Thermal Influence of Cutting Tool Coatings on Tool Life, During
Orthogonal Turning Processes – Study of Two-Dimensional FEA
Simulation vs. Reference Literature Findings
J.W. Navan
Department of Engineering and Science, Rensselaer Polytechnic Institute
275 Windsor Street, Hartford, CT 06120 USA
Submitted: April 19, 2006
1
Table of Content
Page(s)
Table of Content
Abstract
Introduction
Formulation
Results
Discussion
Conclusion
References
Appendix
(A) Analytical Solution
(B) AdvantEdge™ Simulation Contour Plots
Figure P1 through P9
1
2
3-6
6 - 11
11 - 14
15 - 16
16 - 17
18 - 19
20
2
Abstract
This paper deals with the thermal influence of cutting tool coatings on tool life, as
specifically measured by peak tool temperature. The machining process of interest is the
orthogonal turning of AISI 1045 steel. The study employs the two-dimensional
capabilities of the metal cutting, FEA modeling / simulation software package,
AdvantEdge™ - Version 4.71, produced by Third Wave Systems, Inc.
Simulations of non-coated carbide cutting tool conditions are contrasted with single, two
and three layer cutting tool coatings, all conditions having been exposed to the variables
of two machining speed and two machining length conditions. The balance of the work
piece, tool and process parameters were held constant by choice or by software default.
Completed simulation iterations are individually subjected to the Results Analysis and
Visualization module, which offers FEA meshed contour plots that allow a detailed
examination of the tool / workpiece interface, as well as a visual (color coded) depiction
of peak tool and workpiece temperatures.
Peak cutting tool temperatures for the various simulation iterations are compared and
contrasted with recently published experimental, analytical, and FEA/FDM studies. In
addition, and perhaps more importantly, the peak temperature of individual tool coatings
and their underlying tool substrate are probed for their temperature differential. Although
published studies are not entirely in agreement on the role of coatings in the reduction of
peak tool temperatures, it is agreed that appropriately coated cutting tools operate at
substantially lower peak temperatures than their uncoated counterparts. As a result of the
lower substrate temperatures, the coated cutting tools have substantially longer lives. As
such, good general correlation between the subject modeling software and the referenced
literature is apparent.
3
Introduction
The 18th century gave rise to the “Industrial Revolution”, and the mechanization of
industry. It was during this period that Eli Whitney, arguably, developed and
implemented the principal of interchangeable parts manufacture. The ability to assemble
parts, without hand fitting each one drove the need for better machining processes. Ever
since, new methods, machines, materials, and processes have been sought to increase
machining through-put, maximize cutting tool life, and reduce overall costs. Heat,
whether it was known or not, has been a principal enemy in this regard since the first chip
was produced by a cutting tool.
The mechanical work of a machining operation generates heat through the chips plastic
deformation, and as a result of friction between the cutting tool and the work piece. The
generated heat flows into the chip, cutting tool, and the work piece being cut. In addition,
some heat is also lost through convection to the atmosphere and any cutting coolant /
lubricant used.
It is well known that as cutting tool temperatures reach elevated levels, tool life
diminishes quickly, as specifically related to the softening of the tool material and or
diffusion of constituents critical to the tool material strength. For example, the maximum
working temperature for Titanium Nitride (TiN) is 600 deg. C, beyond which it oxidizes
intensively. If a TiN coated tool experiences temperatures beyond this limit, it rapidly
wears. Therefore, the cutting conditions must be selected in such a way that the predicted
temperature does not exceed this limit. As such, the peak cutting tool temperature is a
principal limiting factor to the cutting tools life and performance.
Therefore, the control and reduction of cutting tool temperature becomes a key objective
for the machining industry and a potential competitive advantage for individual
machinists and / or the companies they labor for. As such, many of the early advances
were obtained on an individual basis with little industry wide cooperation. The initial
focus having been on feeds, speeds and coolants / lubrication, which through tribal
knowledge became widespread general practice, with incremental improvements through
the 20th century.
The greatest advances in machining performance were driven by the need to harness, and
fully utilize, the power of the new numerically controlled machines. The ability to obtain
and analyze process data, including cutting tool operational characteristics, provided the
information necessary to focus resources on the areas that provided the most performance
payback. Cutting tool performance, as limited by temperature, was quickly identified as a
critical focus.
For the purposes of this paper, the focus will be on the Contact Conditions, with a
principal focus on Heat Generation, Heat Flow and Heat Partition. The potential
4
influence of cutting tool / insert coatings, including the listed Contact Conditions, has
been captured in Figure 1.
Possible
Coating
Influence
Contact
Conditions
Wear
Resistance
Friction
Interfacial
Effects
Surface
Integrity and
Structural
Effects
Volume Effects
Cutting Edge
Sharpness
Heat
Generation
Abrasion
Crack Initiation
Roughness of
Working Faces
Heat Flow
Adhesion
Scoring
Residual
Stresses
Heat Partition
TriboOxidation
Plastic
Deformation
N - Phase
Diffusion
Figure 1. The Role of Coatings in the Alteration of Cutting Process performance [1]
As temperature in a machining operation is developed at the cutting tool – chip interface,
and the ability to transfer heat away from this area is critical to controlling heat build up
in the interface, one must focus attention on tool wear, life, and surface integrity. To
further exasperate the need and challenge, economical and ecological pressures of the 21st
century have driven machining processes to ever faster speeds and dry (without coolant)
processes.
Composite materials have often been brought to bear on design problems where
homogeneous materials are not capable of achieving necessary performance expectations.
In recent years, this has been found to be true with cutting tools, and their cutting
performance, specifically related to the control of process temperature and ultimately tool
life.
Coatings that provide thermal conductivity, thermal diffusivity, and heat transfer
coefficient properties that complement the substrate properties, as they specifically relate
to temperature buildup at the cutting tool – chip interface and conduction into the
substrate material, are of particular interest.
5
It is estimated [2] that currently about 53% of all cutting tool materials are Chemical
Vapor Deposition (CVD) and Physical Vapor Deposition (PVD) coated carbides, both in
the form of solid tools or indexable inserts. Currently [3, 4] coatings of different
structures containing layers of titanium carbide (TiC), titanium nitride (TiN), titanium
carbonitride (Ti(C,N), aluminum oxide (Al2O3) and titanium aluminum nitride ((Ti,
Al)N) are mostly used in metal cutting manufacturing.
“Chemical Vapor Deposition, or CVD, is a thin-film coating with a chemical and
metallurgical bond that results from the reaction between various gaseous phases and the
heated surface of a substrate. The final product is a hard, wear-resistant coating with an
extremely strong bond to the substrate. CVD is sometimes referred to as a “hot coating”
because the process approaches temperatures around 1925° F. For this reason, special
post-coating vacuum heat-treating processes have been developed for steel components.”
[5]
“Physical Vapor Deposition, or PVD, is a term used to describe a family of coating
processes. The most common of these PVD coating processes are hollow cathode
reactive ion plating, cathodic arc deposition, and magnetron sputtering. All of these
processes occur in vacuum at roughly 10-2 to 10-4 Torr. All of these deposition methods
involve the generation of positively charged ions. These ions react with gases that are
introduced into the vacuum chamber to create various coating compositions. The parts to
be coated are given a negative bias in order to attract the positively charged ions. The
result is a very strong physical bond between the coating and the tooling substrate.” [5]
A typical cross-sectional photomicrograph of a multi-layer carbide tool coating system is
shown in Figure 2. The chemical or physical deposition methods employed assure
intimate contact between layers, supporting
Figure 2. Photomicrograph of Multi-Layer Tool Coating [6]
6
The thermal performance of coated and non-coated tools, utilized in an orthogonal
turning process, will be analyzed via the metal cutting modeling / simulation software
package, AdvantEdge™ (Version 4.71), produced by Third Wave Systems, Inc., and
compared to reference literature for agreement. The following provides insight into the
characteristics of the AdvantEdge™ code, “…the finite element model used for the
plane-strain orthogonal metal cutting simulation is based on the Lagrangian techniques
and an explicit dynamic, thermo-mechanically coupled modeling software with adaptive
remeshing. This means that the initial mesh becomes distorted after a certain length of cut
and is remeshed in this vicinity to form a rectangular mesh again.” [7] For the purposes
of this study, the simulations will be conducted in 2D FEA simulation mode. The analysis
of the coated tool condition will be further broken down into single and multi-layer tool
coatings. Machining feeds, work piece material, and tool material types will be held
constant, as necessary, for a particular iteration.
Formulation
Simulation Development
Since the intent of the paper is to establish the degree of agreement between results found
in the referenced literature, as compared to that which is obtained through the use of the
simulation, a spreadsheet of reference literature studies and findings was prepared to
provide the necessary focus for the simulations.
The search of available research on this topic identified twelve papers that dealt
specifically with the thermo-mechanical properties of cutting tools during orthogonal
cutting processes. Several of those references dealt exclusively with physical experiments
and / or modeling of tool coatings and their effect on thermo-mechanical performance of
the system. In all, eight specific references were chosen as a body of knowledge to draw
upon to compare and contrast AdvantEdge™ simulation results. As shown in Table 1., a
summary of reference work is provided, including, to the degree available in the
literature, workpiece, tool, coating and process parameters.
Many factors determine the type and rate at which cutting tool wear occurs on the tool
surfaces. The major critical variables that effect wear are tool temperature, hardness and
type of tool material, grade and condition of workpiece material, tool geometry, feed,
cutting fluid, and surface finish on the tool. [8]
A thorough examination of the literature for these critical variables reveals that there
were a number of commonalities between the studies, including the lack of definition of
non-trivial parameters in several cases. As we have previously established peak tool
temperature as the defining characteristic that we will use to determine tool life, the
remaining critical variables need to be defined. For the purposes of this study, and a
meaningful application of the simulation package, fixed and variable attributes were
defined as shown in Table 2. and summarized as follows;
7
Insert Table 1 – Reference Literature
8
Insert Table 2
Attribute & Variable
9






Tool Temperature – The Peak Tool Temperature is the simulation output that we
seek to associate with tool life.
Tool Material and Hardness – P20 Carbide
Tool Geometry – Rake & Relief - Angle/Length were fixed at 5 Deg/2 mm
Tool Surface Finish – Set at default via friction coefficient
Workpiece Material (Grade & Condition) – Although more exotic materials were
of interest (i.e. Titanium, Nickel Alloys, Aluminum Alloys, etc.) the reference
materials focused on the examination of steel, specifically AISI 1018, 1035, &
1045. AISI 1045 was chosen for commonality with the most useful and available
data. Default settings allowed for condition.
Cutting Fluid – Dry machining was simulated in all cases.
One of the more elusive parameters that needed to be understood was that of duration, or
length, of cutting. The obvious concern being, whether or not the simulation reached a
steady-state temperature, and therefore, achieved a peak temperature from which to draw
conclusions on tool life expectancy. Extensive AdvantEdge™ FEA work by Grzesik, [8]
helped guide the decision process in this regard. “It was established based on temperature
traces with tool travel that the time required to reach the steady-state temperature was
0.35 – 0.60 ms depending upon the tool material used.” One can presume that higher
thermal conductivity materials will reach steady-state quicker than lower thermal
conductivity materials. As AISI 1045 is the material of choice, and possessing a
relatively low thermal conductivity, a goal figure of > 0.60 ms was assumed to be
conservative criteria for this simulation.
With an understanding of fixed and variable attributes, and the four tool coating
conditions selected (non-coated, TiC, TiC/TiN, and TiC/Al2O3/TiN) the AdvantEdge™
simulations could be planned and conducted. Table 3. provides an all inclusive matrix of
attributes/results. It is important to note that a review of the AdvantEdge™ user’s manual
and training manual, identified several cautionary issues that needed to be
accommodated.




As identified by the User Manual [9], the use of very thin 2D tool coatings (<
.003 mm total) has the potential of yielding erroneous results. For the purposes of
this simulation, all individual coating layers were set at 0.004 mm.
Simulation options include both a Rapid and a Standard simulation. Although the
Rapid mode is up to five times faster it is reported to be prone to a 20% accuracy
error over the Standard mode. For the purposes of this simulation all simulations
were initially done in Rapid mode for development of a simulation matrix, and
then repeated in Standard mode. The Standard mode results are those that are used
for conclusions.
Instantaneous data spikes in Peak Tool Temperature / Force vs. Time data were
output to Tecplot 10 and necessarily “Force Filtered” to provide useable plots.
Automatic re-sizing of the nose radius will occur unless total thickness is less than
3 microns. As such, the coating layer augments your tool dimensions, and
therefore your effective edge radius defined prior will be altered.
10
Insert Table #3
11
Analytical Solution Development
In the interest of completeness, the methods utilized in the reference literature to obtain
an analytical solution of the heat conduction problem in a coated insert were examined
for suitability to this papers work. The detailed development for the one dimensional and
three dimensional analytical solution is provided in Appendix A. [10]
Results
Three individual cutting speed and cutting length combinations were simulated for each
coating condition. Rapid simulation results were initially generated to establish a
baseline, and followed with the more accurate standard simulation. The resulting peak
tool temperature results were picked from generated contour plot peak tool temperatures.
As previously mentioned, and as shown in Table 4., significant errors in results can be
anticipated when using “Rapid” versus “Standard” simulation mode. The quoted 20%
was shown to be understated, and uncoated conditions were clearly the worst offenders in
this regard. This degree of error in the non-coated condition was initially thought to be
counter-intuitive, but quickly understood as being a direct result of the coating additions
“forced” smaller mesh size (necessary to accommodate the coating layer) versus the noncoated configuration, where mesh sizing is freer. The degree of error ranged from 77 %
for the uncoated condition to 0 % for the three layer coating configuration.
Table 4 - Error % - Standard vs. Rapid
Simulation - Peak Tool Temperature
Simulation Name
Noncoated1
Noncoated1A
Noncoated2
Noncoated3
TiC1
TiC1A
TiC2
TiCTiN1
TiCTiN1A
TiCTiN2
TiCAl2O3TiN1
TiCAl2O3TiN1A
TiCAl2O3TiN2
Rapid
Simulation
1310
1275
730
735
760
730
580
770
790
565
770
790
572
Standard
Simulation
740
744
625
545
703
744
537
720
730
550
720
790
573
Difference
570
531
105
190
57
-14
43
50
60
15
50
0
-1
Error
%
77.03%
71.37%
16.80%
34.86%
8.11%
-1.88%
8.01%
6.94%
8.22%
2.73%
6.94%
0.00%
-0.17%
The supporting meshed peak temperature contour plots, provided via the simulations
Tecplot 10 utility, have been placed in Appendix (B) as Figures P1 through P9. The
plots of the tool / workpiece interface are an excellent reference, as they provide
12
temperature color coding and FEA meshing, which gives a thermo-mechanical image of
the interaction.
A somewhat obvious result of the analysis of cutting speeds influence on peak tool
temperature is shown in Figure 3. Regardless of the coating condition, the peak tool
temperatures for the 200 m/min iterations are at least 100 degrees higher than the 50
m/min iterations.
Figure 3. - Cutting Speed Influence on Peak Tool Temperature
800
700
600
Deg. C
500
Uncoated
TiC
400
TiC/TiN
TiC/Al2O3/TiN
300
200
100
0
50 m/min
200 m/min
Cutting Speed
Using the software’s probe utility, the peak tool temperatures of the tool coating and tool
substrate (in this case carbide) were separately probed in the Tecplot 10 contour plot. The
temperature probing was conducted on the outermost edges of the tool coating and
substrate, along the full length of the line of contact, so as to establish the peak tool
temperature utilized in the results. The resulting probed peak tool coating and substrate
temperatures are shown in Table 5. Equivalent process parameters are like color coded
for convenient viewing. As can be seen in Figure 4, 5 & 6 a significant reduction in
substrate temperature is evident in all coating conditions, with the exception of the
uncoated condition.
13
Table 5
AdvantEdge Simulation - Probed Temperature Values - Color Coded to Indicate Equivalent
Process Parameters
Cutting
Speed
(m/min)
Length
of Cut
(mm)
Standard
Run Time
(ms)
Maximum
Probed
Substrate
Temp
(Deg. C)
Uncoated1
Uncoated1A
Uncoated3
TiC1
TiC1A
TiC2
200
200
50
200
200
50
3
10
3
3
10
3
0.8
2.7
3.2
0.8
2.7
3.2
742.996
760.059
577.43
664.343
688.385
514.923
742.996
760.059
577.43
726.681
736.73
550.132
0
0
0
62.338
48.345
35.209
0
0
0
1
1
1
P1
P1A
P3
P4
P4A
P5
TiCTiN1
TiCTiN1A
TiCTiN2
TiCAl2O3TiN1
TiCAl2O3TiN1A
TiCAl2O3TiN2
200
200
50
200
200
50
3
10
3
3
10
3
0.8
2.7
3.2
0.8
2.7
3.2
649.082
668.31
504.68
625.989
699.094
505.504
728.863
725.27
556.638
724.673
758.452
569.449
79.781
56.96
51.958
98.684
59.358
63.945
2
2
2
3
3
3
P6
P6A
P7
P8
P8A
P9
Simulation
Name
Maximum
Probed
Coating
Temp
(Deg. C)
Delta Probed
Coating
vs.
Substrate
Coating
Layers
Contour
Plot
Figure #
Peak Probed Temperature - Figure 4
50 m/min Cutting Speed & 3 mm Cutting Length
600
580
560
Deg.540
C
Substrate
Coating
520
500
480
460
NonCoated
TiC
TiC/TiN
TiC/Al2O3/TiN
14
Peak Probed Temperature - Figure 5
200 m/min Cutting Speed & 3 mm Cutting Length
760
740
720
700
680
Deg. C
Substrate
660
Coating
640
620
600
580
560
NonCoated
TiC
TiC/TiN
TiC/Al2O3/TiN
Peak Probed Temperature - Figure 6
200 m/min Cutting Speed & 10 mm Cutting Length
780
760
740
720
Deg. C
Substrate
700
Coating
680
660
640
620
NonCoated
TiC
TiC/TiN
TiC/Al2O3/TiN
15
Discussion
As the goal of this paper is to compare and contrast AdvantEdge™ simulation results to
analytical and experimental results and conclusions made in selected literature, it is
prudent to include specific quotes on the Literature / Reference based results and
conclusions, summarized as follows, with the direct parallels drawn to this studies
findings.
Selected Literature / Reference Based Results and Conclusions
(A) – FEM / FDM / Analytical Conclusions




Grzesik [7] concludes, “The finite element simulations performed yield the
evidence of existence and localization of the secondary shear zone. In particular,
it was documented that for coated tool areas with the maximum temperatures are
localized near the chip and workpiece. Also the substrate under the thin coating is
visibly cooler in comparison to uncoated tools.” Author’s Comments: It is
apparent from the colored contour plots and the contact line probing, conducted in
this study, that this is an accurate statement.
Kusiak et al [10] concludes, “The presented application consists in estimating the
heat flux in the tool with different types of coatings during steel turning. The
obtained results show a slight heat flux diminution by Al2O3 coating whereas the
others do not modify it significantly.” .Author’s Comments: It is implied that
Al2O3’s superior insulating characteristics should be evident when one probes the
tool temperature drops across the three coating layers (TiC/Al2O3/TiN). This is in
fact true, as can be seen by probing on each layers interior and exterior edge,
noting that the temperature drop across the Al2O3 layer is up to 50 % greater for
equivalent layer thicknesses.
Rech et al [11] concludes, “Investigations on the influence of the thermal
diffusivity and of the thickness of the coating has shown that coatings do not have
any capacity to insulate a substrate in continuous cutting applications.” Author’s
Comments: As 0.6 ms of cutting time has been previously offered as a reasonable
time to assume steady state conditions in the cutting tool, and an examination of
probed temperatures for cutting times of 0.8 and 3.2 ms reveals 60 and 40 degree,
respectively, temperature drop across a three layer coating, it can be concluded
that insulating characteristics do exist. A check of equivalent depth into an
uncoated tool reveals temperature drops that are 30 to 50 % less.
Grzesik et al [12] concludes, “Analytical solutions performed for the cutting
speed of 200 m/min have placed peak temperatures at approximately 1025, 830,
and 790 deg. C for uncoated, three – and four-layer coated tools, respectively.”
Author’s Comments: The peak tool temperatures observed in this study were not
this magnitude for the uncoated and three layer coating configuration. However,
as previously seen a significant temperature drop occurs between uncoated and
multi-layer coating conditions. Grzesik does not make mention of several
parameters in his study that may have an impact on the differences, the most
important of which may be the use of Rapid vs. Standard simulations.
16
(B) - Experimental Conclusions


Rech et al [13] concludes, “…that coatings mainly influence the amount of heat
generated at the tool – chip interface and the tool – chip contact width, but
coatings do not influence the partition of heat between the tool substrate and the
chip body during turning operations.” Author’s Comments: Although it is
accurate to say that coatings mainly influence the amount of heat generated at the
tool – chip interface, the second conclusion regarding the partition of heat
between the tool substrate and the chip body is not substantiated by this studies
simulations.
Grzesik et al [1] concludes, “The experimental results indicated that coatings with
an intermediate ceramic layer can modify substantially the tool-chip interface
behavior and thus friction and the dissipation of frictional heat. It was observed
in this study that the coating system chooses itself the most convenient properties
to dissipate the frictional heat from the interface.” Author’s Comments: As
previously discussed, on a micro-scale the ceramic Al2O3 layer does have a
greater contribution to heat dissipation than its adjacent layers, but as a three layer
system does not fully exploit this characteristic.
Conclusions





Most important to the intent of this study is that it has been proven in all
simulation cases that cutting tool substrate temperatures are substantially
lower when TiC, TiC/TiN, or TiC/Al2O3/TiN coatings have been applied.
Since lower cutting tool temperatures are universally accepted as being
associated with longer tool life, it can be assumed that these coatings will
result in longer tool life versus uncoated tools.
The TiC/TiN coating systems effectiveness was most conclusive in all
simulations, more so than the TiC/Al2O3/TiN results, giving cause to consider
more extensive focused studies in the future.
Cutting speed has been shown to have a significant influence on peak tool
temperatures. The four coating scenarios (uncoated, TiC, TiC/TiN, and
TiC/Al2O3/TiN), were each evaluated at 50 and 200 m/minute cutting speeds.
A peak tool temperature reduction of at least 100 degrees is realized when
cutting speed is reduced to 50 m/minute from 200 m/min. The reduction of
cutting speed will therefore increase tool life, all other parameters being equal.
The ceramic Al2O3 layer, as utilized in the three coating layers
(TiC/Al2O3/TiN) system, did individually exhibit a temperature drop that was
up to 50 % greater than adjacent TiN or TiC coating layers, for equivalent
layer thicknesses.
Cutting duration simulations of 0.8 through 3.2 ms substantiated claims that
steady state was obtained beyond 0.6 ms. Defining the point below 0.8 ms at
which the simulation is not at steady-state was not a goal of this study.
17


“Rapid” versus “Standard” simulation mode, quoted at a 20% potential error
was shown to be understated, actually ranging from 77 % for the uncoated
condition to 0 % for the three layer coating configuration.
This study has clearly identified a framework for additional simulation work,
including the use of more advanced simulation options. As noted in several
references, identifying an appropriate coefficient of friction between tool and
workpiece is perhaps the single most elusive parameter.
18
References
1. Grzesik,W., and Nieslony, P. (2004). “Prediction of Friction and Heat Flow in
Machining Incorporating Thermo-physical Properties of the Coating-Chip Interface.”
Wear. Vol. 256, pp 108-117.
2. Huston, M.F., and Knobeloch, (1998) “VDI Berichte”. Vol. 1399, pp 21-53
3. Klocke, F., Krieg, T., and Gerschwiler, K. (1998) “CIRP”. Vol. 47, pp 65-68
4. Prengel, H.G., Pfouts, W.R., and Santhanam, A.T. (1998) “Surface Coating
Technology”, Vol.102, pp 183 – 190.
5. http://www.richterprecision.com/CVD_coatings.htm
6. http://global.kyocera.com/prdct/tool/ceratip/repert/cvd.html
7. Grzesik,W. (2006). “Determination of Temperature Distribution in the Cutting Zone
Using Hybrid Analytical-FEM Techniques.” International Journal of Machine Tools
& Manufacture. Vol. 46, pp 651-658.
8. Marks’ “Standard Handbook for Mechanical Engineers” (Ninth Edition) McGrawHill Book Company, pp 13-48 to 13-54
9. Third Wave Systems AdvantEdgeTMUser’s ManualVersion 4.71
http://www.thirdwavesys.com
10. Kusiak, A., Battaglia, J.L., and Rech, J.(2005). “Tool Coatings Influence on the Heat
Transfer in the Tool During Machining.” International Journal of Surface & Coatings
Technology. Vol. 195, pp 29-40.
11. Rech, J., Battaglia, J.L., and Moisan, A. (2005). “Thermal Influence of Cutting Tool
Coatings.” Journal of Materials Processing Technology. Vol. 159, pp 119-124.
12. Grzesik,W., and Nieslony, P. (2004). “Physics Based Modeling of Interface
Temperature in Machining with Multilayer Coated Tools at Moderate Cutting
Speeds.” International Journal of Machine Tools & Manufacture. Vol. 44, pp 889901.
13. Rech, J., Kusiak, A., and Battaglia, J.L. (2003). “Tribological and Thermal Functions
of Cutting Tool Coatings.” International Journal of Surface & Coatings Technology.
Vol. 186, pp 364-371.
14. Grzesik,W., Bartoszuk, M., and Nieslony, P. (2005). “Finite Difference MethodBased Simulation Of Temperature Fields For Application To Orthogonal Cutting
With Coated Tools.” International Journal of Machining Science and Technology,
9:529-546
15. Jen, Tien-Chien, and Anagonye, A., (2001). “An Approved Transient Model of Tool
Temperatures in Metal Cutting.” Transactions of the ASME, Vol. 123, pp 30-37.
16. Lazoglu, I., and Altinas, Y., (2002). “Prediction of Tool and Chip Temperature in
Continuous and Interrupted Machining.” International Journal of Machine Tools &
Manufacture. Vol. 42, pp 1011-1022.
17. Anagonye, A., and Stephenson, D., (2002). “Modeling Cutting Temperatures for
Turning Inserts with Various Tool Geometries and Materials.” Transactions of the
ASME, Vol. 124, pp 544-552.
18. Grzesik,W., and Nieslony, P. (2003). “A Computational Approach to Evaluate
Temperature and Heat Partition in Machining with Multilayer Coated Tools.”
International Journal of Machine Tools & Manufacture. Vol. 43, pp 1311-1317.
19
19. M. Necati Ozisik. (1993). "HEAT CONDUCTION", 2nd ed., John Wiley & Sons, Inc,
New York,
ISBN 0-471-53256-8.
20. Bejan, A., and Kraus, A. D. (2003). “Heat Transfer Handbook.” John Wiley & Sons,
Inc, New York, ISBN 1-59124-513-3.
21. “Introductory Short Course on Modeling Metal Cutting” (2001). Third Wave Systems,
Inc, 7900 West 78th Street, Minneapolis, Minnesota.
22. http://www.guhring.com/downloads/CoatingS.pdf
20
Appendix
(A) Analytical Solution
(B) AdvantEdge™ Simulation Contour Plots
Figure P1 through P9