Statistical Process Control (SPC) in a High Volume Machining Center: Value
of Standard Operating Procedures
by
Siddharth Udayshankar
Bachelor of Engineering in Industrial Engineering and Management
BMS College of Engineering, 2014
Submitted to the Department of Mechanical Engineering
in partial fulfillment of the requirements for the degree of
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A uthor......................................................................
Signature redacted
Siddharth Udayshankar
Department of Mechanical Engineering
August 7, 2015
Signature redacted
.
Certifiedby..........................................................
David E. Hardt
Ralph E. and Eloise F. Cross Professor of Mechanical Engineering
Thesis Supervisor
Signature redacted
C ertified by .............................................................
. . .. .. .. .. .. .. .. .. . .. .. .. .\A
-
Duane S. oning
Professor of Electrical Engineering and Computer Science
Thesis Supervisor
Accepted by.......................................................S
ignature redacted
David E. Hardt
Ralph E. and Eloise F. Cross Professor of Mechanical Engineering
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2
Statistical Process Control (SPC) in a High Volume Machining Center: Value
of Standard Operating Procedures
by
Siddharth Udayshankar
Bachelor of Engineering in Industrial Engineering and Management
BMS College of Engineering, 2014
Submitted to the Department of Mechanical Engineering on August
fulfillment of the requirements for the degree of
Master of Engineering in Manufacturing
7 th,
2015 in partial
Abstract
Statistical process control is implemented in a high volume machining center to reduce scrap
and improve the quality of production. New hires are working in a complex production
environment with excellent metrology resources that can be used for real time inspection but there
is a lack of standard operating procedures to help them use these resources. A methodology for
implementation of statistical process control is developed and evaluated by implementing it in a
section of the machining center which has the biggest benefit. Gages are evaluated and control
charts are established in that section. Operators are trained in the standard operating procedures
related to the different components of SPC. The standard operating procedures are developed to
be portable such that SPC can be used in various sections of the machining center. Findings include
cost saving benefits and scrap rate reduction of approximately 50% can be achieved for the entire
machining center by the implementation of statistical process control. A training matrix is
developed to train different people of the company on the concepts of SPC. Implementing SPC in
a high volume machining center has proved to deliver value in reduction of scrap, quality
improvement, ability to react to changes for the new hires and other benefits. Standard operating
procedures have made a difference in the quality inspection of parts and in maintaining high quality
standards that can make the machining center a world class manufacturer.
Thesis Supervisor: David E. Hardt
Title: Ralph E. and Eloise F. Cross Professor of Mechanical Engineering
Thesis Supervisor: Duane S. Boning
Title: Professor of Electrical Engineering and Computer Science
3
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4
Acknowledgements
Firstly, I would like to thank the Almighty for his boundless blessings and grace in helping
me in every aspect of life. Secondly, I would like to thank my parents for their relentless support
through my highs and lows and for always being there when it mattered the most. I would also like
to thank Lalita atthai and Ramki uncle for proofreading my thesis and giving me tips to write a
good thesis.
Thank you to my thesis supervisors Prof. David E. Hardt and Prof. Duane S. Boning for
guiding the whole team and clearing our queries throughout the whole length of the project.
Thank you to Waters Corporation for allowing me to carry out this project and for their
support in making me feel very comfortable to work throughout the whole term. A special thanks
to Dave Terricciano and Jim McPherson in continuing the collaboration between MIT and Waters
Corporation.
Thank you to Gabriel Kelly, Greg Puszko, Leo Bates, Mike Selent and Kerwin Cross for
supporting the whole team and in making sure the success of this project. Thank you for the
contribution and involvement of several Waters Corporation employees including Dan Welch,
Matt Howland, Paul Lussier, Paul Pavone, Dereck Lawes, Steve Trautwein, Dennis White and
others without whom this whole project would not have been possible.
Thank you to my teammates Shaozheng Zhang and Haipei Zhu for their collaboration, ideas
and friendship that helped us to produce results that we could be proud of.
Thank you to Jose Pacheco for welcoming me to the Master of Engineering in Manufacturing
program and his support throughout the last 12 months.
Last but not the least, thank you to the other MEngM students and my friends who have
influenced and given me memorable moments over the last 12 months.
5
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6
Table of Contents
A bstract ...........................................................................................................................................
3
A cknow ledgem ents.........................................................................................................................
5
List of Figures and Tables...............................................................................................................
9
Chapter 1: Introduction .................................................................................................................
11
1.1
Background Inform ation on W aters Corporation........................................................
12
1.2
Liquid Chrom atography and M ass Spectrom etry .......................................................
13
1.2.1
H igh-Perform ance Liquid Chrom atography (H PLC)...........................................
13
1.2.2
U ltra Perform ance Liquid Chrom atography (U PLC) ...........................................
14
1.2.3
M ass Spectrom etry...............................................................................................
15
1.3
W aters G lobal M achining Center...............................................................................
15
1.3.1
Colum ns A rea .........................................................................................................
17
1.3.2
Colum n Tubes M anufacturing Process................................................................
18
1.3.3
Tools U sed to M anufacture Colum n Tubes .........................................................
19
1.3.4
Com m on Defects During Production..................................................................
20
Problem Statem ent .........................................................................................................
21
1.4.1
M otivation...............................................................................................................
21
1.4.2
Identification of Problem .....................................................................................
22
1.4.3
Team A pproach and Task Organization .................................................................
23
1.4
1.5
O utline of Thesis ............................................................................................................
25
Chapter 2: Literature Review ........................................................................................................
26
2.1 Statistical Process Control (SPC)...................................................................................
26
2.1.1
Origin of SPC ............................................................................................................
26
2.1.2 Seven Q uality Control Tools ...................................................................................
27
2.1.3
Control Charts............................................................................................................
28
2.1.4
Value of SPC .............................................................................................................
32
2.2 M achining ............................................................................................................................
34
2.2.1 Tool W ear ...................................................................................................................
34
2.2.2
Part Deflection W hile M achining ...........................................................................
36
2.3 Standard Operating Procedures (SOPs) ..........................................................................
37
Chapter 3: M anufacturing Scenario in the Colum ns Cell..........................................................
39
7
3.1 Lack of Proper Gage Fixture for The OasisM System ....................................................
49
3.2 Lack of Standard Operating Procedures (SOPs)..............................................................
51
3.3 Lack of Statistical Process Control (SPC) ......................................................................
52
Chapter 4: Standard Operating Procedures (SOPs) ..................................................................
54
4.1 Methodology for Implementation of SPC......................................................................
54
4.2 Gage Repeatability and Reproducibility (Gage R&R) study ...........................................
57
4.2.1
Purpose of an SOP for Gage R&R study................................................................
57
4.2.2
Implementation of an SOP to Conduct Gage R&R Study.......................................
59
4.2.3
Results from Implementation of SOP.....................................................................
59
4.3 Baseline Data Collection and Sampling Plan..................................................................
61
4 .4 C ontro l C harts .....................................................................................................................
63
4.4.1
Importance of Control Charts .................................................................................
63
4.4.2
SOP and Results from Implementation of Control Charts ....................
66
4 .5 Process C apability ...............................................................................................................
68
4.6 Long Term Monitoring........................................................................................................
71
4.6.1
Importance and SOP for Long Term Monitoring...................................................
71
Chapter 5: Value Added Due to Standard Operating Procedures.............................................
74
5.1 R ole of O wnership ..............................................................................................................
74
5.2 Importance of Training Matrix........................................................................................
74
5.3 Standard Procedure to Edit SOPs....................................................................................
76
5.4 Scenario After Implementation of SOPs.........................................................................
76
5.5 Feedback from Operators and Supervisors ......................................................................
77
Chapter 6: Conclusion, Future Work and Recommendations ...................................................
78
6 .1 G age E valuation ..................................................................................................................
78
6.2 Real Time Inspection ..........................................................................................................
78
6.3 Defect Rate Reduction due to Application of Control Charts.........................................
79
6.4 Potential Annual Savings ................................................................................................
80
6.5 Future W ork and Recommendations...............................................................................
81
References.....................................................................................................................................
84
A p p en d ix .......................................................................................................................................
86
8
List of Figures and Tables
Figure 1-I W aters Corporation, M ilford, M A . .............................................................................
I1
Figure 1-2 Diversification of Waters Corporation in various fields..........................................
12
Figure 1-3 Pictorial flowchart that describes the procedure in liquid chromatography [2]..... 14
Figure 1-4 Representation of the working of a mass spectrometer [5]......................................
15
Figure 1-5 Waters Global Machining Center, Milford, MA.....................................................
16
Figure 1-6 Representation of the Machining Center. I=Milling Department, 2= Turning
Department, 3= Valve Cell, 4= Column Cell, 5=Model Shop [9]............................................
16
Figure 1-7 Column with two symmetrical ends.........................................................................
17
Figure 1-8 Schematic representation of the important components of a column......................
18
Figure 1-9 From left: single point turning tool, threading tool, cut off tool.............................
19
Figure 1-10 Production defects frequency distribution [8].......................................................
21
Figure 1-11 Project process flow . .............................................................................................
24
Figure 2-1 Different components of a control chart [8]............................................................
29
Table 1: Rules followed by different industries [8]..................................................................
31
Figure 2-2 Benefits and value gained from SPC. .....................................................................
32
Figure 2-3 Scrap reduction from 1985 to 1989 [17]..................................................................
33
Figure 2-4 Different types of tool wear [19].............................................................................
35
Figure 2-5 Occurrence of corner wear in a tool [19]. ..............................................................
36
Figure 3-1 Quick inspection gages like the micrometers and GO/NOGO placed next to the CNC
39
m ach in e .........................................................................................................................................
Figure 3-2 Schematic representation of the CNC machine used in the columns cell [7]......... 40
Figure 3-3 Representation of the different size of columns that are produced in the columns cell
41
and en d fittin g s..............................................................................................................................
Figure 3-4 Optical comparator in the columns cell. ................................................................
43
Figure 3-5 Components of the Oasis inspection system [8]. ....................................................
44
Figure 3-6 Measuring a column on a Johnson GageTM...............................................................
45
Figure 3-7 Profilometer in the columns cell. ...........................................................................
46
Figure 3-8 B lade m icrom eter........................................................................................................
47
Figure 3-9 Flat m icrom eter. ..........................................................................................................
47
Figure 3-10 M icroscope in the colum ns cell.............................................................................
48
Table 2: Measurement devices used to measure the different dimensions on a column tube [7]. 48
9
Figure 3-11 Comparison to show that the existing fixture is not suitable for inspection.......... 49
Figure 3-12 New fixture for the OasisTM system .......................................................................
50
Figure 4-1 Methodology for implementation of SPC ...............................................................
56
Figure 4-2 Screenshot of the SOP developed for a Gage R&R study. .....................................
58
Figure 4-3 The different dimensions that has to be measured on one end of a column tube. ...... 60
Table 3: Comparison of gage capabilities, P/T ratio (%), before and after implementation of SOP
[7 ]..................................................................................................................................................
60
Figure 4-4 Screenshot of the SOP developed for baseline data collection. ...............................
62
Figure 4-5 Screenshot of the control chart being used in ProlinkTM as a real time inspection tool.
.......................................................................................................................................................
64
Figure 4-6 Notes can be recorded in the ProlinkTM software.....................................................
65
Table 4: Meaning of the lines in ProlinkTM software................................................................
66
Figure 4-7 Screenshot of the SOP developed for control charts...............................................
67
Figure 4-8: Control charts showing the process to be stable after implementation of the SOP... 68
Figure 4-9 Screenshot of the SOP developed to calculate process capability...........................
69
Figure 4-10 Screenshot of the Prolink TM software displaying Cpk value..................................
70
Table 5: Values of the Cpk for the different dimensions after using the SOP...........................
70
Figure 4-1 1 Screenshot of the SOP developed for long term monitoring. ................................
72
Figure 4-12 Screenshot of the difference between a process in control (above) and out of control
(b e lo w )..........................................................................................................................................
73
Figure 4-13 Results obtained from long term monitoring. ........................................................
73
Figure 5-1 Training matrix developed for learning SPC. ..........................................................
75
Figure 6-1 Recommended database structure............................................................................
82
10
Chapter 1: Introduction
This thesis concentrates on the value of following standard operating procedures on the road
to achieving statistical process control. This thesis is based on an industrial project at Waters
Corporation which designs, manufactures and services analytical laboratory instruments that are
primarily used by pharmaceuticals, industries, academic personnel and other laboratory
applications. Their primary focus is liquid chromatography, mass spectrometry technology
systems and thermal analysis which includes consumable products such as columns and other
support products. Its headquarters is at Milford, Massachusetts as shown in Figure 1-1. Currently,
there is a need to implement statistical process control (SPC) in the machining center that produces
high volumes of columns and end fittings. This chapter concentrates on providing background
information on Waters Corporation, Waters Global Machining Center at Milford, MA and the
problem statement that this thesis seeks to address.
Figure 1-1 Waters Corporation, Milford, MA.
11
1.1 Background Information on Waters Corporation
Waters Corporation was founded by James Logan Waters in 1958. Waters Corporation
designs and manufactures analytical laboratory instruments that are used in pharmaceutical,
industrial and other academic laboratories. The company has advanced in the field of analytical
chemistry by producing breakthrough research and state of the art technological systems, and has
become a major player in the market. Their revenue for the year 2013 was $1.9 billion. They have
offices in 27 countries which also include 11 manufacturing facilities [6]. On the road to becoming
a major player in the analytical instruments industry, Waters has acquired a number of companies
and thus expanded their business to even greater extents as shown in Figure 1-2.
InsrumntaionInformation and
Services
Consumables
Diagnostics
Figure 1-2 Diversification of Waters Corporation in various fields.
Waters has divided their products into two divisions: the Biochemical and Chemical
Analysis Division, and the Physical Testing Division. The Biochemical and Chemical Analysis
Division is based in Milford, MA and produces liquid chromatography instruments, while the
Physical Testing Division is based in Manchester, England and Wexford, Ireland and produces
mass spectrometry instruments. Thermal analysis and calorimetric instruments are also produced
by their physical testing division. With customer success being the prime mission for Waters
12
Corporation, they have a global network of authorized service centers that can install, repair and
replace part services, thereby creating a strong bond between customers and the company.
This thesis describes the implementation of statistical process control in the columns area at
Waters Global Machining Center, Milford, MA. This thesis is written in conjunction with the work
done by Shaozheng Zhang [7] and Haipei Zhu [8], and several sections and descriptions in this
thesis are written in common with their works.
1.2 Liquid Chromatography and Mass Spectrometry
One of the important tools in analytical chemistry is liquid chromatography. It was defined
by the Russian botanist, Mikhail S. Tswett in the early 1900s. His studies focused on separating
plant compounds by using a solvent and a column packed with materials [1]. This created a
pathway for many scientists to use this technique to separate out the individual parts from the
sample. The technique is based on the phenomenon that different compounds have different
strengths of chemical attraction to particles. When the compound is made to flow using a solvent
(mobile phase) in a column filled with particles (stationary phase), the individual parts are
separated based on the chemical attraction to the particles in the column which creates different
color bands. Based on these color bands, the individual parts of the compound can be identified.
1.2.1
High-Performance Liquid Chromatography (HPLC)
High-performance liquid chromatography (HPLC) has advanced much since the 1970s.
During the 1970s, when a pressure of 500 psi was used to pump the compounds through the
column, it was called high-pressure liquid chromatography. Nowadays, the columns can withstand
a pressure of 6000 psi, helping enable one to separate and identify any compound that can be
13
.
............
dissolved in a solvent, thus making HPLC a key and powerful tool in analytical chemistry [1]. The
procedure of liquid chromatography is illustrated in Figure 1-3.
HP LC Column
Chromatogrmn
Inject
Solvent (Mobile Phase) Reservor
-I
sampl e
POWp
Solvent Manager
Solvent DelivRy System
Waste
Figure 1-3 Pictorial flowchart that describes the procedure in liquid chromatography [2].
1.2.2
Ultra Performance Liquid Chromatography (UPLC)
With the increasing need to have better resolution and sensitivity in liquid chromatography,
Waters Corporation has developed a new system that has particles of 1.7 micron and a pressure
capability of 15,000 psi [1]. This has created a new benchmark in the analytical chemistry business.
Ultra Performance Liquid Chromatography (UPLC) is a trademark of Waters Corporation [3].
Further research is being done to pack columns with particles of one micron diameter and a
pressure capability of 100,000 psi. This gives an idea of what can be expected in the years to
come [1].
14
..............
.
............
...
.....
......
1.2.3
Mass Spectrometry
By using the mass-to-charge ratio, mass spectrometry helps to identify the chemicals present
in a compound. Mass spectrometers vary in size and serve various applications. The unit that is
used to measure atomic or molecular mass in mass spectrometry is the Dalton (Da). Figure 1-4
shows how molecules are converted to gas-phase ions and then imparted electric charge so that
the data system can read the electric current and hence determine the mass spectrum [4].
Detector
heater to vapourise sample
electron beam
sample
Of
ionises
charged particle beam
+
02
inject
sample
heaviest
magnetic field separates particles
based on mass/charge ratio
electron
source
(4)
particles accelerated into
magnetic field
Figure 1-4 Representation of the working of a mass spectrometer [5].
1.3 Waters Global Machining Center
The Waters Global Machining Center based in Milford, MA is the largest machining center
of Waters Corporation and also the largest supplier of machined and fabricated components to
Waters Corporation. The Waters Global Machining Center manufacture high-complexity
components and send to their various facilities and their contract manufacturers worldwide.
15
Figure 1-5 Waters Global Machining Center, Milford, MA.
The Machining Center as shown in Figure 1-5 is about 50,000 sq.ft. in area and operates 6
days per week, 24 hours per day and 52 weeks per year. They produce about 2.7 million parts
annually and have 5 main departments as shown in Figure 1-6 [9].
['
1 11--[1
-I
I
j -
I
Figure 1-6 Representation of the Machining Center. 1=Milling Department, 2= Turning Department, 3=
Valve Cell, 4= Column Cell, 5=Model Shop [9].
16
1.3.1
Columns Area
The columns area is one of the most important locations in Waters Global Machining Center.
The columns cell produces column tubes and end fittings which form a major portion of the
company's revenue. They produce 96 different types of column tubes which vary in outer
diameter, inner diameter, length of the column, type of thread and other intricate features that
satisfy the customer's needs.
Column tubes as shown in Figure 1-7, are the most important part of the liquid
chromatography machines. The column tubes are packed with chemicals and closed with the end
fittings. These are then placed in the Waters liquid chromatography machine for the users to test
their samples. The life of a column tube varies according to the application that it is being used
for. As these are consumables that the customer orders on a regular basis, Waters Corporation
ensures that high priority is given to the columns cell in terms of quality and manpower.
Main. Side
Figure 1-7 Column with two symmetrical ends.
Figure 1-8 shows key features of a column tube. The threads are one of the most important
features of the column tube in terms of the customer's perspective. As these column tubes are sold
at a high price (approximately $750-$1500), the company ensures that the customer finds it easy
to screw the column tube (packed with chemicals and closed by the end fittings) in the machine.
17
The machining center has achieved a positive reputation in making excellent threads on a
consistent basis after different trial and error methods.
Mechanical
Threads
Sealing face
Strength
Inside
diameter
size
Outside visible
finish
Flats
Inside diameter
finish
Figure 1-8 Schematic representation of the important components of a column.
The finish on the sealing face is another critical feature that the company has mastered over
years of experience in trying to make the column as safe as possible for the customer. If the sealing
face is not manufactured properly, this would lead to leaks that could be lethal. As mentioned in
the previous section, the company values customer satisfaction with utmost priority, so they take
every possible step to ensure that they maintain their mission. This project of implementation of
statistical process control in the machining center is an initiative towards that goal.
1.3.2
Column Tubes Manufacturing Process
The column tubes are produced by expensive Swiss CNC machines (approximately
$235,000 to $550,000) that can machine both sides of the column at the same time. This helps the
machining center to save time and also to keep up with the demand. Generally, the 1/4, 3/8, 1/2
and 1 inch outer diameters are the four most produced columns in the columns cell. The raw
materials to manufacture these columns are outsourced; these long rods have a unique lot number
18
that is used to identify the column tubes once they are produced. These column tubes are made of
high purity 316L stainless steel which requires extreme precision machining to ensure that it is not
wasted and put to full use. The company uses an SAP database system to track customer orders
and schedule production, and that also helps to debug when scrap is produced.
The CNC machine has two parts; one is known as the main side that has a movable tool post
and the other is known as the sub side that has a stationary tool post. The production of column
tubes involves six major manufacturing steps: turning the outer surface profile, drilling the inner
diameter, threading, end milling the flats, engraving the lot number, and cutting off the tube. These
are the six manufacturing steps that are used in most column tubes. There may be additional
manufacturing steps for particular column tubes according to customer requirements.
1.3.3
Tools Used to Manufacture Column Tubes
The CNC machine that is used in the columns cell to manufacture these columns is capable
of holding 21 tools at any given time, including both the main side and the sub side. The tools used
to manufacture the column tubes are single point turning carbide insert, engraver, end mill, cut off
insert, threading insert and spot drill.
Figure 1-9 From left: single point turning tool, threading tool, cut off tool.
19
The tools that are replaced often between shifts are the threading and turning inserts. The
other tools last longer and have better tool life. Some of the tools are shown in Figure 1-9. The
tool crib buys these tools in bulk from various suppliers and these tools are given a unique Waters
identification number that can be used in the SAP system. When the operator needs a new tool,
the operator pays a visit to the tool crib to get the new tool.
1.3.4
Common Defects During Production
The shop floor has a characteristic sheet that records the defects when a column tube is
scrapped. These help the supervisor to understand the state of the production system and give
advice to the operators to ensure that it does not happen again. As part of our research, the
characteristic sheets as shown in Figure 1-10 were studied and analyzed, and it was found that tool
change contributes to 25% of the total defects. The other major reasons are due to bad threads,
setup problems, tool wear and surface finish.
By implementing an SPC system, the team aims to reduce scrap rate significantly and also
eliminate the assignable variations that occur in the system.
20
Frequency Distribution
25.00%
-
30.00%
20.00%
15.00%
-
-
10.00%
-
5.00%
0.00%
-s-
-------
Figure 1-10 Production defects frequency distribution [8].
1.4 Problem Statement
This section presents the motivation behind the company's objective of implementing
statistical process control in their machining center, identification of problem and the team's
approach to solving the problem of scrap and quality loss in the machining center.
1.4.1
Motivation
Waters Global Machining Center has had a significant growth rate of staff in excess of 10%
year over year since 201 0.With the expanding customer base and other product lines, there is a
need to hire more workforce to meet the demand. Over the last 18 months, new hires have been
recruited and they form 25% of the workforce, with the number growing to 40% over the last three
years.
21
The columns cell is one of the most profitable and most produced product of Waters
Corporation. In 2014, the total Waters Division product sales amounted to $1.1 billion and the
Waters' instrument sales increased by 4% from 2013 [3].This revenue is critical to Waters
Corporation, motivating the company to maintain and continuously improve their manufacturing
capability.
The operators on the shop floor work in a complex environment, and it becomes difficult for
new hires to maintain the high standards that are established on the shop floor. Though there is a
complex production environment, the machining center has excellent metrology resources to
ensure that high quality standards are maintained by the company. Thus there is an opportunity to
improve the overall production quality and reduce scrap by incorporating real-time inspection
protocols and standard operating procedures with the help of statistical process control.
1.4.2
Identification of Problem
As the Waters Global Machining Center is expanding their workforce to meet the demands
of the market, they are experiencing a significant issue with the operators' ability to clearly
understand real-time inspection protocols and apply them to their everyday activities. Though it is
understandable that they are new to the machining center, it has to be kept in mind that new hires
are working in a high production volume, complex environment. As a result of growth in
production and increase in new hires, a concern is an observed drop in yield and quality of the
products produced. Scrap costs have increased significantly and productivity losses have grown.
There is a lack of documentation on how to use the existing resources effectively to improve
quality and yield performance. Given that Waters Global Machining Center is expanding at a rapid
rate, there is both need and opportunity to improve the quality methodology used in the center. As
22
columns are the most produced and profitable products for Waters Corporation, the initial priority
is to demonstrate improved quality and reduced scrap in this area by using statistical process
control.
1.4.3
Team Approach and Task Organization
When the problem was presented to the team, it was evident that firstly, there needs to be
a methodology set up to solve the quality and scrap issue, and secondly, the methodology needs to
be portable. The portability of the methodology is critical, as the company wants to implement
statistical process control not only in the columns cell but also at the other manufacturing cells.
The team has thus developed a methodology that is evaluated by implementing it in the
columns cell. Phase 1 of the project involves carrying out a gage repeatability and reproducibility
(Gage R&R) study to evaluate the measuring systems that are in the columns cell. The next step
is to collect baseline data. After collection of baseline data, the team analyzed the data and found
trends that help in creating sampling plans and also eliminating the variations. Phase 2 of the
project involves developing sampling plans that make the life of the operator easier and also the
inspection process faster. Assignable causes are eliminated by developing standard operating
procedures that the operators are asked to follow. The final phase of the project is to develop
control charts that help the operator to stabilize the process and have it in a state of statistical
control. The standard three sigma rules are incorporated to create the control charts. Also, reaction
plans are incorporated in the standard operating procedures that help the operator to bring the
process back in control. A process capability study is carried out after the process is in statistical
control in order to quantify the capability of the process to meet its specifications. The operators
are trained in the concepts of statistical process control and in the standard operating procedures
23
that help them in long-term monitoring of the process. By reducing the scrap rate and improving
the quality of production, the team has been successful in validating the adopted methodology.
A booklet has also been developed by the team and delivered to Waters Corporation
containing standard operating procedures that can be used to implement statistical process control
at a different manufacturing cell.
The entire work that we have done as a team is broken into three parts, as summarized in
Figure 1-11. The Gage R&R study is covered by Shaozheng Zhang [7], and the development and
value of control charts is discussed by Haipei Zhu [8]. This thesis concentrates on the standard
operating procedures which is a vital part in bringing the process back in statistical control. It also
discusses the scenarios before and after the implantation of standard operating procedures.
P Evaluate the existing gages and make
improvements
P Collection and analysis of baseline data
* Develop methodology and frequency of measurement
P Development of Standard operating procedures
* Development of Control Charts and Reaction Plans
* Ensure the process is in a state of statistical control
* Evaluate the capability of the process
F Reduction of scrap
" improve quality of production
Figure
1-11 Project process flow.
24
1.5 Outline of Thesis
Background on the company and the environment in which this project has been carried out
is presented in Chapter 1. Chapter 2 provides information and concepts on statistical process
control and standard operating procedures, with the help of examples to convey the concepts.
Chapter 3 discusses the previous state of production in the column cell and the various drawbacks
that were noticed. Chapter 4 presents the methodology that is developed, and the standard
operating procedures for each step that are used to carry out the implementation of statistical
process control. Chapter 5 discusses the value and importance of SOPs and the role of ownership.
It also presents the importance of training matrix and feedback from operators and supervisors on
implementation of SOPs. Chapter 6 provides conclusions, future work and recommendations that
will help the company to ensure the longevity of SPC in its machining center. It provides
information on the potential annual savings and defect rate reduction for the machining center.
25
Chapter 2: Literature Review
This chapter provides information on concepts of statistical process control and the various
components associated with it. It also presents information on problems during machining, and
concepts associated with standard operating procedures.
2.1 Statistical Process Control (SPC)
Quality control has been an important part of manufacturing since the beginning.
Manufacturers would compete with each other and if manufacturer C found that manufacturer B
was making better profits, then the former would try to sell their product at a lower price or
improve their quality. This was the case before statistical process control came into place as a
rather new tool in the mid-1920s [10]. Since then, statistical process control has been widely used
in different manufacturing facilities around the world to reduce scrap and improve quality. Thus,
statistical process control can be defined as a quality control tool that uses statistical analysis to
monitor and improve a given process.
2.1.1
Origin of SPC
There have been many scientists and engineers including F.W. Taylor, F. Gilbreth, and
others, who have paved the way toward quality control with the help of statistics. However, it is
Walter A. Shewhart who is considered to be the Father of statistical quality control [11]. In 1924,
he developed statistical control techniques at Bell Telephone Laboratories [12]. On May 16, 1924,
he wrote a memorandum in which he drew the first modem control chart [ 11]. The inspiration that
led Shewhart to develop statistical quality control tools was that he observed variability in
manufacturing processes that differed from natural phenomena like the motion of molecules [13];
26
these observed variations had assignable causes that could be identified and eliminated, thereby
improving the quality of the process. In 1931, he published a book called "Economic Control of
Quality of Manufactured Product" which was a monumental work that taught the principles of
statistical quality control [10].
H.F. Dodge and H.G. Romig developed the first acceptance sampling methodology at Bell
Labs in 1928 [12]. Western Electric and other manufacturing industries were widely using
statistical control methods by the mid-1930s [12]. It was William E. Deming who further
propagated the theory of statistical quality control to the Japanese people and is considered to be
one of the backbone pillars of the rise of the Japanese industry after World War II [14]. Since then,
there have been contributions from many people including Taguchi, Juran, Ishikawa, and others,
who have helped to make SPC what it is today.
2.1.2 Seven Quality Control Tools
Dr. K. Ishikawa was the first to speak on the seven quality control tools in his book "Guide
to Quality Control" in 1974 [15]. They are:
-
Cause and effect diagrams help to break down the causes of a problem and analyze its
effects. This tool gives the user a clearer picture and a better way to approach a problem.
-
Check sheets are a generic tool used to collect and analyze data. They provide a structure
for the user and can be adapted according to use.
-
Control charts are graphical representations of the process varying with time. They show
if the process is in control or out of control.
27
-
Histograms are a widely used tool that gives information to the user on frequency
distributions.
-
Pareto charts contain both bars and a line graph that help the user identify the significant
factors.
-
Scatter diagrams show the relationship between one variable and another as one is plotted
on the x-axis and the other on the y-axis.
-
Stratification is a technique that helps the user to identify trends and patterns from a wide
variety of data.
These seven tools have helped industries improve the quality of their manufacturing
processes.
2.1.3
Control Charts
Control charts are an integral part of SPC. They are a reflection of the current state of the
system. Variability in the production process and between production processes is a common sight
in any manufacturing company. These may be due to systematic (assignable) variations, or due to
random variations. The key to having successful control of the process is to eliminate the
systematic variations such as tool wear, shift change of operators, tool change, etc., and only have
random variations in place.
Control charts can be used when:
-
Determining if a process is stable or not.
Observing patterns of process variation from assignable causes and random causes.
28
-
Controlling an ongoing process and rectifying the errors as they occur.
-
Predicting the expected range of outcomes.
-
Determining if the quality improvement project needs to aim at specific problems or focus
on fundamental changes to the process [16].
A control chart has a center line, an upper control and a lower control limit as shown in
Figure 2-1. Sometimes, they may also show the upper specification and lower specification limits
for the user's understanding. When defining control charts for variables, the common control
charts that are used are: X - R charts, X - S charts, and individual moving range charts.
Upper Control Limit
Due to normal variation
(Common Cause)
1 0_
(UCL)
* 120-
E
110
-1
I
II
'
0 11'
12
4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
mLor Control Limit
The
T
(L)
Out-of-control Point
(Special Camne)
Figure 2-1 Different components of a control chart [8].
The X chart is used to monitor and control the process average, the S chart is used to monitor
and control the process variability, and the R chart is used to monitor the range (another measure
of within-group process variability). These charts are plotted according to the requirement of the
process, and practice varies from process to process and also from company to company. Moving
29
range control charts are often used when the sample size used for monitoring is one. When there
is a mean shift in the process, then other charts including the cumulative sum (CUSUM) and
exponentially weighted moving average (EWMA) charts can be used to move rapidly, detect small
shifts and thus help better control the process [12].
Three sigma limits are the common industry practice to set the control limits; this
corresponds to a low probability of 0.3% that a measurement will be outside the control limits if
the process is still in control. By plotting data points on the control chart with three sigma limits,
the chart gives a measure of the dispersion of data from the average. When a point lies outside the
three sigma limits, it indicates that the process is likely to be out of control and that there may be
a special cause that is making it go out of control. Over the years, many companies have developed
their own rules to identify when a process is going out of control, as summarized in Table 1.
30
Shewhart
Rule
Rulel
One or more
points more than
3 sigma from the
mean
Rule 2
2 of 3
consecutive
points between 2
and 3 sigma
from the mean
Rule 3
4 of 5
consecutive
points between I
and 3 sigma
from the mean
V
Western
Electric
Rules
Nelson
Tests
ISO
8258
AIAG
Rules
Boeing
ASQ
Rules
Trietsch
V
V V//V
V
v/V
V
V
?9/
V
V
V/
V
Rule 4
8 consecutive
points on one
side of the mean
V/ V/ V
V/ V
Rule 5
6 consecutive
points steadily
increasing or
decreasing
v/v/V
V
Rule 6
15 consecutive
points both
above and below
central line
V
V V
Rule 7
14 consecutive
points
alternating up
and down
Rule 8
8 points in a row
on both sides of
the central line
V
v/V
V
V V
V
Table 1: Rules followed by different industries [8].
31
2.1.4
Value of SPC
Statistical process control is a tried and tested method. The key to SPC is action. The value
gained by implementing SPC are shown in Figure 2-2. Nowadays, manufacturers have become
dependent on a range of machinery and technology to produce parts at a rapid rate. Loss of
productivity and losses due to scrap can affect the company's progress in this world of deadly
competition. Real time SPC gathers process and product information and gives the operators and
supervisors alarms and triggers to rectify the problem immediately. SPC is an iterative process,
and the methodology should be upgraded time and again to ensure high quality standards.
Figure 2-2 Benefits and value gained from SPC.
There are many success stories about SPC implementation across different industries,
ranging from semiconductors to automobiles. One such example relates to the implementation of
SPC at Texas Instruments in 1987 [17]. More than half of their lots of printed circuit boards (PCBs)
32
were being rejected. Hence, the top management decided to implement SPC and to set up a
program to train everybody in the organization in SPC [17]. One of the most important elements
for a successful implementation of SPC is ownership. When one reads this case study, it becomes
evident that everybody, from the top management to the operators working on the shop floor, was
involved to make it successful. The result was that the company reduced its scrap rate to 1/10 the
previous value after the implementation of SPC in 1987, as seen in Figure 2-3. The improvement
made in three years was impressive and since then Texas Instruments has continued to use SPC in
their manufacturing process.
10
9
7
6
5
4
3
2
12
1985
196
1987
1988
1989
Figure 2-3 Scrap reduction from 1985 to 1989 [17].
33
2.2 Machining
Tool wear and part deflection are effects that all high volume machining processes can suffer
from. This section provides information on causes and effect of tool wear and part deflection
during machining.
2.2.1
Tool Wear
A common problem experienced while performing machining operations is tool wear.
Though there are formulas that have been developed to calculate tool life expectancy, it is hard to
determine the tool life precisely as there are many factors that need to be considered.
Taylor's equation for tool life expectancy [18] is a common formula:
VCT' = C
(1)
A general form is
VcTn x DxSY = C
(2)
where Vc is the cutting speed, T is the tool life, D is the depth of cut, S is the feed rate, x and y are
determined by experiments, and n and C are properties of the tool that are found by experiments
or historical data.
Tool wear as illustrated in Figure 2-4 may occur due to:
Crater wear which is caused due to chip accumulation and chip sliding on the tool face.
34
* Flank wear occurs when friction is created between the tool flank and the part to be
machined.
-
Corner wear on tool corners as shown in Figure 2-5, occurring more often during precision
cutting.
CNp contact area
Crate( vear
Corner wear
Maimr w"in edge
"er"ee ownr a ft WqMVnV Of aan
Vom afr cu"in fat son* pened of *m
Rlank vvear
Workpiece motion
Figure 2-4 Different types of tool wear [19].
The effects of tool wear include poor surface finish, increased cutting temperature, tool
breakage, part damage, change in tool geometry, and increased cutting force. Tool wear can be
minimized by controlling the cutting temperature, coolant fluids, work material, working
environment, tool material, etc. [19].
35
work surface
actual part shape
theoretical part shape
if no corner wear
V
corner wear reduces
tool length
feed
Dimensional error
caused by tool
Sharp cutting tool
comer wear
Figure 2-5 Occurrence of corner wear in a tool [19].
2.2.2
Part Deflection While Machining
In a machining process, part deflection is caused due to stresses induced by machining,
deflection of tool and operator intervention, or combinations of these effects such part deflection
becomes
frustrating for operators, as the parts have to be scrapped [21]. Similarly, at Waters
Corporation, part deflection occurs while machining column tubes. The deflection mostly happens
while end milling the flats of the column tubes and occurs mostly on the sub-side as the column
tubes are supported by only one of the spindles. Deflection depends on the depth of cut that the
operator seeks to achieve. To obtain a rough finish, climb milling can be used, but conventional
milling needs to be used for a final finish. Using too much depth of cut while climb milling will
cause deflection of the tool and also the part that is produced [20].
36
2.3 Standard Operating Procedures (SOPs)
A standard operating procedure is a document that instructs the user to follow a set of
guidelines to carry out an operation correctly and always in the same manner [22]. It is an important
part of a quality system that removes ambiguity between the operators. "A SOP is a compulsory
instruction" [22]. To maintain high quality standards in a machining center, it is vital that all
operators follow the same process from manufacturing of the parts to the final inspection. This
will involve a series of SOPs that the operators need to be trained on and also monitored to ensure
that it is properly followed. Different types of SOP include those for quality inspection, safety
precautions, operating instruments, giving instructions to construct other SOPs, describing a
method, and reacting to changes [22].
In the medical industry, SOPs play a critical role. While in the machining center, if the
operator does not follow the SOP then defective parts may be produced and reported as scrap, but
in hospital settings, doctors are dealing with the life of the patient. There is no room for error while
conducting medical surgeries; thus doctors are trained well and advised to follow the standard
procedures [22]. This is a similar case for other professionals who deal with the lives of people,
including fire fighters, policemen, EMS, and others.
Different companies have different formatting options for SOPs according to company
policies and guidelines. But as a general guideline, components that an SOP should have are:
"
The purpose and field of application
"
Scope of the people concerned and important definitions used
*
References to any related SOPs
*
Safety instructions
*
Name, date and signature of the person creating the SOP and also the one authorizing it
37
*
Necessary equipment and apparatus
"
Procedure to follow the instructions
*
Theoretical concepts that can benefit the user
"
Instructions to interpret the results obtained [23]
When the first draft of an SOP is made, it needs to be verified and evaluated by another
officer. Sometimes, SOPs would have to go through different officers to get an approval to start
using it on the shop floor. A standard way needs to be developed to edit, delete and replace SOPs
so that there is no confusion on the current version of the SOP that needs to be used. SOPs have
proven to be vital in the success of a quality improvement or control program; appropriate SOPs
and training are the foundation for carrying out a successful inspection system [24].
38
Chapter 3: Manufacturing Scenario in the Columns Cell
The columns cell is a critical part of Waters Global Machining Center. There are seven CNC
machines in the columns cell which are used to run different components. On a working day, there
are four operators working on these machines. One of them is the section head who monitors the
work of fellow operators. The operators work in a complex environment but they have the
necessary metrology resources to ensure that they produce good parts. They are also provided with
hand held gages for quick inspection as shown in Figure 3-1. Theses gages are placed next to every
CNC machine in the columns cell. The operators do a complete inspection of the first part produced
at the beginning of the shift by using the advanced gages including the OasisTM system, the
comparator, the Johnson GageTM and others that are placed in the inspection area of the columns
cell.
Figure 3-1 Quick inspection gages like the micrometers and GO/NOGO placed next to the CNC machine.
39
A protocol followed by the operators is to send the first conforming part that they produce
to the larger inspection cell. The inspection cell has advanced metrology resources to inspect all
the parts of the machining center. The operators also have to send their first conforming part that
they produce when they come back from lunch and dinner breaks. The inspection cell inspects the
part again to ensure that the operator has checked it correctly and that they are producing good
parts.
The columns cell can be split into the following sections:
Column tube production: Two CNC machines are assigned to produce column tubes. These
machines can also produce end fittings for the column but their primary purpose is
production of column tubes. Figure 3-2 is a representation of the CNC machine used in the
columns cell.
Front spindle
Max- 8,000 min
165mm/1 chucking
(Guide bushing)
2.5D/1 chucking
(Non-guide bushing)
'
Rctary tools on the
gang tool post
Max 8.000 min
(Rating 6.000 min
Back spmndlo
Max 8,000 min
-
*
Figure 3-2 Schematic representation of the CNC machine used in the columns cell [7].
40
*
End fittings and other accessories: The other five machines are assigned to produce end
fittings and other accessories for the column tubes as shown in Figure 3-2. Each column
will have two end fittings as it has two ends. When column tubes are sold they are not sold
separately, they are sold as a complete unit, i.e., a column tube is packed with chemicals
and closed by the end fittings.
Figure 3-3 Representation of the different size of columns that are produced in the columns cell and end
fittings.
"
Cleaning and Polishing area: After the column tubes and the end fittings are produced, they
are sent for cleaning and polishing. There is one operator assigned for this task. The
operator shifts the lot of column tubes and end fittings to the assembly section after they
have been cleaned and polished.
" Assembly area: The assembly area is where column tubes and end fittings are integrated.
It is to be noted that the task of packing the column tubes with chemicals is not done at the
41
Milford site. The column tubes and end fittings are integrated and put in a cover. These
packets are given a unique serial number for identification. They are transported to
Wexford for the final assembly of the product.
*
Inspection area: There is a small inspection area in the columns cell that is used by the
operators to check the parts that they are producing. The inspection area consists of the
following gages:
>
Height Gage: This gage is used to measure the height of the components. At the
beginning of the shift, the operator produces one part and does a complete check
by using all the resources. This is the time when the operator uses the height gage.
It is very rare to have a problem with the height of the column tube. Mostly, it is
used to check the height of the end fittings.
>
Optical Comparator: The optical comparator, as shown in Figure 3-4, is a gage that
measures the dimensions on the columns such as the position of the thread, width
of the wrench flat, location of the wrench flat and the chafer size. The drawback
with this gage is that it is time consuming and also laborious. The time to inspect
a column tube on the comparator can take from 25 minutes to 30 minutes depending
on the dimensions that have to be measured. It does not have an automatic data
capturing function, therefore, the operator has to note down the data manually.
42
Figure 3-4 Optical comparator in the columns cell.
OasisTM inspection system: The OasisTM inspection system, as shown in Figure 35, is an optical measurement device that captures the data when the component is
placed in the inspection zone. It has an automatic data capturing system that is very
helpful for the operators on the machine shop. For every component that has to be
measured on the OasisTM system, a program has to be written to capture the
necessary dimensions. It is a fast way of inspection with an accuracy of 0.0001
inches [25], which is helping the operators do a better job in the columns cell.
43
On-Board Computer
1nspction Zon.
OpOCi8
Lens & Camera
Light
source
Figure 3-5 Components of the Oasis inspection system [8].
Johnson GageTM: This gage, as shown in Figure 3-6, is used to measure the thread
characteristics such as pitch diameter and the form of thread. It has a digital output
that is connected to the ProlinkTM software for real time inspection. The Johnson
GageTM is mostly used to measure the pitch diameter of column tubes in the
columns cell. It is quick and less laborious than the optical comparator.
44
.
Figure 3-6 Measuring a column on a Johnson GageT M
Profilometer: It is a gage, as shown in Figure 3-7, which is used to measure the
surface finish of the column tubes and end fittings. It uses a sensitive probe that
profiles the surface of the part. These probes are expensive and can cost around
$800. Therefore, the operators are trained to use this gage in a careful manner. The
output that is obtained from the Profilometer is a value of the surface finish and a
graph showing the contours on the surface of either a column tube or an end fitting.
45
Figure 3-7 Profilometer in the columns cell.
Micrometers: The common micrometers used by the operators on the columns cell
are the blade micrometer, as shown in Figure 3-8, the flat micrometer, as shown in
Figure 3-9, and the pitch micrometer. Micrometers are quick inspection gages that
help the operator to measure the critical dimensions in a quick and accurate way.
Micrometers, in general, have a resolution of 0.0005 inches [7].
The flat
micrometer is used to measure the outer diameter and the main diameter of the
thread on the column tube. Some micrometer have digital output while others have
to be manually read. Some of the digital output micrometers are capable of being
connected to the real time inspection software. The blade micrometer is used to
measure the thickness of the wrench flats and the pitch micrometer is used to
measure the pitch diameter of the threads. As 100% inspection is not a viable option
46
in the high volume production center of column tubes and end fitting, the
micrometers help the operators produce parts within specification limits.
Figure 3-8 Blade micrometer.
Figure 3-9 Flat micrometer.
Microscope: Microscopes, as shown in Figure 3-10, are placed near every CNC
machine to aid the operator in visual inspection. A column tube is rejected when
the lot number is not visible. Another issue is when there are scratches on the
sealing surface of the column tube. These can be noted by using the microscope.
Experience of the operator plays a big role in identifying these defects. An
experienced operator is able to identify scratches on the surface of the column tube
with the naked eye. Microscopes help the new hires in learning to notice these
defects when they occur.
47
Figure 3-10 Microscope in the columns cell.
These different gages are used to measure the different dimensions on column tubes, as
summarized in Table 2, and end fittings. This shows that the columns cell is equipped with
excellent metrology resources to implement statistical process control.
Dimension
Measurement Devices
a
Outer diameter
Micrometer, Blade micrometer, OASIS
b
Chamfer
OASIS, Comparator, Profilometer
c
The begin of the thread
Comparator
d
The end of the thread
Comparator
e
The location of the thread relief
OASIS, Comparator
f
The location of the flat
OASIS, Comparator
g
The width of the flat
OASIS, Comparator
h
Total length
Height gage
i
Pitch diameter
OASIS, Johnson Gage
j
The thickness of the flat
Micrometer, Blade micrometer, OASIS
Table 2: Measurement devices used to measure the different dimensions on a column tube [7].
48
3.1 Lack of Proper Gage Fixture for The OasisTM System
The OasisTM inspection system is an expensive device that is placed in the columns cell to
aid the operators in giving quick and accurate measurements. At the beginning of the project, it
was observed that the OasisTM system had a fixture that was not suitable to measure the column
tubes as shown in Figure 3-11.
Figure 3-11 Comparison to show that the existing fixture is not suitable for inspection.
The fixture results in variations due to differences in how the operator uses the measurement
system. The operator could manipulate the measurement system by rotating the fixture to show
that the part was within specification limits as shown in Figure 3-11: the red out-of-limit indicators
in the upper right of the left picture turn to green with rotation of part in the right picture. Another
issue with this fixture was that it did not ensure that the column tube could be held in a perfectly
49
vertical direction. This caused tilting of the column tube while measuring it on the OasisTM system.
So, good parts had to be rejected as the OasisTM system showed that the parts were out of
specification limits.
To ensure that the OasisTM system is used to its full capability, a new fixture was designed
to eliminate the variations occurring from the previous fixture. This fixture ensures that the column
tubes are firmly secured and dimensions such as the width of the wrench flat are measured
accurately, which was not possible in the previous fixture. The parallel guiding rail subsystem is
designed to ensure that the column tube is placed in a perfect horizontal direction to the direction
in which the light is transmitted. Detailed analysis, steps in how this fixture was designed and
benefits of this fixture are explained in Zhang's thesis [7].
Figure 3-12 New fixture for the OasisTM system.
50
3.2 Lack of Standard Operating Procedures (SOPs)
Standard operating procedures (SOPs) are vital in any manufacturing facility to ensure
uniformity of production and inspection. The operators in the columns cell do not have SOPs for
inspection of column tubes. This creates variations in the way the operators measure parts, choice
of inspection system, frequency of inspection, tool offset while machining and other scenarios,
resulting in problems on the shop floor.
The operators do not have a record of when tools were changed, so some operators change
tool according to their intuition, some change tools at the beginning of their shift, some change
tools after producing some number of parts and others do not change tools until instructed. This
variation in tool change amongst operators in the column cell not only aids in producing bad parts
but also results in throwing away good tools and loss in capacity. Tool change can take from 30
minutes to three hours depending on the number of tools and the type of tool to be changed. Every
time a tool is changed, the first part that is produced by the machine has to undergo complete
inspection which can take from 15 to 30 minutes. Operators do not like changing tools as it is a
tiresome process, so some of them do it in a random way. Similarly, there is no procedure in place
to instruct the operator on when to do a tool offset to compensate for tool wear. Most operators do
the wear offset by their intuition and this is one of the main origins of variation as operators
compensate for tool wear with different amounts of offset and at different frequencies.
Another concern is the use of different measurement systems by the operators to measure
the same feature. If the measurement system is not capable of measuring a certain dimension, then
the operator might be accepting bad parts which puts the consumer at risk. Therefore, a gage
repeatability and reproducibility study was conducted to evaluate the measurement devices in the
columns cell. This results of this study can be found in the thesis of Zhang [7].
51
3.3 Lack of Statistical Process Control (SPC)
With the expansion of workforce at the machining center, new hires find it difficult to work
in this complex production system at the columns cell. With the lack of standard operating
procedures, new hires are not trained on measurement devices that need to be used for the different
dimensions of column tubes and end fittings. Resources are readily available for real time
inspection, but there are no procedures in place to use those resources.
The machining center used to have statistical process control (SPC) ten years ago, but was
believed to have failed in its purpose for several reasons:
*
Lack of supervision: The operators were asked to collect data on the different
dimensions of the column tube and manually enter it in the software. The operators
did that on a regular basis but there was no one in charge to analyze the data and give
feedback to the operators. As time passed by, the operators lost faith in the system as
it did not serve its purpose.
*
Manipulation: As the operators had to key in the data into the software, some
operators started to manipulate the system by entering values that showed good parts
were being produced, but in reality they were producing bad parts. This was done in
fear of the supervisors penalizing them for producing bad parts.
*
Laborious task: It was a tiresome task to enter the different dimensions into the
software. The number dimensions on a column tube can vary from 22 to 35. The
number of column tubes in a production run on average can vary from 200 to 400,
depending on the size of a column tube. To enter so many data points into the
software made the operators not only angry but also lose faith in the SPC system.
52
*
Lack of training on SPC: The operators were not trained on the concepts of SPC. So,
if the operator was asked to produce the parts by looking at a X - S chart with control
limits, the operator would pay no attention to it and produce parts according to
intuition, which caused production of bad parts.
"
Outdated software: The machining center began to expand and the way the products
were manufactured changed in due course of time, such that the software was not
able to incorporate those changes. Therefore, operators stopped using the software
and lost touch with the SPC system.
*
Lack of manpower: More machines were introduced into the machining center to
cope with the increasing demand of products. So, the operators had to work on
multiple machines and did not find time to inspect parts on a regular basis. They were
more concerned with meeting the demand, so they had no time to enter the data for
the use of SPC system that was in place at that time.
The above reasons noted for the lack of success with the previous SPC implementation were
obtained from speaking to operators who have been in the columns cell for more than a decade.
Identifying theses failure modes also helped to make sure that we did not make the same mistakes
in developing a new SPC system.
53
Chapter 4: Standard Operating Procedures (SOPs)
Standard Operating Procedures (SOPs) are a vital part of this project. They guide not only
the operator but the entire organization to follow certain guidelines in building a quality control
culture.
A common framework adopted while designing the SOPs is to ensure that each SOP includes
purpose, scope, instruments, terms and definitions, procedure, analysis, and result sections. By
having a common framework, it is easier to understand the reasons behind developing an SOP, the
people involved in the operations, the instruments that needs to be considered, important terms to
understand the SOP, procedures for conducting the operation, the procedure to analyze by either
using a software system or manually, and the expected results that will obtained by following the
SOP. This chapter presents the methodology adopted for implementing SPC, purpose, and benefits
of having SOPs for the different components of the methodology.
4.1 Methodology for Implementation of SPC
One of the key deliverables in this project is development of a portable methodology for
implementing statistical process control not only in the columns cell but throughout the entire
machining center. The methodology that we have developed is shown in Figure 4-1. A key step is
to develop standard operating procedures for each of the components that are listed in the
methodology. This thesis discusses the standard operating procedures that are developed for:
"
Gage repeatability and reproducibility (Gage R&R) study
"
Baseline data collection
"
Sampling plan
"
Control charts
*
Process capability
*
Long term monitoring
54
The SOPs are developed for a general case such that they can be used for the entire
machining center. Each of the above SOPs are explained by taking the column tubes as an example
for the benefit of the reader. For developing the SOP on long term monitoring, a basic SOP on
column tube inspection has been developed to ensure that a standard way is followed for the
inspection of column tubes. The methodology is explained in Section 1.4.3 of this thesis. A booklet
on "Implementation of Statistical Process Control" has been delivered to Waters Corporation that
not only contains the SOPs for the different components on SPC, but can also be used as a training
module for new hires. The various SOPs can be found in the Appendix of this thesis. Dimensions
and tolerances have been blacked out in the SOP to avoid disclosure of company confidential
information.
55
Identify the measurement method
for the dimensions on the drawing
IAcceptable
-
Not Acceptab
~
Yes
No
IYes
I
No
Ys
S
-
S
S
Figure 4-1 Methodology for implementation of SPC.
56
f
4.2 Gage Repeatability and Reproducibility (Gage R&R) study
The gage repeatability and reproducibility (Gage R&R) study is the first step in the
implementation of SPC. The gages explained in Chapter 3 are used to conduct the Gage R&R
study. This section describes the development of the SOP for a Gage R&R study, and discusses
the results after implementation of the SOP. The results of the Gage R&R study are based on and
share text with the thesis by Zhang [7].
4.2.1 Purpose of an SOP for Gage R&R study
The purpose of conducting a Gage R&R study is to determine the variability due to errors in
the measurement system. The errors could arise due to the operator, parts being measured or the
gage itself. The Gage R&R study forms the foundation for the entire process of implementing
SPC. An important ratio while conducting the Gage R&R study is the precision-to-tolerance (P/T)
ratio. It is defined as
T
kage
USL-LSL
(3)
where k is a constant related to the significance of the hypothesis test, USL refers to the upper
specification limit, LSL refers to the lower specification limit, and
6
Gage is the estimated gage
standard deviation [7].
While designing an SOP for Gage R&R study as shown in Figure 4-2 (full text available in
the Appendix), the instruments in consideration have to be studied to understand how best to
operate the instruments. Also, the user has to be aware of the functionalities of the software being
used to conduct the study in a proper manner. A Gage R&R study was conducted before the
formation of an SOP. From that study, it was identified that operator variation is the main source
57
of variation, and that there is a necessity for developing an SOP for conducting Gage R&R studies,
as well as training of the operators to follow the SOP in a standard way.
STANDARD OPERATING PROCEDURE: GAGE R&R
1. Purpose:
Gage PAR study determines the variability in measurements due to errors in the
measurement system. The errors could arise due to the operator, parts being measured or
the gage itself. The Gage R&R study forms a platform to conducd the process capability
analysis.
2. Scope:
This document is an Instruction for tue operator to conduct the Gage R&R study. By following this
document, one can Identify the variations that causes the gage to give different measurements for
the same dimension. This will tell the operator Ifthe given measurement system is acce ble or
not. The study has been condcded by taking an eample with column tube part number
3. Instruamntt
Optcal comparator, The Oasis'" and the Johnson Gage'" are the measurement systems used for
part nrkuMr
4. Tewms and Definitions:
Repeatabily - measured varalon resuting from equipment interactions with test reeca
Reprodudblity - measured varaton resulting frn overator interacaons with measurement eauipmerrt
Interaction effects - the variation resulting from appraiser to appraiser deviations in
standard technique
Appraiser- persons taking meastrements, -operators' may be substituted Interdiangeably
Bas - the tendency for a gage to over or under read on a particular measurement
Unearity- the measurement of bias over the range of interest
ANOVA- analysis of variance between groups
Total Variation (TV) - It represents the variation due to the pat, operator, equipment and
gage R&R.
Equipment Variation (EV) - It represents the repeatability of the neasureMent device.
Appraiser Varfation (AV) - It represents the reproducibility of the system
Part Variation (PV) - It represents the variation of the parts used in the gage study.
Gage RR - It represents both the equipment variation and the appraiser variation
5. Procedure:
5.1 Identity the measurement systems that need to be studied.
5.2 Identify the product and the critical dimensions of the product that need to be
studied.
5.3 The study will consist of 10 parts, 3 appraisers who will each measure the parts
three
times each. The number of appraisers, parts and the trials may vary across
dfirftient industrIes but It Is a common practice to follow the above procedure.
5.4 The part samples that are used for the gage study should represent the true
variation of the production process I.e., part samples need to be produced across the
whole tolerance lit. This Is done as Gage R&R Is the evaluation of the Measurement
system and not the part samples.
Figure 4-2 Screenshot of the SOP developed for a Gage R&R study.
58
4.2.2
Implementation of an SOP to Conduct Gage R&R Study
Based on the experience gained in the first Gage R&R study, a new SOP was developed.
The operators were trained on using the new SOP for conducting a Gage R&R study and its
concepts. For the purpose of this study, 10 column tubes, three operators and three trials in random
order were used. With the help of the quality engineer, standard ways were determined to inspect
parts on the optical comparator and the Johnson GageTM. A new fixture was also designed for the
OasisTM system to conduct the study [7]. The Gage R&R study was conducted by three operators
who played different roles in the machining center:
*
Operator A is a quality engineer in charge of the quality of column tubes
"
Operator B is a section head of the operations in the columns cell
"
Operator C is a senior quality technician of the machining center
By training operators from different backgrounds, the scope of the SOP is expanded and
good results from executing the SOP with theses operators validates the procedure defined in the
SOP.
4.2.3
Results from Implementation of SOP
By following a standard procedure, the operators eliminated the large measurement errors
that had come from a lack of SOP. In particular, extreme or outlier data points were eliminated,
and the SOP ensures that these do not occur again. Figure 4-3 represents the different dimensions
that are measured during the Gage R&R study, which helps to understand the results shown in
Table 3. A gage P/T ratio of about 30% or less is desired, to indicate that a gage is capable for
quality monitoring [7]. From Table 3, it can be seen that the gage capabilities are improved by
59
implementing the SOP, and thus validates the benefit of having a standard procedure to conduct a
Gage R&R study.
-l
\1
7
C
e
f
h
g
Figure 4-3 The different dimensions that has to be measured on one end of a column tube.
P/T Ratio (%)
After
Before
Dimension
Sub side
Main side
Main side
Sub side
b
1013.38
93.35
31.57
38.94
c
49.97
23.42
26.3
27.97
d
3634.65
41.77
13.44
19.11
i
179.66
47.12
10.51
8.21
Table 3: Comparison of gage capabilities, P/T ratio (%), before and after implementation of SOP [7].
60
4.3 Baseline Data Collection and Sampling Plan
Baseline data collection and sampling plan form the next parts of the SPC methodology after
the Gage R&R study. We conducted a 36 hour observation analysis of production of column tubes
to collect our baseline data. From this baseline data, we could observe trends and patterns that
helped to better understand the process and develop SOPs that can eliminate variations occurring
from the manufacturing process.
The purpose of baseline data collection is to help the stake holders to have a solid foundation
of data to evaluate and compare with different operating conditions, and to identify quality
bottlenecks by observing the trends shown in baseline data plots. A detailed analysis and procedure
on how we conducted the baseline data collection is explained in Zhu's thesis [8].
We followed a standard procedure to collect the baseline data as shown in Figure 4-4 (the
full SOP is provided in the Appendix), and used that to conduct our further analysis. Collection of
data on 100% of parts produced is not possible for real-time monitoring in the columns cell due to
a complex production environment. We need to create a sampling plan that will not only help the
operator but also aid in real time inspection. By observing the trends in the graphs of the baseline
data and calculating the frequency of failure mode occurrences, we arrive at a sampling plan of
one in ten parts to be measured by the operator. A standard procedure for finding the right sampling
plan has been developed (the full SOP is provided in the Appendix). However, the one in ten
sampling seemed to be tiresome for the operators. Given that the operators conduct quick
inspection with the use of micrometers and GO/NOGO gages, we redesigned the sampling plan to
one in twenty parts, with the operator checking every tenth part by quick inspection. More
information on trends in baseline data and sampling plan is explained in Zhu's thesis [8].
61
STANDARD OPERATING PROCEDURE: BASELINE DATA
COLLECTION
1. Purpose:
Baseline data collection helps the stake holders to have a soid foundation of data to evaluate and
compare It with different conditions and also observe the trend which will help in identifying the
bottlanecks.
2. Scope:
This document Is an instruction to the operators on the steps that needs to be taken while collecting
baseline data. It also gives the operators guidelines to follow and potential pitfais whie doing the
operation.
3. Procedure:
3.1. Manufacture 1000 parts and arrange it accordlingy In sequence.
3.2. A 100% inspection is carried out on these parts.
3.3. Ensure that the variablity in operators Is removed by having the same operator measure
the parts on the same machine.
3.4. I is vital to ensure that the parts have been arranged in the order of production.
3.3. The machine variation can be reduced by having al the parts manufactured on the same
macine.
3.6. Ensure to foltow the same measuring procedure for all the parts acrordIng to the standard
operating promdure for measurement.
3.7. Do not discard bad parts as it will affect the whole procedure.
4.
Analysis:
is a trend In the graph. The
trend in the graph will help give information on the variations during production. This data can
be used to determine the control limits and sampling plan for later inspection.
After all the data has been inputted, plot a run chart to see If there
Figure 4-4 Screenshot of the SOP developed for baseline data collection.
62
4.4 Control Charts
Control charts form the core of statistical process control and are a key component of this
project. For the scope of the project, an individual chart with control limits is implemented with
the help of ProlinkTM. For the SOP on control charts, however, a more generalized procedure is
developed, as the company had asked for a portable SOP that not only can be used in the column
cell but can be used in the entire machining center. Concepts of control charts have already been
discussed in Section 2.1.3. This section discusses the importance of control charts, the
corresponding SOP, and results from implementing the control chart SOP.
4.4.1
Importance of Control Charts
As mentioned earlier, control charts are a vital part of this project. For this project, ProlinkTM
software is used and an individual chart with control limits is implemented as shown in Figure 45. This real time inspection tool has helped operators to look at the graph and produce parts
accordingly, as opposed to producing parts with no guidance. This tool also helps operators to
enter notes such as tool change, operator change, tool break, tool offset and other assignable causes
which makes it easier to debug the process as shown in Figure 4-6. The meaning of the different
colored lines in Figures 4:5 and 4:6 are explained in Table 4.
63
It*
*WV
o
R
SW
exon GLw a9t
100b
Er O&Ae( $*van'; . Pi I
-11 Irtoatfulaftam %4fasttny A&4%A7f
"*
S
raiwlftw
7
QftvrL 1 .47
Target
Value
Process
Mean
Figure 4-5 Screenshot of the control chart being used in ProlinkTM as a real time inspection tool.
64
Figure 4-6 Notes can be recorded in the ProlinkTM software.
65
Type of Lines
Representations
I
Red Solid Line
Upper/Lower Specification Limit
2
Green Solid Line
Nominal Value from Design Specification
Process Grand Mean
Longer Green Dashed Line
3
Upper/Lower Control Limits (
Red Dashed Line
4
ICY,
Shorter Green Dashed Line
5
2cy
Event with Notes
White Vertical Line
6
3a)
Table 4: Meaning of the lines in ProlinkTM software.
By giving the operator training on the use of control charts in the Prolink
TM
software,
operators produced more good parts and achieved better process capability as will be discussed in
the following sections. Detailed analysis on control charts and its implementation is explained in
Zhu's thesis [8].
4.4.2
SOP and Results from Implementation of Control Charts
Control charts are a graphical representation of how the process varies with time, and shows
if the process is in control or out of control. The SOP, as shown in Figure 4-7 (the full SOP is
provided in the Appendix), explains the procedure for choosing the right control chart depending
on the manufacturing process and the software that is used. It also explains the calculation and
setting of control limits, and provides reaction plans for threading tools using the example of a
column tube. The scope of the SOP is for the operators to understand how the quality department
sets these control limits and for the manufacturing supervisors in developing reaction plans that
will help the operators to avoid producing non-conforming parts.
66
STANDARD OPERATING PROCEDURE: CONTROL CHARTS
1. Purpose:
Control Chart is a graph that shows how the prorxs varies with time. They show if the process
is In-control or out of control. A control chart consists of a center line for the average, an upper
line for the upper control limit. a lower fine for the lower control limit. These lines are obtained
from historical data. By utilizing these control charts operators can better monitor the quality of
the process.
7
2.
~
P
Scope.
This document provides an overview of control charts and the procedure that has to be followed
by the quality department ia determining the control limits. The scope of this document also
extends to the operators to understand how the quality department sets these control limits.
3. Terms and Definitionst
Subgroup Size - for a single point of data, the number of sample data colected. If the number
of 'parts' collected for a study datum point Is 10, then the subgroup size Is 10. If only one part
is studied to collect the data for a point, the subgroup size is 1.
4. Procedure:
4.1
4.2
4.3
4.4
4.5
4.6
4.7
Choose an appropriate control chart for the data that Is going to be collected.
An appropriate time period has to be determined for collecting the data and to
plot It on graphs.
Before starting to colled the data, calculate the subgroup size of the data to be
collected. Then, collect the data accordingly.
Calculate the centerline and the control limits of the data and plot it an the
appropriate chart.
Analyze the data and look for out of control patterns or signals.
Mark these signals on the chart and perform a root cause analysis.
Document the investigation of the cause and how it was rectified.
5. Theory
5.1
Control Charts are used to monitor variation. These charts are used to determine if a
process is in a state of statistical control.
Figure 4-7 Screenshot of the SOP developed for control charts.
67
By training operators to follow a standard procedure in using control charts, the quality loss
was reduced and the process was brought back into a state of statistical process control as shown
in Figure 4-8. Our analysis indicates that the scrap rate can be reduced by 50% and there are cost
benefits associated with it.
be
)C-.
Gi;
11.205
Rqwt
Dp
i
Ir &tW. R&
101s
r
e
Toc dOpi
:
r
:
dnw:tra
P3IvIULII pAM -V Rn 1 411.101 II AJj
flesIathsn 0(002
theotod! 37
suolo
m!
I
Qoami
22.46
pntto 2S
Figure 4-8: Control charts showing the process to be stable after implementation of the SOP.
4.5 Process Capability
The purpose of conducting a process capability study is to measure the output of a stable
process in comparison to its specification limits. Different indices are used to measure the process
capability, referred to as the process capability index (Cpk).
An SOP on concepts of process
capability, the procedure to conduct a process capability analysis, and the procedure to use the
MinitabTM software to calculate the various indices is as shown in Figure 4-9 (the full SOP is
provided in the Appendix).
68
STANDARD OPERATING PROCEDURE: PROCESS CAPABILITY
1. Purpose
Process CapabilNty is a measure of the output of a stable process to its specification limits.
There are different Indices that are used to measure process capability and are called process
capability Index (COk. Ppk).
2. Scope:
This document is an instruction for the operator to follow to conduct the Process Capability
study. This study will give an Insight into the capability of the pr ocess as sometimes the process
can produce 100% of output within the specification limits and otherwise not. It is Important
to conduct this study after the process Is stable.
3. Terns and Definitions:
Cpk (Process Capability Index) - It is the ratio between permissible deviation, measured from
the mean value to the nearest specific linit or acceptability, and the actual one-sided three
times sigma spread or the process. Cpk of at least 1.33 is desirable. Cpk accounts for
variability within a subgoup.
Ppk (Process Performance Index) - It represents the overall variability. Ppk measures both the
pact to part variabilty as well as shft and drift between them.
Cam- It is the capability Index that compares the width of the specification limits to the spread
of the process output and also Incorporates an error term to determine how far the center of
the distribution is from the target.
Weibull distribution - A probability distribution function having the three parameters of 3
(shape). q (sAope), and y (location).
DPMO - defects per yIllton
PPM - Parts per mnilion.
4. Procedure:
Make a
4.1
4.2
note of the operating conditions that the study is being conducted In.
Ensure that there Is sufficient raw material available and choose an operator to
conduct the study.
Cpk = mi I3
4.3
4.4
4.5
4.6
USL -~7
- LSL
The process capability study needs to be conducted only after the measurement
system Is confirmed to be acceptable during the Gage RINR analysis.
Run the process and tart coilecting data to ensure that the process is stable.
If the process Is not stable then conduct a root cause analysis and resume the
study only after stabilizing the process.
Collect as many data points as possible (minimum 100 points) to get a better
accuracy of the process capability.
Figure 4-9 Screenshot of the SOP developed to calculate process capability.
69
The operators were trained on conducting a process capability study and on understanding
its results. The ProlinkTM software automatically calculates the Cpk value for the benefit of the
operator as shown in Figure 4-10. This also gives the supervisors and engineers succinct view of
the state of the process when they look at the screen, thus assuring them if the process is in control
or not.
ause:.: Cutoff CHP out
ction: Change todl
.2052 Rec: 37
Figure 4-10 Screenshot of the ProlinkTM software displaying Cpk value.
The results of the process capability study for one of the column tubes is shown in Table 5.
The normal industry practice is to maintain Cpk values greater than 1.33. As can be seen from
Table 5, by implementing the SOP, Cpk values of greater than 1.33 are achieved, and in some
cases the values are greater than 2. This shows that the stable process is capable of meeting the
product specification limits.
Dimensions
OD
Cpk
2.13
Wrench length Thread PD Wrench thickness Wrench location
2.06
1.81
1.68
1.46
Table 5: Values of the Cpk for the different dimensions after using the SOP.
70
4.6 Long Term Monitoring
Long term monitoring is another important component of SPC, as SPC is an iterative
procedure. If the SPC system is not monitored or updated with the advancement of manufacturing
processes in the machining center, then the system is likely to fail as explained in Section 3.3. This
section describes the importance of an SOP for long term monitoring and the results obtained from
it.
4.6.1
Importance and SOP for Long Term Monitoring
The purpose of long term monitoring is to keep the SPC system alive in the company and to
create a quality control culture that will benefit the company in the long run. By monitoring the
process, changes that arise during the initial iterations can be incorporated and high quality
standards can be maintained. The SOP for long term monitoring, as shown in Figure 4-1 l(the full
SOP is provided in the Appendix), and a column cell specific SOP is developed.
71
STANDARD OPERATING PROCEDURE: LONG-TERM MONITORING
1. Purpose:
Lang-term monitoring plays an important role in keeping SPC alive in a company. The purpose
is to incorporate the changes found during the initial iterations and to maintain high quality
standards.
2. Scopet
This document Is for all personnel who are working in the implementation and continuous
monitoring of the SPC system. The scope also extends to the upper management to keep a check
on the SPC system.
3. Procedure:
3.1
The operators need to be trained on the standard operating procedures that are
implemented in the production oor.
3.2
On the next page. an example of a standard operating procedure Is shown that is
used to conduct quality inspection for column tubes.
3.3
By following this example, the reader will be enightened on the Importance of
having standard operating procedures for inspection.
3.4
It is necessary to inorporate changes as and when required with the permission of
the concerned authority ac ding to the SOP that is devised In the depatment to
change an existing SOP.
3.5
Changes can only made if the process is monitored and variations ate observed with
respect to the Iltial process.
3.6
The upper management should make routine checks to ensure that the SPC system
doesn't fall.
3.7
The supervisors on the shop floor should have meetings with the operators to
disoass on the SPC system on a day to day basis.
3.6
Operators need to follow the standard operating procedures and should be kept
accountable for it.
3.9
There needs to be a designated person who can supervise only the SPC system and
dear any querIes brought about it.
4. Resuet
4.1
By foliowing the above steps properly, the company can experience great benefits.
4.2
Benefits like:
* Reduction of scrap
* Improvement in productivity
* Reduction in manuacturing cost
* Overall satistealon of operators
* Customer satisfaction
* Increase in profits
4.3
The above benefits can only be achieved if there is a sense or ownership and
accountability laid down during the initial phases of implementation.
4A
5PC is nt a one man's tool. It is a coitatorative effort of the whole company working
together to inculcate the culture to become a world class manufacturer.
Figure 4-11 Screenshot of the SOP developed for long term monitoring.
By developing a column tube inspection procedure, operators in the columns cell could
experience the difference between having an SOP and not having one. Figure 4-12 illustrates on
how the software shows the operator when the process goes out of control, using a yellow screen
to visually alert the operator to an alarm.
72
..........
: : : : : ; :: : : ; - : . : . : _:I:.
. .. ... ...: - ': , . . . . .
10".---- - -.....................
-----
II
-
-
:*.- ::
: ::
z ; : : ; :;
: . . : . : : I::::::::::::
: ; : : :_:
-.
...
- - - -- -- -- - - - - -- - - - - - - . . I I I . I . .1- I - . I.
II
..
I
: :: : ; z
zz
z
- - - --
......
. .. ... ..
---------
110.2898 Deketed Rec: 22
lCpk= 2.311
Figure 4-12 Screenshot of the difference between a process in control (above) and out of control (below).
By monitoring one of the column tubes, and training the operators on the SOPs, excellent
results can be obtained as shown in Figure 4-13, where certain dimensions show a Cpk of greater
than 13 while the others show a Cpk greater than 2. This validates the reason why standard
operating procedures are required in a machining center.
Figure 4-13 Results obtained from long term monitoring.
73
Chapter 5: Value Added Due to Standard Operating Procedures
As discussed in Chapter 4, SOPs play a significant role in the quality control of a
manufacturing process. Before SOPs are implemented, certain tasks have to be performed to
ensure the success of not only developing an SOP but also in ensuring that it is followed. This
chapter discusses the role of ownership, importance of a training matrix, a standardized way of
editing SOPs, feedback from operators and supervisors on the use of SOPs, and the scenario after
implementation of SOPs in the columns cell.
5.1 Role of Ownership
There needs to be a set of people assigned with the task of ensuring that the SOPs are updated
regularly and that they are followed in the right manner. Due to lack of supervision, as mentioned
in Section 3.3, tools such as SPC have either failed or faded away. To prevent this from repeating
again, the head of manufacturing came up with the idea of creating named specific roles in the
machining center, to hold people accountable for proper enforcement of the SPC tool. By doing
so, operators feel comfortable in using SPC, as they have a helping hand when they don't
understand a certain process or encounter new problems. SPC systems have flourished when the
whole company, from the upper management to the operators on the shop floor, believe that the
SPC system will not only benefit the operators but the entire company in direct or indirect ways
[17].
5.2 Importance of Training Matrix
A training matrix has been incorporated in the SPC methodology booklet delivered to the
company. The training matrix, as shown in Figure 5-1, is a document that shows different
74
designations of people in the company that need to be trained on SPC. This includes the upper
management, the supervisors and engineers, and the operators. By training a wide variety of
people, decisions taken on quality issues become understandable by everyone in the company thus
bringing uniformity. The explanation on use of the training matrix is provided in the Appendix.
TRAINING MATRIX
I.
AMaCbMACK MachU
W_ 'n~ift
W2
SiW
rrjV
Z
LoBob
D1
Oharoie D
Kt
1
1
D
30
3 3 0
Nike
Alonso D
Romeo N
Sid
2
3
ae Yr
WidvY I
I
I
I
I
I
End Yr
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
1
1
2
2
2
C
I
I
3
2
Name of Supervisor
TT
Signature
mod=*hIU|
Date
Figure 5-1 Training matrix developed for learning SPC.
75
3
3
1
1
2
3
David
Tkd
3
C
1
5.3 Standard Procedure to Edit SOPs
As the manufacturing processes become more advanced, existing SOPs will not help the
operators if those SOPs remain static; rather, the SOPs need to be updated with the current
manufacturing processes. To update these SOPs, a standardized procedure has to be followed to
avoid overwriting of SOPs and mixing of different SOPs, which would otherwise cause problems
in the production process. Some companies have a pre-determined procedure to edit SOPs based
on the quality organizations that they are affiliated to, while others need to develop an SOP on
editing the other SOPs. Operators have to be trained on editing SOPs, as they can bring great ideas
that will help in the quality control and improvement of the process.
5.4 Scenario After Implementation of SOPs
After training some of the operators on the SOPs developed here and monitoring their work,
results showed that they were doing a better job in producing conforming parts than before. The
results can be seen in Section 4.6 where the process was brought to a state of statistical control for
certain column tubes and high Cpk values were achieved. Also, operators did not have to offset
the tool or change the tool when it is not required, as the control charts showed them when they
had to execute these reaction plans. By creating a reasonable sampling plan, operators felt more
comfortable, as they did not have to do 100% inspection and they could rely on the tool to produce
good parts by measuring one in 20 parts. A complete change of scenario to what was seen at the
start of the project is seen at the end of our effort.
76
5.5 Feedback from Operators and Supervisors
Operators and supervisors are happy to see that there is a working SPC tool in the columns
cell which helps both of them in meeting the demand of customers and also maintaining high
quality standards. Operators are happy to see that they do not have to waste time in changing tools
when it is not required. Supervisors are pleased to see that the number of non-conforming parts
has reduced and the job of supervising the operators has become easier, as there is a tool in place
to monitor the operator's work.
77
Chapter 6: Conclusion, Future Work and Recommendations
The deliverable requested of us at the beginning of the project was to develop an SPC
methodology that is portable for Waters Corporation and that has been demonstrated by
implementing it in the columns cell. The above deliverables have been achieved: a booklet
containing an introduction to SPC, benefits of SPC, a training matrix, and standard operating
procedures for implementation of SPC has been presented to the company.
This chapter discusses gage evaluation, real time inspection, and defect rate reduction due
to application of control charts, potential annual savings, and future work for the company to
ensure the longevity of SPC in the machining center. It gives an overall perspective of results
achieved for the entire project. This chapter is written together with Zhang [7] and Zhu [8].
6.1 Gage Evaluation
By conducting the Gage R&R study, proper gages for the measurement of different
dimensions on a column tube are identified. Evaluation of gage capabilities and root cause analysis
for incapable gages have been conducted, with subsequent development of standardized
procedures for inspection using gages, and improvement in the capabilities of key gages.
Tolerances for certain dimensions are redesigned to ensure the validity of the SPC monitoring
system without using the optical comparator. Thus, inspection protocols and measurement systems
in the columns cell are made ready for SPC implementation.
6.2 Real Time Inspection
As noted in the problem statement section, one of the main purposes of this thesis project is
to introduce a real time inspection tool that is easy to use, and provides accurate data to monitor
78
the production process in the machining center. Experienced operators can apply the SPC
methodology to better control the production quality and newly hired operators can also learn how
to use this SPC methodology within a short period of time to achieve similar results as do
experienced operators.
Real time inspection means that once a part is inspected, the corresponding data appears
immediately in the control chart. With the control limits calculated from the initial setup, the
operators can view the data points with respect to the control limits and specification limits on the
screen. Western Electric rules [26] are integrated into the ProlinkTM software, so that a warning
when a data point indicates that a process has gone out of statistical control will automatically be
shown on the screen. Thus, the operator does not have to judge the stability of the process by
intuition. The operator's job becomes simpler by only having to enter the events and a possible
reaction plan into the software to help build the root cause analysis database.
Besides ease of operation, SPC helps new hires to have a standardized quality control
methodology that can be easily understood. Operator to operator variation is reduced, as every
operator follows the same SOP for inspection of parts and the use of control charts, thus helping
new hires make better decisions in the production process.
6.3 Defect Rate Reduction due to Application of Control Charts
From the analysis of historical data on previous failure modes in the manufacturing of
column tubes as shown in
Figure 1-10, it can be demonstrated that the top failure modes account
for 80% of scrap. The most frequent failure modes, as shown in Figure 1-10, are tool change,
threads, setup and tool wear, and all of these can be reduced by our implementation of SPC. Scrap
resulting from these failure modes can be reduced by approximately 60% or better by
79
implementation of SPC. Note that the 80% of scrap value is calculated from the failure mode
characteristic sheets for one specific column tube. As all the other families of column tube share
similar features, it is assumed that a similar percentage of the failure modes for the entire column
cell can be reduced by implementing SPC. As a result, the scrap rate can be projected to reduce by
50% annually.
Waters' customer satisfaction is its highest priority. By reducing the scrap rate, customer
orders can be met on time. This will increase customer loyalty to Waters Corporation, customer
base expansion, help beat the market competition, and bring other benefits that will help the
company's growth. Another benefit is reduction in tooling costs by not disposing of good tools
and changing tools only when required.
6.4 Potential Annual Savings
Different stakeholders have different opinions towards the value added by implementing
SPC. For the operators, ease of manufacturing and less setup time are helpful. While for the
engineers, lower scrap rate and higher production rate are valuable improvements. For the upper
management team, potential annual savings in dollars is the greatest value.
Due to the company's confidentiality policy, the dollar value relating to annual savings
cannot be disclosed. As discussed in Section 6.3, 80% of the failure modes can be addressed by
SPC, with 60% reduction in the scrap rate from these failure modes in the columns cell. Using the
same analysis for the entire machining center, a similar percentage of failure modes such as tool
change, tool wear, threads and initial setup that now appear throughout the machining center can
be reduced by implementing SPC. Thus, substantial annual savings can be achieved by the entire
machining center through adoption of the demonstrated SPC system.
80
6.5 Future Work and Recommendations
Given the time constraint, the SPC system was implemented for only several types of column
tubes. A number of opportunities have been identified to improve the process further. This section
describes recommendations for the company to consider in the future.
Firstly, a new database system should be established for better data management in the
future. At present, the method of storing data is inefficient. Data is collected and stored in a file
named with the part number of the column tube. Irrespective of which CNC machine performs the
machining processes, no matter if the dimension is on the main side or the sub side of the column
tube, the measurement results are stored in the same file in the same way, which means that data
cannot be separated into different sets for further analysis. This is a major issue because different
CNC machines have different inherent characteristics while producing the same column tubes.
And in the CNC machine, the main side of the column tube is machined by different tools in
different machining conditions compared to the sub side of the column tube. A new data structure
will help manage the data better and deliver more valuable information in the future for process
diagnosis and improvement.
A possible database structure is developed and shown in Figure 6-1. QCC is the central
database for the whole SPC system. SAP is the internal system the company uses to share data.
All of the automatic gages feed their data into the central database and the data is integrated. Below
the gage is the part structure. A gage can be used to measure column tubes, end fittings and other
parts. First, the parts are divided on the basis of family. Parts in the same family share similar
features and similar inspection protocols. Then there are different part numbers ("P/N"), and
different sides machined by different CNC machines. In this way, all of the data can be separated
in the future and then data management becomes an easier task.
81
QCC (SAP)
Gage: 3
Gage 2
G agel
0 End
n fitting
Column
a
Family 2 JLFamily 3
Family 1j
..
.
.
.Main
Machine 1
P/N 3
P/N 2
I
""P/N
Side
Machine
Sub
Side
...
.
..
EFE
Figure 6-1 Recommended database structure.
Secondly, it is recommended to implement the SPC system across the entire machining
center. As discussed in Section 6.4, there is a large potential for cost savings in the machining
center. It is practical to implement SPC throughout the entire machining center with the help of
the SPC methodology booklet that has been delivered to the company. With this portable SOP
documentation, quality engineers will find it easier to incorporate the SPC culture in the different
sections of the machining center.
Thirdly, a training program is recommended to help the operators understand the concept of
SPC and be able to utilize it as a powerful tool to assist their daily production. A training program
for the management level is helpful to foster a culture of better quality control.
Fourthly, data mining can provide potential opportunities for continuous process
improvement. Once the system is set up, a number of data points can be collected every day.
82
Beyond real time monitoring, this database can be used to identify failure modes and its
frequencies. This will lead to a continuous improvement of the process. An example that illustrates
this point is our analysis of data to identify that tool breakage was the main assignable cause for
producing defective threads. Further analysis might include a tool life study in particular, to
provide valuable insights to help indicate the proper time to change tools before they break.
Finally, regular maintenance is a vital part of the entire process. The SPC software needs to
be maintained and updated regularly to provide real time control charts that will help the operators
and the engineers. Data collected has to be regularly checked to ensure that data is not lost by other
factors. If a new part or process is introduced, an updated inspection protocol should be developed
for the continuous improvement of the manufacturing process.
83
References
[1] J. Arsenault and P. McDonald, Beginners Guide to Liquid Chromatography. Waters
Corporation, 2009.
[2] Waters.com, "How Does High Performance Liquid Chromatography Work?: Waters," 2015.
[Online]. Available: http://www.waters.com/waters/enUS/How-Does-High-PerformanceLiquid-Chromatography-Work%3F/nav.htm?ci d= 10049055&locale=enUS.
[3] Waters Corporation, Annual Report, 2014.
[4] M. Balogh, The Mass Spectrometry Primer. Waters Corporation, 2013.
[5] Mhhe.com, "Mass Spectrometry," 2015. [Online]. Available:
http://www.mhhe.com/physsci/chemistry/carey/student/olc/chl 3ms.html.
[6] Waters.com, "Quick Facts: Waters," 2015. [Online]. Available:
http://www.waters.com/waters/en_US/Quick-Facts/nav.htm?locale=enUS&cid=
134614709.
[Accessed: 14- Jul- 2015].
[7] S. Zhang, 2015, "Statistical Process Control (SPC) in a High Volume Machining Center:
Gage Repeatability and Reproducibility," M.Eng. Thesis, Massachusetts Institute of Technology,
Cambridge, MA.
[8] H. Zhu, 2015, "Statistical Process Control (SPC) in a High Volume Machining Center:
Importance of Control Charts," M.Eng. Thesis, Massachusetts Institute of Technology,
Cambridge, MA.
[9] G. Puszko, 2014, "Efficient Scheduling to Reduce Setup Times and Increase Utilization in a
Multiple-Part Manufacturing System," M.Eng. Thesis, Massachusetts Institute of Technology,
Cambridge, MA.
[10] Itl.nist.gov, "6.1.1. How did Statistical Quality Control Begin?" 2015. [Online]. Available:
http://www.itl.nist.gov/div898/handbook/pmc/section1/pmc11 .html.
[11] Asq.org, "ASQ: About: Walter A. Shewhart," 2015. [Online]. Available:
http://asq.org/about-asq/who-we-are/bioshewhart.html.
[12] D. Montgomery, Introduction to Statistical Quality Control, 6th ed. John Wiley & Sons,
Inc., 2009.
[13] Winspc.com, "Statistical Process Control Explained," 2015. [Online]. Available:
http://www.winspc.com/what-is-spc/statistical-process-control-explained.html.
[14] Asq.org, "ASQ: About: W. Edwards Deming," 2015. [Online]. Available:
http://asq.org/about-asq/who-we-are/bio-deming.html.
84
[15] Asq.org, "Statistical Quality Control Versus Statistical Process Control (SQC Versus SPC)
- ASQ," 2015. [Online]. Available: http://asq.org/learn-about-quality/statistical-processcontrol/overview/tutorial.html.
[16] Asq.org, "Control Chart - Statistical Process Control Charts IASQ," 2015. [Online].
Available: http://asq.org/learn-about-quality/data-collection-analysis-tools/overview/controlchart.html.
[17] P.W. John, "A Success Story in Statistical Process Control at Texas Instruments, Austin,
TX," 1989.
[18] F.W. Taylor, On the Art of Cutting Metals, American Society of Mechanical Engineers
1906, paragraph 700 and paragraph 718.
[19] V. Marinov, "Manufacturing processes", Kandhall Publishers, 2006.
[20] Cnccookbook.com, "Calculating and Minimizing Tool Deflection for CNC Milling," 2015.
[Online]. Available: http://www.cnccookbook.com/CCCNCMillFeedsSpeedsDeflect.html.
[21] S. Jayanti, D. Ren, E. Erickson, S. Usui, T. Marusich, K. Marusich and H. Elanvogan,
"Predictive Modeling for Tool Deflection and Part Distortion of Large Machined Components,"
Procedia CIRP, vol. 12, pp. 37-42, 2013.
[22] A. Gawande, The checklist manifesto. New York: Metropolitan Books, 2010.
[23] Fao.org, "2 STANDARD OPERATING PROCEDURES," 2015. [Online]. Available:
http://www.fao.org/docrep/w7295e/w7295e04.htm#sops.
[24] M. Moreno-Villanueva, M. Capri, N. Breusing, A. Siepelmeyer, F. Sevini, A. Ghezzo, A.
Craen, A. Hervonen, M. Hurme, C. Sch6n, T. Grune, C. Franceschi and A. Biirkle, "MARKAGE standard operating procedures (SOPs): A successful effort," Mechanisms of Ageing and
Development, 2015.
[25] Georgeproducts.com, "Oasis Elite Optical Profile Inspection System," 2015. [Online].
Available: http://www.georgeproducts.com/The-OASIS/.
[26] Western Electric Company, Inc., 1958, Statistical Quality Control Handbook, 2nd ed.,
Easton: Mack Printing Co.
85
Appendix
This appendix includes the training matrix and standard operating procedures that have been
delivered to the company as a booklet. Some information on the SOPs have either been erased or
blackened out due to company's confidentiality policy. The SOPs have been developed in
collaboration with Gabriel Kelly's work at the Machining Center.
86
Training Matrix
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,
-
GageR&R
Proficient
Name of Supervisor
In Train~
Signature
Moderate
Date
Needs Tra
The above training matrix is a document that needs to be used to ensure that the
employees are aware of the concepts required for the implementation of statistical
process control. As one can observe the above matrix makes it clear that a wide a
variety of people needs to be trained. It is important that the trainer not only has
knowledge on the concepts of SPC but also prior experience in its implementation. The
above matrix has 4 four bands of color to indicate one's progress in training. The tally
on the right hand side of the matrix is an indicator for the supervisor on the progress of
concepts learned by the employees. It is vital that the training be done three times a
year, initially, so that the employees don't lose grasp of the concepts taught at the
beginning of the year. Also, as the SOPs and process are updated, employees need to
be trained on them on a regular basis.
87
STANDARD OPERATING PROCEDURE: GAGE R&R
1. Purpose:
Gage R&R study determines the variability in measurements due to errors in
the measurement system. The errors could arise due to the operator, parts
being measured or the gage itself. The Gage R&R study forms a platform to
conduct the process capability analysis.
2. Scope:
This document is an instruction for the operator to conduct the Gage R&R study. By
following this document, one can identify the variations that causes the gage to give
different measurements for the same dimension. This will tell the operator if the
given measurement system is acceptable or not. The study has been conducted by
taking an example with column tube part number
3. Instruments:
Optical comparator, The OasisTm and the Johnson GageTM are the measurement
.
systems used for part number
4. Terms and Definitions:
Repeatability - measured variation resulting from equipment interactions with test
piece.
Reproducibility - measured variation resulting from operator interactions with
measurement equipment.
Interaction effects - the variation resulting from appraiser to appraiser
deviations in standard technique.
Appraiser- persons taking measurements, "operators" may be substituted
interchangeably.
Bias - the tendency for a gage to over or under read on a particular
measurement.
Linearity- the measurement of bias over the range of interest.
ANOVA- analysis of variance between groups.
Total Variation (TV) - It represents the variation due to the part, operator,
equipment and gage R&R.
Equipment Variation (EV) - It represents the repeatability of the
measurement device.
Appraiser Variation (AV) - It represents the reproducibility of the system.
Part Variation (PV) - It represents the variation of the parts used in the gage
study.
Gage R&R - It represents both the equipment variation and the appraiser
variation.
88
5. Procedure:
5.1 Identify the measurement systems that need to be studied.
5.2 Identify the product and the critical dimensions of the product that
need to be studied.
5.3 The study will consist of 10 parts, 3 appraisers who will each measure
the parts three
times each. The number of appraisers, parts and the
trials may vary across different industries but it is a common practice to
follow the above procedure.
5.4 The part samples that are used for the gage study should represent
the true variation of the production process i.e., part samples need to be
produced across the whole tolerance limit. This is done as Gage R&R is
the evaluation of the measurement system and not the part samples.
5.5 Ensure that the fixture and the measurement systems are clean
before the study is started.
5.6 It is vital that the operators share one calibrated gage or
measurement system.
5.7 The part samples should be measured in random order to eliminate
the variation that is caused in picking continuous parts to represent the
true variation of the process.
5.8 The data should be entered in software packages like MinitabT M or
Prolink
as it will automatically give the results. The procedure of
performing Gage R&R on MinitabT M is attached in the later part of this
study.
5.9 The total Gage R&R variation should be less than 10% for it to be
acceptable as this will mean that most of the variation is from the parts
and not from the measurement system.
5.10 It may be acceptable to have the total Gage R&R variation between
10% and 30% depending on the application of the parts and also the cost
benefits.
5.11 If the Gage R&R variation is greater than 30% then the
measurement system is not acceptable and the system needs to be
improved.
5.12 To better understand the above concept, read the below example
that will give a more in-depth explanation
TM
89
6. Procedure for the measuring the column tube ():
*The column drawing is shown at the end of this SOP
6.1.
Instrument- Comparator
6.1.1.The Comparator needs to be on a calibration system. During the Gage
R&R, study, the Comparator shall have a sticker firmly attached indicating
the system is within calibration.
6.1.2.The fixture of the comparator needs to be cleaned from any sort of
dust or other particles that might interfere in the measuring process.
6.1.3.The operator needs to place the main side (M-side which is side
opposite to the lot number) of the column in the fixture and loosely close
the fixture. Ensure that the object on the screen has a sharp image. This
is done by bringing the image to focus by rotating the handle that is
provided. It should also be ensured that the wrench flat on the left side
can be clearly viewed and is not obstructed by the fixture.
90
6.1.4.The M-side will be magnified on the screen and then the image is
brought to focus.
6.1.5.The starting point of the thread lead-in needs to be accurately located.
To ensure this happens, the column is rotated such that the first thread
just disappears on the screen and a sharp triangle like feature can be
observed on the screen. It will be observed that the face of the thread
changes from 30deg to 45deg.
6.1.6. The fixture is then tightened to ensure that the column does not
move.
6.1.7.It is to be noted again that a sharp image is viewed on the screen.
Then, move the upper edge of the column such that it overlaps with the
horizontal X-axis. Similarly, ensure that the left face of the column
overlaps the Y-axis. Set it as X=O and Y=O coordinates.
is measured. To
6.1.8.Firstly, the chamfer dimension of
measure this dimension, the glass screen is rotated in anticlockwise
direction to set it up at 45degrees crosshairs. Then the column is moved
to the left such that the chamfer comes in contact with the Y-axis (on
comparator). The X-axis reading is noted down from the electronic digital
screen that displays the output.
91
6.1.9.Secondly, the distance from the left face of the column to the thread
.The fixture is
lead-in is measured which has to fall within
moved to the right from the position of the above reading. The fixture is
moved till the edge of the first thread comes close to the Y-axis.
Then, the glass screen is rotated such that the X-axis becomes
6.1.10.
parallel to the edge. Move the fixture horizontally to the right to bring
them closer and see if they are parallel or not. If not, rotate the screen
until so. Move the fixture horizontally to overlap X-axis and the edge. The
X-axis reading is recorded down from the electronic digital screen that
displays the output.
Thirdly, the distance from the left face of the column to the right
6.1.11.
face of the thread relief is measured. The dimension has to lie within
. To measure this dimension, move the fixture horizontally to
the right and bring the face of the thread relief close to Y-axis. Rotate the
screen such that the X-axis becomes parallel to the right face of the
thread relief. Move the fixture horizontally to bring them closer and see
if they are parallel. If not, rotate the screen until so. Move the fixture
horizontally to overlap the X-axis and the edge. The X-axis reading is
noted down from the electronic digital screen that displays.the output.
92
.
Fourthly, the distance from the end of thread to the right face
6.1.12.
of the thread relief is being measured. Then the fixture is moved to place
the horizontal edge between the last thread and the thread relief in the
center of the screen. Ensure that a clear sharp image of the edge is
obtained.
Then the fixture is moved vertically to overlap with the
6.1.13.
horizontal edge and the center point. The parallelism of the column needs
to be checked. Move the fixture horizontally to check if the column is
parallel to the surface. If not, adjust the column until so. Move the fixture
horizontally to overlap X-axis with the right face of the thread relief.
Rotate the screen if necessary. From that position the XY axis is set to
zero.
is measured by moving the
The dimension of
6.1.14.
carriage to the left from the right face of the thread relief to the edge of
the last thread. Ensure that the X-axis overlaps the edge of last thread.
Rotate the screen when it's necessary. The X reading is noted down from
the electronic digital screen.
Lastly, the width of the wrench flat is measured. Loosen the
6.1.15.
fixture and then rotate the column to find the lowest point of the edge of
the wrench flat. Tighten the fixture. Adjust the focus of the image to get
a clear line of the horizontal edge of the wrench flat. Move the fixture
vertically and ensure that the center point of the screen lies on the edge.
Move the fixture horizontally to check if the column is placed horizontally.
If not, adjust the column until so.
Then, the fixture is moved horizontally to bring X-axis close to
6.1.16.
the right edge of the wrench flat. Rotate the screen to make X-axis and
the edge mentioned above parallel. Bring them closer and rotate the
screen a little bit to ensure the parallelism. Overlap Y-axis with the right
edge of the wrench flat. Set X and Y coordinates to be zero. Move the
fixture to the left and overlap X-axis with the left edge of the wrench flat.
Rotate the screen if necessary. Note down the reading in the electronic
digital screen. The dimension needs to be within
Having a sharp image on the screen is very important to
6.1.17.
eliminate errors in measurement. Ensure this through steps 3.1.7 to
3.1.15.
The column is taken out from the fixture and the sub-side(S6.1.18.
side) is placed in a similar manner in the fixture.
The same five dimensions are measured on the S-side by
6.1.19.
following the same procedure as for the M-side.
6.2.
Instrument-The OasisTM Inspection System
6.2.1.The Oasis T Inspection System needs to be on a calibration system.
M
93
During the Gage R&R study, the Oasis" system shall have a sticker firmly
attached indicating the system is within calibration.
6.2.2.Firstly, the designed fixture with V-block is placed on to the surface of
The Oasis TM . The M-side of the column is secured in with the help of the
hold down clamp mechanism. Initially, the clamp needs to be loosely fit
to ensure that the column can be rotated to ensure that it is perfectly
horizontal.
6.2.3.The software is opened and the program for the column in
consideration is opened. For this study, part number
is being
used.
6.2.4.It is very important to ensure that the column is horizontal to the
surface of The Oasis T . The guiderail beam fixture is used to ensure that
the wrench flats are parallel to the x-axis. The beam can be easily moved
up and down with the help of the guiderails.
6.2.5.The beam is raised up (as shown in the diagram) and brought above
the flat part of the column. It is then lowered down.
6.2.6. The column needs to rotate such that both the axis are perpendicular
to each other. The clamp can now be tightened.
M
6.2.7.The beam is raised up with the help of the guide rail and is taken out
from view of the OasisTM.
6.2.8.Immediately, the dimensions of the column, USL, LSL, Center limits
94
are shown on the monitor of the computer. The dimensions that are
measured by The Oasis Tm are
These values are captured and transferred to Prolink TM automatically by
clicking on the Data button.
6.2.9.As it can be seen in the picture beside that the dimensions are within
tolerance limits. This is shown by the green color. If it displays red color
then it means that the dimension is above tolerance, if it below tolerance
then it is denoted by blue color. If yellow color shows up then that means
the machine is not able to pick up the reading so the setup needs to be
adjusted or the wrong program has been opened.
A similar procedure is adopted for the S-side of the column as
6.2.10.
well.
6.3.
Instrument- The Johnson GageT M
6.3.1.The Johnson GageT m needs to be on a calibration system. During the
Gage R&R study, the Oasis TM system shall have a sticker firmly attached
indicating the system is within calibration.
6.3.2.Firstly, the Jonson Gage TM needs to be setup for the pitch diameter
that is going to be measured. For the current study with part number
screw (set gage) is used to calibrate and
, a standard
set up the machine.
6.3.3.The M-side of the column is first measured. The column is taken in
one hand and then slowly placed within the provided slot.
95
6.3.4.It has to be ensured that half of the thread column needs to be within
the grooves and the other half above it. It is then given a slight rotation
to ensure that the threads are well engaged.
6.3.5.The reading is noted down from the digital output screen.
6.3.6.It is to be kept in mind that this process needs to be done slowly so
as to not break the threads on the column and also to ensure better
measurement results.
6.3.7.This procedure is then followed for the S-side of the column.
7. Analysis:
After all the data has been collected, the values should be inputted onto MinitabT M
or ProlinkTM. Then the Analysis of Variance function is carried out on the data and
the results are interpreted. These results will help to point out the operator to
96
operator variation, gage to gage variation and also the part to part variation. By
knowing these values, the errors can be determined and rectified.
8. Note:
It is very important to produce the parts across the tolerance limits
8.1.
and measure accordingly.
If the data analysis shows bad results then the operators need to be
8.2.
trained on the SOP and gage R&R needs to be done again.
If the measuring method is very time consuming, for example, the
8.3.
comparator takes a long time to set-up and measure the parts while the
Oasis
TM
system measures the parts in a few seconds. If the dimensions that
are being measured on the comparator are not critical, then discuss with the
design team and relax the tolerance limits on those dimensions. The
instrument can be eliminated for future inspection protocols as it is time
consuming and tedious.
9. Procedure: (MinitabT M 16)
This method is based on ANOVA principles. This method is designed to
give the most accurate results by accounting for Operator by Part
interaction, whereas Xbar and R method does not.
9.1.1.Study assumes availability of a minimum of 20 parts, measured
twice, each by two operators. This is a "Crossed" ANOVA
(balanced)
9.1.2.For tests where it is impossible to measure the part more than once
(destructive testing), use a "Nested" ANOVA analysis option. This will
not be covered in this example.
9.1.3.For test that contain datum points that don't necessarily have two
measurements for each part use an Expanded ANOVA analysis option. This
approach is considered unbalanced and is not favorable. This will not be
covered in this example.
9.2. Select at least 20 sample parts.
Instruct operators in the collection of data. Both operators should
9.3.
consistently follow the same procedure when collecting the measurement
data. At no time should the measurement of an individual part be measured
in series. It is important that each measurement event is unique! Randomize
whenever possible.
Begin collecting data. A suggested table style is included in the appendix
9.4.
(8.1). Alternatively Minitab can design a Gage R&R study worksheet for
you.
After collecting a data set, import the data into MinitabT M (8.2, 8.3).
9.5.
Gage R&R studies are located as shown:
9.6.
9.1
TM
97
"
Worksheet 1
C1
Part
-.
8
9
10
11
1
2
3
4
5
6
7
8
9
10
11
41
12
1
2
3
4
5
6
7
C2
C3-T
measurement Operator
9 8390 op_1
9 8390 op_1
9 8395 op_1
9.8405 op_1
9,8395 op_1
9 8390 op_1
9-8400 op_1
9 8390 op_1
9 8390 op_1
9 8395 op_1
9-8390 op_1
Q R14
C4
nn I
Minitab - Untitled
File
Edit
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graph
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Window
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Regression
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ANOVA
120E
Control Charts
4111120
Welcome to Minitab,
DuOt
Chart..
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Reliability/Survival
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1
Time eries
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Individual Distributio n Identification...
jables
1
Johnson Transforma ion...
-
Nonparametrics
Capability Analysis
EDA
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Tolerance Intervals...
Type1 Gage Study...
create Gage R&R Study Worksheet...
Gage Run Chart...
Crtate Attribute Agreement Analysis Worksheet...
""X Attribute Agreement Analysis...
LIN
Acceptance Sampling by Attributes...
r76 Gage linearity and Bias Study...
Acceptance Sampling by Yariables
jai e R&R Study (Crossed)
Gage R&R Study (Nested)...
Multi-Vari Chart...
Gagg R&R Study (Expanded)..
Symmetry Plot..
Attribute Gage Study (Analytic Method)..
9.7. Use the following parameters. Fill out known information under the "Gage
Info" button and "Options" button. Leave all others default.
98
Gage R&R Study (Crossed)
C1
C2
Part
measurement
Part numbers:
Part
Operators:
Operator
Options...
measurementl
Conf Int...
Measurement data:
Gage Info...
Storage...
Method of Analysis
ANOVA
C Xbar and R
Can
Help
9.8. Results for this particular study:
Gage R&R (ANOVA) for measurement
Reported by:
Tolerance:
Gage name:
Dote of study:
Components of Vadbafon
too
-surement by Part
_
I
Reprod
-
GgeRM
1
Prt,4o#an
3
4
5
6
7
LOIt 121134 IS2*V15 1920
9
PMd
R Chart by Operator
kp
2
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op-2
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Past
op
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I
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op.2
o0_2
Part * Operator Interacton
1r,1 I
II
PP
99
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........
..
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....
..........
...
..
......
......
....
......
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............
........
....................
........
......
....................................................................
....
....................
...........
.. ....
...
Gag R&R
Contribution
(of VarComp)
5.45
4.51
0.94
0.94
94.55
100.00
VarComp
0.0000002
0.0000001
Reproducibility 0.0000000
0.0000000
Operator
0.0000026
Part-To-Part
Total Variation
0.0000030
Source
Total Gage R&R
Repeatability
Process tolerance - 0.02
StdDev (50)
0.0004017
0.0003453
RepeatabIlity
Reproducibility
0.0001671
0.0001671
Operator
0.0016737
Part-To-Part
Total Variation
0.0017212
Study Var
(4 * SD)
0.0024104
0.0021921
0.0010024
0.0010024
0.010042
0.010327
Number of
S
Source
Total Gage R&R
Distinct Categories
%Study Var
(OSV)
23.34
21.23
9.71
9.71
97.24
100.00
%Tolerauce
(SV/Toler)
12.05
10.96
5.01
5.01
50.21
51.64
Gage MR ftr menasuremen
10. Analysis:
10.1.
The default output includes % Contribution Table as well as a % Study
Table. The % Contribution Table contains normalized data that adds to 100%
and thus is convenient for a quick analysis of the variability induced by the gage.
The % Study variation table contains data with standard deviation expressed in
the same units as the process data. Thus allowing other information to be
gleaned such as % tolerance (if spec limits have been entered) and %process (if
historical standard deviation has been entered).
The total Gage R&R contribution in %Study Var %Tolerance Columns:
10.2.
10.2.1
Should be less than 10% to consider the measurement system
acceptable.
10.2.2
May be acceptable between 10% and 30% given specific application
and cost factors.
10.2.3
Is not acceptable exceeding 30% and considerations should
be made to improve the measurement system.
10.3
The total Gage R&R %Contribution Table:
10.3.1.
Should be less than 1% to consider the measurement system
acceptable.
10.3.2.
May be acceptable between 1% and 9% given specific application and
cost factors.
10.3.3.
Is not acceptable if it exceeds 9% and considerations should be
made to improve the measurement system.
100
11. Reaction Plan:
11.1. If it observed that the gage is not capable of measurement of the required
dimensions, then a root cause analysis has to be carried out to identify what went
wrong.
11.2. The common failure modes of Gage R&R study and their reaction plans are:
11.2.1. Variation due to fixture design- If the fixture design is causing
variation during measurement, then a new fixture needs to be
designed to eliminate this variation. It is to be kept in mind that to
have a successful Gage R&R study, most of the variation should only
come from the parts and all other variation needs to be eliminated
to evaluate the measurement system.
11.2.2. Variation due to operator- If the variation is occurring due to the
operator, then the operator needs retrained. If after retraining is
performed and the variation is still operator dependent then the
operator should be changed or the process of inspection be changed
to carry out a successful Gage R&R study.
11.2.3. Variation due to Environment- Environment plays a huge role while
conducting a Gage R&R study as the measurement system can
behave abruptly under different environmental conditions. A suitable
environment needs to be chosen as mentioned by the equipment
manufacturer.
11.2.4. Variation due to Equipment- If there is a variation occurring due to
the equipment then the equipment needs to be inspected.
Otherwise, the results of the Gage R&R study should be compared
with the results of the Gage R&R study conducted on a similar
machine (If the company has two similar machines of the same
manufacturer).By comparing the two results, the operators can get
an idea of the potential failure modes of the former machine.
101
Column drawing is removed due to the company's confidentiality
policy.
102
STANDARD OPERATING PROCEDURE: BASELINE DATA
COLLECTION
1. Purpose:
Baseline data collection helps the stake holders to have a solid foundation of data to
evaluate and compare it with different conditions and also observe the trend which will
help in identifying the bottlenecks.
2. Scope:
This document is an instruction to the operators on the steps that needs to be taken while
collecting baseline data. It also gives the operators guidelines to follow and potential
pitfalls while doing the operation.
3. Procedure:
3.1. Manufacture 1000 parts and arrange it accordingly in sequence.
3.2. A 100% inspection is carried out on these parts.
3.3. Ensure that the variability in operators is removed by having the same operator
measure the parts on the same machine.
3.4. It is vital to ensure that the parts have been arranged in the order of production.
3.5. The machine variation can be reduced by having all the parts manufactured on the
same machine.
3.6. Ensure to follow the same measuring procedure for all the parts according to the
standard operating procedure for measurement.
3.7. Do not discard bad parts as it will affect the whole procedure.
4.
Analysis:
After all the data has been inputted, plot a run chart to see if there is a trend in the
graph.
The trend in the graph will help give information on the variations during
production. This data can be used to determine the control limits and sampling plan for
later inspection.
103
STANDARD OPERATING PROCEDURE: SAMPLING PLAN
1. Purpose:
Sampling plan is determined to make the operator's life easier. By having the correct
sampling plan, 100% inspection is eliminated and the operator can check according
to the sampling plan to determine if the products are confirming to specification or
not.
2. Scope:
This document is for all machining operations personnel involved in creating,
maintaining and modifying sampling plans. The intent behind having a sampling plan
is to enhance the real time SPC inspection procedures and maintain high quality
standards.
3. Terms and Definitions:
Confidence level- Indicates the reliability of the estimate. Typically, 95% confidence
interval is used.
Sigma- Standard deviation
Type I error (Producer's risk) - Rejecting a lot with acceptable quality
Type II error (Consumer's risk) - Accepting a lot with unacceptable quality
Acceptable quality level (AQL) - It is a percent defective that is the baseline requirement
for the quality of the product
4. Procedure:
4.1
The sampling plan is determined after collection of baseline data. The
sampling plan can be chosen only after the process is stable.
4.2
While choosing a sampling plan, it should be kept in mind about the
feasibility of inspection by the operator.
The timeframe to measure the necessary dimensions on the various
4.3
measurement devices to prove that the part being produced is
acceptable should be measured.
4.4
From the run chart of the collected baseline data, trial and error method
should be used to determine the sampling plan.
4.5
If 1 out of 10 parts is the sampling plan that is chosen, then this
sampling plan should be applied on another order of data to ensure that
it is able to pick up the variations of the process.
4.6
If it not able to pick up the variations of the process, then a different
sampling plan needs to be chosen.
4.7
The process should then be run and the operators are asked to follow
the sampling plan that has been chosen.
4.8
This data should be analyzed and feedback from the operators noted to
check on the feasibility of the chosen sampling plan.
104
5. Analysis:
5.1 Sampling plans will vary across different processes and products
depending on the dimensions and measurement systems.
5.2 Sampling plans are critical to ensure high quality standards as if they are
chosen wrongly can create a lot of bad parts depending on the lot size.
105
STANDARD OPERATING PROCEDURE: CONTROL CHARTS
1. Purpose:
Control Chart is a graph that shows how the process varies with time. They show if the
process is in-control or out of control. A control chart consists of a center line for the
average, an upper line for the upper control limit, a lower line for the lower control limit.
These lines are obtained from historical data. By utilizing these control charts operators
can better monitor the quality of the process.
X-Chart I
i-er
cortro Lmit
99
go k
Carter**
We
Lower Cortrol Lkmit
.Pltted Poirts
84 86 88 90 92 94 96 98100 103 106 109 112 115 118 121 124 127
Poirt Labels
-
97
2. Scope:
This document provides an overview of control charts and the procedure that has to be
followed by the quality department in determining the control limits. The scope of this
document also extends to the operators to understand how the quality department sets
these control limits.
3. Terms and Definitions:
Subgroup Size - for a single point of data, the number of sample data collected. If the
number of "parts" collected for a study datum point is 10, then the subgroup size is 10.
If only one part is studied to collect the data for a point, the subgroup size is 1.
4. Procedure:
Choose an appropriate control chart for the data that is going to be
4.1
collected.
4.2 An appropriate time period has to be determined for collecting the data
and to plot it on graphs.
4.3
Before starting to collect the data, calculate the subgroup size of the
data to be collected. Then, collect the data accordingly.
4.4 Calculate the centerline and the control limits of the data and plot it on
the appropriate chart.
4.5 Analyze the data and look for out of control patterns or signals.
4.6 Mark these signals on the chart and perform a root cause analysis.
4.7 Document the investigation of the cause and how it was rectified.
106
5. Theory
5.1 Control Charts are used to monitor variation. These charts are used to
determine if a process is in a state of statistical control.
5.2
A control chart should be used when:
* Determining if a process is stable or not
* Observing patterns of process variation from assignable causes and
random causes.
* Controlling an ongoing process and rectifying the errors as they occur
* Predicting the expected range of outcomes
* Determining if the quality improvement project needs to aim at specific
problems or focus on fundamental changes to the process.
5.3
Subgroup size is critical in choosing an appropriate control chart to use.
Subgroup size should reflect how the data was collected. If the wrong type of
control chart is used, the chart may fail to exhibit sufficient sensitivity to detect
an out of control situation.
The following guidelines should be followed when selecting a control chart:
" For data collected one at a time, an I-MR chart should be used (subgroup
size of 1)
" For data with a subgroup greater than 1 and less than 10 Xbar-R control
charts should be used.
" For data with a subgroup size greater than 10 Xbar-S control charts
should be used.
5.4
5.5
5.6
For Xbar and S charting, the subgroup standard deviation is used to chart
range variability. The standard deviation contains the individual
measurements and is therefore more effective at detecting process spread
than a more traditional Xbar-R chart.
Generally Xbar and S charts are split into two distinct charts. The Xbar
component of this shows the mean of each subgroup and is used to analyze
the central location of the population in question given:
n
Where: x = mean
Xn= sample reading
n = number of samples
5.7 The S (standard deviation) component of the chart is composed of the
standard deviation of the entire subgroup measurement set given:
n-1
107
Where:
s = standard deviation
x = the observed values of
sample items x = mean of those
samples
n = sample size
5.8 For a given control chart a series of rules are used to interpret the results to
understand if the process is behaving in an unusual way. These rules indicate an "out of
control process".
5.8.1 One point is more than 3 standard deviations from the mean, indicating a
majorly out of control sample.
5.8.2 Nine or more consecutive points are on the same side of the mean, indicating
a systemic bias exists.
5.8.3 Six or more consecutive points are increasing or decreasing, indicating a trend.
5.8.4 Fourteen or more consecutive points alternative in direction, indicating
oscillation.
5.8.5 Two or three points in a row out of three are more than two standard deviations
from the mean in a similar direction, indicating a process that is medially out
of control.
5.8.6 Four or five points in a row out of five are more than one standard deviation
from the mean in a similar direction, indicating a process that has a high
tendency to be slightly out of control.
3
9
'13
%7
21
Sampgle
9
3
F
4
1
UL
'
Test performed with unequal sample sizes
5.8.7 Fifteen consecutive points in a row within one standard deviation of the mean;
this is highly unlikely behavior, control limits may need recalculation or subgroup
108
sampling reconsidered.
5.8.8 Eight points in a row with none within one standard deviation of the mean and
with points on both sides of the mean; this is also highly unlikely behavior and
subgroup stratification should be considered and investigated.
5.9
Example of Xbar- S chart
5.9.1 The above chart composed with MinitabT M Ver. 16.
5.9.2 The data above is composed of coating thickness of a DLC substrate on a
stainless steel face. These data were collected from multiple samples
contained within each shipping container.
5.9.3 The above data would indicate a process stability issue as highlighted by the red
dot data points, which violate condition 5.8.1, as they are more than 3 standard
deviations from the mean.
5.10 Example of Xbar- R chart
5.10.1 The following chart composed with MinitabT M Ver. 16.
Xbr-R Chart
34
2
1
5
34
6
7
B
9
Sam pit
LA
.1
DA
1
3
567B9
4
Tests performed with unequal sample sizes
The data above is composed of the coating thickness of a DLC substrate
5.10.2
on a stainless steel face. These data were collected from several locations
within the coating device and those locations used as the subgroup stratification
method.
109
The above data would indicate a process that is generally stable.
5.10.3
Subsequent rounds of testing may be used to further investigate the stability of
the process over time and would be a good measure of overall chamber
performance.
5.11 Example of I-MR chart
5.11.1 The following chart composed with MinitabT M Ver. 16.
I-MR Chart of
0.24
0.2W
0.01
0.01(
0.01
13
179132933
The data above is composed of a measurement of the outer
5.11.2
diameter of a gasket as it is sequentially punched from a die.
5.11.3
The above data would indicate a process that is not considered in
control. As highlighted by the red dot (rule 5.8.6).
6. Analysis and Reaction Plan
6.1 If the process is not stable then improve the process.
6.2 Control charts should not be used for unstable process.
6.3
Example of failure modes and reaction plan for threading tools in the
manufacture of columns:
6.3.1 Single Peak
110
Cause: This may be caused due to the chip on the threading insert.
Reaction Plan: Blow the chip away.
Cause: When the machine stops and the engine oil gets cold
Reaction: Monitor the machine until it warms up
Cause: Change of Operator
Reaction: None (Add in the reaction plan, if known)
6.3.2 Sudden Mean Shift (Up)
I'I,
Cause: Threading insert tool wear
Reaction Plan: Change insert
Cause: When the collar becomes loose
Reaction: Tighten the collar
6.3.3 Gradual Shift (Up)
Cause: When the tool wears
Reaction Plan: Do an offset.
Cause: When the threading insert is not aiming in the correct direction
Reaction: Adjust the insert accordingly.
111
Cause: When there is a material difference between bars
Reaction: None (Add in the reaction plan, if known)
6.3.4 Sudden Mean Shift (Down)
-- -
44 -
- - - - --
Cause: When the operator does an offset
Reaction Plan: None (Add in the reaction plan, if known)
Cause: When there is chip accumulation
Reaction: Clean the chips from the tool and ensure it is placed back
properly.
Cause: When the guide bushing is loose
Reaction: Tighten the guide busing
Cause: When the machine stops and the engine oil gets cold
Reaction Plan: Monitor the machine until it warms up
Cause: When the guide busing is too tight
Reaction: The guide bushing needs to be loosen up.
6.3.5 Small Slope Shift (Up)
Cause: This may be caused due to tool wear
Reaction Plan: Do an offset
112
STANDARD OPERATING PROCEDURE: PROCESS CAPABILITY
1. Purpose:
Process Capability is a measure of the output of a stable process to its specification
limits. There are different indices that are used to measure process capability and
are called process capability index (Cpk, Ppk).
2. Scope:
This document is an instruction for the operator to follow to conduct the Process
Capability study. This study will give an insight into the capability of the process as
sometimes the process can produce 100% of output within the specification limits and
otherwise not. It is important to conduct this study after the process is stable.
3. Terms and Definitions:
Cpk (Process Capability Index) - It is the ratio between permissible deviation,
measured from the mean value to the nearest specific limit of acceptability, and the
actual one-sided three times sigma spread of the process. Cpk of at least 1.33 is
desirable. Cpk accounts for variability within a subgroup.
Ppk (Process Performance Index) - It represents the overall variability. Ppk measures
both the part to part variability as well as shift and drift between them.
Cpm- It is the capability index that compares the width of the specification limits to
the spread of the process output and also incorporates an error term to determine
how far the center of the distribution is from the target.
Weibull distribution - A probability distribution function having the three parameters
of P (shape), ri (slope), and y (location).
DPMO - defects per million
PPM - Parts per million.
4. Procedure:
4.1
4.2
Make a note of the operating conditions that the study is being
conducted in.
Ensure that there is sufficient raw material available and choose an
operator to conduct the study.
Cp =
4.3
.i
USL -i 5
3a
- LSL
3a
The process capability study needs to be conducted only after the
measurement system is confirmed to be acceptable during the Gage
R&R analysis.
113
4.4
4.5
4.6
4.7
4.8
4.9
4.10
4.11
Run the process and start collecting data to ensure that the process is
stable.
If the process is not stable then conduct a root cause analysis and
resume the study only after stabilizing the process.
Collect as many data points as possible (minimum 100 points) to get a
better accuracy of the process capability.
Calculate the process mean and variation for the output.
Compare the process output to the specification limits by calculating Cpk
and other process capability indices as desired. Establish a plan for
continuous improvement.
Normally Ppk values are greater than Cpk values as there is less source
of variation in the process performance study compared to the process
capability study.
Industrial standards follow a Cpk value greater than 1.33.
It is always better to have higher Cpk value because:
SLess scrap
SImproved quality
SCustomer satisfaction
Cpk
Process Capability
0.33
0.67
68.27%
95.45%
1.00
1.33
99.73%
99.99%
1.67
2.00
99.9999%
99.999999998%
114
5. Procedure: (Minitab" 16)
5.1 This method assumes stable data, collected rigorously with appropriate
equipment. It may be necessary use control charting to evaluate the stability of
the process before assessing the process capability if you are unsure of the
stability. This may be existing data, or data that is procured for one subgroup.
5.2 Select one key parameter you wish to evaluate. In the example, overall column
length was selected as the key parameter. It is indicative of how well the machine
is performing and is also a critical performance characteristic of the product.
5.3 Collect the data. 30 samples is generally enough data for a sequential (Cpk)
evaluation, however a larger more complete sample size should be made for
establishing true "overall" process performance (Ppk).
TM
5.4 After collecting a data set, import the data into Minitab (8.2).
5.5 Capability studies are located as shown: We will select a non-normal distribution
type and Weibull fit distribution for this example. Previous distribution
identification study indicated that a Weibull model was the more accurate model
for this data.
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Mnitab,
Reliabiity/Surva
Multivarrate
Run Chart...
-
Time Series
Caust-and-Effect
individual Distribution Identification..
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Nonparametrics
EDA
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Acceptance Sampling by Attributes.
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(Nonnormat..
' " Multipte
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LL Jinomat
-
Worksheet...
Criate Attribute Agreement Analysis
X Attriblite Agreement Analysis.
Acceptance Sampling by yariables
Multi-Van Chart..
Symmetry Plot
5.6
Use the following parameters: Select the data in question as your single
column data set. You must also enter the upper and/or lower spec limits for
your measurement. Leave all other menu items default.
115
Capability Analysis (Nonnormal Distribution)
Data are arranged as
Estimate...
(Sine columrn: Length
r' Suboups across rows of:
Optionsr...
Storage ..
I
Fit distribution:
Wexbu
Lower spec:
9.83
Upper spec:
198
r
Bouidary
r
Boundary
OK
Cancel
5.7
Results for this particular study:
Process Capability of Length
Procesw Capability of Length
Calculations Based on Wesbull Distribution Model
an~ Cwat*W
1
PiCftS~ Da4ta
PO
H
Sam
PPu
Pok
Wan
Savf N
EXP. Ov'eral
1
PP TOW4
Observed P*tfomTWrV
PPM < L%
PPM > USL
PP14 loti
twfotmanite
PPM < LSL
PPM >USL
000
0.00
000
1
I
FT]-' F
F.-
9.831 9.834 9.837 9.840 9.843 9.846 9.849
6
a
6. Analysis:
6.1 An alternative analysis is included in the appendix (7.3) for discussion purposes.
This analysis is for a molded 0-ring with considerably tighter tolerances.
6.2 Graphically, it is obvious that this process is capable of producing this feature
(length) within the desire specifications. This process exceeds Six Sigma quality
specifications (index of 2.0).
116
6.3 Process capability indices are the ratio of the specification spread compared to the
process spread. In this way, a capability index of 1.0 indicates that the spreads
are the same. There may be a risk that process shift and drift could produce out of
specification parts. Any index ratio greater than 1 indicates a process that is
capable of shifting around, and still producing "good" parts.
Note: process index less than 1 indicates that the specification spread is less
than the process spread. It is likely that "bad" parts are being produced. The
expected population of bad parts in directly related to the low index number
and will increase your DPMO.A process capability index of 1.33 is the minimum acceptable process capability
6.4
specification.
6.5 A process capability index greater than 2.5 indicates a process that is being
produced with an unnecessarily high level of precision, and thus may be
unnecessarily expensive.
7. Appendix:
Weibull distribution function:
_
f (T) -
3
T___
7-7
f(T) > 0, T> 0 or,
7.2
e
-
-
7.1
> 0, 7> 0, -oo <y < oo
Screen Capture of Minitab TM input:
Worksheet I1
Cl
Length
117
1
2
3
98390
9-8390
98395
4
9.8405
5
6
98395
7
98400
8
9
10
11
2
13
9,8390
9 8390
9.8396
9.8390
98335
9 8395
14
9.8390
15
16
17
18
98390
9.8390
9.8390
9-8390
98390
19
9.8390
20
9.8350
C2
7.3 Process capability study. Process has very poor yield. Note: This was
modeled with a normal distribution.
Process Capability of
LSL
USL
Process Data
LSL
Target
ust
Mean
Sample N
StDev(Within)
StDev(Overall)
Overall
Cpk
A
Overall Capabiity
Pp
PPL
PPu
Ppk
(pm
'I.
11
I
0.1812 0.1824 0.1836 0.1848 0.18W6
L
Within
- --
Potential (Within) Capability
(p
Sample
Observed Performance
PPM < LSL
PPM > USL
PPM Total
-
Exp. Within Performance
PPM < LSL
PPM > USL
PPM Total
Exp.
PPM
PPM
PPM
I
0.1872 0.1884
Overall Performance
< LSL
> USL
Total
118
I
STANDARD OPERATING PROCEDURE: LONG-TERM
MONITORING
1. Purpose:
Long-term monitoring plays an important role in keeping SPC alive in a
company. The purpose is to incorporate the changes found during the initial
iterations and to maintain high quality standards.
2. Scope:
This document is for all personnel who are working in the implementation
and continuous monitoring of the SPC system. The scope also extends to the
upper management to keep a check on the SPC system.
3. Procedure:
3.1 The operators need to be trained on the standard operating
procedures that are implemented in the production floor.
3.2 On the next page, an example of a standard operating
procedure is shown that is used to conduct quality inspection
for column tubes.
3.3
By following this example, the reader will be enlightened on
the importance of having standard operating procedures for
inspection.
3.4 It is necessary to incorporate changes as and when required
with the permission of the concerned authority according to the
SOP that is devised in the department to change an existing
SOP.
3.5 Changes can only made if the process is monitored and
variations are observed with respect to the initial process.
3.6 The upper management should make routine checks to ensure
that the SPC system doesn't fail.
3.7 The supervisors on the shop floor should have meetings with
the operators to discuss on the SPC system on a day to day
basis.
3.8 Operators need to follow the standard operating procedures
and should be kept accountable for it.
3.9 There needs to be a designated person who can supervise only
the SPC system and clear any queries brought about it.
4. Result:
4.1 By following the above steps properly, the company can
experience great benefits.
119
4.2
4.3
4.4
Benefits like:
* Reduction of scrap
* Improvement in productivity
* Reduction in manufacturing cost
" Overall satisfaction of operators
* Customer satisfaction
* Increase in profits
The above benefits can only be achieved if there is a sense of
ownership and accountability laid down during the initial
phases of implementation.
SPC is not a one man's tool. It is a collaborative effort of the
whole company working together to inculcate the culture to
become a world class manufacturer.
120
STANDARD OPERATING PROCEDURE: COLUMN TUBE
INSPECTION
1. Purpose:
To create a standardized way to inspect column tubes and eliminate
variations occurring due to operators.
2. Scope:
This document is an instruction for the operator to inspect column tubes after
production in the columns cell. By following this document, the operator will be
able to detect variations immediately and correct them.
3. Instruments:
The OasisTM Inspection System, Johnson Gage T M , Profilometer,
Microscope,
Micrometers and GO/NOGO gage
4. Terms and Definitions:
Appraiser- persons taking measurements, "operators" may be
substituted interchangeably
Equipment Variation (EV) - It represents the repeatability of the
measurement device.
Appraiser Variation (AV) - It represents the reproducibility of the system
Part Variation (PV) - It represents the variation of the parts used in the
gage study.
5.
Note:
5.1. Before inspection, it is important to ensure that the operator
has followed the machine setup procedure and done it accordingly.
5.2. The machine setup procedure varies from cell to cell and needs
to be updated according to the job as the machines get moved
from one cell to another.
5.3. The operators have to follow a strict procedure of the location
of coolant pipes and not mess around with it every time there is a
change in shift.
5.4. The operators are advised to contact the supervisor if there is
any query before starting production.
5.5. Before starting the inspection procedure, ensure that all the
inspection measuring systems are calibrated.
121
6. Procedure:
6.1. Firstly, the operator will instruct the machine to produce only
one part and will check the part for its dimensions.
6.2. The operator will first check this part on the Oasis T inspection
system.
6.3. The part is loaded on to fixture that has been designed
especially for the OasisTM inspection system.
6.4. The software used is ProlinkTM.
6.5. The operator will ensure that the part is correctly fixed like
shown in the below diagrams.
M
6.6.
The operator then has to click on QC Calc-Real Time
Inspection TM software and a window like the below picture
will open.
122
6.7 If the part is within dimensions, then the operator should click on
the "DATA" button as shown in the above picture to capture the
dimensions. If not, generally, it is because the OasisTM system is not
able to capture the transition point on the edge of the wrench flats.
Reaction plan- clean the wrench flat reload the column onto the
fixture and measure it.
6.8 A window with different graphs that will contain the dimensions
and its specification limits will open up.
6.9 There are three types of colors that will be displayed in the above
page to denote if the part is within the specification limits or not:
* Green- the part is within specification limits
* Blue- the part is below specification limits
" Red- the part is above specification limits
" Yellow- the instrument is not able to capture the
dimension
6.10 If the part is out of specification limits, then the operator needs
to identify the cause of variation and correct it like an offset or a tool
change, etc. The operator has to look at the graphs that are
generated and do the offset accordingly.
6.11 After a good part is produced, the operator can go ahead to the
next inspection device, which is the Johnson Gage".
6.12 The Johnson Gage TM is primarily used to measure the pitch
diameter.
6.13 The column tube has to be placed correctly onto the grove and
then the value needs to be recorded.
123
6.14 The subside of the column (the side having the lot number) is
measured first and then the main side. Then click on "Finish" to record
the data points.
6.15 If the part is out of specification limits, then the operator needs
to produce a good part by doing the necessary offset according to the
graph that is shown on the screen. Offset is just one of the reaction
plans. The operator will perform the necessary reaction as per the
defect.
6.16 After a good part is produced, the operator will measure the
surface finish on the Profilometer. The column tube has to be fixed
properly as seen in the diagram.
6.17 If the surface finish is not as per the specification, then the
operator will change the feed rate accordingly. The surface finished
is not recorded by the ProlinkTM software.
6.18 After it has been assessed as a good part, the operator has to
take this part and views it under a microscope.
124
6.19 The operator has to check the engraving of the lot number and
also see that there are no scratches on the sealing face.
6.20 Once a part satisfies all the above measuring instruments, the
operator has to produce 9 more parts to plot the control limits.
6.21 After production of 9 parts, the operator will follow steps 6.5
to 6.7 again.
6.22 When the 10 data points have been captured by the Prolink'T M
software, control limits are plotted as shown in the below pictures.
125
6.23 Click on "Tools" and then "Calculate Limits". Control limits are
calculated based on the mean of the displayed data points and three
sigma limit standard deviation. Then click on "Save Calculated
Limits".
6.24 A similar procedure is adopted while measuring the pitch
diameter on the Johnson GageM.
6.25 A sampling plan has been created based on the baseline data
collection and also the feasibility of it being carried out by the
operators. Sampling plans differ according to the part number and
critical dimensions.
6.26 For example: if the sampling plan was to measure one out of
every 10 parts being produced, then the operator is required to do a
full inspection which means measure all the dimensions as
mentioned above on the various measurement systems.
6.27 The operator is also advised to carry out the quick inspection
system which uses different micrometers and GO/NOGO gages on
the fifth part to reduce the scrap if the tenth part being inspected is
defective.
6.28 The operator is asked to record the events on the software
when any change occurs like a tool change, offset, etc.
126
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"Assign Cause".
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is placed on the point, the assignable cause can be viewed. This
helps the operator, supervisor, etc. to debug the root cause and
eliminate it.
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record the various events and help in debugging.
6.33 Whenever the process goes out of control, the operator has to
assess the situation before taking any steps to correct it.
6.34 Based on the baseline data, the engineer should calculate the
process standard deviation and set a range for the acceptable
process mean value according to the calculation. When the process
mean drifts to the calculated limits, an offset is required. The
operator has to calculate the amount of offset according to the
current process mean. The offset has to bring the process mean
close its design nominal value with a certain amount of safety gap,
which will be different for different dimensions.
128
7. Result:
7.1 By following a stand inspecting procedure, the operator produces
less scrap and eliminates rejection of good parts.
7.2 When the operators are operating different machines, it becomes
easy for the operator to follow the instructions then for them to do it
intuitively.
129