Comparators operate on different principles depending on the transmission mode of the measuring signal from the measuring probe to the cursor; most are designed to work on: Mechanic (accuracy of 1/100 of mm) Optical (accuracy of 1/1000 of mm) Pneumatic (accuracy of 0.2 µm) Hydraulic (accuracy of 0.2 µm) Electric (accuracy of 1/1000 of mm) and Combined principle. 2.6 Angles and cones measurement Angle measurement is performed by single purpose and multipurpose measuring tools, and by applying methods of indirect measurement. The single purpose measuring tools for angles include: limit and tolerance gauges, angle gauges and templates. The multipurpose measuring instruments include: protractors (mechanical and optical), an optical dividing head and spirit levels. Angle gauge blocks are limit gauges whose combination may achieve the desired angle. As to the single purpose measuring tools in workshops, one uses the angle gauge blocks with the angles of 60º, 90º, 120º, and 135º, and the most used one is the angle of 90º. Templates are used to control the angles of the cutting tools after damage and in the different types of threads production. Figure 2.25 shows angle limit gauges. Figure 2.25 Angle limit gauge blocks Figure 2.26 Universal protractor and measuring possibilities 29 METAL CUTTING – Theory and Applications Universal protractor, Figure 2.26, is used for the measurement of angles that should have accuracy of less than one degree. Protractor has two scales; one fixed with 360 degrees division, and a movable scale with 12 divisions, each one of 11 degrees. Universal protractor may also have a double scale. For ease of reading most of the protractors have a dual vernier, whose 12 divisions are distributed in an arch which corresponds to an angle of 23º, instead of 11º. In this case, a value corresponding to each division is 115', i.e. 23º: 12 = 1380':12 = 115’. For very accurate measurements of angles and slopes, one uses a special, precisely designed prism which relies on two identical rolls of the same machining precision. Surfaces of such sine bar are ideally flat, allowing accurate measurements up to 10". Figure 2.27 shows sine bar and measuring principle. Setup consists of a flat steel straight edge (the sine bar), and two precision rolls set a known distance apart on the bar. The straight edge is aligned with the part angle to be measured, and gauge blocks or other accurate linear measurements are made to determine the height. The procedure is carried out on a surface plate to achieve the most accurate results. This height H and the length L of the sine bar between rolls are used to calculate the angle A using sin Figure 2.27 Sine bar and measuring principle During the measurement and control of the rake angle and tool clearance of the cutting wedge, especially in the process of regeneration and the sharpening of cutting tools, the following devices and instruments are used: Tool and universal measuring microscope (Chapter VII elaborates on these measurements). Special protractors for the control of appropriate cutting tools, Figure 2.28. Special measurement and control templates for specific tools, Figure 2.29. Universal protractors, Figure 2.30. 30 MEASUREMENT AND CONTROL IN MACHINING PROCESSES Figure 2.28 Special protractors for cutting tools control Universal protractors allow measurements of geometry and angles for majority of the cutting tools. The principle of operation is as follows: cutting tool (turning tool) is placed on a flat surface (control or measuring plate), and the base plane of the protractor on the surface of the cutting wedge (rake or flank face depending on which angle is measured). By pressing the button to block the protractor, the hand that always takes the vertical position is activated (with the weight due to gravitational force) demonstrating the value of the controlled angle. Figure 2.29 Control template for spiral drill angles [5] Figure 2.30 Universal dial bevel protractor [5] 2.7 Laboratory work – cutting wedge angles measurement The goal of any theoretical presentation of this book is to familiarize students with the basic theoretical knowledge which is necessary to properly set up a laboratory work, and to perform the required measurements. All the measuring tools and instruments for measuring length, angles and cones are described above. The laboratory work refers to the measurement of tool wedge angles, so that the list below only represents the basic theoretical explanations relating to this issue. 31 METAL CUTTING – Theory and Applications 2.7.1 Geometry of the cutting tool All cutting tools consist of at least two parts; the tool body where the cutting elements of the tool (tool wedge) are located, and the handle or the opening in the tool body, through which the setting and fastening of the tool is carried out to the tool holder or to the machine. On the tool wedge the characteristic elements can be identified, Figure 2.31; rake face Aγ or the area where the chips slide, flank face Aα or the surface facing cut surface and minor flank face A’α or the surface of the tool wedge facing the machined surface of the workpiece. The major cutting edge of the tool S is located at the intersection of the surfaces of the rake and flank face of the tool. Minor cutting edge is located at the intersection of the rake face and minor flank face. Intersection of the major and minor cutting edge defines the tip of the tool, which is usually rounded and called the tool nose radius r. Figure 2.31 Cutting edges and faces of the wedge, acc. to ISO 3002-1 The characteristic angles of the tool wedge can be defined by introducing the tool frame of reference in which the following planes are defined; see Figure 2.32: The cutting edge plane Ps runs tangentially to the cutting edge S and perpendicularly to the tool reference plane Pr. The tool orthogonal plane Po is perpendicular to the tool cutting edge plane Ps. The tool cutting edge normal plane Pn is perpendicular to the cutting edge S. Figure 2.32 Tool frame of reference, acc. to ISO 3002-1 32 MEASUREMENT AND CONTROL IN MACHINING PROCESSES Looking at the tool frame of reference, tool wedge characteristic angles can be defined, Figure 2.33: Clearance angle α or the angle between flank face Aα and the cutting edge plane Ps; the size of the clearance angle affects tool wear, friction on machined surface, heat generation, quality of the workpiece, hardness of the surface layer, etc. Rake angle γ is the angle between the rake face and tool reference plane Pr; affecting the degree of deformation, chip formation process, and tool wear, etc. The angle of the tool wedge β is the angle between the rake and flank face of the tool and affects the resistance of the tool wedge, friction on the flank face and hence the stability and tool life. Tool cutting edge inclination λs is the angle between the major cutting edge and the reference plane Pr measured in the tool cutting edge plane Ps. It influences the chip formation and evacuation process. By measuring and analysing the tool geometry in the reference plane Pr, the following angles can be defined: Major tool cutting edge angle κr is the angle between the working surface and the major cutting edge; Tool included angle εr as an angle between the major and the minor cutting edge. These angles affect the surface quality, the vibration occurrence during machining, the cutting resistance, the evacuation of the generated heat, etc. Figure 2.33 Single point cutting tool angles, acc. to DIN 6581 The positioning of the cutting tool above or below the workpiece axis during machining affects the cutting tool geometry. This results in the geometric values of rake angle γ and clearance angle α being changed to kinematic values γk αk, see Figure 2.34. The roughing tool is usually placed above the axis in order to allow a smaller chip deformation and facilitate processing. The finishing tool is placed below the axis of the workpiece in order to optimize the process of the chip deformation. Figure 2.34 Influence of the cutting tool positioning on the tool wedge rake angle γ and the clearance angle α [6, 7] 33 METAL CUTTING – Theory and Applications 2.7.2 Description of the experimental work The aim of the laboratory work is to measure rake angle γ and clearance angle α for different cutting tools. Additionally, other angles of the cutting wedge should be defined, such as: tool cutting edge inclination λs, major tool cutting edge angle κr and tool included angle εr. During the laboratory work, students should understand the change in values of the tool geometric angles depending on the method of tool positioning in turning. A universal protractor is used in the laboratory work to measure the value of rake angle and clearance angle and all other angles listed above. All tests should be recorded in the test report - Measuring form 1 and 2 (Table 2.6 and 2.7). A. Laboratory work Task. Identify and measure the tool elements of geometric quantities on selected cutting tools. Measurement procedure: 1. Choose a cutting tool for experimental measurements 2. Identify tool elements 3. Identify tool geometric features 4. Measure the geometric features Table 2.5 Measuring instruments and accessories No. Name and characteristics 1 Calliper Measuring range: 0 - 150 mm Accuracy: 0.01 mm 2 Universal protractor Measuring range: 0 - 150 mm Accuracy: 0.01 mm 3 Radius gauge 34 Figure MEASUREMENT AND CONTROL IN MACHINING PROCESSES Table 2.6 Measuring form 1 Measuring method outline Measured/calculated quantities Observations and comments: 35 METAL CUTTING – Theory and Applications Table 2.7 Measuring form 2 Measuring method outline Observations and comments: 36 Measured/calculated quantities MEASUREMENT AND CONTROL IN MACHINING PROCESSES Literature: [1] Zaimović-Uzunović N., Lemeš S., Denjo D. Softić A.: Production measurements, Faculty of Mechanical Engineering, Zenica, 2009 (in Serbian) [2] Lazić M.: Metal cutting process, Faculty of Mechanical Engineering, Kragujevac, 2002 (in Serbian) [3] Mikell P. G.: Principles of Modern Manufacturing, SI Version, Mth Edition, John Wiley & Sons (Asia) ISBN: 978-0-470-50592-2, 2011 [4] American National Standards Institute, Inc. Dimensioning and Tolerancing, ANSI Y14.5M-1982. American Society of Mechanical Engineers, New York, 1982 [5] Lazić M.: Metal cutting process, handbook for laboratory exercises second edition, Faculty of Mechanical Engineering, Kragujevac, 1987 (in Serbian) [6] Globočki-Lakić G., Metal cutting process – theory, modelling and simulation, Faculty of Mechanical Engineering, Banja Luka, 2010 (in Serbian) [7] Globočki-Lakić G., Sredanović B.: Supplementary material to perform laboratory exercises in metal cutting process, Faculty of Mechanical Engineering, Banja Luka, 2011 (in Serbian) 37 CHAPTER III CHIP SHAPES AND TYPES Contents 3.1 3.2 3.3 3.4 3.5 Chip shaping and forming process Rating of chip forms; favourable and unfavourable chip forms Experimental chip shape determination Main conclusions regarding the creation of favourable chip forms Laboratory work – Determination of chip shape and type Cutting process, i.e. the process of excess material removal and chip formation is very complex and occurs in a narrow localized zone that is called the cutting zone. The understanding of the complex physical and chemical processes that take place in this zone to manage the chip shaping and forming process represents one of the most important tasks in the course of providing a complete automated cutting process with no operator control. Chip formation control and tool wear control are the basic prerequisites for process automation. With the development of modern tool materials, advanced machining systems and modern materials, cutting regimes have largely increased, the cutting speed in particular. This has resulted in a longitudinal continuous chip being formed, which is very unfavourable for the operation and could harm the finished surface. In modern machining systems, the automatic chip removal and storage must be resolved. Therefore, chip control, transport and storage are one of the most serious problems in the automation of the cutting process. Troubleshooting is possible in the following ways: Control of chip formation, Automatic chip removal, Cutting regime correction, and Appropriate workpiece material selection. The simplest, and therefore the most used way is the control of chip formation. Due to a large number of influencing factors on the chip formation process, it is not possible to predict the form of chip without having previously performed experimental tests. 3.1 Chip shaping and forming process The process of chip formation takes place in three successive stages: 1. Plastic deformation of the workpiece material and chip formation, 2. Chip evacuation from the cutting zone, and 3. Chip breaking using special additional elements (chip breaker). The last stage does not appear in all processes. The most important is the first stage. It has been the subject of numerous studies due to the complexity of the phenomenon in the cutting zone as well as many other factors relating to workpiece material, tool material, tool geometry, machining system, coolant and lubrication, and technological parameters (Figure 3.1) [1, 2]. 39 METAL CUTTING – Theory and Applications In the cutting process, elastic (initial) strain and plastic deformation are present in a narrow localized zone – the cutting zone. Given that the size of elastic deformation is much smaller than the plastic, and that almost the entire cutting operation is done by the plastic deformation of the affected layer of the material in the cutting zone and by the friction on contact surfaces of the tool, then the process of elastic deformation during cutting, according to some authors [3, 4], can be neglected. Thus, the cutting process is viewed as a process of plastic deformation of the affected layers of material in the cutting zone. Following this approach, it should be emphasized that the process of plastic deformation when cutting is very specific in relation to the processes that have been studied in the general theory of plasticity. These specifics are reflected in the following: Plastic deformation of cut layers takes place in a narrow localized zone – the cutting zone, Cutting process is accompanied by complex tribological processes at the contact surfaces of the cutting wedge, During plastic deformation strong thermodynamic processes take place in the cutting zone, etc. In the cutting zone, some very complex processes that take place are conditioned by the action of a number of influencing factors in some correlative dependencies, Figure 3.1. Figure 3.1 Chip shaping and forming process The process of chip formation is created by a local plastic deformation of the workpiece material. During penetration of the cutting tool wedge into the workpiece material, complex stresses occur in the material ahead of the cutting wedge. The plane where the maximum shear stresses are located is called the shear plane, and its position is determined by the shear angle . The cutting process does not take place in the shear plane (one level) only, but in a narrow layer around that plane, called the shear zone or zone of deformation (cutting zone). 40 CHIP SHAPES AND TYPES Figure 3.2 shows characteristic deformation zones: I – primary deformation zone – zone ADOHB. In front of ODA zone, metal is elastically deformed. II – secondary deformation zone – (OHC) with a braking layer of thickness a1 ≈ 0.1 hch. III – tertiary deformation zone consists of a deformed layer of thickness a2, which depends on the workpiece material and tool loading. Figure 3.2 Shear plane and deformation zone with texture lines The simplest way to explain the stages of the chip formation process is in orthogonal cutting, where considering the case of the workpiece being stationary and the tool moving in a straight line. In general, it can be divided into three or four typical stages of chip formation. It depends on the relationship between the values of shear angle ϕ and rake angle γ whether there will be three or four phases. If the normal to the shear plane AA falls outside the tool wedge, then the process of forming a chip ends in three stages. If the normal to the shear plane passes through the tool wedge , then the fourth stage of chip formation takes place – subsequent plastic deformation of the chip on the tool rake face (see Figure 3.3). Shear angle ϕ largely depends on the type of material being processed. Figure 3.3 Characteristic phases of chip formation [5] 41 METAL CUTTING – Theory and Applications In the first stage of the chip forming process, the material is compacted in front of the rake face of the blade until the stress in the material has exceeded the value of the tensile strength RM. At this point, the crack is formed in front of the tool tip, which begins the second phase of chip formation. Further penetration of the cutting tool wedge in the material causes the shear stress that is constantly growing. The moment these stresses exceed the shear strength of the material, the shear of the affected and compacted layer of material along the shear plane AA will occur. This part of the process is the third phase of chip formation. If the value of angle ϕ is less than the value of rake angle γ, i.e. when the normal to the shear plane falls out of the tool wedge, the chip formation process is completed in three phases. Further penetration of the tool wedge in the material just repeats these three phases and creates a series of connected slats. In such a case, linked or strip chips form (processing of ductile materials). In the case where the normal to the shear plane passes through the cutting tool wedge (when ϕ > γ), the fourth stage in the chip formation process takes place. The elementary lamella is tearing in the shear plane AA but tends to move in the direction normal to the plane of shear NN. In the case where ϕ > γ lamella is diverted from its natural way by rake face of the tool so that it is subsequently deformed-broken on the rake face, which represents the fourth phase. In this way a broken-disrupted chip is formed. Therefore the knowledge of chip formation is very important for the production practice and, as shown in Figure 3.3, it can be formed through three or four stages, or can form a continuous or intermittent chip. Numerous factors that affect the chip formation process (Figure 3.1) define the shape and type of chip as well as the way chip evacuates from the cutting zone. The individual effects of each factor and their mutual interaction often cause unexpected changes in chip formation. The shape and type of chip, beside the relative values of shear plane angle ϕ and tool rake angle γ, also depend on the characteristics of the workpiece material, cutting speed, depth of cut and feed rate. The influence of the workpiece material on the form and type of chip is reflected in the fact that during the processing of brittle materials (cast iron, non-ferrous metals, etc.) a broken chip occurs, and during the processing of ductile materials (mainly all kinds of steel) strip a continuous chip occurs. The effect of the cutting speed – processing with lower values of cutting speed results in broken chips, whilst strip chips occur when working with higher cutting speeds. Creating conditions for the formation of desired chip shape, i.e. strip chips, by using the cutting speed is not simple because the cutting speed is selected and defined in accordance with a number of other parameters mainly of economical nature. The same goes for depth of cut and feed rate. Strip chip occurs at lower values of depth of cut and feed rate, whilst broken chips form at higher values. Depending on the mechanism and character of chip origin, the chip of different forms and types form. The chip form and type depend on the sort and physical-mechanical properties of the workpiece material (plasticity above all), and conditions for plastic deformation of cutting layer, strain character (continuous or discontinuous cutting), time, degree and speed of deformation. Generally, there are four chip types (Table 3.1): Unbroken or continuous (strip), Broken or discontinuous (resulting from the processing of brittle materials), Continuous in terms of BUE occurrences, and Lamellar chip. Chip shapes that form in the machining of different materials are displayed in Figure 3.4. 42 CHIP SHAPES AND TYPES Figure 3.4 Chip shapes formed at different materials machining [6] Table 3.1 Chip types and shapes and description of the characteristics [7] CONTINUOUS CHIP occurs if the angle between the rake face and the shear zone is less than 90 degrees, at relatively high cutting speed, small and medium-sized chip thickness, elongated structure, lamellas well-welded to each other, chips are very strong and long, workpiece materials must have a high capacity for deformation. LAMELLAR CHIP occurs when increased deformation in the shear zone decreases the strength of the material (vibration), generated at cutting speeds of 20 to 80 m/mm and when material has sufficient plasticity and ductility, which are not subject to corrosion and have an austenitic structure, lamellar structure, jagged outside, lamellas are deformed and welded together. SEGMENTED CHIP DISCONTINUES CHIP occurs when deformation in the shear zone exceeds the limit strength, at cutting speed and chip thickness high enough, less plastic or heavily hardened material, lamellas are poorly welded together; in the chip formation cracks propagate from the exterior to the interior. formed in brittle materials that have a low ability of deformation, an irregular structure and inclusions (gray cast iron, stone, brass, hard alloy), occurs also in ductile materials machining, when small wedge angles and low cutting speeds (up to 10 m/s) are used, chip particles are torn, flat and brittle, so the machined surface is rough, chip cracks are propagated in the direction opposite to the cutting edge. 43 METAL CUTTING – Theory and Applications Chip forming and shaping depends on the bending moment at the root of the chip, which changes the flow angle of the chip. Different bending of the chip occurs due to: uneven speed of chip flow along the tool, chip net weight, slowing down the chip flow and collisions of elementary lamellas, dynamic character of force in the shear zone, and variability of material properties of the workpiece. Models and methods of chip bending and flowing are shown in table 3.2 [7]. Table 3.2 Chip forms caused by different bending [7] Flat vc = 0 vc ≠ 0 Theoretical form Bending upwards Bending sideways only only vc = 0 vc ≠ 0 vc = 0 vc ≠ 0 Chip axis parallel to major cutting edge Chip axis through major cut. edge Chip axis intersects major cut. edge Chip axis perpendicular to major cutting edge Bending upwards and sideways vc = 0 vc ≠ 0 Chip axis through major cut. edge Chip axis intersects major cut. edge Chip axis inclined to major cutting edge Long chips Flat Bending sideways only Bending upwards only Bending upwards and sideways Flat ribbon chip Snarled chip Flat Cylindrical spiral chip Helical chip Flat helical chip Long chips Bending sideways Bending upwards only only Cylindrical chip segment 44 Oblique spiral chip Oblique chip segment Ring-shaped chip Coneshaped spiral chip Oblique helical chip Bending upwards and sideways Cone-shaped chip segment CHIP SHAPES AND TYPES 3.2 Rating of chip forms; favourable and unfavourable chip forms The type and form of the chip, as well as the manner of its removal from the cutting zone is of particular importance in the process of automatic production. In principle one can separate short (preferred) from long (continuous, adverse) forms in terms of favourable and unfavourable chip forms. Undoubtedly, there is a series of transitional forms in between them. The long, continuous chips are considered unfavourable as they cause a large number of faults when working on the machine: 1. Interruption of the machining process for machine servicing. The machine must be stopped frequently to remove the wounded chip. 2. Damages the finished area, especially in automatic machine tool. 3. Chip Transportation is rendered across the rake face and tool holder that might cause damage and breakage of tools. 4. Increases injury risk for machine operator. When working on manually operated machines, the problem of chip flow is important in terms of protection of operators rather than in terms of chip flow, because the machine can be stopped and the wounded chips removed by the operator. With automatic machines, the problem of chip form and the ways of its removal is of particular importance. Unfavourable chip forms are present in the turning and milling process due to its machining principle, whilst in other processes favourable chip forms occur. These two processes comprise about 70% of all machining, so the question of forms and types of chips, as well as ways of their removal are very important. In principle, the chip shape and dimensions can be manipulated in two ways: 1. Choice of tool geometry and machining regime – the tendency of chip breakage increases by decreasing the values of rake angle, by reduction of the cutting speed or by increasing the feed rate and depth of cut. It is often impossible to set these parameters in order to obtain the desired shape of chips, and thereby achieve an appropriate, costeffective and productive processing. The reduction of the cutting speed often leads to a reduction in production economics (longer production time). 2. Planned chip breaking – this application is particularly present in turning, and can be accomplished in several ways: By using fixed and adjustable chip breakers on the tool rake face; By creating longitudinal grooves on the surface of the workpiece by milling or by using lasers; With the addition of alloying elements in the material of the workpiece; By cutting with two knives set at an angle of 45°; By periodic interruption of cutting through the control system; By turning with tools for milling (driven tools); By using high-pressure jet assisted machining, etc. All of these approaches, except for the chip breaker, require additional, expensive equipment on the machine, so the chip breaker approach is still the most applied. The shape of the cutting edge, geometry of the insert, shapes and geometry of the chip breaker, cutting regimes, and rigidity of the machine tool are of vital importance for the chip formation process and tool life. The geometry of the insert, especially rake angle and cutting regime (feed rate) have the most important role in the process of chip formation. Taking into account that 80% of the generated heat in the cutting zone is removed by chip, it is obvious how significant is the matter of chip breakage and its fast evacuation from the cutting zone. 45 METAL CUTTING – Theory and Applications One is faced with the problem of selecting the appropriate criteria when rating and classifying chips. Chip dimensions, bulk gravity and radius of curvature are preferred because number indication gives uniform ranking. Practice has shown that the detection of these numbers is complicated and time-consuming. Better chip assessment allows tables. Many different tables for chip classification indicate that there is still no optimal classification. The forms of unbroken - continuous to broken chips are presented in Figure 3.5. The ranking is done according to the extension rather than the radius of curvature. For the classification of different forms in appropriate groups, a special row with characteristic values is given in the table in Figure 3.5. 1. 2. 3. 4. 5. Ribbon chip Snarled chip Flat helical chip Angular helical chip Helical chip 6. 7. 8. 9. 10. Helical chip segment Cylindrical helical chip Spiral chip Spiral chip segment Discontinous chip Figure 3.5 Classification table for chip shape assessment in turning operations [7] Natural chip flow means its free flow across the rake face of the tool. Such chips can eventually break due to internal stresses or their own weight, even though most of them are long and unbroken, Figure 3.6. These correspond to the types and forms of chips from 1-6 in Figure 3.5. Figure 3.6 Natural chip flow 46 Figure 3.7 Chip breaks on obstacle Figure 3.8 Short, favourable shape of chips CHIP SHAPES AND TYPES Chips do not usually flow freely across the tool rake face, they come across an obstacle, be it the tool or the workpiece. Either because of its self-bending or because of the shape of the cutting tool, the chip comes across a barrier - the tool or the workpiece, Figure 3.7. The chip is broken due to the increased bending. This way, chip forms from 4 to 10 are created (table in Figure 3.5). Figure 3.8 shows the short, desired shape of chip. 3.3 Experimental chip shape determination It is obvious from Figure 3.1 that a large number of factors affect the chip shape. In experimental studies, the determination of the chip shape is carried out for the workpiece – tool pair. In various machining processes the impact of regimes on the chip form is different. Nevertheless, it is the cutting depth and the feed rate that have the greatest impact. Based on this, a diagram of chip forms depending on these two parameters has been made. Figure 3.9 shows the forms of chips, depending on the depth of cut and feed rate for a particular tool – workpiece pair. γ α λs r εr r - 6 6 - 6 75 90 0.8 mm Figure 3.9 Diagram with a photograph of chip shapes depending on depth of cut and feed rate for defined tool-material pair [7] 47 METAL CUTTING – Theory and Applications To determine the utilization area of chip shapes, chips are evaluated according to the following criteria: good, acceptable and unfavourable. Based on this classification, it is possible to simplify the previous diagram (Figure 3.9) with the one in Figure 3.10 where the shaded area shows favourable (+) chips, and the rest of the diagram shows the area acceptable (±) and unsuitable (nonacceptable) (-) chips. Figure 3.10 Diagram of favourable, acceptable and nonacceptable chip areas [7] The same result is shown in Figure 3.11, however in a different form. In this diagram, limits of the formation of favourable shape filings with aspects of feed and depth of cut are precisely defined. When defining these diagrams during experimental tests, other processing parameters (type of workpiece material, cutting speed, types of tools, etc.) typically do not change. Figure 3.11 Determination of area for favourable chip shape formation for different values of feed rate and depth of cut [6] 48 CHIP SHAPES AND TYPES This way it is very easy to create diagrams of optimum cutting data for a variety of cutting tools depending on the feed rate and depth of cut and other important parameters. The making of these diagrams of chip forms has a particular significance in automated production. The proper selection of the cutting regime directly affects the processing with increased productivity and reduced downtime due to the machine, tool or workpiece failure. When optimizing cutting data from the point of forming a favourable chip form in compliance with used cutting tools, one cannot speak of a single-unambiguous approach in order to simultaneously achieve optimum costs and optimum technology for the manufacture of a certain product. Figure 3.12 Two approaches for optimization of technological and economic parameters [6] Figure 3.12 a) and b) shows two possible approaches to optimize the high-tech process with regard to the processing costs. Figure 3.12 a) shows three different areas of origin of favourable chip form with respect to feed rate and cutting depth, regarding the type of processing (rough, semi, finish). In this example are used three tools, which are specific and intended for certain type of machining (rough, semi, finish). Tools for semi machining and recommended values for feed rate and depth of cut allow roughing and finishing, but only up to a certain limit. Restrictions or the area of favourable chip forms is primarily determined by the cutting insert geometry , chip breaker, ... Tools for semi machining conditions can be used for a wide range of cutting conditions, however in this case very fine or very rough machining with these tools is not productive. Very fine machining for getting high quality machined surfaces (very low surface roughness) requires a different form of the cutting tool blade and different regimes in order to create favourable chip forms, and indirectly the corresponding surface integrity and processing costs. On the other hand, that same tool is very unprofitable for very rough machining conditions. Due to the geometry of the tool and demanding machining conditions, adverse chip are formed, which increases tool wear and can reduce its stability. Another approach to the optimization of the cutting process is shown in Figure 3.12 b). Recent detailed and extensive studies that refer to the cutting zone, new materials, chip formation conditions, etc., offer as a result the market tools that can be used in rough, medium and finish machining. Specially adapted geometry of the cutting insert with special chip breakers creates favourable conditions for chip formation in a wide range of cutting regimes, i.e. depth of cut and feed rate. Likewise, the material properties of cutting tools adapted to a wide range of cutting regimes certainly determine the higher cost of the tool. However, extreme regimes for finishing as well as for roughing do not allow the creation of favourable chip forms, so it is better to use the tools that are designed especially for rough or finish machining. 49 METAL CUTTING – Theory and Applications Naturally, the question then arises as to which approach is better in the optimization of the machining processes. It is difficult to give an answer to this as it depends on many factors and parameters pertaining primarily to the workpiece material, equipment, machine tool, available funds for tools, but also on decisions made by the machine operator, and eventually on the company policy [8, 9]. 3.4 Main conclusions regarding the creation of favourable chip forms Studies have shown that favourable chip formation depends on: Workpiece material and its structure; brittle materials are easier to handle. Depth of cut and feed rate have the greatest impact, therefore with the change of these two parameters one can easily create a diagram of favourable chip shapes. To some extent, the cutting speed has a smaller impact on the chip shape and it must be selected according to the productivity and power of machines. Very important is the material and the tool geometry. With correct choice of chip break geometries, energy consumption for cutting could be 20% less. One must not ignore the influence of other parameters, such as: tool wear, coolant and lubrication fluid, stiffness of the tools, etc. To achieve favourable chip forms, a greater cutting depth should be selected as thicker chips are easier to break. Increasing the cutting depth can reduce the number of necessary cuts, and thus the main and auxiliary processing time. At the same time, it is better to choose a higher feed rate to obtain a more favourable chip form, which shortens the processing time. Also the specific cutting force is smaller and the process productivity is higher. However, the depth of cut and feed rate are usually limited to other criteria that should be considered for quality assurance. If the depth of cut is too large, the cutting forces will suddenly increase and might significantly reduce the tool life. Excessive feed rate value has a direct impact on reducing the high surface quality (increased surface roughness). Favourable chip formation leads to: Safe working process. Satisfactory quality of machined surface. Possibility of automation due to uninterrupted processing procedures. Increased productivity. Greater tool stability. Simpler transport and storage of the chips. Achieving favourable chip forms represents a proof of a good selection of the cutting regime and cutting conditions, a key to productive process from the economic and technological point of view. 3.5 Laboratory work – Determination of shape and type of the chips This laboratory work is divided into two parts. The first part of the work consists of the determination of favourable, acceptable and adverse chip forms in turning. During the experiments, machining regimes vary (depth of cut and feed rate), while the other processing parameters (material of the workpiece, tool, cutting speed) are kept constant (Table 3.3). The determination is made according to the classification table (Figure 3.5) which is handed out to each student and is part of the form for the laboratory work. 50 CHIP SHAPES AND TYPES The second part of this laboratory work relates to the definition of the fields of depth of cut and feed rate where favourable (+), acceptable (±) and unfavourable (-) forms of chips occur (Table 3.4). Precisely, the second part of the work pertains to the determination of boundaries to create favourable chip forms for different values of depth of cut and feed rate. Based on the defined area of favourable chip forms, a diagram of favourable chip formation (region of operability) is created; Table 3.5. Theoretical background and recommendations for the laboratory work performance are given in the previous paragraphs. A. Laboratory work Task. Identify the type and form of chips for different cutting regimes. Enter results and conclusions into the tables. Table 3.3 Measuring instruments and accessories No. Name and characteristics 1 Metal box for chip collection Figure Accessories for chip evaluation 2 Digital camera Scale paper Flashlight The measurement procedure: 1. 2. 3. 4. 5. 6. Choosing machine tool and cutting tool for experiment Choosing the value of depth of cut ap and feed f Collecting chips in a metal box for each cutting regime combination Taking photos and classification of the chip for each cutting regime Estimate the chip for suitability Draw the diagram of acceptable cutting regimes (region of operability) 51 METAL CUTTING – Theory and Applications Table 3.4 Machine tool data Elements Values Machine tool Type Designation Power P (kW) Feed range (mm/rev.) Spindle speed range (rev./min) Adopted revolution speed nr (rev./min) Tool Designation Tool wedge angle α = β= Tool cutting edge angle, nose radius κr = rε = Workpiece Tool-overhang ln (mm) Material designation Hardness HRC Tensile strength Rm (N/mm²) Dimension D L (mm) Figure 3.13 Background for photos of chips with scale 52 γ= CHIP SHAPES AND TYPES Table 3.5 Chip classification sheet – photos Depth of cut ap [mm] 0.5 1.5 2.5 3.5 4.5 0.20 0.30 0.40 0.50 Feed f [mm/rev.] 0.10 0.05 0.02 vc = 250 [m/min] 53 METAL CUTTING – Theory and Applications Based on the photos filled in Table 3.5 classify suitability of chips, and represent results into the Table 3.6. Define the regime of operability based on chip form criteria. Tabela 3.6 Chip classification sheet – definition of suitable regimes Depth of cut ap [mm] 0.5 1.5 2.5 3.5 4.5 0.10 0.20 0.30 0.50 0.40 Feed f [mm/rev.] 0.05 0.02 vc = 250 [m/min] Remarks 54 ± + unsuitable acceptable favorable CHIP SHAPES AND TYPES Literature: [1] Globočki-Lakić, G.: Metal cutting process – theory, modelling and simulation, Faculty of Mechanical Engineering, Banja Luka, 2010 (in Serbian) [2] Lazić, M.: Metal cutting process, Faculty of Mechanical Engineering, Kragujevac, 2002 (in Serbian) [3] Armarego, E. J. A., Brown, R. H.: Обработка металов резанием, Машиностроение, Moskva, 1997 (in Russian) [4] Бобров, В. Ф.: Основы резания металов, Машиностроение Moskva, 1975 (in Russian) [5] Milikić D., Gostimirović M., Sekulić M.: Basics of machining technology, Faculty of Technical Science, Novi Sad, 2008 (in Serbian) [6] Sandvik Coromant: Metal Cutting Technology, Technical Guide, 2010 [7] Cedilnik M., Rotar V., Kopač J.: Cutting 1, supplementary material for lectures and exercises, script, Ljubljana, 2006 [8] Kramar, D., Krajnik, P., Kopač, J.: Capability of high pressure cooling in the turning of surface hardened piston rods. Journal of materials processing technology, 2010, vol. 210, iss. 2, 212-218 [9] Globočki, L. G., Sredanović, B., Kramar, D., Nedić, B., Kopač, J.: Experimental Research Using of MQL in Metal Cutting, Journal Tribology in industry, 2013, Volume 35, No. 4, 276-285 55 CHAPTER IV CHIP COMPRESSION RATIO Contents 4.1 4.2 4.3 4.4 Theoretical considerations Influence of the cutting regime on the chip compression ratio Experimental determination of the chip compression ratio Laboratory work – Determination of the chip compression ratio 4.1 Theoretical considerations The chip formation process occurs due to the local plastic deformation of the workpiece material. The thickness of the shear zone, i.e. the thickness of the zone of plastic deformation is affected by the type of workpiece material and the cutting conditions. At high cutting speeds when using tools with small or negative values of rake angle, the thickness of the shear zone is relatively small, so that it can be approximated by a shear plane. The chip formation process goes through several stages, Figure 4.1, which is explained in detail in Chapter 3. Figure 4.1 Stages in chip formation process [1, 2] High specific heat and mechanical loading lead to high temperatures up to 1600 K and contact pressures up to 35000 MPa, suitable for BUE occurrence on the surface of the tool rake face, Figure 4.2. The role of BUE has different sides; it can be considered as a positive property protection of the rake face against the wear, while on the other hand, BUE may cause tearing of the tool material when removed from the surface. This changes the tool geometry and puts at risk the quality of machining. The following are used as parameters for the chip material deformation process: chip compression ratio, relative sliding, relative speed of sliding, squared elongation, relative dilation, and actual or logarithmic degree of deformation. Figure 4.3 presents the definition of the chip compression degree. 57 METAL CUTTING – Theory and Applications Figure 4.2 BUE formation at the rake face [2] The chip compression ratio λch is commonly used to identify the degree of chip deformation - it represents the ratio between chip thickness hch and undeformed chip thickness h (i.e. depth of cut ap): 2 5 4.1 Large values of the chip compression ratio must be avoided as a higher degree of deformation requires greater energy consumption. The cutting process is carried out well if 2 < λch <3. According to these values of the chip compression ratio λch, one can conclude that the chip speed on the tool rake face is much lower than the cutting speed. Figure 4.3 Definition of chip compression ratio [1, 2] Values of the chip compression ratio λch can be defined based on the values of rake angle γ and shear angle ϕ. The chip compression ratio λch can also be defined as the ratio between the cutting speed vc and the chip sliding speed on the tool rake face vch, Figure 4.4. 58 CHIP COMPRESSION RATIO Figure 4.4 Definition of chip compression ratio λch [1, 2] According to Figure 4.4, one can make the following equation to define the values of the chip compression ratio λch: 4.2 For a particular type of material, for which the shear angle ϕ is approximately constant, one can conclude that the chip compression ratio λch will then depend on the rake angle γ only. If the value of rake angle γ increases, the chip compression ratio λch decreases, which is logical because a sharp tool easily penetrates the material and cutting is done with a lower degree of deformation. However, one should be careful and rational when increasing the values of rake angle γ. If the increase is too big, the cutting wedge will lose strength. 4.2 Influence of the cutting regime on the chip compression ratio The value of the chip compression ratio λch depends on mechanical properties of the material, tool geometry, cutting regime, and cooling and lubrication conditions. By increasing material plasticity, the chip compression ratio increases because plastic materials deform more easily than brittle ones. From the point of view of tool geometry, rake angle of the cutting tool wedge γ has the greatest impact on the chip compression ratio. With the increased value of this angle, cutting tool easily penetrates into the material of the workpiece, chips are less deformed, and the value of the chip compression ratio drops. This has been demonstrated in a number of researches noting that with increased rake angle γ, friction force on the tool rake face decreases, while the shear angle ϕ increases. The fact is that by increasing the shear angle ϕ, the value of the chip compression ratio λch reduces, as evident from the Eq. 4.2. One can also conclude from the same equation that increasing the depth of cut will decrease the chip compression ratio λch, Figure 4.5 (increasing the depth of cut ap will increase the shear angle ϕ as well). The influence of the feed rate on the chip compression ratio λch is monitored through chip thickness hch. Increased chip thickness (with decreasing feed rate) increases the chip compression ratio, resulting from the shear angle ϕ increase. 59 METAL CUTTING – Theory and Applications Figure 4.5 Effect of cutting speed and depth of cut on chip compression ratio λch [1, 3] There will be a non-monotonic change in the value of the chip compression ratio λch with the increase of the cutting speed, Figure 4.5. The change of λch with the change of the cutting speed v is conditioned by high mechanical and thermal stresses which occur in the cutting zone and by the formation of BUE on the cutting tool. The minimum value of the chip compression ratio is favourable for the conditions in which occur the largest deposits on the tool. Characteristic saddle point (λch,max) is moved to the field of lower cutting speeds when machining ductile materials using smaller values of the rake angle γ and a smaller depth of cut ap. By increasing the cutting speed, BUE is growing and thus increasing the real - effective value of the rake angle γ. As a result, the chip compression ratio decreases to a minimum. With further increase in the cutting speed, BUE does not form and the chip compression ratio reaches its maximum. With still further increase of the cutting speed, λch decreases as the softening of the material occurs near the top of the cutting edge. This softening of the material results from high temperatures in the cutting zone as well as from the reduction of the friction coefficient on the tool rake face [4]. The type, concentration and flow rate of the coolant and lubricant significantly affect the reduction of the chip compression ratio. 4.3 Experimental determination of the chip compression ratio The value of the chip compression ratio can be experimentally determined in three ways: by measuring the cutting speed vc and the speed of chips vch, by volumetric method, and by a weight basis. Volume and mass methods are very simple and can be applied in each laboratory because they do not require special equipment. Volumetric method is based on the equality of the volume of the removed layer of material before cutting V and the volume of cut chips Vch. The assumption is that the width of the chip bch is approximately equal to the width of cutting b, i.e. the deformation of material by width is minimal. By adopting this assumption one can note: where is V=Vch, i.e. h∙b∙l = hch∙bch∙lch, 4.3 b≈bch, follows 4.4 hch l ch h lch 4.5 where: l – length of material, or the length of the tool path, lch – length of the chip. 60 CHIP COMPRESSION RATIO When applying this method, it is simply necessary to measure the chip length and calculate the chip compression ratio. In cases where it is difficult to straighten the chip, its length can be measured using a thin, soft wire that passes through the inside of the chip, cut off at the ends, and then accurately measured. Mass method is based on the equality of the chip mass and the mass of removed material before cutting, and is slightly more accurate than volumetric method. Taking into account again that the width of the cut layer b is approximately equal to the width of the chip bch, a simple mathematical Eq. 4.6 can be derived: ∙ ∙ ∙ ∙ ∙ ∙ ∙ 4.6 where: mch – chip mass, lch – chip length, ρm – chip specific mass. Taking into account the Eq. 4.6, and the value of the chip width bch, the chip compression ratio λch can be calculated using the following equation: ∙ ∙ where: ∙ ∙ ∙ ∙ 4.7 ∙ , cross section. By applying this method, the following features can be measured: the length of chips lch, the mass of chips mch and the specific mass ρm by pycnometer. 4.4 Laboratory work – Determination of the chip compression ratio The aim of this experimental work is to analyse the process of deformation in the cutting zone, exploring the nature of chip formation and to confirm the acquired theoretical knowledge. The process of chip formation, which is analysed by the chip compression ratio, is of crucial importance for the machining system. The chip compression ratio refers to consumed power, the influence of the tool geometry and workpiece material on machining system and machining process. In order to successfully optimize the machining study, analysis and modelling (or the knowledge acquisition) about the process of formation and deformation of the chips must be carried out. This is the aim of this experimental work. In a laboratory work, the previously described mass method is applied. By measuring the mass and the length of the chips, the chip compression ratio λch and the shear angle ϕ can be calculated. Test equipment consists of the following elements: 1. Metal box for chip collection, 2. Workshop calliper, 3. Analytical balance, accuracy of 0.01 grams. The measurement procedure, Figure 4.6, is performed in the following manner; machine tool is set and adjusted for the experiment, i.e. feed rate f and depth of cut ap, marking on the workpiece is made for the adopted length of machining and simultaneously the diameter of the workpiece is measured. During machining, the chips are collected in a metal box. When the tool tip reaches the point where the length of cutting is marked, the process is stopped. After collecting the chips, the measuring of the chip mass and length begins. The chip will usually form a spiral, so the measurement is carried out by the recalculation from step, diameter and length of the chip spiral measurement, Figure 4.6. This procedure describes one run of the experiment or one cycle of measurement. Other measurements are performed with a different combination of cutting conditions. 61 METAL CUTTING – Theory and Applications All combinations of the machining conditions and all measurements are recorded in a spreadsheet included in the report. Measured quantities are recalculated using forms provided in the table 4.1, to finally calculate the appropriate level of the chip compression ratio λch and shear angle ϕ. Figure 4.6 Mass method for chip compression ratio determination [1, 2] A. Laboratory work Task. For a determined cutting regime, measure the chip compression ratio λch and calculate the shear angle ϕ. Table 4.1 Measuring instruments and accessories No. Name and characteristics 1 Metal box for chip collection Caliper 2 Measuring range: 0 - 150 mm Accuracy: 0.01 mm Analytical Balance 3 62 Range: -500 … +1000 g Accuracy: 0.01 g Figure CHIP COMPRESSION RATIO Measurement procedure: 1. Choosing machine tool and cutting tool for experiment 2. Defining the length of machining lm 3. Choosing the value of rake angle γ and feed f 4. Collecting the chips in a metal box for each cutting regime combination 5. Measuring the length of the chips for each combination lch 6. Weighing the chips for each combination. Table 4.2 Machine tool data Elements Values Workpiece Tool Machine tool Type Designation Power P (kW) Feed range (mm/rev.) Spindle speed range (rev./min) Adopted revolution speed nr (rev./min) Designation Tool wedge angle Tool cutting edge angle, nose radius Tool-overhang ln (mm) Material designation Hardness HRC Tensile strength Rm (N/mm²) Specific mass ρm (kg/m³) Dimension D L (mm) Machined length lm (mm) α= κr = β= rε = γ= Table 4.3 Measurements and calculations sheet (case study) 1 2 3 4 5 6 7 8 9 Rake angle Feed γ [°] f mm/o Selected Selected 12 12 12 6 6 6 2 2 2 0.165 0.175 0.330 0.165 0.175 0.330 0.165 0.175 0.330 Length of the tool Chip length path l mm ∙ ∙ 9520 8976 4760 9520 8976 4760 9520 8976 4760 Chip mass Chip compression ratio lch mm mch g λch - Measured Measured 1322 1264 1127 2434 2226 1687 2261 2199 1268 10.00 9.66 7.68 19.32 17.14 17.00 24.16 23.78 22.31 ∙ ∙ 2.92 2.78 1.32 3.06 2.80 1.95 4.12 3.94 3.40 Shear angle ϕ [°] ∙ 19.8 20.8 41.5 18.6 20.2 28.4 13.7 14.4 16.6 63 METAL CUTTING – Theory and Applications Using MS Excel, a diagram is drawn showing the influence of feed and rake angle on shear angle, where one must take into account the conversion of degrees to radians and vice versa, Figure 4.7. Figure 4.7 Influence of feed on shear angle for different values of rake angle The following functional dependence is given when using regression analysis (LINEST): 32.418 ∙ . ∙ . Using MATLAB and the following program code, a three-dimensional graph of the aforementioned dependence is provided: vg=1:.01:12; vf=0.1:.001:0.4; [g,f] = meshgrid(vg,vf); C=32.418; F = C.* (f.^0.313 + eps) .* (g.^0.635 + eps); mesh(g, f, F) colorbar Figure 4.8 Influence of feed and rake angle on shear angle 64 CHIP COMPRESSION RATIO B. Practical tasks and calculations Task 1. Turning is performed on a universal lathe. Workpiece diameter is D = 50 mm. After machining, which is done in i = 3 passes, the final workpiece diameter is d = 38 mm. The spindle speed is n = 316 rev./min. The selected cutting insert has the following geometry: clearance angle α = 8°, and the angle of the tool wedge β = 78°. Chip velocity vch = 90 m/min is determined by measuring. With given processing data, calculate the chip thickness hch and the shear angle ϕ. Solution: First, one must calculate the depth of cut ap at the last passage (assuming that the process is running with the same dimensions of the tool at each passage): ap D d 50 38 12 2 2i 23 23 mm Cutting speed vc at last passage is: d 2 a p n 38 2 2 316 vc 41.7 1000 1000 m/min The chip compression ratio λch amounts to: ch vc 41.7 2.32 vch 18 Chip thickness hch is then: hch ch a p 2.32 2 4.64 mm To calculate the shear angle ϕ, it is necessary to know the value of the rake angle γ, which is calculated from: 90 90 8 78 4 or 4 / 180 0.069 rad And finally the shear angle ϕ amounts to: arctg cos cos 4 arctg 23.9 2.32 sin 4 ch sin 65 METAL CUTTING – Theory and Applications Task 2. Turning is performed on a universal lathe at feed rate f = 0.2 mm/rev. Workpiece diameter is D = 50 mm. After machining, which is done in i = 3 passes, the final workpiece diameter is d = 38 mm, and the length of cutting L = 15 mm. The spindle speed is n = 316 rev./min. Selected cutting insert has the following geometry: clearance angle α = 8° and the angle of the cutting wedge β = 78°. The mass of the chips mch = 19 g and the length of the chips lch = 2500 mm is determined by measuring. The density of the workpiece material is ρ = 7.85·10-3 g/mm3. With given conditions, calculate the chip velocity vch and shear angle ϕ, on the assumption that the width of the cutting layer has not changed during processing. Solution: First, one needs to calculate the depth of cut ap at the last passage (assuming that the process is running with the same dimensions of the tool at each passage): ap D d 50 38 12 2 mm 2i 23 23 The chip compression ratio λch amounts to: ch mch mch 19 2.42 A lch m a p f lch m 2 0.2 2500 7.85 103 Cutting speed vc at last passage is: vc d 2 a n 38 2 2 316 41.7 m / min 1000 1000 p Chip velocity vch sliding over the rake face of the blade is then: vch vc ch 41.7 17.23 m / min 2.42 To calculate the shear angle ϕ, it is necessary to know the value of the rake angle γ, which is calculated from: 90 90 8 78 4 or 4 / 180 0.069 rad And finally the shear angle ϕ amounts to: arctg 66 cos cos 4 arctg 23 ch sin 2.42 sin 4 CHIP COMPRESSION RATIO Remarks Literature: [1] Globočki-Lakić, G.: Metal cutting process – theory, modelling and simulation, Faculty of Mechanical Engineering, Banja Luka, 2010 (in Serbian) [2] Globočki-Lakić, G., Sredanović, B.: Supplementary material to perform laboratory exercises in metal cutting process, Faculty of Mechanical Engineering, Banja Luka, 2011 (in Serbian) [3] Lazić, M.: Metal cutting process, Faculty of Mechanical Engineering, Kragujevac, 2002 (in Serbian) [4] Nedić, B., Globočki-Lakić, G.: Development Model for Control of Metal Cutting Process, 10th DEMI Conference, Banja Luka, Bosnia and Herzegovina, 2011, 309-315 67 CHAPTER V CUTTING FORCES Contents 5.1 5.2 5.3 5.4 5.5 5.6 5.7 Theoretical considerations Determination of specific cutting forces Determination of the resultant cutting force components Statistical evaluation of experimental results Cutting force components measuring system Laboratory work – Measurements of cutting force components Final conclusions 5.1 Theoretical considerations Cutting forces and torques represent the characteristics of the state and behaviour of the cutting process. Cutting forces are one of the most important machining parameters. Knowledge of the size and direction of the resultant cutting force F and its components: main cutting force Fc, feed force Ff, and passive force Fp is very important for: 1. Design of the machine tools (supporting structure, selection and definition of the operation, budget, and guiding system) 2. Selection of the cutting and working conditions in the technological preparation, 3. Assessment of the processing accuracy due to deformation of the machining system, 4. Analysis of phenomena in the cutting zone and definition of the tool-wear mechanisms, 5. Vibration analysis in the cutting process and dynamic behaviour of the machining system. The size of cutting forces is the criterion for the evaluation of machinability, because in the processing of hard-to-machine materials higher cutting forces appear. The size of the cutting force as well as workpiece materials affect a range of other factors, Figure 5.1. Penetration of the tool wedge into the material of the workpiece causes cutting resistance by the action of internal forces in the material. The resultant force F, represented here in the turning process as an example, can be decomposed into the following components: cutting force Fc, feed force Ff and passive force Fp (Figure 5.2). These resultant force components are usually detected metrologically by using piezoelectric force sensors explained in detail further in this chapter. 69 METAL CUTTING – Theory and Applications Figure 5.1 Factors affecting the size of cutting forces [1] The first component is the main cutting force Fc whose vector operates at the tool contact point with the machined surface in the direction of the cutting speed vector. Passive force Fp represents resistance to the tool penetration into the workpiece material, and acts perpendicular to the machined surface. In oblique cutting, there is resistance to feed motion, i.e. feed force Ff, which acts counter feed direction. Figure 5.2 Resultant force F and its components in the cutting process, acc. to DIN 6584 70 CUTTING FORCES Figure 5.3 Components of resultant force in working plane For each type of cutting (Figure 5.4), the analysis of forces derived for the orthogonal cut by Merchant is the basis for determining the forces acting on the tool cutting edge, as shown in Figure 5.3. Resultant cutting force FR can be divided into: Tangential force (friction force) FT and normal force FN, Tangential force of shear plane (share force) Fϕ and normal share force FϕN, Major cutting force Fc and passive force Fp, and also feed force Ff in oblique cutting. In practice is the most significant the relationship between friction force FT and FN, which determines the coefficient of friction μ on the tool rake face, i.e. friction angle ρ, because it allows the calculation of the individual components of the resulting cutting force, Eq. 5.1: tg FT FN 5.1 Expressions for the calculation are usually determined depending on the main cutting force Fc. Other components of the resulting force can be calculated on the basis of the main cutting force. Based on the resulting cutting force F and the main cutting force Fc, other components of the resulting cutting force can be defined as: F Fc cos and F p Fc tg FT F sin Fc FN F cos Fc sin FN cos cos cos F F cos Fc cos cos 5.2 5.3 5.4 5.5 71 METAL CUTTING – Theory and Applications Figure 5.4 Components of forces for different types of machining [2, 3] Based on the measured values of the force components Fc and Fp, it is possible to determine the value of the angle of friction and friction coefficient . tg 72 Fc sin F p cos Fc tg F p FT FN Fc cos F p sin Fc F p tg 5.6 CUTTING FORCES The average normal and tangential stresses originating from the resultant force components acting on the rake face can be calculated using Eq. 5.7 and 5.8. F N A F A sin Fc sin Fp cos a pb 5.7 sin Fc cos Fp sin a pb 5.8 where: A a pb A – shear plane area, sin sin ap – depth of cut [mm], b – width of cut [mm], – shear angle. Derived expressions for calculating the cutting forces in orthogonal cutting indicate that the cutting force and, thus, the power consumption depend on: Workpiece material properties (stresses , ), Tool geometry (rake angle), Friction in the contact zone between the tool and the workpiece material, Machining geometry (depth and width of cut). The size and direction of the resultant force are strongly influenced by the cutting parameters and cutting section geometries used [4 - 6]. Figure 5.5 shows the dependence of the static components of the resultant cutting force Fc, Ff and Fp on the feed f, cutting speed vc, depth of cut ap and the tool cutting edge angle κr qualitatively in a linear coordinate system. The extremes in the profiles of the resultant force components over cutting speed can be ascribed to growth of built up-edge (BUE). The reduction of forces with increasing cutting speed is caused by the reduction of material strength at higher temperatures. The components of the resultant force increase proportionally over the depth of cut ap. Yet this is only valid if the depth of cut is larger than the corner radius of the tool. The profile of feed force Ff and passive force Fp over the tool cutting edge angle κr results from the geometric position of the cutting edge with respect to the workpiece axis, since with a larger cutting edge angle the resultant force component aimed in the feed direction increases, and its maximum is reached at κr= 90°. If the tool cutting edge angle is increased, the undeformed chip thickness h increases proportionally to the reduction of the width of undeformed chip b. Since cutting force Fc is proportional over depth of cut ap ( width of undeformed chip b) but increases degressively over feed f ( undeformed chip thickness h), a light reduction of Fc with increasing κr is the outcome of both changes. 73 METAL CUTTING – Theory and Applications Figure 5.5 Components of resultant force depending on feed f, cutting velocity vc, tool cutting edge angle κr, and depth of cut ap (qualitative) The influence of the tool geometry (Figure 5.6) includes tool wedge angle, tool cutting edge inclination s, tool tip radius r and tool cutting edge angle κr. For example, the value of the clearance angle does not substantially affect the cutting force, whilst a 1° change in the rake angle leads to a 1-2% change in the main cutting force. Reducing the value of the rake angle will lead to cutting forces being reduced but will decrease the tool strength and might cause its breakage. The strongest cutting edge is achieved with a negative rake angle value. The tool cutting edge inclinations has only a slight influence on cutting forces, mostly on the radial component – passive force Fp. Tools with high values of the inclination angle generate high impact forces that cause buckling (deflection) of the workpiece. Otherwise, this force is very small when using a tool with major tool cutting edge angle κr= 90. In this case, it is also possible to process small-diameter workpieces. Major tool cutting edge angle κr also significantly affects the cutting force Fc (also the force components Fp and Ff) due to changes in chip shape and dimensions. 74 CUTTING FORCES Figure 5.6 Influence of tool geometry on cutting forces [2] If there is alteration in cutting forces in a time period with the processing parameters remaining unchanged, it is obvious that the value of the cutting force changes with the processing time. In instances of a stationary random process, statistic parameters can easily be determined – the mean force (static component of the cutting force) and standard deviation as the dynamic component of the cutting force, Figure 5.7. Figure 5.7 Static FS and dynamic FD component of cutting force 5.2. Determination of specific cutting forces In the past there have been several attempts to mathematically describe the dependence of cutting force on influential parameters, but not very successfully. Kienzle and Victor established the principle of cutting force changes influenced by the relevant parameters, Figure 5.8. 75 METAL CUTTING – Theory and Applications Figure 5.8 Parameters influencing cutting force [1] If the components of the cutting forces are divided with the chip cross-sectional area, we get the factor of proportionality referred to as the specific cutting force ki; ki Fi bh i = c, f, p 5.9 The value of the specific cutting force is not constant but changes depending on the thickness of the chip. If we now plot the values thus found over undeformed chip thickness h in a double logarithmic plot, the measurement points arrange themselves in a straightline, Figure 5.9: ki ki ,1x1h mi i = c, f, p 5.10 ki,11 – unit specific cutting force; the cutting force required to detach a chip of undeformed chip width b = 1 mm and undeformed chip thickness h = 1 mm, mi – exponent. Figure 5.9 Influence of undeformed chip thickness h on specific cutting force ki [1] The corresponding linear equation log Fi / b log ki ,11 1 mi log h 5.11 can be converted into the Kienzle-Viktor Equation Fi b h (1 mi ) ki ,1x1 76 i c, f , p 5.12 CUTTING FORCES If one wants to track the dependence of the cutting force on the chip thickness, the previous equation can be easily written in the form: Fi Fi / b ki ,1x1 h1 mi 5.13 To determine ki,11 and (1–mi), cutting experiments are carried out for the combination of workpiece material and cutting tool material under investigation. In these experiments, the relevant cutting forces are measured with constant cutting speed, depth of cut and cutting section geometry and plotted in accordance with Figure 5.10. The required specific cutting force characteristic parameter ki,1x1 is determined by extrapolating the undeformed chip thickness to h = 1 mm. The tangent of the angle between the straight line and the x-axis is the desired gradient value (1–mi). Figure 5.10 Graphical determination of characteristic values ki,11 and (1–mi) Table 5.1 Experimentally determined values for specific cutting force [1] Specific cutting force kc (N/mm2) for different values of chip thickness h (mm) Tensile Material strength; No. hardness 1.0744 1.0050 1.0060 1.0070 1.0722 1.1221 1.7131 1.5920 1.7225 1.7220 1.8159 1.7262 1.1165 GGG70 GG 10 GG 15 GG 20 GG 25 340/370 520 620 720 670 770 770 630 730 800 600 590 770 300 HB 180 HB 180 HB 220 HB 220 HB Cast iron 55 HRC 0.063 0.08 2850 4080 3380 5180 3270 3500 4310 5180 5130 4000 4560 3660 3050 2550 1070 1700 2040 2380 3860 2730 3840 3240 4820 3160 3360 4050 4820 4820 3810 4280 3520 2830 2400 1040 1610 1920 2240 3690 0.1 2630 3620 3120 4510 3060 3220 3820 4510 4550 3630 4040 3390 2660 2260 1010 1540 1810 2110 3530 0.125 0.16 2540 3430 3000 4220 2970 3100 3610 4220 4290 3470 3810 3260 2540 2130 980 1470 1720 1990 3390 2430 3210 2880 3920 2870 2960 3380 3920 4030 3290 3580 3130 2350 2000 950 1400 1610 1870 3230 0.2 2340 3020 2770 3660 2780 2850 3190 3660 3800 3140 3370 3010 2180 1890 920 1330 1530 1760 3100 0.25 0.315 0.4 2250 2850 2670 3430 2700 2730 3010 3430 3580 3000 3180 2900 2050 1780 900 1270 1440 1660 2970 2170 2690 2570 3200 2610 2620 2840 3200 3380 2850 3000 2790 1920 1670 870 1210 1360 1570 2850 2080 2530 2470 2980 2520 2510 2660 2980 3170 2720 2820 2680 1830 1580 840 1150 1280 1470 2720 0.5 0.63 0.8 2000 2380 2370 2780 2450 2410 2510 2780 2990 2590 2660 2580 1770 1490 820 1100 1210 1390 2600 1930 2250 2280 2600 2370 2310 2370 2600 2820 2470 2500 2480 1740 1400 800 1050 1150 1310 2490 1850 2110 2190 2420 2290 2220 2230 2420 2650 2350 2350 2380 1700 1320 770 1000 1080 1230 2390 kc1×1 1-mc h=1 1780 0.83 1990 0.74 2110 0.83 2260 0.70 2220 0.86 2130 0.82 2100 0.74 2260 0.70 2500 0.74 2240 0.79 2220 0.74 2290 0.83 1680 0.72 1240 0.74 750 0.87 950 0.79 1020 0.75 1160 0.74 2280 0.81 5.3 Determination of the resultant cutting force components This chapter briefly presents theoretical equations for determination of the resultant force components for different machining operations. 77 METAL CUTTING – Theory and Applications 5.3.1 Components of resultant cutting force in turning Resultant cutting force F on a turning tool, which overcomes the cutting resistance, consists of three components: major cutting force Fc, feed force Ff and passive force Fp, Figure 5.11. Undeformed chip width: ap b sin r Undeformed chip thickness: h f sin r Figure 5.11 Components of resultant cutting force in longitudinal turning [1, 3] If we take into account the terms of the width and thickness of the chip, the expressions for the cutting force components are as follows: Fc A k c bh 1 mc k c ,11 F f A k f bh F p A k p bh 1 m f kc k f ,11 kf k p ,11 kp 1 m p Fc k c ,11 h mc bh Ff bh Fp bh 5.14 k f ,11 h m f 5.15 k p ,11 h m p 5.16 Resultant cutting force can be calculated using the following relation: F Fc2 F p2 F f2 78 5.17 CUTTING FORCES 5.3.2 Components of resultant cutting force in drilling In drilling, it is necessary to determine the moment of cutting Mc [Nm] and feed force, i.e. axial force Ff [N]. The cutting force is calculated from the equation of torque assuming that the force Fc/2 operates in the middle of the cutting surface, Figure 5.12. Cutting moment: F D Mc c 2 2 Undeformed chip width: D b 2 sin 2 Undeformed chip thickness: h f sin 2 2 Figure 5.12 Components of cutting force in drilling and the chip cross-sectional area [1, 7] If the main cutting force is represented depending on the chip cross-sectional area with Kienzle's equation: Fc A k c 2bh k c 2bh k c ,11 h mc . 5.18 If in the previous equation, the values for the width and thickness of the chip are entered, we get the expression for the specific cutting force kc: kc 4M c 1 Fc 2bh D 2bh kc 8M c . D2 f 5.19 The feed force can be calculated by similar expression: F f A k f 2bh k f 2bh k f ,1 x1 h m f , 5.20 and the specific feed force is: kf Ff 2bh . 5.21 79 METAL CUTTING – Theory and Applications 5.3.3 Components of resultant cutting force in milling It is typical for the milling process that the size and position of the cutting force components change during the process. Therefore, when considering this process, two coordinate systems have to be adopted: a fixed coordinate system of the machine tool (Fx, Fy, Fz) and a variable (co-rotating) coordinate system Fc, Ff, Fp on the cutting edge of the tool. For practical use of the measured values of the force components (Fx, Fy, Fz), the tangential component, i.e. peripheral cutting force Fc(), the radial component - feed force Ff() and the thrust component, i.e. passive force Fp() in the direction of the axis of the spindle, have to be calculated, Figure 5.13. Figure 5.13 Components of cutting force in face milling and chip cross-sectional area [1, 7] Tangential force: Fc Fx cos Fy sin 5.22 Radial force: Ff Fx sin Fy cos 5.23 Passive force: Fp Fz 5.24 The main cutting force can be expressed in Kienzle’s equation Fc bhm k c bhm1mc k c ,1x1 5.25 Undeformed width of cut b can be expressed by a similar equation as in case of turning: b 80 ap sin r 5.26 CUTTING FORCES Since the cross sectional area of the cut during milling varies, the geometric mean chip thickness hm is calculated, Figure 5.14: hm 2 f z sin 1 d fz 2 1 where: cos 1 cos 2 cos 1 a e 2e D 5.27 cos 2 ae 2 e . D 5.28 Finally, the mean thickness of the chip in face milling is, Figure 5.14, right: hm 2 ae fz fz a 2e ae 2e e D 2 1 D D 2 1 5.29 In the equation 5.29 we must write angles φ1 and φ2 in arched coordinates. Since the arc cos function has infinite solutions, the following values for both angles must be used: 0 1 / 2 and / 2 2 . Figure 5.14 Medium chip thickness for peripheral milling (left) and face milling (right) [8] and the mean thickness of chip for peripheral milling is, Figure 5.14. left: hm f z sin 0 d fz 1 cos 5.30 When replacing values from φ and sinφ, we will get 2 2 D D ap ap ap 2 2 2 sin 1 D D D 2 ap 1 cos sin D 2 2 D a p D 2a 2a p p 1 cos 2 D D D 2 5.31 5.32 5.33 81 METAL CUTTING – Theory and Applications fz ap hm D arcsin 5.34 ap D Value hm is calculated at half the angle φ, i.e. for ψ=φ/2. Since milling is an interrupted cutting operation, the angle of engagement φ refers to a certain number of teeth zFi z Fi z F (rad ) 2 5.35 where zF is a number of cutters teeth. When measuring forces, cutter with single blade is used so that the number of teeth zFi= 1. Simplifying the equations for the main cutting force Fc bhm k c bhm1mc k c ,1x1 , 5.36 we come to the expression for specific cutting force kc Fc kc ,1x1hmmc . bhm 5.37 In a similar manner the expression for feed force can be derived 1 m f F f bh m k f bh m k f ,1 x1 , 5.38 or for specific feed force kf Ff bh m m k f ,1x1hm f . 5.39 5.4 Statistical evaluation of experimental results In many experimental studies we want to determine the effect of one variable to another. In most cases the relation is not linear and we can find a bigger or smaller scatter in results, which is due to inaccuracies in the measurement of both variables or incorrect assumptions about a linear function. Statistical method to determine the linear relationship between the dependent and independent variable is called the linear regression, and result is the regression equation. Coefficients of the linear regression equation are usually determined by the least squares method. In order to obtain a linear form of the equation, an equation that connects the chip thickness and specific cutting force kc, has to be logarithmic: kc kc ,1x1h mc logkc logkc ,1x1 mc logh . 5.40 The last equation can be written in the following form: y a0 a1x 5.41 where: y = log (kc) x = log (h) 82 dependent variable independent variable a1 = - mc a0 = log (kc1x1) inclination angle section on the ordinate. CUTTING FORCES Table 5.2 The values of dependent and independent variables Independent variable x1 x2 x3 … … … xn Dependent variable y1 y2 y3 … … … yn a0+a1x1 a0+a1x2 a0+a1x3 … … … a0+a1xn Regression values of dependant variable The coefficients of the regression equation (a0, a1) are obtained using the least deviation of the measured values to the values obtained by regression equation. The sum of squares of all deviations must be minimal. Function S will have a minimum value only for those coefficients a0 and a1 for which its partial derivatives are equal to 0. 2 N S 0 a 0 S a0 a1xi yi i 1 S 0 a1 5.42 The system can be reduced to two inhomogeneous linear equations with two unknowns, i.e. the normal equations that can be solved using different methods (by use of matrix calculus, determinants application or by use of already made software). Using the method of least squares on a concrete example, and solving this system of equations, regression coefficients are obtained: log k c ,11 N N i 1 i 1 N N i 1 i 1 2 N N log hi i 1 N mc log kci log hi log hi log hi log kci 2 N log hi i 1 N 5.43 2 N N log hi log kci log hi log kci i 1 i 1 5.44 i 1 2 2 N log hi log hi i 1 i 1 N N Measure of connection between the two variables is the correlation coefficient r. Its values lie between +1 and -1. When the value is 0, there is no linear relationship between the two variables, and when the value is ± 1 the connection is linear. It is calculated according to the formula: N r N N i 1 i 1 N log hi log kci log hi log kci i 1 N N 2 N log hi log hi i 1 i 1 2 N N log kci i 1 2 log kci i 1 N 2 5.45 5.5 The cutting force components measuring system The measurement of forces in cutting is the result of problems encountered in the analytical determination of the cutting force components. Since it is impossible to measure the components of cutting forces in their positions, their reactions to a certain distance to the cutting edge are measured. So we need a measuring system which can perform accurate measurements regardless of the position of force or torque application. 83 METAL CUTTING – Theory and Applications The measuring system must meet the following requirements: to maintain the accuracy of the base, dynamic properties must be highly similar to the original situation, mounting the tool or workpiece should not significantly change its position, frequency response should be as wide as possible, the interaction between the components of forces and moments should be minimal, the sensitivity of the transducer has to be stable with time, temperature, and fastening tool and the workpiece, high resolution; the ability of measuring small changes in the forces and moments, easy to set a zero point, sensitivity, measuring ranges etc.. Systems for measuring forces were developed in university laboratories. These systems are described in detail in the literature and require highly skilled people and special equipment. The aim of the development of the measurement system is to provide industrial applied research with simple and effective measurement systems. These measurement systems should give answers to problems that arise in the design, manufacture and use of tools. They are utilized to exert comparing of the machinability of materials as well as for the optimization of machining parameters. Figure 5.15 Measurement system for measuring the cutting force components in the processes of drilling, milling and turning Figure 5.15 shows a measurement system for measuring the cutting force components in the processes of drilling, milling and turning, and is sufficient for all the requirements listed above. Piezoelectric sensor – dynamometer changes the mechanical signal into the electric one which is then amplified by the charge amplifier. Through the A/D digitizer the signal is transferred from the charge amplifier to a PC computer, where the appropriate software package calculates the specific cutting force. Piezoelectric principle: One of the properties of some crystals is that under mechanical load on their surface an electric charge will occur. This phenomenon is called piezoelectric effect, discovered by the Curie brothers in 1880th. These crystals are also called transducers, as they change mechanical load in electric charge. (Dynamo) meters are composed of several transducers, which are differently prestressed and calibrated. Quartz crystals are most commonly used for the force transducers, which are known as a very good piezoelectric material. Three piezoelectric effects are visible on the crystal, Figure 5.16. The electric charge, which is obtained on the surface of the crystal, is collected by the electrode. Charge is converted into an analogue voltage by charge amplifier. 84 CUTTING FORCES Longitudinal effect Electric charge Qe is proportional to the force F and independent of crystal size Transversal effect Electric charge Qe is proportional to the force F and to the crystal dimension ratio(y vs. x) Shear effect Electric charge Qe is proportional to the shear force F and independent of crystal size Figure 5.16 Piezoelectric effects in quartz crystal [1] Transducers: quartz crystals are cut in the crystallographic directions. This gives the crystal plates, which are brought into the steel casing of the force transducer. Steel housing provides uniform distribution of deformation of the crystal plates, while protecting them from dirt. Housing must be well insulated (resistance 1013 Ω). One should use the longitudinal piezoelectric effect when observing the forces acting on a single axis. The electric charge is proportional to the active force and is independent of the size of the crystal. Multi-component transducers are composed of several crystals which are mechanically arranged in series. Thus, a force is acting on each of the crystal and at the same time on all together. Each element is sensitive to the load in one direction only, since the crystal plates are cut in different crystallographic directions. This method allows the determination of the individual component of the force. To measure the shear effect, the crystal plates are attached to the steel plate through which shear stresses are transmitted, or by prestressing where achievement of sufficient friction between the surfaces is needed. 85 METAL CUTTING – Theory and Applications Transducers for torque measurements: can be made by the placement of small circular plates of crystal arranged in a circle. Orientation of their shear sensitive axes is tangent to the circle. The plates are mechanically and electrically parallel. Torque acting on the axis of the transducer causes an electrical charge that is proportional to the torque load. Again, the transducer is prestressed so that the frictional force between the elements is capable of transmitting torque. Described transducer is an essential part of the device for measuring the axial force and torque in drilling. Dynamometers: transducers can be used independently only in special cases. Most are set up as components of dynamometers. Their advantage is that each transducer is loaded in a particular direction designed in the construction of the dynamometer. The result is a much smaller load of transducers than in their sole use. Dynamometers also allow greater tolerance in point of application of the load. Thus, the force with constant magnitude and direction of operation but by changing the point of application always gives the same measurement results. Piezo-meters can be built in various forms and for various purposes. Operating range is very broad and different loads can be measured. In orthogonal turning, the following components of the cutting force are interesting: cutting force, feed force and passive force. Therefore, the tool is clamped in the threecomponent force piezoelectric sensor. The dynamometer is rigidly attached onto the lathe cross slide. In milling, two ways of force measuring can be used; mounting the workpiece on a threecomponent dynamometer, or mounting the transducer on the cutter. For small workpieces, the first method is more appropriate. Clamping of larger workpieces causes a problem. In this case, the second method must be used. This method is much more demanding. In drilling, feed force and torque of the main cutting force is measured. In addition to them, the passive force occurs in the form of a vector, which is normal to the axis of rotation, and rotates around the axis. In ordinary spiral drills the two passive forces between two cutting edges cancel each other. We get a resultant passive force that bends the drill when using drills with interchangeable inserts. The dynamometer is placed under the workpiece, because this is the easiest way to trace cutting forces reactions. Figure 5.17 shows a multicomponent sensor, which is mounted on the table of the drilling machine. This measurement is based on a two-component transducer (Ff and Mc), which is installed between the lower and the upper plate of the housing. Converter is preloaded. If we are interested in the lateral passive forces, a two-component transducer which is sensitive to the shear stress in the X and Y directions is installed in the dynamometer. Passive force is measured with the two components and is determined as a record of the two sinusoidal signals with a phase shift for 90 degrees. Figure 5.17 Multi component dynamometer for measuring the cutting force components in the processes of drilling [1] 86 CUTTING FORCES Piezoelectric sensor (material) is the insulator and for that reason metal plates that are linked to the plate of the piezo transducer have the role of the electrodes. From the electrical point of view, a system can be considered as capacitor, where the resulting voltage is proportional to the charge generated by the crystal and the inverse capacitance of the system: U kq – crystal constant xi – crystal deformation proportional to the load Co – crystal capacitivity Cs – cables and instrument capacitivity k x Qe q i C C0 CS 5.46 The resulting electric charge in the crystal causes a current through a resistor, and thus the voltage drop. Voltage changes with time, Figure 5.18: U t U t 0 e t Ri C 0 C S U t 0 e 1 T 5.47 T – time constant Figure 5.18 Piezo sensor circuit model and voltage drop in time [1] Hence it follows that the measurement has correct reading at t = 0, and no longer. For this reason, we strive to maximize the time constant, which requires a lot of resistance. Piezo crystal is suitable for the measurement of very rapid processes (large input frequency), and less for slow or stationary states. In order to achieve high input resistance (impedance), piezo transducer is connected to an amplifier with high input impedance. Charge amplifier consists of a DC amplifier with high input impedance, a capacitor in feedback loop C and adjustable ohm resistor R. The capacitor C converts electric charge Qе generated in the sensor into the proportional voltage U. By varying the capacitance of the capacitor in feedback loop, the amplification factor changes. Due to the current losses for charging the capacitor, ohm resistor is included in the feedback loop too. The ohm resistor prevents current losses and improves the amplifier characteristics. With this option, the time constant is set, Figure 5.19. U k T X i 1 T T RP C P k – amplification factor T – time constant Figure 5.19 Principle of charge amplifier circuit [1] 87 METAL CUTTING – Theory and Applications 5.6 Laboratory work – Measurements of cutting force components The aim of the laboratory work is to execute measurements of cutting force components and establish as to how different cutting regimes reflect on the cutting forces. To obtain results, it is necessary to execute regression analyse and show the results in diagrams. Figure 5.20 Principle of cutting force measurements in turning A. Laboratory work Task. For different depth of cut and feed rate settings, measure cutting forces in turning and carry out statistical data processing. Figure 5.21 Schematic setup of cutting forces measurements principle 88 CUTTING FORCES Table 5.3 Measuring instruments and accessories No. Name and characteristics 1 Calliper Measuring range: 0 - 150 mm Accuracy: 0.01 mm Figure Force measurement chain Connected to PC: 2 dynamometer, tool holder, charge amplifier, cables, A/D card, software. Measurement procedure: 1. Choose machine tool and cutting tool for experiment 2. Connect force measurement chain to the universal lathe 3. Select three different depths of cut ap and three different feed rates f 4. Measure cutting forces for each cutting regime combination 5. Perform statistical data processing 89 METAL CUTTING – Theory and Applications Table 5.4 Machine tool data Elements Values Machine tool Type Designation Power P (kW) Feed range (mm/rev.) Spindle speed range (rev./min) Adopted revolution speed nr (rev./min) Tool Designation Tool wedge angle α = β= Tool cutting edge angle, nose radius κr = rε = γ= Tool-overhang ln (mm) Workpiece Material designation Hardness HRC Tensile strength Rm (N/mm²) Dimension D L (mm) One must take into account that the values of the forces from dynamometer correspond to cutting forces according the following schedule; Fz value corresponds to the main cutting force Fc, Fy is the value of the feed force Ff and Fx is the value of the thrust or passive force Fp. Table 5.5 Measurements and calculations sheet (case study) No. 1 2 3 4 5 6 7 8 9 Depth of cut ap (mm) 2.5 2.5 2.5 2.0 2.0 2.0 1.5 1.5 1.5 Feed f (mm/rev.) 0.280 0.355 0.400 0.280 0.355 0.400 0.280 0.355 0.400 Main cutting force Fc (N) Feed force Ff (N) Passive force Fp (N) 1419 1834 2021 1164 1468 1609 944 1156 1165 607 716 780 542 586 615 438 481 489 451 559 619 407 477 518 356 418 423 MS Excel diagrams show the influence of depth of cut and feed on cutting forces components, Figure 5.22 - 24. 90 CUTTING FORCES Figure 5.22 The influence of feed on main cutting force at different depths of cut Figure 5.23 The influence of feed on feed force at different depths of cut Figure 5.24 The influence of feed on passive force at different depths of cut 91 METAL CUTTING – Theory and Applications With regression analysis (function LINEST in MS EXCEL), empirical models showing the influence of depth of cut ap and feed f on cutting force components can be derived: 1849 ∙ 0.925 ∙ 0.850 558 ∙ 0.776 ∙ 0.458 656 ∙ 0.590 ∙ 0.692 Using MATLAB and the following program code a three-dimensional graph of the aforementioned dependence is provided: va=1:0.05:3; vf=0.2:.001:0.42; [a,f] = meshgrid(va,vf); C=1849; F = C.* (a.^0.925 + eps) .* (f.^0.850 + eps); mesh(a, f, F); colorbar Figure 5.25 The influence of depth of cut and feed on cutting force 5.6.1 Software for cutting force measurement and analysis The Laboratory for Machining (LABOD) of the Faculty of Mechanical Engineering, University of Ljubljana, Slovenia, has developed a software application for cutting force and torque measurements and analysis named “LABOD_Forces”. LABView based software saves machining parameters and calculates Kienzle regression equation for cutting force modelling. Figures 5.26 – 5.29 represent sequences (tabs) in the LABOD_Forces measurement and calculation procedure. 92 CUTTING FORCES Measurement procedure: Signal Tab: In this part a capture of the signal is carried out. To be precise, the upper graph represents the current value of the signal with a short history. This graph is for information purposes only. In order to obtain the desired signal for further processing, pressing the START button is required just before the cutting process. With this button the capture of signal is initiated, as demonstrated by the red light below the button. When the process is complete by pressing the START button, recording is stopped (red light turns to green). The recorded signal is located in the graph below. If the analysis does not need the entire signal, part of the signal can be cut with sliders: "Beginning of the signal" and "End of the signal" (Fig. 5.26) Figure 5.26 Definition of the part of signal for analysis and signal capturing [1] Saving Tab: This window provides an overview of signal for analysis, determination of the process type (turning or drilling), input of cutting parameters and saving the file of a single experiment. Once the measurement is performed, it is necessary to determine the appropriate cutting process by clicking TURNING/ DRILLING. Then it is necessary to enter the appropriate amplification, which is set on charge amplifier and selected cutting parameters. Finally, it is necessary to specify a file name, in which all the data of each machinability test is saved and press SAVE to store the average values of forces or moments and associated machining parameters (Fig 5.27). Representation Tab: This window provides only an overview of individual measurements and eventual deletion of incorrect entries. Deleting an individual entry is performed by entering the row (No. of experiment) you want to delete and press the DELETE key. Calculation Tab: The last part or window represents the conversion of the Kienzle equation based on linear regression of cutting forces. In order to implement the calculation, it is only necessary to choose which component of cutting force will be set as input to the analysis of linear regression and the computer automatically calculates the coefficients of the Kienzle equation. Matching of linear regression 93 METAL CUTTING – Theory and Applications with experiments is shown graphically, and accuracy is quantitatively characterized by the value of the MSE (mean square error). In addition, the result which is also very important and useful for the industry, is the dependency graph of the specific cutting force of the chip thickness. Therefore, the right part of the window also shows this dependence. Figure 5.27 Input of the cutting conditions, amplification and saving data into the file [1] Figure 5.28 Representation of forces or moments at different experiments (cutting conditions) [1] 94 CUTTING FORCES Figure 5.29 Linear regression of measured data and generation of Kienzle equation [1] 5.6.2 Measurements of feed force and torque in drilling The aim of the measurements on the machine tool is to determine the size of torque and feed force when drilling with screw drill in the workpiece material. For practical work execution, the following equipment is needed: 1. Machine tool – drilling machine. 2. Tool – twist drill with diameter d. 3. Workpiece (low mass, not to influence on measurements) – with known mechanical and heat treatment properties. 4. Measurement chain (dynamometer, charge amplifier, cables, A/D card, and software). Process parameters such as spindle speed and feed rate are changed, and for each setting the measurements of forces and torques are performed. With this the cutting speed and chip cross section are changed. Statistical evaluation of the measurement; program provides a measurement-based plotting graphs: Fc / b-h; Ff / b-h; kc-h; kf-h From the obtained results, formulate a correlation between the change of the cutting parameters and the size of the forces and torques. 1 According to the known equations, calculate the specific cutting force kc1×1, mc coefficient and correlation factor r. 2 Calculate the size of the feed force and torque cutting forces generated by the cutting of the test piece with similar tool; the drill bit with a diameter of 22 mm and a feed rate of 0.18 mm/rev. 95 METAL CUTTING – Theory and Applications Table 5.6 Results of measurements for forces and torques in drilling Measurement table Machine tool: Power: Workpiece material: Heat treatment: Dimensions: Tool / drill type: Measurement chain: Dynamometer: Tool material: Point angle: Helix angle: No. Amplifier: A/D converter: Software: Drill diam. d (mm) Cutting speed vc (m/min) Feed f (mm/rev.) Torque Mc (Nm) Feed force Ff (N) 1 2 3 4 5 6 7 8 9 10 Table 5.7 Statistical data processing Table for statistical data processing No. h log h (log h)2 kc 4 5 (log kc)2 log kc log h∙log kc 1 2 3 4 5 6 7 8 9 10 No. h (mm) Fc (N) b (mm) 96 1 2 3 6 7 8 9 10 CUTTING FORCES Figure 5.30 Dependence Fc/b-h and kc-h [1] 97 METAL CUTTING – Theory and Applications Practical task and calculations Task. Machining is performed on a universal lathe with feed f = 0.1 mm/rev, and depth of cut ap= 1.5 mm. Turning has tool cutting edge angle κr = 45°. Specific cutting force of the workpiece material is kc = 1990 N/mm2 and cutting force exponent is mc= 1. Calculate the cutting force. Solution: To calculate the main cutting force, it is necessary to define the geometric parameters of the processing. Based on the cutting parameters (feed and depth of cut), it is possible to calculate the geometric parameters of the process - the width and thickness of the cutting layer, Figure 5.31. According to the established relations given in Figure 5.31, the width of the cutting layer is: b ap sin r 1.5 2.121 mm , sin 45 and the thickness of the cutting layer is: h f sin r 0.1 sin 45 0.071 mm . Figure 5.31 Geometrical and technological parameters of turning The main cutting force is calculated based on the specific cutting resistance and geometric parameters in the following form: Fc b h 1 mc kc ,11 2.121 0.071 1 0.19 1990 495 N 5.7 Final conclusions The measured values of the cutting force components along with the tool life represent the most important information about the machinability of a particular material. Coefficients of specific forces are entered into the database, and from the determination of the individual factors influencing the size of the cutting forces, we can choose the appropriate tools parameters. 98 CUTTING FORCES Table 5.8 Influence of different factors on cutting forces – conclusions Influencing factor Influence on cutting force feed, f Double feed leads to rise of cutting force for 20-85% (mean value for steel is cca. 60%). Maximal feed is limited by tool radius. depth of cut, ap Double depth of cut results in double cutting force. Depth of cut is limited by power and rigidity of the machine tool. cutting speed, vc Cutting force reaches its maximum in a curtain region (see figure; 80 m/min for steels) and decreases at higher plasticity of material. tool wear Worn cutting edge leads to higher forces. For each 0.1 mm of wear, cutting force increases for 10%. Maximal allowed wear depends on requested results (tolerances, surface quality ...) and tool material and geometry. For rough machining this means 10% of the insert thickness. rake angle, Enlarging the rake angle for one degree leads to decrease of force for 1-2% for steel. Maximal rake angle is limited by tool edge rigidity. tool cutting edge angle, With smaller tool cutting edge angle, chips are narrower, which leads to rising of cutting forces. The angle is limited with process stability. material Materials with higher hardness and strength are harder to machine and forces are higher. Larger wedge angles are needed for such materials to prevent tool breaking. tool material Coated tools (carbides or HSS) especially with TiN and Ti(C,N) have lower friction and lower forces. The same is with finish treated cutting surfaces (grounded and polished) with sharp edges. chips evacuation Grooves for chips evacuation have positive rake angle which leads to smaller forces. The shape of grooves depends on depth of cut and feed rate. Higher feeds lead to chips jamming and rising of cutting forces. cutting edge shape (phase, roundness) Phases and roundness compared to sharp edges give higher cutting forces; i.e. for phases 0.2×20 deg. and roundness 0.03-0.05 leads to 5-10% increase of cutting forces. 99 METAL CUTTING – Theory and Applications Literature: [1] Cedilnik, M., Rotar V., Kopač J.: Cutting 1, supplementary material for lectures and exercises, script, Ljubljana, 2006 [2] Globočki-Lakić G.: Metal cutting process – theory, modelling and simulation, Faculty of Mechanical Engineering, Banja Luka, 2010 (in Serbian) [3] Globočki-Lakić, G., Sredanović B.: Supplementary material to perform laboratory exercises in metal cutting process, Faculty of Mechanical Engineering, Banja Luka, 2011 (in Serbian) [4] Cica, Dj., Sredanović, B, Globočki-Lakić, G., Kramar, D.: Modeling of the cutting forces in turning process using various methods of cooling and lubricating: an artificial intelligence approach. Journal of Advances in mechanical engineering, 2013, vol. 2013, 1-8 [5] Sredanović, B., Globočki – Lakić, G., Čiča, Đ., Borojević, S., Golubović – Bugarski, V.: Modeling of Cutting Forces with Artifical Neural Netvorks, ICMEN 2011 – 4th International Conference on Manufacturing Engineering, Thessaloniki, Greece, 2011 [6] Globočki-Lakić G., Cica Dj., Sredanović B.: Application of Artificial Intelligence in Modeling of Metal Cutting Process, 9th International Scientific–practical conference “Research, development and Application of High Tehnologies in Industry”, Saint Petersburg, Russia, 2011, 120-124 [7] Kopač, J.: Metal cutting – theoretical bases and technological instructions, Faculty of Mechanical Engineering, Ljubljana, 2008 (in Slovenian) [8] Muren, H.: Odrezavanje in odnašanje, Faculty of Mechanical Engineering, Ljubljana, 1995 (in Slovenian) 100 CHAPTER VI THERMAL PHENOMENA IN MACHINING PROCESSES Contents 6.1 6.2 6.3 6.4 Theoretical considerations Temperature field of the cutting zone Methods for determining temperatures in cutting Laboratory work - Calorimetric method for mean chip temperature measurements - Cutting temperature measurements with thermocouple This chapter discusses the theoretical basis concerning the thermal phenomena that are present in the cutting zone as well as a detailed analysis of heat sources and heat sinks in the area of treatment. It also analyses methods and techniques for the measurement of heat and temperatures generated in cutting, with an emphasis on methods for the measurement of the mean cutting temperature. A detailed explanation of the measurement method for the mean chip temperature using the calorimetric method and thermocouple method for direct cutting temperature measurement is given along with a laboratory work procedure. 6.1 Theoretical considerations Heat generation in the cutting zone results from the conversion of mechanical work into thermal energy due to material internal friction and friction that occurs on the tool contact surfaces. Heat in the cutting zone has a major impact on: chip formation, chip deformation and compression, cutting forces and power, tool wear and deposit formation on the tool (BUE), surface quality, structure and thickness of the affected surface layer, etc. More than 99.5% of mechanical energy in the cutting process consumed for the workpiece material deformation and for overcoming the friction force on the contact surfaces of the tool wedge is converted into heat. Vibrations are ignored here assuming that the kinetic energy of the chips and the potential energy of elastic deformation of the crystal lattice of the workpiece material, chips and tools are negligibly small. The amount of generated heat, i.e. consumed mechanical work, can be represented by the following expression: ∙ ∙ 6.1 where: Q – heat generated in the cutting zone, W – mechanical work [J], Fc – main cutting force [N], vc – cutting speed [m/min] t – cutting time [min] 101 METAL CUTTING – Theory and Applications The conversion of mechanical energy into heat takes place in four characteristic zones, with some of the zones overlapping, Figure 6.1. Generated heat is the result of the appearance of four heat sources Q in the cutting zone. The highest percentage of heat is generated: 1. in the shear zone caused by internal friction between sheared layers in the material of the workpiece, where Q1 = 75 – 80% of total Q – a primary deformation zone, 2. on the rake face caused by the friction between the chip and tool rake face, where Q2 = 19 – 22.5% of Q, 3. on the clearance face caused by the contact of this tool surface and machined surface, where Q3 = 2 – 3.5% of Q, and 4. in the zone of elastic deformation, i.e. below shear zone, where Q4 0.5% of Q. Figure 6.1 Heat sources in the cutting zone The character of heat extraction (distribution) is defined through a heat sink q, Figure 6.2. Heat dissipation from the cutting zone depends on the machining procedure, cutting speed, thermal conductivity of the workpiece and tool material, workpiece dimensions, tool geometry, etc. Figure 6.2 shows that the highest percentage of generated heat goes into the chip. A smaller percentage represents the heat sink in the processing environment, i.e. the surrounding air. If CLF is used during processing, the heat dissipation percentage is much higher. Heat sinks: 1. the chip, where q1 = 68 – 80% of total q; heat from sources Q1 and Q2 is dissipated with the chip, 2. the tool, q2 = 2 – 5% of q; heat from sources Q2 and Q3 is dissipated over the tool, 3. the workpiece, q3 = 2 – 10% of q; heat from sources Q2, Q3 and Q4 is dissipated over the workpiece, 4. the surroundings or CLF, q4 = 8 – 25% of q, 5. the tool surface layer q5 = 1 – 6% of total q. Figure 6.2 Heat sinks in the cutting zone 102 THERMAL PHENOMENA IN MACHINING PROCESSES Figure 6.3 Influence of cutting speed on heat dissipation over chip, workpiece and cutting tool [1] The percentage of dissipated heat in the given processing conditions depends on the cutting speed. The main part of the generated heat is dissipated with chips, Figure 6.3. At low cutting speeds, the amount of generated heat dissipated with chips and the workpiece is approximately the same. In modern machining and high-speed cutting, chips take up to 95% of the generated heat, so that the tool and the workpiece are relatively "cold". Figure 6.3 shows that as the cutting speed increases, the amount of heat dissipated with chips increases, and the amount of heat dissipated with the tool and the workpiece decreases. For example, when cutting steel with carbide tools at the cutting speed of 150 m/min, the percentage of heat that dissipates with chips is about 80%, 15% with the workpiece, and approximately 5% with the tool. 6.2 Temperature field of the cutting zone Temperature field is generated in the tool, the workpiece and the chip as a result of the formation and function of heat sources. This temperature field changes until thermal balance has been restored, i.e. the balance between heat sources and heat sinks. Once a steady state has been established, a so called quasi-steady thermal field occurs. It has been determined through experiments that the establishment of thermal equilibrium process takes about 15 seconds. The temperature field in the cutting zone and the tool, chip and workpiece characteristic temperatures that can occur in the processing of steel are shown in Figure 6.4. The temperature field changes because the heat sources in processing change; (tool wear during processing; conditions of deformation and friction at the contact surface of the tool change). The temperature results from the heating elements that are in the zone of processing. It is primarily manifested by elevated tool and workpiece heating. Heat conduction through tools and the workpiece causes the appearance of the isotherms on the tool (or field lines with the same temperature). Figure 6.4 clearly shows that different points of chips and the tool rake face are at different temperatures. In both cases, i.e. the rake and the clearance face of the tool, the maximum temperature is in the middle of the contact zone. Maximum temperature is achieved in the middle of the rake face area, at the contact between the tool and the chip, and not at the top of the tool as the tip of the tool and the clearance face are cooled by the workpiece. In addition, in contact with the tool, the new volume of material is coming which is moving opposite to the flow of heat, so the 103 METAL CUTTING – Theory and Applications clearance face has a lower temperature than the rake face. Based on the analysis of many researchers, the maximum temperature in the shear zone ranges from 300 to 450°C and heat from this zone is generally dissipated to the chip. It is well known that the complete temperature field in the cutting zone is very difficult to determine. For this reason, in the analysis of the thermal load of tools and workpiece, the characteristic temperature points of the cutting zone are defined, Figure 6.5, as well as the mean temperature of cutting, Figure 6.6. Figure 6.4 Temperature field in the cutting zone and characteristic temperatures in steel machining [1] There are four characteristic temperature points: 1. Maximum temperature on the tool rake face T1 – the temperature that occurs as a result of the friction between the rake face and the chip. The peak is reached in the middle of the contact and usually coincides with the maximum depth of the crater on the tool rake face. When processing hard-to-machine materials, it can reach a value of 1300°C and it is also the highest possible temperature in the cutting zone. 2. Maximum temperature on the tool clearance face T2 – the temperature which occurs in the middle of the contact zone between the tool clearance face and the machined surface. Since this contact is very small, this point is very close to the tool tip. This temperature is considerably lower than the temperatures of the tool rake face and it can go up to a maximum of 850°C in severe processing conditions. 3. Machined surface temperature T3 – temperature of the machined area is significantly lower than the temperature of the tool and reaches the maximum value of approximately 250C for hard turning. This leads to a conclusion that the tool in the process of cutting is much more exposed to heat stresses than the workpiece. 4. Temperature in the shear plane T4 – the temperature that results from cleavage of the workpiece material. We may say that this temperature has a positive effect on the cutting process; the material softens and is therefore easier to deform. For the toughest conditions, temperatures reach the values of 450C. 104 THERMAL PHENOMENA IN MACHINING PROCESSES Figure 6.5 Temperatures in characteristic points of the cutting zone [2] The mean temperature of cutting, i.e. the temperature defined as the contact zone temperature is shown in Figure 6.6. In the same figure, the temperature dependence on the cutting speed is presented. Figure 6.6 Mean cutting temperature and its dependence on cutting speed 6.3 Methods for determining temperatures in cutting There is a number of methods for the modelling and simulation of the thermodynamic phenomenon in the cutting zone as well as for determining cutting temperatures. It is known that experimental measurement methods are beset with many problems, because in the cutting process many specifics occur compared to the conventional conditions of temperature measurement. These specifics pertain to a narrow localized heating zone, the specific pressures and temperatures, etc. All methods of the cutting temperature determination can be classified into three groups: 1. Computational methods (finite difference method, variational method), 2. Methods of electro-thermal analogies, and 3. Methods of cutting temperature measurement. Methods for the cutting temperature measurement can be divided according to different criteria - measurement aim, type of sensors, etc., see Figure 6.7. Regarding the measurement aim, the following methods can be singled out: Measurement of the mean temperature, Measurement of the local temperature, i.e. temperature at the point, Measurement of the temperature field, and Definition of certain laws. 105 METAL CUTTING – Theory and Applications Figure 6.7 Temperature measurement in cutting processes [3] According to the type of sensor, the methods can be classified into: calorimetric, contact and contactless. The most used methods for measuring the cutting mean temperature are: calorimetric method, method of thermo-sensitive coatings, thermocouples, and method of changing the colours of the chip thin oxide layer. The most widely used methods for measuring the cutting temperature at the point (in individual places of the tool, chip or workpiece) are: method of thermocouples, radiation or optical method, microscopic analysis, and the method of electro-thermal analogy, etc. 6.3.1 Caloric heat measurements This is the simplest method to measure the cutting zone mean temperature. It is based on the fact that the highest percentage of the generated heat in the cutting zone dissipates to chips. By measuring the amount of heat generated in chips and at the appropriate relation definition, one can calculate the mean cutting temperature as well as the amount of generated heat. The principle consists of the chip generated in the machining being captured into liquid and its heating is measured. One uses a liquid with known specific heat (water - cw). In order to reduce losses, the vessel is thermally insulated (calorimeter). Based on the results of the temperature measurement of fluid in the calorimeter before (T0) and after the chip 106 THERMAL PHENOMENA IN MACHINING PROCESSES falls into the calorimeter (T1), and on the mass of the chip mch, when the liquid mass (mw) and the heat of the workpiece material - chip cch are known, the mean temperature of the chip Tch can be determined by: ∙ ∙ ∙ 6.2 By applying this method one can measure the mean chip temperature before the chip has fallen into the calorimeter. Necessary equipment is listed and presented in Figure 6.8: 1. 2. 3. Thermally insulated vessel (calorimeter) with water as a chip catcher, Sensitive and precise thermometer, Stopwatch to measure the time of machining, the accuracy of 0.1 s and calliper. Figure 6.8 Equipment and principle of calorimetric method for mean chip temperature measurements [4] During the experiment, the calorimeter is placed below the workpiece and the tool, so that chips fall directly in the calorimeter. Chapter 6.4 gives a detailed description and a practical work of the chip mean temperature measurement using this method. 6.3.2 Measurement with thermo-colours The method of thermo-sensitive coatings is often used to measure the mean temperature of the cutting. The coatings - chemical compounds that change their original colour at the right temperature are used here. Certain temperatures correspond to certain colours of the coating. The resulting colour will not change even after cooling, making this method suitable for the formation of the temperature fields (zones) of the tool wedge, Figure 6.9. In this manner, a temperature range from 45 to 740°C can be determined with a measurement error in the range of 10°C. Figure 6.9 Method of cutting temperature measurement with thermo-coatings - coating colour change on the tool rake face 107 METAL CUTTING – Theory and Applications 6.3.3 Thermoelectric measurement methods Thermocouples have always been a popular transducer used in temperature measurement. Thermocouples are very rugged and inexpensive and can operate over a wide temperature range. According to the Thomson-Peltier law, a thermocouple is created whenever two dissimilar metals touch and the hot contact point produces a small open-circuit voltage (emf - electromotive force) as a function of temperature. If these two dissimilar materials are the cutting tool and the workpiece materials, as shown schematically in Figure 6.10, then this thermocouple is called a tool/work (chip) natural thermocouple or dynamic thermocouple. The method of tool/work (chip) natural thermocouple is commonly used to measure the mean value of cutting temperature. Figure 6.10 Scheme of tool/work (chip) natural thermocouple and calibration curve [1, 5] Some wires are required to make a complete circuit between the recorder and the tool and the recorder and the work, as well as a special mercury slip-ring device due to transmission of the emf signal from the rotating workpiece. As a rule, both the tool and workpiece are electrically insulated from the post and the chuck, respectively. The emf measured in cutting must be converted to temperature, hence prior to measurement the tool/work thermocouple is calibrated using the same materials as in the cutting tests and the reference thermocouple, for example the chromel/alumel standard thermocouple. Each different type of tool and work materials used must be calibrated individually. It is possible to calibrate separately, for example, the tool/chromel and work/chromel junctions and in such a case the tool/work emf - vs temperature relation is the difference between the foregoing relations [6]. The hot junction is created by rapid heating using an infrared heating furnace equipped with a high power halogen lamp or standard TIG welding apparatus. It should be noted that generally, the emf/temperature relation for tool/work thermocouples is nonlinear. Errors arising from uncertain calibration of the thermocouple can be partially eliminated by using two different tool materials to cut the same bar of work material, simultaneously, under the same conditions. This is the greatest disadvantage of the tool/work (chip) natural thermocouple. Voltage values are very small and amount up to 10 mV depending on the thermocouple materials and other parameters. While the tool/work (chip) natural thermocouple method is relatively simple to use, it has certain limitations. First, it measures the mean temperature over the entire area between the chip and the tool including the wear land on the clearance face. Second, misleading results may be obtained if a BUE is formed because then dissimilar materials do not exist over the entire area. Third, there is a question whether static calibration is valid for a dynamic situation. Fourth, oxide layers formed on the carbide tools during machining may change the calibration of the tool-chip thermocouple. Fifth, for each tool–work material combination, separate calibration is needed. Sixth, a rotating contact as well as insulation of the workpiece system and the tool system is required. This process can detect temperatures of up to 1200°C. 108 THERMAL PHENOMENA IN MACHINING PROCESSES The tool/work (chip) natural thermocouple with two tools is also a well known solution. The thermocouple consists of two tools of identical geometrical parameters, but made of different materials. The circuit is formed over two tools, the workpiece serving as a conductor of large dimensions, and the measuring instrument, Figure 6.11. The method of two tools as a thermocouple eliminates the influence of the workpiece material on the form of the calibration curve. The advantage of this thermocouple is that calibration is not required when switching from one material of the workpiece to another [1, 3]. Here, the tool and the workpiece must be isolated as well. The disadvantage of this thermocouple is a big consumption of materials and the need to ensure the same conditions for both tools. . Figure 6.11 Scheme of Two-tool thermocouple measuring method [1, 7] The wire-tool (semi artificial) thermocouple method was developed to measure the temperature at the point of contact between the chip and rake face, Figure 6.12. One element of the thermocouple is a platinum wire (part of inserted thermocouple) and the second element is the workpiece (part of natural thermocouple). The method is therefore called the wire-tool (semi artificial) thermocouple. The platinum wire is sintered in (electro non-conductive) the ceramic insert with one end coming out on the tool rake face. The other end is connected to the conductor and the measuring instrument. The second element of the thermocouple is connected to the workpiece and the second part of the measuring instrument. If the measurement is done when processing with hard metal, wire thermocouples in the tool must be isolated. The wire-tool (semi artificial) thermocouple method can be used to measure the temperature on the tool [7]. Figure 6.12 Scheme of wire-tool (semi artificial) thermocouple method and measurement results 109 METAL CUTTING – Theory and Applications By using the wire-tool (semi artificial) thermocouple, it is possible to determine a part of the tool temperature field. This is achieved by grinding the rake and flank face of the tool so that the point of measuring relatively moves in relation to the cutting edge. The method of inserted thermocouples is often used because it is reliable and accurate. It is used to measure the temperature of the tool and workpiece, in the different types of processing. This method can also be used for testing of the temperature field in the cutting zone. The method consists of placing two insulated wires (iron-constant, platinum-iridium, brass-constant, etc.) in a pre-drilled hole in the tool or workpiece depending on where you measure cutting temperature, Figure 6.13 [7, 8]. Temperature measurement with thermocouples is one of the most common techniques today. Insulated thermocouple wires are connected only at the top where the temperature measurement is carried out. In cutting, the thermocouple wears together with the tool so that contact is made through the chip and it can continually measure temperature. The other ends of the wire are connected to the measuring instrument which registers changes in the circuit voltage. Based on the known values of circuit parameters and calibration curve of the specific thermocouple, cutting temperature is identified. Figure 6.13 Scheme of inserted thermocouple method and tool with embedded thermocouple acc. to Kusters [7-9] Thermocouples can be applied in blind holes in the tool [7-9] or in the workpiece. Recently, non-traditional machining techniques, such as EDM or laser drilling are generally used to make these holes in view of the high hardness of the tools and relative ease of drilling holes by these techniques. Figure 6.13 shows the carbide insert with builtin thermocouple (NiCr-Ni) with diameter of 0.34 mm. The thermocouple is embedded at the location of the maximum crater depth and that way registers the maximum cutting temperature in turning. Temporal resolution is influenced by the response time of the thermocouple and heat transfer between the thermocouple and the device under test. These techniques generally have low temporal resolution. Also problematic is the contact heat transfer resistance between the surface under test and the thermocouple due to the roughness of the bore. This causes a difference in temperature between the measurement surface and the thermocouple. In the case of sheathed thermocouples with isolated measuring points, there is also the distance between the thermocouple surface and the internal measurement point. Due to the extremely high temperature gradients with short test time characteristic of cutting processes, this can lead to much lower measurements. 110 THERMAL PHENOMENA IN MACHINING PROCESSES Thermal compounds are used to improve heat transfer between the thermocouple and the surface. Another disadvantage is that direct contact between the thermocouple and the test object is necessary and that the holes used to position the thermocouples can significantly affect the distribution of temperature and limit the strength of the tool. 6.3.4 Radiation measurement The most important techniques in radiation measurement, which determines temperature by measuring the heat radiation emitted from a surface, are pyrometry and thermography. Pyrometry is the contact-free determination of absolute temperature by measuring the inherent radiation of a body without spatial scanning of the object field. Thermography provides a pictorial representation of temperature distribution. Radiation techniques have decisive advantages compared with thermoelectric methods: the time resolution is much higher (whereby pyrometers are principally faster than infrared cameras), and they are also contact-free. One significant problem when measuring for an exact absolute temperature with a radiation method is the dependence of the radiation emitted on the grade of emission of the surface. Since the emission grade is the function of many factors like temperature, wavelength, angular position, material and surface condition, calibrating the measurement device for a particular surface is very difficult. The precision of total radiation and broadband partial radiation pyrometers are especially influenced by factors that alter the spectral grade of emission of the surface. In cutting, effects such as surface roughness and oxidation influence the grade of emission of different surfaces greatly. To limit the influence of the grade of emission on measured temperatures, narrow-band partial radiation, two-colour and multi-colour pyrometers have been developed. The two-colour pyrometer (Figure 6.14) has the advantage that the spectral grades of emission ε1 and ε2 of the surface need not be known. Since the two selected wavelengths lie directly next to each other, ελ1 ∼ ελ2. An error in measurement will only result if both wavelengths λ1 and λ2 differ greatly. Further advantages of this principle are that the measured temperature is independent of signal dampening, due to dust for example, as long as both signals are dampened equally. Moreover, the temperature of objects that are smaller than the optical field of vision can be measured without error [3]. Figure 6.14 Build-up of a two-colour pyrometer in principle [3] 111 METAL CUTTING – Theory and Applications 6.4 Laboratory work 6.4.1 Calorimetric method for mean chip temperature measurement Described below is a laboratory work using the calorimetric method of measuring the amount of generated heat dissipated by the chip. In the work, the mean temperature of the chip is determined applying this method. Laboratory work Task. For different cutting speeds determine the amount of heat generated during processing, the amount of heat taken by the chip and the chip temperature. Table 6.1 shows the necessary measuring equipment and instrumentation for the execution of the laboratory work. Table 6.1 Measuring instruments and accessories No. Name and characteristics 1 Thermo isolated vessel calorimeter for chip collection Calliper 2 3 Measuring range: 0 - 150 mm Accuracy: 0.01 mm Cutting forces measuring chain – dynamometer Sensitive thermometer 4 112 Measuring range: -10 … 40°C Accuracy: 0.1°C Figure THERMAL PHENOMENA IN MACHINING PROCESSES Measurement procedure, Figure 6.15: 1. Choose a tool and a cutting tool for experiment 2. Define the machining time t 3. Define three different cutting speeds vc 4. Fill 1 litre of water in the calorimeter and measure the temperature T0 5. Collect chips in the calorimeter for each cutting regime combination 6. Measure the average cutting force Fc 7. Wait for stabilisation of the chip and water mixture temperature 8. Measure the mixture temperature T1 Figure 6.15 Principle of calorimetric method for measuring heat generated in the chips Table 6.2 Machine tool data Machine tool Elements Values Type Designation Power P (kW) Feed range (mm/rev.) Spindle speed range (rev./min) Tool Designation Tool wedge angle α= β= Tool cutting edge angle, nose radius κr = rε = γ= Tool-overhang ln (mm) Workpiece Material designation Hardness HRC Tensile strength Rm (N/mm²) Specific mass ρm (kg/m³) Dimension D L (mm) 113 METAL CUTTING – Theory and Applications Table 6.3 Measurements and calculations sheet (case study) No. Symbol Dimension Name 1 2 3 selected 150 220 316 selected 2.5 2.5 2.5 selected 0.2 0.2 0.2 measured 60 60 60 30 30 30 1 1 1 1 n 2 ap 3 f 4 D1 mm 5 t s 6 mw kg Mass of water 7 Fc N Main cutting force measured 1012 986 978 8 T1 °C Water temperature at the beginning measured 14.6 14.3 14.3 9 T2 °C Water temperature at the end measured 15.9 17.2 18.7 10 D2 mm Cut diameter D1 – 2 ∙ ap 55.0 55.0 55.0 11 lc mm Cutting length n∙f 30.0 44.0 63.2 12 vc m/min Cutting speed D1 ∙ π ∙ n / 60000 0.471 0.691 0.993 13 D12 m2 The square of D1 D12 0.00360 0.00360 0.00360 14 D22 m2 The square of D2 D22 0.00303 0.00303 0.00303 15 ΔD2 m2 Difference of squares D12 - D22 0.00058 0.00058 0.00058 16 ΔT K Temperature differences T2 – T 1 1.3 2.9 4.4 17 PFc W Cutting power Fc ∙ vc 477 681 971 18 Qh kJ Generated heat PFc ∙ t 14.306 20.444 29.126 19 cw kJ/(kg·K) Water specific heat capacity constant 4.182 4.182 4.182 20 cch kJ/(kg·K) Chip specific heat capacity constant 0.466 0.466 0.466 21 mch kg Chip mass ΔD² ∙ π ∙ lc ∙ ρch / 4 0.106 0.156 0.224 22 Qw kJ Heat transferred to water mw ∙ cw ∙ ΔT 5.437 12.128 18.401 23 Qch kJ Heat generated in chips Qw 5.437 12.128 18.401 24 ΔTch K Chip temperature rise Qch / (cch ∙ mch) 109.700 166.851 176.246 25 Tch °C Chip temperature T2+ ΔTch 130 187 196 26 qch % Percentage of heat dissipated with the chip 100 ∙ Qch / Qh 38 59 63 114 rev./min Spindle speed Source mm Depth of cut mm/rev. Feed Workpiece Diameter Machining time selected and measured selected and measured THERMAL PHENOMENA IN MACHINING PROCESSES Using MS Excel, a diagram showing the influence of the cutting speed on the chip temperature is drawn, Figure 6.16. A trend line is added and polynomial equation is derived: 439 ∙ 770 ∙ 136 Figure 6.16 The influence of cutting speed on chip temperature Figure 6.17 shows the percentage of the total heat generated in machining and dissipated by the chip. Figure 6.17 Percentage of the total generated heat dissipated by the chip 115 METAL CUTTING – Theory and Applications 6.4.2 Cutting temperature measurements with thermocouple Laboratory work Task. For different cutting speeds and depths of cut, determine the temperature of the cutting zone, i.e. the temperature below the rake face. Table 6.4 shows the necessary measuring equipment and instrumentation for the execution of the laboratory work. Table 6.4 Measuring instruments and accessories No. Name and characteristics 1 Thermocouple (calibrated) Figure Calliper 2 3 4 Measuring range: 0 - 150 mm Accuracy: 0.01 mm Charge amplifier Connected to computer Turning tool insert with a blind hole Measurement procedure, Figure 6.18: 1. Choose a machine tool and a cutting tool (with a blind hole) for the experiment 2. Define the machining time t 3. Define fixed feed f, and three different depths of cut ap and cutting speeds vc 4. Embed the thermocouple and prepare the experimental set-up according to Figure 6.18 5. Measure the rake face temperature θ 116 THERMAL PHENOMENA IN MACHINING PROCESSES Figure 6.18 Scheme of experimental set-up for built-in thermocouple method Table 6.5 Machine tool data Workpiece Tool Machine tool Elements Values Type Designation Power P (kW) Feed range (mm/rev.) Spindle speed range (rev./min) Designation Tool wedge angle Tool cutting edge angle, nose radius Tool-overhang ln (mm) Material designation Hardness HRC Tensile strength Rm (N/mm²) Specific mass ρm (kg/m³) Dimension D L (mm) α= κr = β= rε = γ= Table 6.6 Measurements and calculations sheet (case study) No. Feed f (mm/rev.) Depth of cut ap (mm) Cutting speed vc (m/min) Measured temperature θ (°C) 1 2 3 4 5 6 7 8 9 0.26 0.26 0.26 0.26 0.26 0.26 0.26 0.26 0.26 0.20 0.20 0.20 0.35 0.35 0.35 0.60 0.60 0.60 20 70 100 20 70 100 20 70 100 142 251 287 208 323 341 269 377 416 117 METAL CUTTING – Theory and Applications Using MS Excel, a diagram showing the influence of the cutting speed and depth of cut on the rake face temperature is drawn, Figure 6.19. A trend line is added and polynomial equation is derived: 112.6 ∙ . ∙ . Figure 6.19 Influence of cutting speed and depth of cut on rake face temperature Using MATLAB and the following program code, a three-dimensional graph of the aforementioned dependence is provided: vv=10:.05:110; va=0:0.05:1; [a,v] = meshgrid(va,vv); C=112.6; t = C.* (v.^0.344 + eps) .* (a.^0.430 + eps); mesh(a, v, t); colorbar Figure 6.20 Influence of depth of cut and cutting speed on rake face temperature 118 THERMAL PHENOMENA IN MACHINING PROCESSES Remarks Literature: [1] Lazić M.: Metal cutting process, Faculty of Mechanical Engineering, Kragujevac, 2002 (in Serbian) [2] Milikić D., Gostimirović M., Sekulić M.: Basics of machining technology, Faculty of Technical Science, Novi Sad, 2008 (in Serbian) [3] Klocke, F.: Manufacturing Processes 1, Cutting, Springer Heidelberg Dordrecht London New York, 2011 [4] Globočki-Lakić G., Sredanović B.: Supplementary material to perform laboratory exercises in metal cutting process, Faculty of Mechanical Engineering, Banja Luka, 2011 (in Serbian) [5] Nedić, B., Lakić Globočki, G.: Friction Coefficient for Al Alloys and Tool Materials Contact Pairs, Tribology in industry, 2005, Vol.27, No. 3, 4, 53-56 [6] Grzesik, W.: Advanced machining processes of metallic materials, Theory, Modeling and Applications, Elsevier, 2008 [7] Kovač P, Milikić D.: Metal cutting, Faculty of Technical Science, Novi Sad, 1998 (in Serbian) [8] Kusters, K.J.: Das Temperaturfeld in Drehmeissel (The Temperature Field in the Cutting Edge of a Cutting Tool). Essen, Germany: Verlag W. Girardet, 1954 (in German) [9] Courbon, C., Kramar, D., Krajnik, P., Pusavec, F., Rech, J., Kopac, J.: Investigation of machining performance in high-pressure jet assisted turning of Inconel 718: An experimental study, International Journal of Machine Tools & Manufacture, 2009, No. 49, 1114–1125 119 CHAPTER VII TOOL WEAR Contents 7.1 7.2 7.3 7.4 7.5 7.6 Theoretical considerations Determination of tool wear Tool life line determination Final conclusions Experimental measurement of tool wear Laboratory works 7.1 Theoretical considerations Tribological processes on contact surfaces between the tool and the workpiece influence the character of tool wear, surface integrity, machining accuracy, etc. Contact between the chip and the rake face is characterized by variable quality of contact surfaces, uneven stresses, and changes of contact temperature on a large scale. In machining, tools are loaded with forces resulting from deformations that occur during chip formation and friction between the tool and the workpiece. This develops heat that heats up the tool, the clip and partly the workpiece. All contact surfaces are usually clean and chemically very active, so that cutting is always accompanied by complex physical and chemical processes. Tool wear is the gradual removal of particles from the surface which is under the influence of mechanical and thermal loads as well as chemical influences. Tool wear is monitored (measured) at three levels (see Figure 7.1): flank wear, rake face wear (crater wear), and tool nose radius whereby flank wear is the most common and determining criterion for tool replacement or tool sharpening. Figure 7.1 Flank and rake face, and tool nose radius [1] 121 METAL CUTTING – Theory and Applications Intense heat and mechanical stresses create conditions for the process of friction connections formation and disruption between the tool and the workpiece material. The nature of friction in the cutting process can be clarified by frequent formation and disruption of friction connections, while particle removal from the tool material causes tool wear. These processes lead to energy loss, extra labour to sever connections and heat generation. Figure 7.2 Basic mechanisms of tool wear [2, 3] Tool wear is influenced by mechanical impacts associated with the heat load leading to, Figure 7.2: Abrasive wear is a typical mechanical wear. It occurs because tool material is removed when harder particles penetrate its surface. This type of wear is typical for high-speed steels. In carbide cutting tools, abrasive wear is less obvious due to relatively lower hardness of the workpiece inclusions and due to higher cutting speeds. Adhesive wear occurs when two materials with good surface treatment and similar hardness slide past each other. The tool and the chip touch each other only in specific points where large surface pressures cause plastic deformation and weld the chip to the insert (BUE formation). With increased contact area, the size of deformation and removed particles increases, as well as the wear rate, and by chemical impacts causing: Diffusion wear - diffusion is a chemical process that occurs at the tool-chip contact surface, Figure 7.3. This type of wear is typical for carbide tools and cutting ceramic. Diffusion wear occurs at temperatures ranging from 800 to 850°C as a result of tool material diffusion dissolution in the workpiece material (chip and cutting surface). Different components of the cemented-carbide tool diffuse into the workpiece at different speeds. Because carbon diffuses first, and more slowly tungsten, cobalt and titanium, the tool subsurface containing Fe3W3C or a more complex carbides weakens and a crater wear develops rapidly. Severe crater wear ultimately leads to a tool failure due to breakage. At the same time, there is a diffusion of some components of the workpiece material into the tool material. For 122 TOOL WEAR example, the processing of steel comes to the diffusion of Fe into carbide tool. The result of the diffusion process (i.e. different dissolution rates between the tool, chip and workpiece material) is the forming of three diffusion layers. The farthest from the contact area is noncarbon layer (C). The second layer (B) is a solid solution C and W or W and Ti in iron. Third layer is intermetalid in the form of Fe-W, or more complex carbides. Figure 7.3 Diffusion wear mechanism of carbide tool [2, 4] Oxidation wear is the consequence of a chemical reaction between oxygen in the air and the components of the cemented-carbide metal. This results in the formation of oxides on tool surfaces that will corrode. The reaction occurs at temperatures between 700 and 800°C. At these temperatures, oxygen in the air reacts with the cobalt phase of carbide tool and with W and Тi carbides forming oxides (Co3O4, CoO, WO3, TiO2) with hardness 40 to 60 times lower than the hardness of carbide tools. Oxide places swell and begin to peel away. With the softening of the cobalt phase, the link between W and Ti grains and cementing ties is weakening, which disturbs carbide compactness and starts the oxidation wear. This phenomenon is more present in W carbide than in Ti carbide and other carbides. Figure 7.4 Oxidation wear of turning tool [5] 123 METAL CUTTING – Theory and Applications Tool wear represents the loss of cutting tool capabilities. The result is a plastic deformation of the tool tip, chipping, breaking off or destruction of the cutting tool wedge. Basic forms of cutting tool wear are, Figure 7.5: wear exclusively on the rake face in the form of craters (typical for the tools of high speed steel without the use of cutting fluid), wear exclusively on the flank face in the form of a belt wear of certain width (typical for finishing), and general form of wear, at the flank and at the rake face (typical for machining of brittle materials, steels lean for deposits formation, machining at larger depths of cut and in the application of cutting fluids). Figure 7.5 Forms of tool wear [5] The aforementioned mechanical and thermal stresses and chemical influences cause different types of wear. Some of them, along with possible causes of wear and possible solutions to reduce them, are shown below, Tables 7.1 - 7.8 [6]. Table 7.1 Flank wear Tool wear Rapid flank wear causing poor surface finish or out of tolerance. Possible causes Cutting speed too high or insufficient wear resistance. 124 Possible solutions Reduce the cutting speed. Select a more wear resistant grade. Select an Al2O3 coated grade. For work-hardening materials, select a smaller entering angle or a more wear resistant grade. TOOL WEAR Table 7.2 Crater wear Tool wear Excessive crater wear causing a weakened edge. Cutting edge breakthrough on the trailing edge causes poor surface finish. Risk of insert breakdown. Possible causes Possible solutions Select an Al2O3 coated grade. Select positive insert geometry. First, reduce the speed to obtain a lower temperature, and then reduce the feed. Diffusion wear due to cutting temperatures that are too high on the rake face. Table 7.3 Plastic deformation Tool wear Edge depression or flank impression. Leads to poor chip control and poor surface finish. Risk of excessive flank wear leading to insert breakage. Possible causes Possible solutions Select a harder grade with better resistance to plastic deformation. Edge depression – reduce feed. Flank impression – reduce speed. Cutting temperature is too high, combined with a high pressure. Table 7.4 Built-up edge (BUE) Tool wear Built-up edge causing poor surface finish and cutting edge frittering when the built-up edge is torn away. Possible causes Workpiece material is welded to the insert due to: Cutting speed that is too low. Negative cutting geometry. Adhesive workpiece material. Possible solutions Increase the cutting speed or cool heavily. Select a positive geometry. Reduce feed at the beginning of the cut. Select a thin coated PVD grade and a positive geometry. 125 METAL CUTTING – Theory and Applications Table 7.5 Thermal cracks Tool wear Small cracks perpendicular to the cutting edge causing frittering and poor surface finish. Possible causes Possible solutions Select a tougher grade with better resistance to crack propagation. Coolant should be applied copiously, or not at all. Thermal cracks due to temperature variations caused by: - Intermittent machining. - Varying coolant supply. Table 7.6 Frittering Tool wear Small cutting edge fractures (frittering) causing poor surface finish and excessive flank wear. Possible causes Grade is too brittle. Insert geometry is too weak. Built-up edge. Possible solutions Select tougher grade. Select an insert with a stronger geometry (bigger chamfer for ceramic inserts). Increase the cutting speed or select a positive geometry. Decrease the cutting speed and coolant. Reduce feed at the beginning of the cut. Table 7.7 Insert breakage Tool wear Insert breakage that damages not only the insert but also the shim and workpiece. Possible causes Grade is too brittle. Excessive load on the insert. Insert geometry is too weak. Insert size is too small. 126 Possible solutions Select a tougher grade. Reduce the feed and/or the depth of cut. Select a stronger geometry, preferably a single-sided insert. Select a thicker/larger insert. TOOL WEAR Table 7.8 Notch wear Tool wear Notch wear causing poor surface finish and risk of edge breakage. Possible causes Possible solutions Select a cermet grade. Reduce the cutting speed. (When machining heat resistant material with ceramics, increase cutting speed). Oxidation. Attrition. The wear process of cutting tool elements or the loss of tool cutting properties can be traced by numerous parameters that are classified as (Figure 7.6): Direct parameters of wear - line or one-dimensional (wear bandwidth on the flank face - VB), plane or two-dimensional (the area of the crater on the rake face) and volumetric or three-dimensional (volume or mass of battered material tools) and Indirect parameters of wear (surface roughness, accuracy of machining, cutting temperature, cutting forces, etc.). Based on observed wear parameters, special methods for tool wear determination have been developed: Direct methods, which can directly measure the wear parameter (mass method, microscopic method, ‘fingerprint’ method, radioactive methods, etc.), Indirect methods, for which models were developed, are based on the monitoring of other process parameter to determine tool wear (measurement of surface roughness, cutting force measurement, cutting temperature measurement, etc.). Due to different wear forms shown previously, and thus due to different criteria for tool replacement, it is difficult to determine the proper moment to replace the tool with a new one. In any case, one should avoid the worst situation when the tip of the tool breaks. Prior to this happening, there will be signs on the tool or the workpiece directly or indirectly indicating excessive tool wear or cutting edge wear: Tool loses its cutting ability, A ring is formed around the workpiece, Need for greater processing power of the machine, Workpiece overheating, Uncontrolled chip formation (unfavourable chips), Workpiece dimensions out of tolerance, Excessive noise during processing, Poor surface quality , Uneven heat transfer between processing, Excessive vibration. 127 METAL CUTTING – Theory and Applications Figure 7.6 Measured quantities of tool wear according to DIN ISO3685 7.2 Determination of tool wear In all cutting processes, tool wear begins after a certain time period. The size of the wear and wear rate depends directly or indirectly on many factors determined by the processing parameters and by the properties of the tool and workpiece material. In general, a tool is operable as long as there is no breakage or can be used to such extent that further work is no longer appropriate. Tool breakage often occurs unexpectedly and with no sign of it happening. Different types of wear have therefore set different criteria that dictate tool replacement or sharpening. If we focus on the turning process, flank wear (under normal operating conditions) is the criterion for tool replacement or sharpening. In this general case, the wear on the flank face significantly increases (Figure 7.7), allowing to some extent the estimation of when the tool should be repaired or replaced. Such estimations are naturally based on experimentally derived models (equations) that link the size of the wear to individual influential parameters. Figure 7.7 Tool life curve for flank wear VB 128 TOOL WEAR Flank wear VB rate is relatively fast to some initial value, and then rises evenly (almost linearly) within a specified time interval. The wear curve then moves into an area of relatively rapid wear of the cutting edge and finally to the fracture of the tool tip (Figure 7.7). Experimental results and analysis of wear progress as a function of the cutting speed and feed rate can be used as criterion for allowable size of flank wear. In general, the criterion for permissible flank wear of the high-speed steel and carbide tools is determined separately for finishing and for roughing. VBper = 0.4 to 0.5 mm for rough machining; VBper = 0.1 to 0.2 mm for finishing. Given that the experimental results show very different slope angles of wear curves for the last (steeper) part, the criterion of permissible flank wear is determined as a certain kind of the highest point of yet linear section of the wear curve. Experimental measurements have shown that cutting speed has the greatest impact on tool wear. Tool wear curves for different cutting speeds (Figure 7.8) show that by increasing the cutting speed, the wear curves move toward the ordinate axis. It means that by increasing the cutting speed, the tool wears faster (angle of curve wear increases) and its operable time shortens (T1 < T4). Also, the S-shape wear curve, typical for low cutting speeds, disappears and transfers into almost linear dependence at higher cutting speeds. Figure 7.8 Tool life curves for different cutting speeds [1] Mathematical description of the wear curve that corresponds to only a narrow field of cutting speed, is expressed by the equation: ∙ 7.1 where: VB – flank wear [mm] C – constant t – turning time [min] p – exponent. 7.3 Tool life line determination In practice, the measurement and monitoring of tool wear is a relatively unusual task. This because it is a task associated with a precise and time consuming work on toolmakers microscope, which is often hard to achieve in the conditions of mass production. 129 METAL CUTTING – Theory and Applications Additionally, the size of tool wear is in fact of secondary importance for machine operators. The most important information for machine operators is the tool life or how long a tool can perform its function depending on the choice of other cutting parameters (cutting speed above all). A number of influential parameters that affect the rate of tool wear require a lot of experimental work, results and analysis that must be included in technological databases for each material to be cut. In this text, we shall focus on the most influential parameter only, the cutting speed. A tool life diagram can be determined in the following manner: if we calculate logarithm for the equation that gives the tool wear curve (eq. 7.1), we shall obtain a double logarithmic diagram line: ∙ 7.2 For more different cutting speeds in the diagram [log VB (log T)], more parallel lines are obtained, Figure 7.9. Tool life in machining is defined as the time T for tool in function until the permissible tool wear is achieved. Figure 7.9 shows how to obtain a tool life line in [log T (log vc)] diagram. Figure 7.9 Tool life line determination in a double logarithmic diagram Tool life line can be expressed in the following mathematical form: ∙ 7.3 where: T… tool life [min] C… constant υ … line inclination angle [o] vc … cutting speed [m/min] By calculating anti-logarithm and rearranging the equation 7.3, we will obtain the well known Taylor equation for durability. For turning with high-speed steel tools, Taylor found that the most evident interdependence between tool wear and cutting speed is given by the equation: ∙ where: m … Taylor equation exponent Cv … Taylor equation constant 130 7.4 TOOL WEAR Matching this exponential equation with the actual course of the wear curve, which is shown in Figure 7.10, is valid only within a relatively narrow range of cutting speeds. In the figure, the double-logarithmic diagram shows the curve of the actual tool wear in dependence on the speed and theoretically (mathematically) obtained straight tool life line. Match of the actual curve and stability of the theoretical line is obvious only in a relatively narrow range of cutting speeds. Humped shape of the actual wear curve shows the change in tool life rate for minimum and maximum cutting speed. In the middle the curve descends relatively straight, which corresponds to the Taylor equation. At low cutting speeds, BUE may form on the cutting edge, area b in Figure 7.10. In area d of higher cutting speeds, there may occur plastic deformation of the tool cutting edge (Figure 7.10). Figure 7.10 Wear curve and tool life line Nevertheless, to illustrate the wear curve with the tool life line in this narrow interval requires many assumptions. Tool life is affected by the above-mentioned different types of wear on the cutting edge and many other parameters, in addition to the most influential parameter, the cutting speed. As a result, starting from the Taylor equation, many authors try to expand it to include other influential parameters. The expanded equation that includes the influence of feed and cutting depth, in addition to cutting speed, is called the expanded Taylor’s equation: ∙ ∙ 7.5 ap … depth of cut [mm] f … feed [mm/rev.] Cv, r, s … constants of expanded Taylor equation m … Taylor equation exponent 131 METAL CUTTING – Theory and Applications If we express an exponential dependence of cutting speed vc [m/min] on other machining parameters, we obtain the most commonly used form of the tool life equation: Turning: vc const f b1 ab 2 t b3 VBb 4 7.6 Drilling: vc const f b1 ab 2 l b3 VBb 4 7.7 Milling: vc const f b1 ab 2 (ae / D)b3 l bf 4 VBb5 7.8 where: f … feed [mm/rev.] ae/D … milling width ratio [-] ap … depth of cut [mm] lf … milling length [mm] t … turning time [min] const … Taylor equation constant [-] d … drill diameter [mm] b1 … tool life equation exponents [-] l … drilling length [mm] Cutting speed dependence on the changing influence of each parameter in turning is shown in Table 7.9. Table 7.9 Cutting speed dependence on other influential parameters [1] Turning vc const f b1 abp2 t b3 VBb 4 1 2 3 4 132 TOOL WEAR 1. If we monitor the influence of feed f on cutting speed vc, we find that the feed is inversely proportional to the influence (tanφ1 > 90° → b1 < 0), in case if other influential parameters do not change. In other words, increasing the feed, cutting speed decreases under the preset condition that permissible tool wear VB is reached in the same time t without changing cutting depth ap. 2. Monitoring the influence of the depth of cut ap with respect to cutting speed vc shows the same similarity, namely the relation is also inversely proportional (tanφ2 > 90° → b2 <0). This means that with increasing the depth, cutting speed decreases, under the proviso that the obtained permissible tool wear VB at a given time t and without changing the feed f is the same. 3. Monitoring the impact of the time variable t with respect to cutting speed vc also shows the same similarity as in the case of previous two quantities, namely the relationship is also inversely proportional (tanφ3 > 90° → b3 < 0). This means that cutting speed is reduced if desired machining time increased, under the condition that the test was carried out with the same depth of cut ap, and feed rate f to achieve the (same) permissible tool flank wear VB. 4. Monitoring the impact of the flank wear VB with respect to cutting speed vc shows a proportional relation (tanφ4 < 90° → b4 > 0), which means that greater flank wear VB is achieved at higher cutting speed, assuming that turning time t as well as the depth of cut ap and the feed f remain the same. The constant and exponents of the Taylor equation are determined by various statistical methods of tool wear experimentally measured values in relation to the changing of cutting parameters. Multiple linear regression is the most used method. Due to a large number of influential parameters (independent variables) and a large number of measured values of tool wear, the coefficients of the equation are determined by using appropriate numerical methods using PC. Reliability of such a regression equation depends on the number of influential parameters in the equation, the number of attempts and accuracy of the tool wear measurement. In order that the experimental work is not excessively broad, and thus time-consuming and expensive, it is reasonable to carry out the wear tests of systematically pre-selected combinations of different cutting speed, feed and depth of cut necessary to prepare a design of the experiments. In doing so, we try to choose the combination of influential parameters in order to cover the widest possible area. Based on a number of analyzed experiments [7 – 9] it was found that: Cutting speed has the greatest influence on tool wear or tool life Feed has less impact on tool wear than cutting speed Depth of cut has a very subordinate influence on wear. 7.4 Final conclusions Influence of cutting conditions on tool life is systematically presented in table 7.10. 133 METAL CUTTING – Theory and Applications Table 7.10 Influence of variables on tool life [1] Variable Increasing depth of cut ap1 < ap2 < ap3 Increasing feed f1 < f2 < f3 Application of cutting fluids (CF) Decreasing tool cutting edge angle κr2 > κr1 Increasing allowable wear criteria VB1 < VB2 Lower material machinability More wear resistant tool material grade 134 Influence on tool life Tool life decreases with increase of depth of cut. Increasing depth is limited and related to material of the workpiece shape inserts, process stability, ... Increasing feed rate reduces tool life. Maximum feed rate is limited by surface roughness , suitable chip formation, ... Cooling lubricant increases tool life. In particular, the use of CF is efficient in processes that create high temperatures, which may cause temperature cracks, plastic deformation, BUE on the tool rake face, ... Reduction of tool cutting edge angle has positive effect on tool life. Wear is spread over a longer cutting edge. The minimum angle is dependent on workpiece shape and is limited by stability of the process. Tool life is prolonged. The safety of the process decreases as possibility for breakage of the tool tip increases. Workpiece material affects position and slope of tool life lines. Large slope means strong influence of heat on wear resistance. Cutting speed can vary only within narrow limits. Better cutting material has greater resistance. Very wearresistant tool allows higher cutting speed and/or stability. TOOL WEAR 7.5 Experimental measurement of tool wear It is recommended for measuring the wear of the tool cutting edge that it is measured by toolmakers microscope (Figure 7.11) at 20 to 50-fold magnification and a sensitivity of at least 0.01 mm. Figure 7.11 Toolmakers microscope In tool wear measurements, the middle half of the flank face wear b/2 is measured as shown in Figure 7.12. Wear on the flank face VB is measured according to still undamaged cutting edge of the tool. Even when the cutting edge size reduces, the starting point for wear measurements is its intact part. The maximum wear on the flank face VBmax is often taken as the wear criterion . It should be noted that the maximum wear is mainly used as a parallel criterion for wear evaluation. Figure 7.12 Tool wear measurement on flank (and rake) face in turning [1, 4] In milling, the width of flank wear is not always the same for the entire length of the cutting edge, but varies considerably in the range of rounding off the blade and at the end of the wear trace (Figure 7.14). Wear on the flank face is measured relative to the new cutting edge (a part of the cutting edge, which is not in contact with the workpiece) on the main cutting edge, on chamfered or rounded corner of the tool or on the side cutting edge. Individual types of wear on the main cutting edge are: The notch length on the main flank face at the maximum depth of cut is VNmax, Width of the wear trace on the flank face is VB, and the maximum width of the flank wear in this area is VBmax. 135 METAL CUTTING – Theory and Applications Additional types of tool wear are (see Fig. 7.13): The average width of the wear on chamfered or rounded cutting edge is marked with VC (maximum value of VCmax) The width of the average wear on the minor cutting edge is indicated by VS. Figure 7.13 Tool wear measurement on flank (and rake) face in turning [1] In drilling, flank wear of the drill increases with increasing cutting speed from the chisel edge to the outer part of the main cutting edge. Depending on the increase in flank wear and the rounding of the cutting edge, an offset of the cutting edges in the direction towards the leading edge of the drill bit occurs (Figure 7.14). The base line for the measurement of flank wear of the drill is the undamaged main cutting edge, which in the worn blade cannot be used for measurement. Therefore, in the transition area from the major flank face to the minor flank face behind the leading edge, a scratch with a diamond needle is made. Then, the distance from the scratch line to the main cutting edge for the case of a sharp new tool is measured. With successive measurements from scratch line to wear line, flank wear of the drill is determined. We need to measure the wear on both blades and determine the mean wear value according to the following equation: VB VB1 VB2 2 7.9 Figure 7.14 Determination of tool wear on flank face and on leading edge in drilling [1, 4] 136 TOOL WEAR Information about wear tests should be collected very carefully and systematically. In wear tests, it is not enough to only record the depth of cut, feed, cutting speed and cutting time. Without data on all the wear phenomena, the results cannot be used well enough. Further use of such data is impossible if one wants to deal with similar problems in machining. Boundary conditions must be systematically organized in the following order: workpiece material, machine tool, cutting tool material, constant or fixed cutting parameters, and sorted out in the form of a test. Table 7.11 shows a wear measurements form for turning. Table 7.11 Tool wear measurements form for turning (case study) Depth of cut Feed Cutting speed T (min) 1 3 6 9 12 16 20 24 28 Cutting edge angle Workpiece diameter Spindle speed ap = 2 mm f = 0.16 mm/rev. vc = 0.63 m/min VB (mm) 0.06 0.12 0.15 0.21 0.23 0.26 0.30 0.34 0.43 VBmax (mm) / / 0.16 0.24 0.27 0.31 0.38 0.42 0.55 KT (mm) KM (mm) Chip class 9-10 9-10 9-10 9-10 10 10 10 10 10 κr = 75o D = 176 mm n = 114 rev./min Remarks 137 METAL CUTTING – Theory and Applications 7.6 Laboratory works A. Laboratory tool wear measurements 1 Task: For selected regime and cutting conditions for turning, Table 7.13, it is necessary to determine the size of tool wear on the rake and flank face and draw the wear curve. Figure 7.15 Schematic setup of tool wear measurements principle [2] Table 7.12 Measuring instruments and accessories No. Name and characteristics Toolmakers microscope 1 Magnification 75× 30× High-resolution camera (5 MPx) Image processing software 138 Figure TOOL WEAR Table 7.13 Tool wear measurements form for turning Depth of cut Feed Cutting speed T (min) ap = f= vc = VB (mm) Cutting edge angle Workpiece diameter Spindle speed mm mm/rev. m/min VBmax (mm) KT (mm) KM (mm) Chip class κ= D= n= o mm rev./min Remarks 139 METAL CUTTING – Theory and Applications B. Laboratory tool wear measurements 2 Task. Measure and perform statistical data processing for flank wear at different cutting speeds. Measurement procedure: 1. Choose machine tool and cutting tool for experiment 2. Select three different cutting speeds vc 3. Remove insert from tool holder after each 2 minutes of machining 4. Measure flank wear VB on toolmakers microscope for each cutting speed setting 5. Perform statistical data processing Figure 7.16 Principle of tool wear measurements using toolmakers microscope Table 7.14 Machine tool data Elements Values Machine tool Type Designation Power P (kW) Feed range (mm/rev.) Spindle speed range (rev./min) Selected revolution speed nr (rev./min) Tool Designation Tool wedge angle α = β= Tool cutting edge angle, nose radius κr = rε = Workpiece Tool-overhang ln (mm) 140 Material designation Hardness HRC Tensile strength Rm (N/mm²) Dimension D L (mm) γ= TOOL WEAR Table 7.15 Measurements and calculations sheet (case study) Parameters ap (mm) f (mm/rev.) D (mm) Spindle speed n (rev./min) 2.0 220 0.350 Time t (min) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 467 Cutting speed vc (m/min) 60 No. 316 41 60 88 Flank wear VB (mm) 0.000 0.020 0.040 0.061 0.073 0.088 0.094 0.101 0.107 0.116 0.128 0.137 0.143 0.166 0.219 0.270 0.000 0.039 0.057 0.081 0.099 0.112 0.120 0.126 0.139 0.152 0.166 0.201 0.256 0.000 0.060 0.076 0.090 0.112 0.132 0.150 0.169 0.193 0.233 0.273 Using MS Excel, a diagram showing the dependence of tool flank wear VB on machining time is drawn, Figure 7.18. Figure 7.18 Wear curves for different cutting speeds [2] Trend lines are added and polynomial equations are derived (Add trendline – Display equation on chart in MS EXCEL), which show the influence of machining time T and cutting speed vc on flank wear VB: / / / 0.001 ∙ 0.001 ∙ 0.001 ∙ 0.018 ∙ 0.022 ∙ 0.024 ∙ 0.008 0.002 0.007 141 METAL CUTTING – Theory and Applications Practical tasks and calculations Task 1. Based on the monitoring of tool wear process on peripheral milling cutter tooth with milled teeth, shown in Figure 7.19, one obtains the flank tool wear functional dependence on the machining time, and it is approximated with parabola function: 0.05 1.8 ∙ 10 ∙ . Determine the overall tool life, if the maximum wear criterion on the flank face is VBmax = 0.3 mm, the size of the defect layer cutting edge c = 0.05 mm. Determine the reduction of tool diameter in each sharpening. Tool geometry: α = 20°, γ = 8°, lt = 6 mm. Figure 7.19 Wear process on peripheral milling cutter tooth with milled teeth [10] Solution: As for tools that need sharpening (HSS tools), the total tool life is calculated from the expression: Tu 1 i T where: i - the number of sharpenings, T - tool life. The number of sharpenings depends on the method used for tool sharpening, i.e. on the number and shape of cutting edges. The most commonly applied method is the sharpening on the rake face, where the number of possible sharpenings is calculated by the expression: i 0.5 lt lsh where is: lsh - tool length removed in one sharpening; lt - length of the tool flank face. Cutter tooth wear layer VBα is to be increased by the size of the defect layer removed by sharpening, and the length of sharpening can be expressed: where: VBα - the size of measured flank tool wear cα - the size of defect layer measured on the flank face 142 TOOL WEAR Figure 7.20 The scheme of sharpening peripheral cutter From the scheme of cutter sharpening, Figure 7.20, can be derived the following relation: VB c VB cos c cos cos When these expressions are included in the expression for calculating the size of material to be removed in one sharpening, we get the following: lsh VB c VB c cos 0.3 0.05 cos8 0.373 mm . cos cos cos 20 cos 20 Number of sharpenings of the cutting tool will be: i 0,5 6 8.04 0.373 rounded to the nearest smaller value, the number of sharpenings will be: i = 8 Tool life can be determined from the above-defined functional dependencies on the tool wear exactly defined criterion, VBmax = 0.3 mm: 1 1 VB 0, 05 3 1,38 0,3 0, 05 3 1,38 T max 10 10 36 min . 1,8 1,8 Total tool life will be: Tu 1 i T 1 8 36 324 min . Teeth Height is reduced with sharpening. The size of this reduction can be calculated with the expression: Dt 2 lsh sin 2 0.373 sin 20 0.255 mm . C. Remarks 143 METAL CUTTING – Theory and Applications Literature: [1] Cedilnik M., Rotar V., Kopač J.: Cutting 1, supplementary material for lectures and exercises, script, Ljubljana, 2006 (in Slovenian) [2] Globočki-Lakić G., Sredanović B.: Supplementary material to perform laboratory exercises in metal cutting process, Faculty of Mechanical Engineering, Banja Luka, 2011 (in Serbian) [3] Lazić M.: Metal cutting process, Faculty of Mechanical Engineering, Kragujevac, 2002 (in Serbian) [4] Kopač J.: Metal cutting – theoretical bases and technological instructions, Faculty of Mechanical Engineering, Ljubljana, 2008 (in Slovenian) [5] Klocke, F.: Manufacturing Processes 1, Cutting, Springer Heidelberg Dordrecht London New York, 2011 [6] Sandvik Coromant: Metal Cutting Technology, Technical Guide, 2010 [7] Çalşkan, H., Kurbanoğlu, C., Panjan, P., Čekada, M., Kramar, D.: Wear behavior and cutting performance of nanostructured hard coatings on cemented carbide cutting tools in hard milling, Tribology international, 2013, vol. 62, 215-222 [8] Globocki - Lakic, G., Nedic B., Ivkovic, B., Golubović - Bugarski, V., Cica Dj.: Possibility of Determination of Material Machinability Over Tribological Parameters by Use of Tribometer Block on Disk, Proc. of 9th CIRP International Workshop on Modelling of Machining Operations, Bled, Slovenia, 2006 [9] Globočki - Lakić, G., Sredanović, B.: The importance of modeling in the study of machinability, 5th International Conference on Manufacturing Engineering, ICMEN 2014 Thessaloniki, Greece, 2014 [10] Lazić M.: Metal cutting process, material for exercises, Faculty of Mechanical Engineering, Kragujevac, 2002 (in Serbian) 144 CHAPTER VIII SURFACE ROUGHNESS Contents 8.1 8.2 8.3 8.4 8.5 Theoretical considerations Basic definitions of surface roughness Surface roughness in machining Surface roughness measurements Laboratory work - Surface roughness measurements 8.1 Theoretical considerations No mechanical cutting process provides a perfect smooth surface. Every real surface deviates from the nominal (ideal) surface to some extent. The extent of geometric imperfection is defined at the macro-geometric level (shape and dimensions) and the micro-geometric level (waviness and roughness). Figure 8.1 Factors influencing the quality of machined surface 145 METAL CUTTING – Theory and Applications The quality of machined surface is an important parameter for defining the machinability of a material in cutting, especially when one must ensure: required tolerances pertaining to the quality of machined surface (fits of functional surfaces, etc.), required quality of processing in order to increase resistance to abrasion, corrosion, and friction (the sliding surfaces of bearings, surfaces of fits), lower processing costs (no additional fine finish costs). There is a large number of influential parameters that affect surface quality, Figure 8.1. Due to a large number of influencing factors, it is very difficult to set a reliable connection between machining methods and the quality of machined surface [1–4]. To illustrate, systematized links between quality and roughness classes for different types of machining are shown in Table 8.1. Table 8.1 Overview of quality classes and surface roughness values which can be achieved with different manufacturing processes GRADATION Finest machining Fine machining Pretreatment Roughing QUALITY CLASSES Arithmetic deviation from the mean line profile Ra [μm] 0.025 0.05 0.1 0.2 0.4 0.8 1.6 3.2 6.3 12.5 Rough planning Fine planning Rough turning Pretreatment turn. Fine turning Finest turning Drilling Countersinking Reaming Fine reaming Finest reaming Rough milling Pretreatment mill. Fine milling Finest milling Broaching Fine broaching Rough grinding Normal grinding Fine grinding Finest grinding Honing Fine honing Finest honing Rough lapping Pretreatment lapp. Fine lapping Finest lapping 146 25 50 SURFACE ROUGHNESS 8.2 Basic definitions of surface roughness With regards to components, a distinction is often made between macro-geometric parameters and surface quality. Macro-geometric parameters refer to deviations from dimension, form and position. Surface quality is defined by roughness parameters. Transitions between these categories are not always clearly definable. DIN 4760 offers a general system for organizing structural deviations (Figure 8.2). It is therefore necessary to define the term “surfaces” at the beginning. Real surface is the surface that results from the processing of a part. Actual surface is the effective (measured) surface. It may differ from the real surface, since any measuring method can only approximate the real surface. Figure 8.2 Structural deviations, acc. to DIN 4760 A geometrically ideal surface is specified in designs and it forms the basis of tolerances. In Figure 8.3 six orders of structural deviations are defined on the basis of these observations. Structural deviations of the 1st order are frequently the result of systematic errors (errors in machine guides, machine or workpiece bending, incorrect workpiece clamping, deformation due to annealing, wear, ...) With regards to waviness, i.e. the structural deviations of the 2nd order, one cannot clearly define whether they are caused by systematic or random influences (the eccentric clamping of the workpiece, errors in cutter shape, tool or machine vibration). The unbalance of a rotating tool and any periodical oscillations caused by it are forced, while sudden rattling oscillations are self-starting. In general, fundamentally different actions must be implemented in order to exclude any systematic or random causes of error. Structural deviations of the 3rd order also occur regularly. They are to be attributed to the penetration between tool and workpiece and are often determined by means of penetration calculations. Examples of these are kinematic roughness associated with turning, surface marks created in peripheral milling and generated cut deviations created in hobbing. In such cases, structural deviations can be influenced in a targeted way by means of generation of kinematics and tool design. The higher orders of structural deviation are primarily random in their occurrence. Examples of structural deviations of the 4th order include chip formation processes and removal processes. Roughness of the 5th order is rendered visible by structural properties on the surface. This can play a significant role in the high-precision machining of metallic optical mirrors. Thus in high-precision turning of multicrystalline metals, grain boundaries may 147 METAL CUTTING – Theory and Applications become visible because the individual crystals exhibit varying orientations and therefore varying stiffness. In this case, anisotropism of the grains becomes visible on the surface. In general, all the structural deviations on a real surface are superposed. Filters are employed to separate roughness and waviness in a measurement process. Roughness parameters are defined according to the system centre line (M system), which represents the base line of the profile. It is determined so that the profile mean square deviation is minimum within the reference length. For the profile of the machined surface in the figure 8.3 the following parameters are defined: The total height of the profile (maximum height of irregularities) Rmax (Rt): the sum of the highest profile point and the depth of the deepest profile valley within the measured length L. Ridge width k is the distance between two adjacent peaks. The mean roughness value (centreline average) Ra: the arithmetic mean of the values of the y-coordinates Z(x) within a sampling length Li Ra 1 n Yi n i 1 or l Ra 1 Y dx L 0 8.1 Ten-point mean roughness (ten point height of irregularities) Rz is the average distance between the five peaks and the five deepest valleys within the sampling length, Rz R1 R3 ..... Rm ( R2 R4 ..... Rn ) 5 8.2 Figure 8.3 Fundamental terms of surface inspection technology The basic and most widely used roughness criterion is the medium arithmetic profile deviation Ra, while the remaining criteria are complementary. According to the standard, Ra roughness is classified into twelve classes. Comparison between classes and criteria of roughness are shown in Table 8.2. 148 SURFACE ROUGHNESS Table 8.2 Roughness classes and corresponding ridge width Roughness class N1 N2 N3 N4 N5 N6 N7 N8 N9 N10 N11 N12 Highest value in µm Ra Rz 0.025 0.10 0.050 0.20 0.100 0.40 0.20 0.80 0.40 1.60 0.80 3.20 1.60 6.30 3.20 12.50 6.30 25 12.50 50 25 100 50 200 Ridge width [mm] 0.006 0.0125 0.025 0.050 0.100 0.20 0.40 0.80 1.60 3.20 6.30 12.5 8.3 Surface roughness in machining In machining with defined tool shape, ideal surface roughness represents smoothness, which is dependent on sharpness of the tool used in the cutting process. Medium arithmetic profile deviation is calculated from the profile of machined surface so that with the centre line, the profile is divided into two equal parts. The criterion for surface roughness Ra is given as the sum of the absolute values of the areas above and below the mean line divided by the length of the reference (see Figure 8.3 and Eq. 8.1). If we carefully monitor the cutting process, we can conclude that the medium arithmetic profile deviation Ra is the most depending on feed rate f and on cutting tool corner radius r. The following example shows the generation of surface quality for a simple external turning process. Since chip formation processes are ignored, we speak in this case of the generation of kinematic surface roughness. For this, the tool penetration into the workpiece is geometrically evaluated taking into consideration the kinematics in the tool reference plane Pr, Figure 8.4. Figure 8.4 Geometric ratio of engagement in cutting process and theoretical kinematic surface roughness definition 149 METAL CUTTING – Theory and Applications It is practically impossible to achieve ideal machining conditions, so the actual surface roughness usually differs very much from the theoretical kinematic one. Due to the presence of BUE, wear and vibration, tool and workpiece, irregularity in the feed movement of the tool, irregularity in the structure of the workpiece, uneven chip formation and many other effects, the actual surface roughness has very random shape. In the practical machining of a particular piece with a selected tool, the impact of feed and cutting speed on surface finish is often analysed. From the diagram in Figure 8.5, which shows the influence of feed and tool radius on theoretical and actual surface roughness in turning, it can be seen that roughness increases by increasing feed rate and decreasing tool corner radius. Figure 8.5 Influence of feed and tool radius on theoretical and measured roughness Rz Final conclusions With experimental monitoring of various machining conditions, the influence of various parameters that affect surface finish can be determined. In particular in high-speed machining, one of the most serious problems is the occurrence and presence of vibrations, which (in) directly affect the quality (or roughness) of machined surface. In Figure 8.6 – first row, the influence of the tool cutting angle κ on the formation and amplitude of vibrations. The presence and amplitude of vibrations in a tool are directly linked with the choice of tool corner radius r (2nd row), rake angle γ (3rd row) and tool wear (or shape), last row in Figure 8.6. 150 SURFACE ROUGHNESS Figure 8.6 The influence of tool cutting angle κ, corner radius r, rake angle γ and tool wear on formation and amplitude of vibrations [5] 8.4 Surface roughness measurements Surface quality is a three-dimensional problem. Surface roughness parameters describe the size and shape of micro-surface roughness measurements and therefore represent a very complicated technical problem. For this reason, we must often use several criteria for evaluating surface roughness or even specify a type of machining. Methods for measuring the surface profile are quantitative methods. Most used are the principles that contact the surface with stylus profilometer. Its movements are registered by means of electric instruments. Conversion of mechanical movements into electrical impulses is carried out with piezo crystal or inductive coils. In order to follow the profile, diamond stylus should be rounded with probe tip as small as possible (0.02 – 50 µm). Principle of operation of such instruments is shown in Figure 8.7. Figure 8.7 Two working principles of mechanical roughness measuring methods 151 METAL CUTTING – Theory and Applications The relevant ISO-standards give not only the definition of characteristics but also requirements on measuring instruments (e.g. probe tip radius; distance between measuring points) and software (e.g. phase-correction Gauss filter). The profile, which is obtained by means of the section probing method, is called, after the application of the filter for short wavelengths λs, the primary profile (P-profile). The roughness profile (R-profile) is obtained through the deletion of the long-wavelength profile features (threshold wavelength λc) from the primary profile. The waviness profile (W-profile) is made by filtering the primary profile by means of λc and λf, as depicted in Figure 8.8. Figure 8.8 Separation of waviness and roughness profile by wave filter [6] The threshold wavelengths λc and λs necessary for this filtering readable in Figure 8.9 after profile classification between periodic and aperiodic. No concrete definition currently exists for the threshold wavelength λf, only the recommendation of λf = 10(5)λc. Besides the threshold wavelengths for the separation of profile elements, definitions of the maximum probe element radii and the distances between measuring points are established. However, there are severe restrictions for the use of instruments in this way [7]. Figure 8.9 Measuring conditions (ISO 3274 and ISO 4288) 152 SURFACE ROUGHNESS The additional assembly of y-shift table perpendicular to the actual feed direction allows the collection of data from flat, three-dimensional structures. Using an appropriate software package, one can derive three-dimensional surface characteristics from this data, or rather a visual impression of the surface for the benefit of the user. This allows conclusions on properties of the surface, which one cannot easily derive from a single profile. Figure 8.10 3D surface structure in turning Regarding the practice, 3D parameters are signed with the letter S. Their indexes, principal, and geometrical content are similar to 2D parameters. While 2D parameters are described by functions with one variable [y=f(x)], 3D parameters are characterized by functions with two variables [z=f(x,y)]. It possesses a sampling area, while it is a sampling length for 2D parameters. Most of the 2D parameters have their 3D equivalent [8]. Figure 8.10 shows the three-dimensional measured structure of a workpiece that was machined on conventional lathe. The differences in altitude are represented by different colours. The ridge width caused by the tool shape engagement and feed rate curvature left behind the tool is clearly recognizable. 8.5 Laboratory works – Surface roughness measurements Task 1. For different values of feed rates, measure mean roughness value Ra of the machined surface. Figure 8.11 Schematic diagram of roughness measuring principle [9] 153 METAL CUTTING – Theory and Applications Table 8.3 Measuring instruments and accessories No. Name and characteristics 1 Calliper Measuring range: 0 - 150 mm Accuracy: 0.01 mm Figure Portable Surface Roughness Tester 2 ISO, ANSI, JIS Measurement procedure: 1. Choose machine tool and cutting tool for experiment 2. Define six different feed values f 3. For each parameters combination measure the surface roughness of the three sites 4. Perform statistical analysis of results Figure 8.12 Roughness measurement procedure and printed result 154 SURFACE ROUGHNESS Table 8.4 Machine tool data Machine tool Elements Values Type Designation Power P (kW) Feed range (mm/rev.) Spindle speed range (rev./min) Tool Designation Tool wedge angle α= β= Tool cutting edge angle, nose radius κr = rε = γ= Tool-overhang ln (mm) Workpiece Material designation Hardness HRC Tensile strength Rm (N/mm²) Specific mass ρm (kg/m³) Dimension D × L (mm) Table 8.5 Measurements and calculations sheet (Surface roughness – measured values) f (mm/rev.) vc (m/min) ap (mm) 0.0175 200 0.4 0.10 200 0.4 0.125 200 0.4 0.15 200 0.4 0.20 200 0.4 0.25 200 0.4 Ra (µm) Ra (µm) - average 155 METAL CUTTING – Theory and Applications Figure 8.12 Diagram of feed rate influence on surface roughness Ra Table 8.6 Measurements and calculations sheet (Surface roughness – case study) No. f (mm/rev.) 1 0.1 2 0.2 3 0.3 4 0.4 5 0.5 6 0.6 156 Ra (µm) 0.34 0.38 0.31 1.29 1.22 1.34 2.97 2.88 2.91 5.21 5.14 5.15 8.23 8.21 8.26 9.99 10.19 10.27 Ra (µm) - average 0.34 1.28 2.92 5.17 8.23 10.15 SURFACE ROUGHNESS Using MS Excel, a diagram showing the influence of feed on surface roughness can be created. By applying least squares method (in Excel: function Add trendline – Display equation on chart) an empirical model is generated, Figure 8.13. Figure 8.13 Influence of feed rate on surface roughness Ra Task 2. Derive the equation for theoretical total height of the profile Rmax in turning based on feed f and tool corner radius r. _________________________________________________________________________ _________________________________________________________________________ _________________________________________________________________________ _________________________________________________________________________ _________________________________________________________________________ _________________________________________________________________________ _________________________________________________________________________ _________________________________________________________________________ _________________________________________________________________________ 157 METAL CUTTING – Theory and Applications Task 3. Define the highest feed rate f, which can be used in turning with tool corner radius r = 0.4 mm when total height of the profile Rmax = 1.6 μm should be achieved. _________________________________________________________________________ _________________________________________________________________________ _________________________________________________________________________ _________________________________________________________________________ _________________________________________________________________________ _________________________________________________________________________ _________________________________________________________________________ _________________________________________________________________________ _________________________________________________________________________ _________________________________________________________________________ _________________________________________________________________________ Remarks 158 SURFACE ROUGHNESS Literature: [1] Globočki, L. G., Sredanović, B., Kramar, D., Nedić, B., Kopač, J.: Effects of Using of MQL Technique in Metal Cutting, 13th International Conference on Tribology SERBIATRIB 13, Kragujevac, Serbia, 2013, 292 - 301 [2] Raykar, S. J., D'addona, D. M., Kramar, D.: Analysis of Surface Topology in Dry Machining of EN-8 Steel. Procedia materials science, 2014, vol. 6, 931-938 [3] Globočki- Lakić G., Sredanović B., Jokanović S., Borojević S.: Vector Based Approach in Defining of Universal Machinability, In-TECH, Prague, Czech Republic, 2010, 326 - 329 [4] Nedić B., Jovanović D., Globočki Lakić G.: Influence of previous machining on characteristics of galvanic cooatings, 12th International Conference on Tribology SERBIATRIB 11, Kragujevac, Serbia, 2011, 146 - 151 [5] Sandvik Coromant: Metal Cutting Technology, Technical Guide, 2010 [6] Klocke, F.: Manufacturing Processes 1, Cutting, Springer Heidelberg Dordrecht London New York, 2011 [7] Grote K-H., Antonsson, E. K.: Handbook of Mechanical Engineering, SpringerVerlag, 2008 [8] Staut, K. et al.: (The development of methods for the characterisation of roughness in three dimensions. Report EUR 15178 EN. EC. Brussels,1994 [9] Globočki-Lakić G., Sredanović B.: Supplementary material to perform laboratory exercises in metal cutting process, Faculty of Mechanical Engineering, Banja Luka, 2011 (in Serbian) 159 CHAPTER IX MANUFACTURABILITY AND MACHINABILITY Contents 9.1 9.2 9.3 9.4 Theoretical considerations Manufacturability Machinability Case studies 9.1 Theoretical considerations Parts that are machined by cutting can be encountered in all branches of industry [1]. Metal cutting is used for the production of components which require high dimensional accuracy, complex surface, and high quality of the machined surface. The manufacturing of the mentioned parts is carried out in large, medium, and small batches, and in individual production with defined appropriate workpiece stock (Figure 9.1). Current trends in production technologies affect the planning and execution of machining in the way that they require [1]: shorter timespan from request to final product, near shape processing to increase utilization of materials, increased precision machining, reduction of production costs, ability to create various forms, product life extension, compliance with principles of ecological production. Figure 9.1 Machined part and corresponding stock [2] 161 METAL CUTTING – Theory and Applications Table 9.1 Manufacturability and machinability parameters [3] Component Materials P M K N S H Steel Stainless steel Cast Iron Aluminium Heat resistant m. Hard materials Operation Conditions Environment Turning Clamping Coolant Milling Hardness Cutting parameters Boring Dry machining The planning of a machining process is a complex task due to many interactions of parameters. New technologies and materials, non-systematic knowledge, and machining methods further complicate the mentioned problem. In product development, the designer’s objective must be to achieve product functionality taking into consideration production costs and possibility of using available technologies and processes. The main part of the planning process is the recognition and analysis of the technological features of a workpiece (Figure 9.2). Figure 9.2 Recognition of technological features (holes, channels, pockets) Technological features represent the ordered information set about geometric forms that are defined by appropriate machining process, process parameters and non-geometrical parameters related to the same machining process. The information contained in the technological features includes: class of forms (cylindrical, prismatic, complex surface, 162 MANUFACTURABILITY AND MACHINABILITY etc.), geometric shapes (cylinder, groove, pocket, channel, etc.) and production conditions (quality and accuracy). Based on the type and size of the technological features, one can define the necessary operations, the required characteristics of tool machines, cutting tools and clamping accessories. The planning process includes: 1. analysis of workpiece, 2. stock definition (defining of roughing and finishing allowance), 3. operations plan, 4. plan for clamping (requirements for clamping devices and grouping of operations), 5. plan for tool machine (requirements for work space and movements, for example), 6. plan for cutting tools (requirements for tool types and characteristics), 7. processing parameters definition (cutting speed, depth of cut and feed). In product design, designers and technologists work together in order to improve and adapt product characteristics to suit production capabilities, a practice known as the concept of DFM (Design for Manufacturing). Process planning is usually based on the criterion to reduce machining time and cost of production without reducing nominal demands for the quality and functionality of parts. When developing a possible execution of the machining process, it is necessary to take into account the following: manufacturability - in accordance with capabilities to machine technological features, machinability - in accordance with capabilities to machine workpiece material. Figure 9.3 Influence on machinability and manufacturability definition The analysis of manufacturability and machinability based on geometric characteristics and characteristics of the workpiece material is related to the characteristics of machining equipment, processing conditions, external environment conditions, human factor, availability of equipment, etc. (Figure 9.3). The analysis of manufacturability and machinability is mostly based on empirical knowledge. The complexity of this problem has led to the development of CAPP system that incorporates the technologist’s knowledge and database of materials, tools and tool machines [4]. CAPP can be defined as a set of computer aided activities that simplifies and supports the work of technologists. As such, it represents the link between product design systems (CAD) and machining design systems (CAM). The development of CAPP was aimed at reducing the manual work of technologists, optimization performance, knowledge systematization and proper analysis of machining time and production cost [4]. Knowledge about technology is based on the understanding of the workpiece geometry and non-geometrical information about product (type of treatment, clamping and positioning of workpiece, type of cutting tools, etc.). 163 METAL CUTTING – Theory and Applications 9.2 Manufacturability Manufacturability can be defined as the ability to manufacture a part with ease regarding its geometric features and additional technological characteristics [5]. It is defined as the ability of a workpiece to be manufactured by executing appropriate operations. Manufacturability is difficult to express as an explicit value. When analyzing a workpiece in process planning, the following characteristics must be included: workpiece dimensions (maximum and minimum dimensions), workpiece shape (dimensional size, relative size), complexity (symmetry, latency of technological forms), dimensional and positional tolerances (values, relations) surface roughness (maximum height roughness, mean deviation), batch size (number of pieces to be produced), delivery speed (required time of manufacture), cost of processing. Figure 9.4 Tool machine movements as the basis for determination of manufacturability [3] The processing plan includes a sequence of operations in accordance with the clamping plan. Possible tool machine movements and workpiece orientation must be considered when planning the operations sequence (Figure 9.4). The basic rule for determining the operations sequence is that prior to the machining of the observed surface, the surface based on which it is dimensioned must be machined. The surface that is dimensioned based on the clamping base has the priority. The workpiece area with defined position tolerances must have the priority in machining. The basis for the cutting plan definition is to extract information about individual technological features. Technological features in cutting can be produced through the following operations: turning, milling, drilling, grinding etc. The choice of operation is essentially influenced by the required surface quality of a workpiece (Figure 9.5). Some operations cannot provide fine surface quality [5]. The problem can be partially resolved by introducing the roughing and finishing operation. Roughing and finishing processes in an operation differ in the values of process parameters, and very often, in the type of cutting tools, and relative movements between the tool and the workpiece. Due to different tool types used for roughing and finishing, these two types of processing can be defined as separate operations and thus defined as specific technological features. 164 MANUFACTURABILITY AND MACHINABILITY Figure 9.5 Value of surface roughness for different types of operations Cylindrical technological features (with given surface roughness, tolerances, and shapes) can be obtained by turning, but also by milling (Table 9.2). However, turning is a more productive process than milling. In machining of cylindrical shapes by turning, one can achieve a more precise geometry because it is realized through the natural rotation of the workpiece. In turning, it is necessary to avoid situations where cutting depth and feed are equal (Figure 9.6). The relation between cutting depth and feed should be ap > fn. It is necessary to provide processing conditions where cutting depth is greater than the tool tip radius ap > rε. Chamfers on the workpiece contour greater than 22° are inadequate for turning with other contour and with one cutting tool. To solve this problem, one must use acceptable tool insert shapes or the right turning tool (Figure 9.7). Low roundness is difficult for turning and must be machined with cutting tools whose tip radius is smaller than the roundness in order to avoid vibrations (Figure 9.8). 165 METAL CUTTING – Theory and Applications Table 9.2 Turning operation and its application [3] Turning operations Application External turning It is used for: - external facing - external longitudinal turning - external radial turning Can be performed with multi passes or specific CNC cycles. This operation type is used for medium feeds and steps in turning. Internal turning It is used for: - internal facing - internal longitudinal turning - internal radial turning Can be performed with multi passes or specific CNC cycles. This operation type is used for medium feeds and steps in turning. Parting It is used for: - grooving - parting - making of rotational channels (internal and external) Can be performed with multi passes or one pass. This operation type is used for low feeds and steps in turning. Figure 9.6 Recommendations for relation between cutting depth, feed and tool tip radius [3] 166 MANUFACTURABILITY AND MACHINABILITY Figure 9.7 Recommendation for cutting tool use in machining of chamfers [3] Figure 9.8 Recommendation for tool tip radius in machining of fillets [3] Table 9.3 Milling operations and their application [3] Milling operations Application Face milling It is used for milling of planar surface, with smaller depths of cut. Can be performed with appropriate CNC cycles for facing. Shoulder milling It is used for milling of shoulder and steps, with smaller depths of cut. Can be performed with multi passes and appropriate tool machine movements. 167 METAL CUTTING – Theory and Applications Edge milling It is used for milling of edge side and deeper shoulder, with higher depths of cut. Can be performed with multi passes and appropriate tool machine movements. Slot milling It is used for milling of slot, pocket and simple profile milling, with higher depths of cut. Can be performed with multi passes and appropriate tool machine movements. Profile milling It is used for milling of complex surfaces. Must be performed with multi-simulating movements of tool machine. For this type of milling ball nose cutter is commonly used. Prismatic parts can be primarily manufactured by milling operations (Table 9.3). In case of defining simple shapes, technological features on prismatic parts can be manufactured by milling operations on tool machines with 2½ D control. In modern industry appear prismatic parts with complex shape and their configuration cannot be described through simple technological features. If processes on machines have a higher level of control (for example 3D or 5D control), it complicates the definition of technological features. In milling, deep features and features on a workpiece with inaccessible surface are complicated for machining with conventional tools, operations and tool machine movements (Figure 9.9). Machining of inaccessible and deep places on a workpiece, due to poor chip evacuation and tool vibration, destroys the machined surface and causes parts spoilage (Figure 9.10). Figure 9.9 Problem of inaccessible surface machining [3] 168 MANUFACTURABILITY AND MACHINABILITY Figure 9.10 Problems of deep inaccessible machining [3] In milling of pockets with rounded corners, it is necessary to use specific strategies and circular movements of tool machine. For this to be possible, the radius of the milling cutter must be smaller than the radius of the rounded corner. One must avoid situations where the tool axis coincides with the workpiece axis or workpiece edge. In milling of channels, it is preferable that the diameter of the milling cutter is smaller than the channel width. These strategies result in higher accuracy and lower incidence of vibration. Sudden changes in the continuity of the workpiece volume (such as holes, pockets, chamfers, channels, etc.) result in vibration and tool breakage (Figure 9.11). Processing unfavourable thin-walled structures on a workpiece requires a special machining strategy, where at any time of machining one must ensure support to the observed structure. Figure 9.11 Features with discontinuous structure [3] Drilling processes are intended for the machining of volatile and non-volatile holes. The basic drilling operations include: drilling, boring and reaming (Table 9.4). In addition to the basic operations, one can perform other operations such as start-drilling, deep holes drilling and threading. The main problem in hole drilling is the formation of inadequate chip shapes and their removal from the cutting zone. Long chips get stuck between the drill tool and the hole, and this situation distorts the surface quality. If the input or output surface of the hole is uneven, it is necessary to reduce the feed (Figure 9.12). Drilling on asymmetrical and inclined surfaces and expansion of holes with small cutting depth with a drill tool is not allowed (Figure 9.13). 169 METAL CUTTING – Theory and Applications Table 9.4 Drilling operations and their application [3] Drilling operations Application Drilling It is used for drilling of holes with lower quality of machined surface. It is used for: - simple holes, - blind holes, - irregular holes, - deep holes. Commonly, it is performed with appropriate CNC cycles. Chamfering It is used for: - step holes, - taper holes, - chamfered holes. Commonly, it is performed with appropriate CNC cycles or one pass machining. It is used for drilling of holes with lower quality of machined surface. Boring It is used for drilling of holes with higher quality of machined surface. It is used for: - boring of simple holes, - boring of holes with large diameters, - special boring, - reaming. Commonly, it is performed with one pass machining. Figure 9.12 Reduction of feed during drilling on complicated start surfaces [3] 170 MANUFACTURABILITY AND MACHINABILITY Figure 9.13 Recommendations for drilling on complicated surfaces [3] 9.3 Machinability Machinability is a relative characteristic of a material and can be defined as the ease with which the material can be machined. Machinability, being a technological characteristic of materials, can be defined as material’s ability to be machined with ease or difficulty using appropriate operations within a narrow range of defined process parameters and conditions (Figure 9.14). Generally, machinability is defined as the ability of a material to be processed using economical methods of machining. The disadvantage of this definition is that it does not make it possible to quantify or measure machinability. Therefore, machinability is a material’s ability to provide required quality, high efficiency, productivity and process costeffectiveness in machining. Figure 9.14 Parameterization of machinability [6] 171 METAL CUTTING – Theory and Applications As a technological characteristic, machinability is not only related to material, but also to the cutting process. The study and definition of machinability in metal cutting includes several phases: experimental measurements, modelling of process parameters, definition of machinability, and utilization of knowledge about machinability of a material. The aim of the machinability study is the need for increased productivity and decreased production costs. Machinability covers the following areas [6]: machining of materials, process planning, optimization of machining processes, construction of new tools, inserts and coatings, testing of dosage techniques and type of coolants and lubricants. There are many direct and indirect factors that influence machinability, but they all fall into three basic categories that are related to the workpiece and tool material, cutting conditions and machining system characteristics. Influential factors can be divided into three groups: factors related to the cutting process, factors related to the cutting tool and factors related to the workpiece (Figure 9.15). Figure 9.15 Influential factors on machinability [1] Figure 9.16 Direct and indirect functions and criteria of machinability [1] 172 MANUFACTURABILITY AND MACHINABILITY Machinability is defined by the basic and additional set of functions and criteria. Figure 9.16 shows the correlation between the criteria for the definition of machinability, where is: MRR - material removal rate for standard tool life, MPR - mechanical properties of the workpiece, CF - cutting forces, CHCOM - chemical properties of the material, TCOND thermal conductivity of the material, CT - cutting temperature and CHF - chip shape. A set of machinability functions can define machinability accurately enough [10]. When defining a material’s machinability, it is important to select and rank the basic machinability functions taking into consideration the following facts [7, 8, 10, 11]: 1. The basic machinability functions do not have equal importance in all types of processes. For example, in roughing tool life has the greatest importance, as it provides maximum productivity. In this case, the aim is to minimize the cutting force. In finishing, most affected functions are surface quality and dimensional accuracy. The above facts indicate the complexity of defining, where requirements must be met. 2. A material may have contrasting indications of machinability with respect to different criteria. Some materials have good machinability according to one criterion, and poor according to another. For example, aluminium has good machinability regarding the cutting forces criterion, and poor machinability regarding the surface roughness criterion. Table 9.5 Machinability testing methods [6] Groups Subgroups Method of cutting forces measurement Method of friction measurement in cutting zone Comparative methods (index methods) Method of temperature measurement in cutting zone Radioactive method Method of constant length of cutting Method of constant loads Express method Complex methods (functions methods) Method of orthogonal plans Chemical composition test Tapper turning test Absolute methods (tests on complex parts) Step turning test Variable feed rate test Modern experimental techniques and procedures in cutting processing have contributed to the development of different machinability testing methods (Table 9.5). All testing methods are based on some machinability criteria [12, 13]. One of the most common ways to express machinability is through machinability index [14]. It is a relative measure of machinability that is compared with the selected material - etalon material (Figure 9.17). 173 METAL CUTTING – Theory and Applications Figure 9.17 Machinability indexes for different materials and criteria [6] The following are three most commonly used physical material parameters for analyzing machinability of materials: hardness (HRc), strength (Rm), and thermal conductivity (c). The effect of alloying elements in a workpiece material has a crucial influence on the ease of machining. Figure 9.18 Machinability indexes for different steels [6] Various combinations of alloying elements in steel as well as the chemical composition of alloys used in metal industry have different influence on the ease of the cutting process (Figure 9.18). Structural steels have good machinability. They can be machined at higher cutting speeds, do not stick on the tool edge and have good thermal conductivity. Manganese stainless steels are difficult to machine due to their high strength. They are machined at medium cutting speeds. Chromium-Nickel steels have low machinability due to the occurrence of carbides and nitrides, high strength, hardness and heat resistance. They usually have an austenitic structure. Chromium-Nickel steels are machined at lower cutting speeds. 174 MANUFACTURABILITY AND MACHINABILITY Table 9.6 Influence of alloy elements on machinability of steels Element Carbon Silicon Manganese Chrome Nickel Tungsten Chem. mark C Si Mn Cr Ni W Percentage of alloying Influence on machinability < 2% Steel with 0.8% has maximum machinability, with highest Rm. Reducing the percentage of carbon causes increase of toughness. Increasing the percentage causes increase of hardness. > 0.6% Moderately increases Rm and elasticity and decreases toughness of steel. Increases resistance to corrosion. It has diverse impact on machinability. > 0.8% Expanded austenitic field of steel moderately increases the strength, toughness and hardness. Strongly reduces tendency to oxidation. It causes intense abrasion of tool. > 0.3% The most used element. Extends ferrite area and increases hardness and dynamic strength, resistance to oxidation and chemical reagents. It causes intense abrasion of tool. > 0.3% It is always combined with other elements. Expands austenite field and increases strength and toughness at very low temperatures. Increases resistance to influence of chemical reagents. > 0.1% Intensively increases hardness of steel and wear resistance. Extremely intense, increases steel resistance (hardness and strength) at higher temperatures. Molybdenum Mo > 0.08% Extremely increases material toughness, strength and dynamic strength, and thus causes intense abrasion of cutting tool. Vanadium V > 0.1% Very intensively increases strength and toughness of steel, which are retained at higher temperatures. Increases elasticity of steel. Cobalt Co > 0.1% Greatly increases strength, corrosion resistance and wear resistance of material. It causes intense abrasion of tool. Ni alloys have very poor machinability due to nitride in their structure. They have stable hardness and strength at high temperatures and are high cutting resistance materials. Appearance of vibrations during machining leads to the strength of surface layers. Titanium alloys have very poor machinability because of their high strength, hardness and toughness, and because of their small thermal conductivity. They can be machined at lower speeds. 175 METAL CUTTING – Theory and Applications Aluminium alloys have better machinability at higher cutting speeds as it avoids the appearance of build on edge (BUE) on the cutting tool and appearance of higher surface roughness. Brass, the alloy of copper and zinc, has low machinability in cutting, because it results in very short chip. When machining at higher cutting speeds, BUE will appear due to the increase of cutting temperatures. Bronze, the alloy of copper and zinc alloy, is difficult to process due to high tensile strength at higher temperatures, as well as increased dynamic strength and toughness. Figure 9.19 Influence of vibrations on surface roughness [3] Elements of the machining system influence machinability in the following ways: Increase in cutting resistance; use smaller feed, smaller cutting depth and lower rake angle to reduce it. More intensive wear of the cutting edge; use lower cutting speed and a coolant to reduce it. Increase in the cutting edge temperature; use lower cutting depth, lower cutting speed, and a coolant to reduce it. Increase in surface roughness; use lower feed, the highest cutting speed and tool tip radius to reduce it. Appearance of unfavourable chip shape; use the highest cutting depth, tool with chip-breaker and smaller tool tip radius to reduce it. Increase of vibrations; to reduce them use stiffer cutting tool. Figure 9.20 Problems during machining of soft materials [3] Vibration is a very negative phenomenon in cutting. It occurs on the workpiece and the cutting tool and results in decreasing surface roughness (Figure 9.19). Brittle or soft workpiece material and vibration can lead to the appearance of "phantom holes" or larger or smaller values of diameter than the nominal diameter. A soft workpiece material, large inclination angle and lower feed can lead to the appearance of fat on the cut edges of the workpiece (Figure 9.20). This problem requires the introduction of additional operations. 176 MANUFACTURABILITY AND MACHINABILITY Research on manufacturability and machinability requires a complex experimental research, modeling, analysis and data sorting (Figure 9.21). In order to obtain conclusions about machinability of new materials machined with latest cutting processes, new tools, and different cutting parameters, one must perform complex process monitoring. Figure 9.21 Data flow in machinability research [6] In order to improve product quality, increase productivity and reduce costs, one needs to integrate continuous monitoring systems of the process on tool machine. The effectiveness of the cutting process monitoring depends on the ability to identify unfavourable events during cutting process. Monitoring process can be: on-line (monitoring during machining): measuring of cutting forces, measuring of vibration, measuring of cutting temperature, off-line (monitoring after machining): measuring of tool wear, measuring of surface quality, chip shape classification. Technological windows can be created during machinability testing. They are based on the French national standard NF E 66-520-6. A technological window is a graphical representation of the area of cutting parameters applicable value (Figure 9.22). It is obtained from experimental measurements and it represents the limit of the values of cutting parameters (cutting speed, depth of cut and feed), and other geometrical and physical parameters, too. An experimental research starts with setting the initial cutting parameters values. One parameter is set as a constant, while the other is changed in several levels. After exhausting all the combinations, the research procedure sets a new parameter as a constant. During the experimental research, the measurement of cutting force, vibrations, and surface roughness is performed, as well as the chip shape classification. The boundaries of the applicable area are determined when the measured values of the cutting parameters rapidly increase or reach a predetermined value [15]. The results of research on manufacturing and machinability by means of the mentioned experimental measurement can be sorted in a database and included in an appropriate catalogue of the world's leading producer of cutting tools. Databases that offer tool producers are often automated and available on the internet, which contributes to the development of CAPP system [3]. 177 METAL CUTTING – Theory and Applications Figure 9.22 Example of technological window for turning of C45E with conventional flooding and High Pressure Jet Assisted Machining (HPJAM) on pressure 110 MPa [15] 9.4 Case studies The following practical tasks are related to the manufacturability and machinability research and analysis (Task 1) and the use of the existing database related to machinability and manufacturability (Task 2). To perform cutting operations with no unfavourable events and with processing cost reduction is the main goal of the research of manufacturability and machinability. Task 1: Perform the complex testing of machinability for new tool insert for turning of bearing steel 100Cr6 with special CLF dosing techniques - High Pressure Jet Assisted Machining. Make the technological window for tested condition [15]. Solution: Solution will be achieved through the implementation of several phases pertaining to: setting initial requirements, experimental setup, description of the measurement equipment, and finally, analysis and presentation of the results. A. Cutting tool A new carbide tool insert for turning will be tested (Figure 9.23). Cutting tool mark is CNMG 1204 08 MF5 - TH1000, coated with nano-layer, and manufactured by SECO tools. It is a rhomboid insert with clearance angle 5° and rake angle 0°, radius of tool tip is 0.8 mm. Inclination angle is κ = 120°. The insert has special chip break geometry with trace for jet cooling and lubrication. Tool holder is PCBNR 2525 M12 by SECO tools. B. Workpiece materials Workpiece material is heat treated bearing steel 100Cr6. Tensile straight of this material is σ = 1000 N/mm², module of elasticity E = 2·10³ MPa and hardness is 62 HRc. Experimental research will be performed on rod workpiece with dimensions 60×250 mm. 178 MANUFACTURABILITY AND MACHINABILITY Figure 9.23 Tool insert TH1000 by SECO tools C. Tool machine Tool machine is universal lathe BOEHRINGER PRVOMAJSKA. Properties of tool machine are: power P = 8 kW, maximum spindle speed nmax = 2240 rev/min, maximum feed fmax = 1.6 mm/rev. Maximum dimension of workpiece is D×L = 250×1500 mm. Lathe is equipped with high pressure plunger pump for HPJAM (Figure 9.24). Figure 9.24 Universal lathe (left) and high-pressure pump for HPJAM machining (right) D. Experimental setup Figure 9.25 Experimental setup and data flow 179 METAL CUTTING – Theory and Applications Cooling and lubrication fluid is 3% emulsion of vegetable oil and technical water without chlorine by PRIMOL 3000. It is an organic emulsion with good tribological characteristic. HPJAM turning was performed at pressure 50 MPa and flow rate 2 l/min. The coolant jet from sapphire nozzle is directed to the cutting edge at angle of 30° with the rake face at the distance of 30 mm, in zone between clearance tool face and chip. Jet was hit on the tip of cutting edge at the angle of 90°. Nozzle diameter is 0.4 mm. E. Measuring devices The cutting forces were measured with a “KISTLER” measuring chain. The measuring chain consisted of 4-component dynamometer, connection cables, amplifier for signal conversion and software for monitoring and processing measuring signals. Measurement of tool wear was performed on a “MITOTOYO TM505” microscope with CCD camera and appropriate software for images processing. It has light source and 30x zoom lens, with positioning accuracy 0.001 mm. Surface roughness was measured using the measuring device “MITOTOYO Surftest SJ 301” with different measuring functions, which correspond to ISO, JIS, DIN and AISI standards. Measurement results can be transferred to PC via the external RS232 connection or on device monitor. Figure 9.26 Measuring devices: cutting force dynamometer (left), tool microscope (middle) and surf tester for roughness (right) F. Results and analyses Measured values of the cutting forces components (main cutting force – Fc, feed cutting force – Ff and passive cutting force – Fp) for different combinations of cutting parameters, are shown in Table 9.7. Table 9.7 Cutting forces for machining 100Cr6 with tool CNMG 1204 08 MF5 No. 1 2 3 4 5 6 7 8 180 Depth of cut Feed Cutting speed ap (mm) f (mm/rev) vc (m/min) 0.5 0.080 65 0.5 0.080 85 0.5 0.080 100 0.5 0.125 85 0.5 0.160 85 0.5 0.180 85 0.75 0.125 85 0.25 0.125 85 Fc (N) Ff (N) Fp (N) 302 293 278 337 361 383 409 269 211 201 196 227 242 251 350 122 239 247 244 304 348 365 417 184 MANUFACTURABILITY AND MACHINABILITY Figure 9.27 shows tool wear curves for different combinations of technological parameters. Table 9.8 shows the values of material removal rate (MRR), tool life and surface roughness at the beginning and end of machining time. Figure 9.27 Tool wear for different input parameters (ap = 0.5 mm) [6] Table 9.8 Tool life and surface roughness for machining 100Cr6 Depth of cut ap (mm) Feed f (mm/rev.) Cutting speed vc (m/min) MRR (cm³/min) Tool life T (min) Beg. time End time Beg. time End time 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.200 0.125 0.125 0.125 0.125 0.180 0.160 0.008 85 85 120 100 65 85 85 85 8.50 5.31 7.50 6.25 4.06 7.65 6.80 0.34 4.0 13.2 4.0 5.1 17.1 3.5 4.5 22.7 0.91 0.48 0.52 0.53 0.58 0.86 0.85 0.36 0.96 0.50 0.57 0.58 0.63 0.99 0.97 0.62 3.98 2.51 2.61 2.86 3.18 3.93 3.90 2.12 4.51 2.88 2.93 3.62 3.28 4.67 4.22 3.35 Ra [μm] Rmax [μm] Based on the analysis of cutting forces, it can be concluded that they increase by increasing feed and cutting depth, and reduce by increasing cutting speed. Tool wear increases by increasing feed and cutting speed. The analysis of measured values of surface roughness tells us that surface roughness increases with the increasing of tool wear. Average value of tool life for used cutting parameters is 9.25 min, and average value of material removal rate is 5.80 cm³/min. Technological parameters that allow optimal machining in accordance with the tool wear and productivity of machining (MRR), is ap = 0.5 mm, f = 0,125 mm/rev. and vc = 85 m/min. Tool wear in turning can be monitored through chip shape (Figure 9.28). Chip shape becomes unfavourable by increasing the flank tool wear. 181 METAL CUTTING – Theory and Applications Figure 9.28 Phase of flank tool wear and chip shapes in HPJAM turning [6] G. Presentation of results Tool wear is a dominant problem in the turning of hardened steel 100Cr6, so there is a tendency to use lower cutting parameters values. On the other hand, the mentioned decreasing leads to a reduction in productivity. Based on these facts, it is necessary to determine the area of acceptable parameters combinations, and based on that, technological windows can be formed (Figure 9.29). Figure 9.29 Technological window for tool insert TH1000 in HPJAM turning of 100Cr6 182 MANUFACTURABILITY AND MACHINABILITY Task 2: Workpiece is given in Figure 9.30. Present the process plan for machining; define operations, cutting tools, clamping plan and comments regarding manufacturability and machinability. Based on the above information, take cutting parameters from the catalogue and execute necessary calculation. Figure 9.30 Workpiece for practical example Solution: A. Comments about manufacturability: To machine the workpiece, it is necessary to use turning, drilling and milling (Figure 9.31). Turning must be performed first in order to remove material at diameters 32 mm and 50 mm. The above operation is followed by the drilling of a through hole 14. Then follows the milling of slots and a channel of diameter 50 mm. The drilling of the hole before milling is required due to non-favourable shape of the output surface that would result from the milling of the channel. This sequence is a good solution because of operations grouping, and because the drilling of the central hole can be performed on lathe. Figure 9.31 Phases of production by cutting 183 METAL CUTTING – Theory and Applications B. Comments about machinability: Structural steel C45E has medium machinability. It can be machined at higher cutting speeds and medium cutting depth. C. Stock definition: Based on the given machining operations, a metal rod with diameter 60 mm can be used (Figure 9.32). Machining will be performed on CNC machines. After turning, the workpiece will be cut-off from longest rod, so the stock length is not defined. Figure 9.32 Stock shape of workpiece D. Process planning For recognized machining operation can be used CNC lathe EMCO Turn 500 and CNC milling centre EMCO Concept Mill 450 (Figure 9.33). For this case, operation plan, tool plan and clamping plan is given in Table 9.8. Detailed tool information will be given in calculations. Figure 9.33 Tool machines for production of parts: milling machine (left) and lathe (right) 184 MANUFACTURABILITY AND MACHINABILITY Table 9.9 Process plan and other requirements Clamping No. 10 20 Clamping no. 1 Lathe jaws Clamping no. 2 Prismatic clamp devices 30 Name of operation Facing 60 on front side Rough turning: - taper 22×32×15, - cylinder 32×27, - radius R3, - shoulder from 32 to 50 - cylinder 50×25 Finish turning: - taper 22×32×15, - cylinder 32×27, - radius R3, - shoulder from 32 to 50 40 Drilling of hole 14×70 on lathe 50 Reaming of hole 14 h6×70 on lathe 60 Parting of workpiece on 70 mm 70 Edge milling of side on cylinder 50×25 80 90 Cutting tools Tool with insert for facing and longitudinal turning Drill 14 mm Reamer 14 h6 Turning tool for parting Rough slot milling in centre of cylinder 50×25 Finish slot milling in centre of cylinder 50×25 Flat end mill 8 mm Flat end mill 8 mm Flat end mill 8 mm E. Process parameter for operations E.1 Operation 30 Description: Fine turning of: taper 22×32×15, cylinder 32×27, radius R5, and shoulder from diameter of 32 to diameter 50. Figure 9.34 Cutting plan for operation 30 185 METAL CUTTING – Theory and Applications Turning tool: Insert: CNMG 12 04 04 - PF, SANDVIK carbide insert with quality GC4215 Rhomboid with angle 80° and radius of tool tip: rε = 0.4 mm Tool holder: DCLNR 2525 M 12 with inclination angle: r = 95° Figure 9.35 Cutting tool for operation 30 [3] Cutting parameters: For steel finishing and carbide inserts, cutting parameters are: Depth of cut: ap = 0.5 mm Feed: f = 0.15 mm/rev. Cutting speed: vc = 380 m/min Depth of cut must be greater than the feed value: ap > f → 0.5 > 0.15 and that is acceptable. Depth of cut must be greater than the tool tip radius: ap > rε → 0.5 > 0.4 and that is acceptable. Figure 9.36 Cutting parameters for turning from catalogue SANDVIK [3] 186 MANUFACTURABILITY AND MACHINABILITY Calculation of cutting parameters: Number of revolutions: 1000 ∙ ∙ 1000 ∙ 380 32 ∙ 3780 rev./min Feed velocity: ∙ 0.15 ∙ 3780 560 mm/min Power and productivity: Power, for specific cutting force kc = 2200 N/mm² and machine efficiencies c = 0.9: ∙ ∙ ∙ ∙ 60 ∙ 10 0.5 ∙ 0.15 ∙ 380 ∙ 2200 0.9 ∙ 60 ∙ 10 1.2 kW Productivity: ∙ ∙ 0.5 ∙ 0.15 ∙ 380 285 cm /min Machining time: Number of passes: i = 1 Entrance and exit of tools: e = 5 mm Length of cutting: 18 15 7 50 32 58 mm Machining time: ∙ 2∙ ∙ 1 ∙ 58 2 ∙ 5 0.15 ∙ 3780 0.12 min E.2 Operation 40 Description: Drilling of through hole 14×70 mm Figure 9.37 Cutting plan for operation 40 Drilling tool: Solid drill: R840-1380-50-A0A, with TiN/TiAlNi multilayer, with quality GC1220 Maximum drill depth: l4 = 70 mm Solid drill with cylindrical shank Inclination angle: r = 70° 187 METAL CUTTING – Theory and Applications Figure 9.38 Cutting tool for operation 40 [3] Cutting parameters: For steel drilling and solid drill, cutting parameters are: Depth of cut: ap = 7 mm Feed: f = 0.2 mm/rev. Cutting speed: vc = 80 m/min The required quality of hole diameter tolerance IT9 is equal to possible quality tolerance IT9 and that is acceptable. Required quality of machining Ra = 1.6 is equal to possible Ra = 1-2 μm and that is in compliance with requirements. Figure 9.39 Cutting parameters for drilling from catalogue SANDVIK [3] Calculation of cutting parameters: Number of revolution: 1000 ∙ ∙ 1000 ∙ 80 14 ∙ 1820 rev/min Feed velocity: 0.2 ∙ 0.2 ∙ 1820 364 mm/min Power and productivity: Power, for specific cutting force kc = 800 N/mm² and machine efficiencies c = 0.9: 188 MANUFACTURABILITY AND MACHINABILITY ∙ ∙ ∙ ∙ 240 ∙ 10 7 ∙ 0.2 ∙ 80 ∙ 800 0.9 ∙ 240 ∙ 10 0.42 kW Axial force: 0.25 ∙ ∙ 0.25 ∙ ∙ ∙ ∙ 0.25 ∙ 800 ∙ 14 ∙ 0.2 ∙ 70° 562 N Productivity: ∙ 0.25 ∙ 7 ∙ 0.2 ∙ 80 28 cm /min Machining time: Number of passes: i = 1 Entrance and exit of tools: e = 5 mm Length of cutting: Lc = 70 mm Machining time: 2∙ ∙ ∙ 1 ∙ 70 2 ∙ 5 0.2 ∙ 1820 0.22 min E.3 Operation 80 Description: Rough milling of slot, in centre of larger cylinder 50×25. After the mill cutter pass, on the sides and bottom of the slot remains material addition of 1 mm for finishing. This operation can be performed with appropriate CNC cycles. Figure 9.40 Cutting plan for slot milling in operation 80 Milling tool: Rough end mill: R216.34-08050-AK19H, material HSS, with quality GC4230 Diameter: D = 8 mm Maximum milling depth: amax = 19 mm Number of teeth: z = 4 189 METAL CUTTING – Theory and Applications Figure 9.41 Cutting tool for operation 80 [3] Cutting parameters: For steel milling with HSS end mill, cutting parameters are: Depth of cut: ap = 4 mm Width of cut: ae = 8 mm Feed per tooth: fz = 0.1 mm/tooth Cutting speed: vc = 230 m/min The first choice in milling is down milling. The shoulder mill cutter location is: 8 8/2 2 8 - that is not desirable, but is accepted in first pass of slot milling. Figure 9.42 Cutting parameters for end milling [3] Calculation of cutting parameters: Number of revolution: 1000 ∙ ∙ 190 1000 ∙ 230 8∙ 9150 rev./min MANUFACTURABILITY AND MACHINABILITY Feed velocity: ∙ 0.1 ∙ 9150 915 mm/min Power and productivity: Power, for specific cutting force kc = 1700 N/mm² and tool machine efficiencies c = 0.9, is: ∙ ∙ ∙ ∙ ∙ ∙ 240 ∙ 10 4 ∙ 8 ∙ 0.1 ∙ 4 ∙ 250 ∙ 1700 0.9 ∙ 60 ∙ 10 0.4 kW Productivity: ∙ ∙ 1000 4 ∙ 8 ∙ 915 1000 29 cm /min Machining time: Number of passes: i = amax / ap = 12 / 4 = 3 Entrance and exit of tools: e = 3 mm Length of cutting: Lc = 50 mm Machining time: ∙ 2∙ 2∙ 3∙ 2∙8 50 915 2∙3 0.25 min Literature: [1] Gresik, W.: Advanced Machining Processes for Metallic Materials - Theory, Modeling and Application, Elsevier B. V., Amsterdam, 2008 [2] Guptaa S. K., Nau D. S.: Systematic approach to analysing the manufacturability of machined parts, Computer-Aided Design, 1995, Vol. 27 , 323-342. [3] Sandvik Coromant: Metal Cutting Technology, Technical Guide, 2010 [4] Radhakrishnan P., Subramanvan S., Raju V.: CAD/CAM/CAPP, New Age International Limitted Publisher, New Delhi, 2008 [5] El Wakil S. D.: Processes and Design for Manufacturing, Waveland Press, Long Grove, 2002 [6] Sredanović B.: Development of model for universal machinability defining based on the cutting process parameters, Master Thesis, Faculty of Mechanical Engineering, Banja Luka, 2012 (in Serbian) [7] Sredanović, B., Globočki - Lakić, G., Cica, Dj., Borojević, S.: A nouvel method for material machinability evaluation, Conference MIT&SLIM 2013, Piran, Slovenija [8] Globočki - Lakić, G., Sredanović, B., Nedić, B., Cica, Dj., Čatić, D.: Development of Mathematical Model of Universal Material Machinability, Journal of the Balkan Tribological Association, 2011, Vol. 17, No. 4, 501 – 511 [9] Pušavec, F., Kramar, D., Krajnik, P., Kopač, J.: Transitioning to sustainable production. Part 2, Evaluation of sustainable machining technologies. Journal of cleaner production, 2010, vol. 18, iss. 12, 1211-1221 [10] Rao R. V., Gandhi O. P.: Diagraph and matrix methods for machinability evaluation of works material, Int. J. of Machine Tools & Manufacture, Vol. 42 (2002), 321-330 [11] Ong S. K., Chew L. C.: Evaluating the machinability of machined parts and their setup plans, International Journal of Production Research, 2000, vol. 38, 2397–2415 191 METAL CUTTING – Theory and Applications [12] Enache, S. et al.: Mathematical model for the establishment of material machinability, Annals of CIRP, 1995, Vol. 44, 79-82. [13] Theile E. W., et al.: Comparative machinability of brasses, steel and aluminum alloy: CDA's universal machinability index, Publication of CDA, New York, 1990 [14] Lakić-Globočki, G., Nedić, B., Golubović-Bugarski, V.: Application of "Block on Disk" tribometer in researching materials workability, Balkantrib 05, 5th International conference on tribology, Kragujevac, Serbia, 2005 [15] Kramar D.: High-pressure cooling assistance in machining of hard-to-machine materials, Doctoral Thesis, Faculty of Mechanical Engineering, Ljubljana, 2009 (in Slovenian) 192 CHAPTER X PROCESS MODELLING USING DESIGN OF EXPERIMENTS Contents 10.1 10.2 10.3 10.4 Introduction Process modelling Methodology for Design of Experiments Laboratory work 10.1 Introduction The goal of this chapter is to present the background and specific analysis techniques needed to construct a statistical model that describes a particular scientific or engineering process. The types of models discussed in this chapter are limited to those based on an explicit mathematical function. These types of models can be used for prediction of process outputs, for calibration, or for process optimization. Experiments are performed today in many manufacturing organizations to increase our understanding and knowledge of various manufacturing processes. Experiments in manufacturing companies are often conducted in a series of trials or tests which produce quantifiable outcomes. For continuous improvement in product/process quality, it is fundamental to understand the process behaviour, the amount of variability and its impact on processes. In an engineering environment, experiments are often conducted to explore, estimate or confirm. Exploration refers to understanding the data from the process. Estimation refers to determining the effects of process variables or factors on the output performance characteristic. Confirmation implies verifying the predicted results obtained from the experiment. In manufacturing processes, it is often of primary interest to explore the relationships between the key input process variables (or factors) and the output performance characteristics (or quality characteristics). For example, in a metal cutting operation, cutting speed, feed rate, type of coolant, depth of cut, etc. can be treated as input variables and surface finish of the finished part can be considered as an output performance characteristic. In engineering, one often-used approach is the best-guess (with engineering judgment) approach. Another strategy of experimentation employed by many engineers today in manufacturing companies is One-Variable-At-a-Time (OVAT) also known as COST (changing one separate factor at a time), where we vary one variable at a time keeping all other variables in the experiment fixed. This approach depends upon guesswork, luck, experience and intuition for its success. Moreover, this type of experimentation requires large resources to obtain a limited amount of information about the process. OVAT experiments often are unreliable, inefficient, time consuming and may yield false optimum condition for the process. These methods of experimentation became outdated in the early 1920s when Ronald A. Fisher discovered much more efficient methods of experimentation based on factorial designs. This class of experimental designs includes the general factorial, two-level factorial, fractional factorial, and response surface designs among 193 METAL CUTTING – Theory and Applications others. These statistically based experimental design methods are now simply called design of experiment methods or DOE methods. Statistical thinking and statistical methods play an important role in planning, conducting, analysing and interpreting data from engineering experiments. When several variables influence a certain characteristic of a product, the best strategy is then to design an experiment so that valid, reliable and sound conclusions can be drawn effectively, efficiently and economically. In a designed experiment, the engineer often makes deliberate changes in the input variables (or factors) and then determines how the output functional performance varies accordingly. It is important to note that not all variables affect the performance in the same manner. Some may have strong influences on the output performance, some may have medium influences and some have no influence at all. Therefore, the objective of a carefully planned designed experiment is to understand which set of variables in a process affects the performance most and then determine the best levels for these variables to obtain satisfactory output functional performance in products. Basically, DOE is a methodology for systematically applying statistics to experimentation. DOE lets experimenters develop a mathematical model that predicts how input variables interact to create output variables or responses in a processor system. DOE can be used for a wide range of experiments for various purposes including nearly all fields of engineering and science. The use of statistics is important in DOE but not absolutely necessary. In general, by using DOE, one can: learn about the process being investigated; screen important factors; determine whether factors interact; build a mathematical model for prediction; and optimize the response(s), if required. Engineers in general carry out a fair amount of physical experimentation in the laboratory and on the computer using a variety of numerical models. Experiments are carried out to (1) evaluate and compare basic design configurations, (2) evaluate material alternatives, (3) select design parameters so that the design will work well under a wide variety of field conditions (robust design), and (4) determine the key design parameters that impact performance [1, 2]. As with most engineering problems, time and budget are often limited. Hence it is necessary to gain as much information as possible and do so as efficiently as possible from an experimental program. The potential applications of DOE in manufacturing processes include [3]: improved process yield and stability improved profits and return on investment improved process capability reduced process variability and hence better product performance consistency reduced manufacturing costs reduced process design and development time heightened morale of engineers with success in chronic-problem solving increased understanding of the relationship between key process inputs and output(s) increased business profitability by reducing scrap rate, defect rate, rework, retest, etc. 194 PROCESS MODELLING USING DESIGN OF EXPERIMENTS For the successful application of an industrial designed experiment, the following skills are generally required [3]: Planning skills; understanding the significance of experimentation for a particular problem, time and budget required for the experiment, how many people are involved with the experimentation, establishing who is doing what, etc. Statistical skills involve the statistical analysis of data obtained from the experiment, assignment of factors and interactions to various columns of the design matrix (or experimental layout), interpretation of results from the experiment for making sound and valid decisions for improvement, etc. Teamwork skills involve understanding the objectives of the experiment and having a shared understanding of the experimental goals to be achieved, better communication among people with different skills and learning from one another, brainstorming of factors for the experiment by team members, etc. Engineering skills; Determination of the number of each factor levels, range at which each factor can be varied, what to measure within the experiment, determination of capability of the measurement system in place, determination of which factors can be and which cannot be controlled for the experiment, etc. DOE methods are useful as a strategy for building process models, and they have the additional advantage that no complicated calculations are needed to analyze the data produced from the designed experiment. It has now been recognized that the factorialbased DOE is the correct and the most efficient method of conducting multi-factored experiments; they allow a large number of factors to be investigated in few experimental runs. The efficiency stems from using settings of the independent factors that are completely uncorrelated with each other. That is, the experimental designs are orthogonal. The consequence of the orthogonal design is that the main effect of each experiment factor, and also the interactions between factors, can be estimated independent of the other effects. As stated earlier, many industries have recognized this fact and a DOE methodology is a key component of the Six-Sigma quality program used by many major corporations. Yet it is surprising that after more than 90 years since the invention of modern experimental design it is still not widely taught in schools of engineering or science in our universities. The wide variety of experimental designs and their statistical details can be found in many excellent texts including Antony (2003) [3], Montgomery (2005) [4], Taguchi et al. (2004) [5], among others. Note that most of the DOE methods presented here are supported by standard software such as Design-Expert®, JMP, and Minitab® software. 10.2 Process modelling The goal of this section is to give the big picture of function-based process modelling. This includes a discussion of what process modelling is, the goals of process modelling, and statistical method used for model building. Detailed information on how to collect data, construct appropriate models, interpret output, and use process models is covered in the following sections. The final section of the chapter contains a case study that illustrates general information presented in the first sections using data from a laboratory work (longitudinal turning process). Process modelling is the concise description of the total variation in one quantity y, by partitioning it into: 1. a deterministic component given by a mathematical function of one or more other quantities, x1, x2, ... , plus 2. a random component that follows a particular probability distribution. 195 METAL CUTTING – Theory and Applications Figure 10.1 General model of a black box process/system [4] In Figure 10.1, a general model of production process as a system with a set of inputs and an output is presented. The inputs x1, x2, …, xn are controllable factors, such as cutting speeds, feed rates, tool geometries, and other process variables. The inputs z1, z2, …, zn are uncontrollable (or difficult to control) inputs, such as properties of raw material provided by different external suppliers or environmental factors. Sometimes these factors are called noise factors. The manufacturing process transforms these inputs into a finished product with several quality characteristics. The output variable y is a measure of process quality also called a process response. A designed experiment is extremely helpful in discovering the key variables influencing the interested process response. It is an approach to systematically vary the controllable input factors and determine the effect these factors have on the process output parameters. Statistically designed experiments are invaluable in reducing the variability in the quality characteristics and in determining the levels of the controllable variables that optimize process performance. There are three main parts of every process model. These are 1. the response variable(s) (outputs), usually denoted by y, 2. the mathematical function, usually denoted as , 3. the random errors, usually denoted by The general form of the model is , 10.1 All process models discussed in this chapter have this general form. The random errors that are included in the model make the relationship between the response variable and the predictor variables a "statistical" one, rather than a perfect deterministic one. This is because the functional relationship between the response and predictors holds only on average, not for each data point. The response variable y is a quantity that varies in a way that we hope to be able to summarize and exploit via the modelling process. Generally it is known that the variation of the response variable is systematically related to the values of one or more other 196 PROCESS MODELLING USING DESIGN OF EXPERIMENTS variables before the modelling process has begun, although testing the existence and nature of this dependence is part of the modelling process itself. The mathematical function consists of two parts. These parts are the predictor variables (factors), x1, x2, …, the regression coefficients parameters, β1, β2, …, and β0 is the average response in a factorial experiment. The term ‘ε’ is the random error component which is approximately normally and independently distributed with mean zero and constant variance σ2. The predictor variables are observed along with the response variable. They are the quantities described as inputs to the mathematical function, , . The regression coefficients and predictor variables are combined in different forms to give the function used to describe the deterministic variation in the response variable. Thus, the first step is to find a suitable approximation for the true relationship between y and the independent variables. Usually, a low-order polynomial is employed. If the response is well modelled by liner function of the independent variables, then the approximating function is the first-order model: y = β0 + β1x1 + β2x2 + … + βkxk + 10.2 If there is curvature in the system, then a polynomial of higher degree must be used, such as the second-order model: ∑ ∑ ∑ ∑ . 10.3 Poor values of the coefficients are those for which the resulting predicted values are considerably different from the observed raw data y. Good values of the coefficients are those for which the resulting predicted values are close to the observed raw data y. The best values of the coefficients are those for which the resulting predicted values are close to the observed raw data y, and the statistical uncertainty connected with each coefficient is small. For a given data set (e.g., 10 (x, y) pairs), the most common procedure for obtaining the coefficients for Eq. 10.1 – 10.3 is the least squares estimation criterion R2 (R-squared). This criterion yields coefficients with predicted values that are closest to the raw data y in the sense that the sum of the squared differences between the raw data and the predicted values is as small as possible. R2 = 1 means perfect fit between predicted and experimental values. If this is a response surface design you want to use for modelling the design space, then the R-squared values should be rather high (perhaps above 0.60, but this is not a "set in stone" rule). If this is a factorial design you are using to simply identify the significant factors, then it really does not matter what the value is. The significant factors are still significant, even if the polynomial is not perfect. There are many statistical tools for model validation, but the primary tool for most process modelling applications is graphical residual analysis. Different types of plots of the residuals from a fitted model provide information on the adequacy of different aspects of the model. Numerical methods for model validation, such as the R2 statistic, are also useful, but usually to a lesser degree than graphical methods. Graphical methods have an advantage over numerical methods for model validation because they readily illustrate a broad range of complex aspects of the relationship between the model and the data. Numerical methods for model validation tend to be narrowly focused on a particular aspect of the relationship between the model and the data and often try to compress that information into a single descriptive number or test result. 197 METAL CUTTING – Theory and Applications Figure 10.2 Graphical residual analysis: Normal probability plot (above) and Residuals vs Run plot (below) 'The normal probability plot' indicates whether the residuals follow a normal distribution, in which case the points will follow a straight line. Expect some moderate scatter even with normal data. Look only for definite patterns like an "S-shaped" curve, which indicates that a transformation of the response model may provide a better analysis. 'Residuals vs Run' is a plot of the residuals versus the experimental run order. It allows you to check for lurking variables that may have influenced the response during the experiment. The plot should show a random scatter. Trends indicate a time-related variable lurking in the background. Blocking and randomization provide insurance against trends ruining the analysis. 198 PROCESS MODELLING USING DESIGN OF EXPERIMENTS Figure 10.3 Graphical process model validation: 'Predicted vs Actual' response values A graph 'Predicted vs Actual' shows relation between the actual response values versus the predicted response values. It helps detect a value, or group of values, that are not easily predicted by the model. The data points should be split evenly by the 45 degree line. If they are not, you may try a transformation (check the Box Cox plot) to improve the fit. An explanation on data transformation is beyond the scope of this book and therefore readers are advised to refer to Montgomery’s book, Design and Analysis of Experiment [4], which covers the use of data transformation and how to perform data transformation in a detailed manner. 10.3 Methodology for Design of Experiments It is widely considered that DOE forms an essential part of the quest for effective improvement in process performance or product quality. This chapter presents a systematic methodology to guide students with limited statistical ability for solving manufacturing process-related problems in real life situations. The methodology of DOE is fundamentally divided into five phases. These phases are: 1. planning phase 2. designing phase 3. conducting phase 4. analysing phase and 5. conformation phase The planning phase consists of the following steps. A) DETERMINING CAUSES FOR PROBLEMS AND THEIR FORMULATION The best way to quickly isolate quality problems is to make everyone an inspector. This means every worker, foreman, supervisor, engineer, manager, and so forth is responsible for making it right the first time and every time. Thus an experimentation team can be formed. The team may include a DOE specialist, process engineer, quality engineer, machine operator and a management representative. One very helpful tool in this effort is the fishbone diagram. As shown in Figure 10.2, the fishbone diagram can be used in 199 METAL CUTTING – Theory and Applications conjunction with the control chart to root out the causes of problems. The problem can have multiple causes, but in general, the cause will lie in the process, operators, materials, or method (i.e., the four main branches on the chart). Every time a quality problem is caused by one of these events, it is noted by the observer, and corrective action is taken. Figure 10.4 Ishikawa diagram for the process of turning Cause-and-effect (C&E) diagrams are also known as fishbone diagrams because of their structure. Initially developed by Kaorw Ishikowa in 1943, this diagram organizes theories about possible causes of a problem. On the main line is a quality characteristic that is to be improved or the quality problem being investigated. Fishbone lines are drawn from the main line. These lines organize the main factors that could have caused the problem. Branching from each of these factors are even more detailed factors. Everyone taking part in making a diagram gains new knowledge of the process. When a diagram serves as a focus for the discussion, everyone knows the topic, and the conversation does not stray. The diagram is often structured around four branches: the machine tools (or processes), the operators (workers), the method, and the material being processed. The three main applications of C&E diagrams are as follows: I. Cause enumeration: Every possible cause and subcause is listed. a. Visual presentations are one of the most widely used graphical techniques for QC. b. A better understanding of the relationships within the process yields a better understanding of the process as a whole. II. Dispersion analysis involves grouping causes under similar headings; the 4 Ms stand for men, machines, materials, and methods (can be further expanded to 6 or even 8 Ms: measurement, management, Mother Nature as environment and maintenance). a. Each major cause is thoroughly analyzed. b. There is the possibility of not identifying the root cause (may not fall into main categories). III. Process analysis is similar to creating a flow diagram. a. Each part of the process is listed in the sequence in which operations are performed. The problem statement should contain a specific and measurable objective that can yield practical value. 200 PROCESS MODELLING USING DESIGN OF EXPERIMENTS Some manufacturing problems that can be addressed using an experimental approach include: Development of new products; improvement of existing processes or products. Improvement of the process/product performance relative to the needs and demands of customers. Reduction of existing process spread, which leads to poor capability. B) SELECTION OF RESPONSE OR QUALITY CHARACTERISTIC The selection of a suitable response for the experiment is critical to the success of any industrial designed experiment. The response can be variable or attribute in nature. Variable responses such as length, thickness, diameter, viscosity, strength, etc. generally provide more information than attribute responses such as good/bad, pass/fail or yes/no. Moreover, variable characteristics or responses require fewer samples (experiments) than attributes require to achieve the same level of statistical significance. Experimenters should define the measurement system prior to performing the experiment in order to understand what to measure, where to measure, who is doing the measurements, etc. so that various components of variation (measurement system variability, operator variability, part variability, etc.) can be evaluated. It is good to make sure that the measurement system is capable, stable, robust and insensitive to environmental changes. Sometimes the method of measurement may require a separate experiment. C) SELECTION OF PROCESS VARIABLES OR DESIGN PARAMETERS Some possible ways to identify potential process variables are the use of engineering knowledge of the process, historical data, cause-and-effect analysis and brainstorming. This is a very important step of the DOE procedure. If important factors are left out of the experiment, then the results of the experiment will not be accurate and useful for any improvement actions. It is good practice to conduct a screening experiment in the first phase of any experimental investigation to identify the most important design parameters or process variables. More information on screening experiments/designs can be obtained in the next Chapter. D) CLASSIFICATION OF PROCESS VARIABLES Having identified the process variables, the next step is to classify them into controllable and uncontrollable variables. Controllable variables are those which can be controlled by a process engineer/production engineer in a production environment. Uncontrollable variables (or noise variables) are those which are difficult to control or expensive to control in actual production environments. Variables such as ambient temperature fluctuations, humidity fluctuations, raw material variations, etc. are examples of noise variables. These variables may have some immense impact on the process variability and therefore must be dealt with for enhanced understanding of our process. The effect of such nuisance variables can be minimized by the effective application of DOE principles such as blocking, randomization and replication described before (see [3-7] for details). E) DETERMINING THE LEVELS AND VALUES OF PROCESS VARIABLES A level is the value that a process variable holds in an experiment. The number of levels depends on the nature of the process variable to be studied for the experiment and whether or not the chosen process variable is qualitative (e.g.: type of catalyst, type of material, etc.) or quantitative (temperature, speed, pressure, etc.). For quantitative process variables, two levels are generally required in the early stages of experimentation. However, for qualitative variables, more than two levels may be required. If a non-linear function is expected by the experimenter, then it is advisable to study variables at three or more levels. 201 METAL CUTTING – Theory and Applications This would assist in quantifying the non-linear (or curvature) effect of the process variable on the response function. In designing phase, one may select the most appropriate design for the experiment. Experiments can be statistically designed using classical approach advocated by Sir Ronald Fisher, orthogonal array approach advocated by Dr. Genichi Taguchi or variables search approach promoted by Dr. Dorian Shainin. Within Fisher’s approach, one can choose full factorial, fractional factorial or screening designs (such as Plackett-Burmann designs). The size of the experiment is dependent on the number of factors and/or interactions to be studied, the number of levels of each factor, budget and resources allocated for carrying out the experiment, etc. During the design stage, it is quite important to consider the confounding structure and resolution of the design. It is good practice to have the design matrix ready for the team prior to executing the experiment. The design matrix generally reveals all the settings of factors at different levels and the order of running a particular experiment. All combination of parameter settings in the experimental design should be possible to conduct. Designing phase and selection of appropriate DOE is discussed in the Chapter 10.3.1. In conducting phase the planned experiment is carried out and the results are evaluated. Several considerations are recognized as being recommended prior to executing an experiment, such as [1]: Selection of suitable location for carrying out the experiment. It is important to ensure that the location should not be affected by any external sources of noise (e.g.: vibration, humidity, etc.). Availability of materials/parts, operators, machines, etc. required for carrying out the experiment. Assessment of the viability of an action in monetary terms by utilising cost-benefit analysis. A simple evaluation must also be carried out in order to verify that the experiment is the only possible solution for the problem at hand and justify that the benefits to be gained from the experiment will exceed the cost of the experiment. The following steps may be useful while performing the experiment in order to ensure that the experiment is performed according to the prepared experimental design matrix [1]: The person responsible for the experiment should be present throughout the experiment. In order to reduce the operator-to-operator variability, it is best to use the same operator for the entire experiment. Monitor the experimental trials. This is to find any discrepancies while running the experiment. It is advisable to stop running the experiment if any discrepancies are found. Record the observed response values on the prepared data sheet or directly into the computer. Having performed the experiment, the next phase is to analyse and interpret the results so that valid and sound conclusions can be derived. In DOE, the following are the possible objectives to be achieved from this phase: Determine the design parameters or process variables that affect the mean process performance. Determine the design parameters or process variables that influence performance variability. Determine the design parameter levels that yield the optimum performance. Determine whether further improvement is possible. The last phase in DOE methodology is conformation phase. Confirmatory experiment should always be run to verify predicted results. If results are not confirmed or are otherwise unsatisfactory, additional experiments may be required. 202 PROCESS MODELLING USING DESIGN OF EXPERIMENTS The statistical confidence interval (at 99 per cent confidence limit) for the mean response can be computed using the equation: 3 √ 10.3 where y is mean response obtained from confirmation trials or runs, s is standard deviation of response obtained from confirmation trials, and n is number of samples (or confirmation runs). As the predicted value based on the regression model falls within the statistical confidence interval, we will consider our model good! If the results from the confirmation trials fall outside the statistical confidence interval, possible causes must be identified. Some of the possible causes may be [3]: incorrect choice of experimental design for the problem at hand improper choice of response(s) for the experiment inadequate control of noise factors, which causes excessive variation some important process or design parameters which have been omitted in the first rounds of experimentation measurement error wrong assumptions regarding interactions errors in conducting the experiment, etc. If the results from the confirmatory trials are within the confidence interval, then improvement action on the process is recommended. The new process or design parameters should be implemented with the involvement of top management. After the solution has been implemented, control charts on the response(s) or key process parameters should be constructed for constantly monitoring, analysing, managing and improving the process performance. 10.3.1 Selecting an appropriate design for the experiment Screening In many process development and manufacturing applications, the number of potential process or design (factors) is large. Screening is used to reduce the number of process or design parameters (or factors) by identifying the key ones that affect product quality or process performance. This reduction allows one to focus process improvement efforts on the few really important factors, or the ‘vital few’. Screening designs provide an effective way to consider a large number of process or design parameters (or factors) in a minimum number of experimental runs or trials (i.e. minimum resources and budget). The purpose of screening designs is to identify and separate out those factors that demand further investigation. Fractional factorial designs, Plackett-Burman (P-B) designs, and 2-level orthogonal arrays by Taguchi can be used for screening many factors to find the significant few. Especially P-B designs should be used if you can assume the absence of two-factor interactions; otherwise a higher resolution fractional factorial design should be chosen. The number of factors allowed is up to one less than the number of runs (for example 11 factors in 12 runs.) Choose the design with the number of factors equal to or just larger than the number you actually have. DOE: Response Surface Methodologies Response surface methodologies (RSM) are primarily relevant when we desire (1) to create a relatively accurate prediction of engineered system input-output relationships and (2) to 203 METAL CUTTING – Theory and Applications “tune” or optimize thoroughly the system being designed. Since these methods require more runs for a given number of factors than screening using fractional factorials, they are generally reserved for cases in which the importance of all factors is assumed, perhaps because of previous screening experimentation. The methods described here are called RSM because they are widely used and the prediction models generated by them can yield 3D surface plots. The methods are mostly based on two types of design of DOE matrices. First, “central composite designs” (CCDs) are matrices corresponding to (at most) five level experimental plans from Box and Wilson (1951). Second, “Box Behnken designs” (BBDs) are matrices corresponding to three level experimental plans from Box, Behnken (1960). The most popular RSM design is the CCD [6]. A CCD has three groups of design points: 1. two-level factorial or fractional factorial design points 2. axial points (sometimes called "star" points) 3. centre points CCD's are designed to estimate the coefficients of a quadratic model. All point descriptions will be in terms of coded values of the factors (Figure 10.5). Figure 10.5 Graphical representation of CCD in terms of coded factor values 1. Factorial Points; The two-level factorial part of the design consists of all possible combinations of the +1 and -1 levels of the factors. For the two factor case there are four design points: (-1, -1) (+1, -1) (-1, +1) (+1, +1). 2. Star or Axial Points; The star points have all of the factors set to 0, the midpoint, except one factor, which has the value +/- Alpha. For a two factor problem, the star points are: (-Alpha, 0) (+Alpha, 0) (0, -Alpha) (0, +Alpha). The value for Alpha is calculated in each design for both rotatability and orthogonality of blocks. The experimenter can choose between these values or enter a different one. The default value is set to the rotatable value. Another position for the star points is at the face of the cube portion on the design. This is commonly referred to as a face-centred CCD. You can create this by setting the alpha value equal to one, or choosing the Face Centred option. This design only requires three levels for each factor. 3. Centre Points; as implied by the name, are points with all levels set to coded level 0 the midpoint of each factor range: (0, 0). Centre points are usually repeated 4-6 times to get a good estimate of experimental error (pure error). For example, with two factors the design will be created with five centre points by default. To summarize, central composite designs require 5 levels of each factor: -Alpha, -1, 0, 1, and +Alpha. One of the commendable attributes of the central composite design is that its structure lends itself to sequential experimentation. Central composite designs can be carried out in blocks. You may also add categorical factors to this design. This will cause the number of runs generated to be multiplied by the number of combinations of the categorical factor levels. Box-Behnken designs are response surface designs, specially made to require only 3 levels, coded as -1, 0, and +1. Box-Behnken designs are available for 3 to 10 factors. They are formed by combining two-level factorial designs with incomplete block designs. This 204 PROCESS MODELLING USING DESIGN OF EXPERIMENTS procedure creates designs with desirable statistical properties but, most importantly, with only a fraction of the experiments required for a three-level factorial. Because there are only three levels, the quadratic model is appropriate. Blocking options are also offered for most of these designs (see [3-7] for details). You may also add categorical factors to this design. This will cause the number of runs generated to be multiplied by the number of combinations of the categorical factor levels. DOE: Orthogonal arrays - Robust Design (Taguchi approach) Taguchi used and promoted statistical techniques for quality from an engineering rather than from a statistical perspective. Although Taguchi has played an important role in popularising DOE, it would be wrong to consider Taguchi Methods as just another way to perform DOE. Since the core of Taguchi’s parameter design is based on experimental methods, he went to great lengths to make DOE more user-friendly. Basically, he simplified the use of DOE by incorporating the following: a standard set of experimental design matrices (Orthogonal arrays), a graphical aid to assign the factors to the experimental matrix (linear graphs), clear guidelines for the interpretation of results, special data transformation to achieve reduced variation (S/N Ratios) and a formal study of uncontrollable factors using the robust design technique, among others [5]. Taguchi’s main contribution to experimental design was a strong emphasis on variation reduction. Therefore, he proposed a novel design, where factors (included in experimentation) are classified into two main groups: Control factors and Noise Factors. The first one includes parameters that can be easily controlled or manipulated, whereas noise factors are difficult or expensive to control. Therefore, the basic idea in parameter design is to identify, through exploiting interactions between control parameters and noise variables, the appropriate setting of control parameters at which the system’s performance is capable of withstanding uncontrollable variation among noise factors. Since the goal is to make the system resistant to variation of noise variables, the approach has also been called “Robust design”. Taguchi designs also known as orthogonal arrays are a type of factorial design. The convention for naming arrays is La(bc) where a is the number of experimental runs, b the number of levels of each factor, and c the number of columns (or number of parameters and interactions) in the array. Design options are available with differing numbers of factors and levels. L12, L18, L36, and L54 arrays are among a group of specially designed arrays that enable the practitioner to focus on main effects. Such an approach helps to increase the efficiency and reproducibility of small scale experimentation. A recent bibliography on Taguchi’s approach to DOE may be found in Taguchi et al.’s (2004) Quality Engineering Handbook [5]. Note that standard screening using fractional factorials, response surface methods, and robust design methods are all based on regression analysis. Yet, regression modelling is relevant whether the response data is collected using a randomized experiment or, alternatively, if it is “on-hand” data from an observational study. In addressing on-hand data, primary challenges relate to preparing the data for analysis and determining which terms should be included in the model form. Regression is a family of curve-fitting methods for (1) predicting average response performance for new combinations of factors and (2) understanding which factor changes cause changes in average outputs. Regression methods are perhaps the most widely used statistics or operations research techniques. Also, even though some people think of regression as merely the “curve fitting method” in Excel, the methods are surprisingly subtle with much potential for misuse (and benefit). For more details on regression analysis refer to literature [3-7]. 205 METAL CUTTING – Theory and Applications 10.3.2 Analytical tools of DOE The following tools can be used for the analysis of experimental results. As the focus of this chapter is to ‘Keep It Statistically Simple’ for the readers, only simple but powerful tools for the analysis and interpretation of results will be introduced. There is a number of DOE books (see Literature of this chapter) that cover more sophisticated statistical methods for the analysis. The authors encourage students to use MINITAB® or DesignExpert® software for the analysis of experimental results. A main effect plot is a plot of the mean response values at each level of a design parameter or process variable. One can use this plot to compare the relative strength of the effects of various factors. The sign and magnitude of a main effect would tell us the following [3]: The sign of a main effect tells us of the direction of the effect, i.e. if the average response value increases or decreases. The magnitude tells us of the strength of the effect. If the effect of a design or process parameter is positive, it implies that the average response is higher at high level than at low level of the parameter setting. In contrast, if the effect is negative, it means that the average response at the low level setting of the parameter is higher than at the high level. Figure 10.6 illustrates the main effect of tool nose radius on the surface roughness Ra in turning. As you can see from Figure 10.6, roughness decreases when the setting of nose radius varies from low to high (i.e. -1 to 1). Figure 10.6 Main effect plot of tool nose radius on surface roughness Ra. An interactions plot (Fig. 10.7) is a powerful graphical tool which plots the mean response of two factors at all possible combinations of their settings. An interaction occurs when the response is different depending on the settings of two factors. Plots make it easy to interpret two factor interactions. They will appear with two non-parallel lines, indicating that the effect of one factor depends on the level of the other. 206 PROCESS MODELLING USING DESIGN OF EXPERIMENTS Figure 10.7 Interaction plot: influence of tool nose radius on surface roughness Ra at different feed rate settings Cube plots are useful for representing the effects of three factors at a time. They show the predicted values from the coded model for the combinations of the –1 and +1 levels of any three factors that you select. Non-selected factors, numerical or categorical, can be set to a specific level. If you select a factor that is not in your model, the predicted values will not change when you move from the –1 to the +1 side of that factor’s axis. Figure 10.8 illustrates an example of a cube plot for a surface roughness optimization study (see chapter 10.4; case study in laboratory work) with three process parameters; tool nose radius, feed rate and cutting speed. The graph indicates that roughness increases with increase in feed rate when using smaller tool nose radius. The worst condition (the highest roughness Ra = 7.69 µm) occurs when a tool with smaller radius is used. Cutting speed has no influence in this case. One can easily determine the best and the worst combinations of factor levels for achieving the desired optimum response. A cube plot is useful for determining the path of steepest ascent or descent for optimization problems. Figure 10.8 Cube plot: influence of tool nose radius r, feed rate f, and cutting speed v on surface roughness Ra 207 METAL CUTTING – Theory and Applications Response 3D surface plots are useful for establishing desirable response values and operating conditions. A surface plot generally displays a three-dimensional view that may provide a clear picture of the response. If the regression model (i.e. first-order model) contains only the main effects and no interaction effect, the fitted response surface will be a plane. Surface plots help experimenters to understand the nature of the relationship between the two factors (nose radius and cutting speed) and the response (roughness). As can be seen in Figure 10.9, the roughness decreases with increase in tool nose radius application; cutting speed has no influence. Moreover, we can use a fitted surface (Figure 10.9) to find a direction of potential improvement for a process. A formal way to seek the direction of improvement in process optimization problems is called the method of steepest ascent or descent (depending on the nature of the problem at hand, i.e. whether one needs to maximize or minimize the response of interest). Figure 10.9 3D surface plot: influence of tool nose radius r and cutting speed v on surface roughness Ra 10.4 Laboratory work Task: Verify the theoretical influence of tool nose radius r and feed rate f on surface roughness Ra, and no or marginal influence of cutting speed vc. Use DOE methodology for empirical model construction. Define the optimal process parameters settings for determined roughness Ra = 1 µm at highest productivity possible. Industrial experiments involve a sequence of activities, i.e. work procedure: 1. Hypothesis – an assumption that motivates the experiment 2. Select an appropriate DOE for defined process parameters and their levels 3. Experiment – a series of tests conducted to investigate the hypothesis 4. Analysis – involves understanding the nature of data and performing statistical analysis of the data collected from the experiment 5. Interpretation – is about understanding the results of the experimental analysis and determination of the optimal input variables setting to achieve output objectives 6. Conclusion – involves whether or not the originally set hypothesis is true or false. 208 PROCESS MODELLING USING DESIGN OF EXPERIMENTS Hypothesis in our case study is related to the cutting theory. We want to confirm that tool nose radius and feed rate influence surface roughness, while cutting speed has only marginal or no influence. Inserts made by Sumitomo, used for the experiments have the following designation: DCMT11T3(02) N-SU, appropriate for steel turning. The number in brackets gives the value for tool nose radius (02 … r = 0.2 mm). Three different nose radiuses were used for experiments, namely 02, 04, and 08. Table 10.1 shows selected parameters for DOE. Cutting parameters levels were determined according to the cutting tools suggested region of operability. The lowest level value (-1) for feed rate and cutting speed is the lowest value of individual parameter common for all three tools, and the highest parameter value (1) is the highest value of recommended region of operability common for all three tools. Namely, all the parameters values in DOE should give appropriate cutting conditions. Three levels are used since according to the theory (see Figure 8.4) second-order model is expected. The middle level value for cutting parameter is the mean value. For tool nose radius r = 0.4 mm is selected, since r = 0.5 mm is not available on the market. Table 10.1 Parameters selected for DOE and their levels (case study) Tool nose radius [mm] 0.2 0.4 0.8 1. level (-1) 2. level (0) 3. level (1) Feed rate [mm/rev.] 0.08 0.14 0.20 Cutting speed [m/min] 210 260 310 Table 10.2 DOE based on CCD together with measured and theoretical values for roughness parameters Ra and Ry (case study) Std. Run 2 8 1 13 7 20 19 18 16 17 6 15 5 3 14 9 4 11 12 10 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 r [mm] 0.8 0.8 0.2 0.4 0.2 0.4 0.4 0.4 0.4 0.4 0.8 0.4 0.2 0.2 0.4 0.2 0.8 0.4 0.4 0.8 f [mm/rev.] 0.08 0.2 0.08 0.14 0.2 0.14 0.14 0.14 0.14 0.14 0.08 0.14 0.08 0.2 0.14 0.14 0.2 0.08 0.2 0.14 vc [m/min] 210 310 210 210 310 260 260 260 260 260 310 260 310 210 310 260 210 260 260 260 Ra,mean. [µm] 0.63 1.52 1.09 1.70 7.88 1.76 1.68 1.68 1.69 1.66 0.41 1.65 0.96 8.03 1.64 3.79 1.32 0.61 3.00 0.68 Ra,theor. [µm] 0.25 1.56 1.00 1.53 6.25 1.53 1.53 1.53 1.53 1.53 0.25 1.53 1.00 6.25 1.53 3.06 1.56 0.50 3.13 0.77 Ry,mean. [µm] 4.25 7.88 6.71 8.61 31.24 8.94 8.30 8.04 8.30 8.32 2.88 7.82 5.45 31.74 7.51 17.19 6.26 3.59 13.10 3.91 Ry,theor. [µm] 1.00 6.25 4.00 6.13 25.00 6.13 6.13 6.13 6.13 6.13 1.00 6.13 4.00 25.00 6.13 12.25 6.25 2.00 12.50 3.06 209 METAL CUTTING – Theory and Applications For DOE face centred CCD (α = 1) was selected, (see [2] for details). Software packages listed above allow user-friendly construction of DOE. Table 10.2 shows in first five columns constructed DOE sorted by ‘Run’ to apply randomization. In the last four columns results of mean surface roughness measurements are inserted for Ra and Ry = Rmax (Ra,mean and Ry,mean), that is each measurement was repeated three times, together with calculated theoretical values (Ra,theor and Ry,theor). See Chapter 8 for roughness measurements details. In Table 10.3, other information according to the experiment is listed. Table 10.3 Machine tool data (case study) Elements Values Machine tool Type Mori Seiki SL-153 Designation SL-153 Power P (kW) 7.5 kW Feed range (mm/rev.) Spindle speed (rev./min) max. 5000 Tool Designation DCMT11T3(02) N-SU Tool wedge angle α = β= γ= Tool cutting edge angle κr = Workpiece Tool-overhang ln (mm) Material designation 100Cr6 soft annealed stage Hardness HRC 23 Tensile strength Rm (N/mm²) 750 Dimension D L (mm) 35 × 300 Once experiments have been conducted and results of surface roughness collected, ANOVA is performed. Each response must be analyzed individually (Ra and Ry). Analyze one response at a time using software by following these steps: 1. If desired, choose a transformation. Otherwise, leave the option at "None." 2. Choose the model. 3. Do analysis of ANOVA, analysis of individual model coefficients and case statistics for analysis of residuals and outlier detection. 4. Inspect various diagnostic plots to statistically validate the model. 5. If the model looks good, generate model graphs for interpretation: For factorial designs, look at the main effect (One Factor) and interaction graphs and the cube plot. For RSM and mixture designs, look at the contour and 3D graphs. 6. After each response is analysed, move on to multiple response optimization, either by inspection of the interpretation plots, or with the graphical and numerical tools provided for this purpose by software packages. A second-order polynomial model (quadratic) was selected as the model for both Ra and Ry. After ANOVA and model diagnosis, the best fit of quadratic model gives ‘Square root’ transformation. 210 PROCESS MODELLING USING DESIGN OF EXPERIMENTS For roughness Ra the following model was constructed: 0,37515 2,94093 17,73182 17,78915 3,7744 Numeric validation of the Ra model gives the following values: 0,9843 51,305 R2 value shows almost perfect fit of the model with the experimental results. The same conclusion gives graphical process model validation: 'Predicted vs Actual' response values in Figure 10.3, which is taken from this case study. "Adeq Precision" measures the signal to noise ratio. It compares the range of the predicted values at the design points to the average prediction error. A ratio greater than 4 is desirable. Resulted ratio of 51.305 indicates an adequate signal. This model can be used to navigate the design space. Model shows that rε, f, interaction ‘rε f’, and rε2 are significant terms or process parameters, that influence the roughness Ra. No influence of cutting speed vc on roughness Ra is found. This can also be seen from Figure 10.6 - 10.11. Figure 10.10 Main effect plot of feed rate on surface roughness Ra. Figure 10.11 3D surface plot: influence of tool nose radius r and feed rate f on roughness Ra 211 METAL CUTTING – Theory and Applications Almost similar results were derived for surface roughness Ry model: 1,49612 6,08408 31,23071 31,82302 7,45631 Numeric validation of the Ry model gives the following values: 0,9792 44,443 The same conclusions as in Ra case can be made for Ry model. From the results of both models we can confirm the hypothesis stated at the beginning of DOE procedure. Figure 10.12 shows graphical interpretation of the Ry model. Figure 10.12 Model graphs for roughness Ry: cube plot (above), 3D surface plot (below) Finally the optimal settings of process parameters should be selected to achieve the objectives, i.e. highest possible productivity with constraint of Ra 1 µm. The optimization can be made by the graphical or numerical way. When using graphical optimization, software package displays the area of feasible response values in the factor space. Regions that do not fit the optimization criteria are shaded. For multiple responses 212 PROCESS MODELLING USING DESIGN OF EXPERIMENTS you may see several overlapping shaded areas. Any "window" that is NOT shaded satisfies the multiple constraints on the responses. The area that satisfies the constraints is yellowcoloured, while the area that does NOT meet your criteria is grey (see Figure 10.13). In our case as shown in Figure 10.13, limits for Ra are 0.9 Ra 1 µm, and this because achieving good roughness (i.e. low roughness) means slowing down the production (i.e. lower productivity).From the optimization graph both process parameters (factors) can be chosen. Since tool nose radius has no influence on productivity, the value is chosen where the highest productivity in sense of feed rate can be achieved. This means that r = 0.8 mm is chosen, and using feed rates around f = 0.16 mm/rev. still gives sufficient Ra and highest productivity. Cutting speed has no influence on Ra so the highest value vc = 310 m/min can be chosen for the highest productivity. Figure 10.13 Graphical representation of process parameter optimization for criterion 0.9 Ra 1µm More accurate results for process parameters optimization can be achieved by numerical way. Criteria are given for all process parameters (input factors) and responses. In our case study, the criteria are: r in range (0.2 r 0.8 mm) f maximize (to achieve productivity goal; check for Ra influence) vc maximize (to achieve productivity goal; no influence on Ra) Ra target 1 Ry minimize Software gives us the same parameters as in the graphical method. Therefore in our case study, for the selected criteria the following process parameters are chosen: r = 0.8 mm f = 0.16 mm/rev. vc =310 m/min With this parameters setting, roughness Ra = 1 µm and Ry = 5.42 µm is predicted. The last step of DOE procedure is to conduct conformation tests. In conformation tests, experiments are performed using chosen parameters setting and measuring Ra and Ry in three different locations. The same experiment is repeated at least 3 times. Results of conformation test are given in Table 10.4. Very good agreement between predicted and actual values is gained. The error is around 3%. 213 METAL CUTTING – Theory and Applications Table 10.3 Results of conformation tests (case study) Measurement1 Measurement2 Measurement3 1 [µm] 0.94 0.99 0.97 2 [µm] 0.96 0.96 0.94 3 [µm] 0.99 0.97 0.97 1 [µm] 2 [µm] 3 [µm] 5.11 5.23 5.08 5.41 5.33 5.12 5.86 5.48 5.62 1,avg [µm] 0.97 2,avg [µm] 0.95 3,avg [µm] 0.98 1,avg [µm] 5.14 2,avg [µm] 5.29 3,avg [µm] 5.65 stdevRa = 0.0181 avg.avg [µm] 0.97 avg,avg [µm] 5.36 From these results statistical confidence interval CI (at 99% confidence limit) for the mean response can be computed using Eq. 10.3: 0.97 3∙ . √ 0.97 0.03 μm. Try DOE methodology with the same parameters and their values using different designs (Box-Behnken or OA) and construct a model for Ra and Ry using the same procedure as explained above. A. Remarks 214 PROCESS MODELLING USING DESIGN OF EXPERIMENTS Literature: [1] Çalşkan, H., Kurbanoğlu, C., Panjan, P., Kramar, D.: Investigation of the performance of carbide cutting tools with hard coatings in hard milling based on the response surface methodology. The international journal of advanced manufacturing technology, 2013, vol. 66, no. 5-8, 883-893 [2] Courbon, C., Kramar, D., Krajnik, P., Pusavec, F., Rech, J., Kopac, J.: Investigation of machining performance in high-pressure jet assisted turning of Inconel 718: An experimental study, International Journal of Machine Tools & Manufacture, 2009, No. 49, 1114–1125 [3] Antony, J., Design of Experiments for Engineers and Scientists. Elsevier, ButterworthHeinemann, 2003 [4] Montgomery, D. C. Design and Analysis of Experiments, Wiley, New York, 2005 [3] Taguchi, G., Chowdhury S., and Wu Y., Taguchi's Quality Engineering Handbook. 1st edition ed., 2004 [5] Funkenbusch, P. D., Practical guide to Designed Experiments. A unified modular approach. 2005: Marcel Dekker. [6] Design-Expert® Software User Manual, 2007 215
