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Cpk A Guide to Using Cpk 
a Process Capability Index 
LSL 
Cpk = Min [ U S L , ] _ X X _LSL 
3s 3s 
Specification Width 
Process Spread 
X USL
The following information is provided by the 
Technology Issues Committee of AMT – 
The Association For Manufacturing Technology 
to assist in the use and understanding of the 
Process Capability Index Cpk. 
Published by: 
AMT – The Association For Manufacturing Technology 
7901 Westpark Drive, McLean, VA 22102 
Printed in the United States of America 
Copyright © 2002 AMT – The Association For Manufacturing 
Technology all rights reserved. Permission to photocopy this 
material is granted provided credit is given to AMT. 
For ordering information, see the Publication section of the 
AMT Website at www.AMTonline.org or contact the AMT 
Information Resource Center (IRC) at 703-827-5220 or 
703-893-2900.
11/02-PS150 
7901 Westpark Drive, McLean, VA 22102-4206 
Phone 703-893-2900  Fax 703-893-1151 
AMT@AMTonline  www.AMTonline.org
A Guide to Using Cpk 
a Process Capability Index 
1 
Introduction 
The purpose of this guide is twofold. The first is to provide 
information on the process capability index Cpk. The second is 
to list various actions that can be taken or parameters checked 
in order to reduce process variation. 
The idea of comparing the specification of a part parameter to 
the measured variation or distribution of the process producing 
the parameter has been with us for many years. It has only 
been in recent years that the comparison has been given a for-mal 
name and a means of calculation. 
All authors and analysts writing on Cpk hasten to point out that 
the index is a statistic based on measurements and, like all such 
statistics, has an associated degree of uncertainty. However, 
most practitioners consider Cpk to be a fixed number without 
regard to the nature of the data that produced it. We will point 
out the uncertainty involved in any statement of Cpk. 
This guide assumes the reader has knowledge of control charts 
and methods for calculating standard deviations. A good refer-ence 
is the NIST/SEMATECH Handbook of Statistical Methods. 
The complete Handbook is on the Internet and may be accessed 
at www.itl.nist.gov/div898/handbook. 
What is Cpk? 
Cpk is a Process Capability Index. The term index is used 
because the value is a comparison or ratio. It is the ratio of the
workpiece specification or tolerance (allowed variation) com-pared 
to the process variation (produced variation) expressed in 
terms of ± 3 standard deviations. When standard deviation is 
used in a calculation, the assumption is that the underlying 
measurements form a normal distribution. 
Therefore, in the case of calculating Cpk, all known assignable 
causes for variation in the process should be minimized before 
measurements are taken that will be used in the final calcula-tion. 
In other words, the process should be stable and in statis-tical 
control. 
Some processes may use a positive stop or an in-process gage 
to produce part size. In those cases, the size distribution may 
not be normal, and the calculations described here will not be 
valid. Other sources should be consulted on how to deal with 
skewed distributions. 
In other cases, the specification is not bimodal nor is it given as 
a range. Examples might be “hardness at least – ” or “surface 
finish not to exceed –.” In those situations a Cpk cannot be cal-culated 
since the part specification is not stated as a range. Of 
course, the standard deviation for the process output can still be 
calculated, and an estimate made about the probability of stay-ing 
within the specification. But this is not a comparison such 
as Cpk. 
The importance of sample size in acquiring data cannot be over 
emphasized. As we shall see, the calculated value of Cpk 
depends on what is technically termed an “estimate” of the 
standard deviation. The larger the sample size, the more accu-rate 
is the estimate. 
2
Calculating Cpk 
Once data on the process has been gathered and analyzed, and 
the standard deviation calculated, a comparison to the product’s 
specification can be made. This simple comparison yields the 
process potential Cp. In some cases, the mean of the process is 
at the center of the product’s specification limit as shown in 
Figure 1. The term Cp assumes centering and should be equal 
to or greater than 1. 
Specification Width 
− 
Process Spread 
Specificat ion Pr s 
USL is the upper specification limit 
LSL is the lower specification limit 
X is the process mean 
Note: The symbol σ is used for standard deviation when very 
large samples are used that accurately represent the total popu-lation. 
In most cases, it is not feasible to use large samples, 
and the resultant standard deviation is represented by s. 
3 
= 
ocess USL LSL 
6 
Cp =
However, in most cases, the process will not be centered on the 
specification as shown in Figure 2. The actual process capabili-ty 
Cpk then becomes 
X Nearest Specificat ion Limit 
X Nearest Specification Limit 
USL X 
− 
X LSL 
In Figure 2, the nearest specification limit is USL. An 
inspection of Figure 2 will show that the first step in increasing 
Cpk should be to take action to align the center of the process 
spread with the center of the specification spread. This 
assumes that the two spreads are close to equal, or the process 
spread is actually less than the specification spread. 
4 
s 
3 
− 
s 
3 
− 
s 
3 
Cpk = 
This is usually stated as 
Cpk = Min [ , ] 
FIG. 2
Of course, if the process spread greatly exceeds the specifica-tion 
spread, steps must be taken to reduce the process spread. 
In Figure 2, Cpk would be about 0.5. However, if the process 
spread were aligned with the specification, Cpk would be about 
1.0. 
Putting Cpk in Perspective 
For the sake of simplicity, let’s assume that the process is cen-tered 
on the product specification. How many defective parts 
per million (parts out of tolerance) would we expect for differ-ent 
values of Cpk? Table 1 lists some values: 
Table 1: Expected number of defective parts 
for values of Cpk 
Cpk Parts per million defective 
1.00 2,700.0 
1.10 967.0 
1.20 318.0 
1.30 96.0 
1.40 26.0 
1.50 6.8 
1.60 1.6 
1.70 0.34 
1.80 0.06 
2.00 0.0018 
It should be noted that a Cpk of 2 equates to roughly two parts 
per billion defective! Such a number highlights the signifi-cance 
of sample size and the related issue of uncertainty associ-ated 
with the actual value of Cpk. 
5
Suppose we would like to start with a 90% confidence level 
that a calculated value of Cpk based on measured data is equal 
to or greater than a specified value. What value would we have 
to see based on various sample sizes? Table 2 provides some 
examples: 
Table 2: Required Test Cpk Values for 90% Confidence 
in Specified Value 
Specified Value for Cpk 
Sample 
Size 1.00 1.30 1.50 1.70 2.00 
200 1.08 1.40 1.61 1.82 2.14 
100 1.11 1.44 1.66 1.88 2.21 
50 1.17 1.51 1.74 1.97 2.31 
30 1.24 1.60 1.84 2.07 2.45 
10 1.50 1.93 2.22 2.52 2.95 
Most experts agree that the sample size should be at least 30. 
For derivation of how to calculate the values in Tables 1 and 2 
above, see the referenced NIST/SEMATECH Handbook (noted 
on page 1), section 7.1.4. 
Things to Remember About Cpk 
 Cpk is used to provide some expectation about the future 
capability of a process. However, the number calculated 
is based on a snapshot of the process at only one point 
in time. The calculated Cpk is only an estimate of how 
the process might be expected to perform. 
 The confidence level we can assign to the calculated 
value is a function of sample size. 
6
We should not lose sight of the fact that establishing process 
capability gives us a benchmark for improvement. Continuous 
improvement is the ultimate goal of making the measurements. 
Factors to Consider in Improving Cpk 
Measurement 
The key element in establishing Cpk with a customer is reach-ing 
agreement on the measurement method and gauges to be 
used. The condition of the measurement equipment, and gauge 
reproducibility and repeatability (RR) should be stated. In 
fact, for tight tolerances, the conditions used to determine RR 
should be stated – such as the number of appraisers and the 
number of repeat measurements. In order to be able to analyze 
data for events that happen during a test run, make sure that 
measurements are recorded chronologically. 
See Section 2.4 in the NIST/SEMATECH referenced Handbook 
for a complete discussion on gauge RR. 
Machine 
Thermal deformation is one of the greatest contributors to 
change in the output of a machine tool. All elements respond-ing 
to temperature change should be understood and monitored. 
Machine accuracy and repeatability should be determined using 
statistical techniques. Factors such as alignment, spindle 
runout and balance, and dynamic stability should be accessed 
with respect to the contribution to desired workpiece parame-ters. 
Machine maintenance is useful to restore parameters that have 
deteriorated and are contributing to variations. Company pro-cedures 
should be established for maintaining machine calibra-tion. 
7
Tooling 
Changes in tool condition are a common source of shift in 
workpiece size or surface finish. These changes can best be 
analyzed from a histogram of data taken chronologically. 
Changes are not limited to tool wear, but may also be created 
by dirt on the toolholder, a balance condition, or repeatability 
when changing inserts. 
Workholding 
The ability of the workholding device to position each part con-sistently 
is critical to maintaining uniform output. Tests should 
be made to determine the repeatability of workholding devices. 
The rigidity of the workholding device in relation to the rigidity 
of the workpiece and process-induced forces can also influence 
size variation. 
Workpiece 
Variations in workpiece initial stock conditions are a common 
source of output variation. Workpieces should be checked for 
incoming size and hardness. Both parameters cause changes in 
process forces. Cpk of incoming parts would be desirable. 
8

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Cpk guide 0211_tech1

  • 1. Cpk A Guide to Using Cpk a Process Capability Index LSL Cpk = Min [ U S L , ] _ X X _LSL 3s 3s Specification Width Process Spread X USL
  • 2. The following information is provided by the Technology Issues Committee of AMT – The Association For Manufacturing Technology to assist in the use and understanding of the Process Capability Index Cpk. Published by: AMT – The Association For Manufacturing Technology 7901 Westpark Drive, McLean, VA 22102 Printed in the United States of America Copyright © 2002 AMT – The Association For Manufacturing Technology all rights reserved. Permission to photocopy this material is granted provided credit is given to AMT. For ordering information, see the Publication section of the AMT Website at www.AMTonline.org or contact the AMT Information Resource Center (IRC) at 703-827-5220 or 703-893-2900.
  • 3. 11/02-PS150 7901 Westpark Drive, McLean, VA 22102-4206 Phone 703-893-2900 Fax 703-893-1151 AMT@AMTonline www.AMTonline.org
  • 4. A Guide to Using Cpk a Process Capability Index 1 Introduction The purpose of this guide is twofold. The first is to provide information on the process capability index Cpk. The second is to list various actions that can be taken or parameters checked in order to reduce process variation. The idea of comparing the specification of a part parameter to the measured variation or distribution of the process producing the parameter has been with us for many years. It has only been in recent years that the comparison has been given a for-mal name and a means of calculation. All authors and analysts writing on Cpk hasten to point out that the index is a statistic based on measurements and, like all such statistics, has an associated degree of uncertainty. However, most practitioners consider Cpk to be a fixed number without regard to the nature of the data that produced it. We will point out the uncertainty involved in any statement of Cpk. This guide assumes the reader has knowledge of control charts and methods for calculating standard deviations. A good refer-ence is the NIST/SEMATECH Handbook of Statistical Methods. The complete Handbook is on the Internet and may be accessed at www.itl.nist.gov/div898/handbook. What is Cpk? Cpk is a Process Capability Index. The term index is used because the value is a comparison or ratio. It is the ratio of the
  • 5. workpiece specification or tolerance (allowed variation) com-pared to the process variation (produced variation) expressed in terms of ± 3 standard deviations. When standard deviation is used in a calculation, the assumption is that the underlying measurements form a normal distribution. Therefore, in the case of calculating Cpk, all known assignable causes for variation in the process should be minimized before measurements are taken that will be used in the final calcula-tion. In other words, the process should be stable and in statis-tical control. Some processes may use a positive stop or an in-process gage to produce part size. In those cases, the size distribution may not be normal, and the calculations described here will not be valid. Other sources should be consulted on how to deal with skewed distributions. In other cases, the specification is not bimodal nor is it given as a range. Examples might be “hardness at least – ” or “surface finish not to exceed –.” In those situations a Cpk cannot be cal-culated since the part specification is not stated as a range. Of course, the standard deviation for the process output can still be calculated, and an estimate made about the probability of stay-ing within the specification. But this is not a comparison such as Cpk. The importance of sample size in acquiring data cannot be over emphasized. As we shall see, the calculated value of Cpk depends on what is technically termed an “estimate” of the standard deviation. The larger the sample size, the more accu-rate is the estimate. 2
  • 6. Calculating Cpk Once data on the process has been gathered and analyzed, and the standard deviation calculated, a comparison to the product’s specification can be made. This simple comparison yields the process potential Cp. In some cases, the mean of the process is at the center of the product’s specification limit as shown in Figure 1. The term Cp assumes centering and should be equal to or greater than 1. Specification Width − Process Spread Specificat ion Pr s USL is the upper specification limit LSL is the lower specification limit X is the process mean Note: The symbol σ is used for standard deviation when very large samples are used that accurately represent the total popu-lation. In most cases, it is not feasible to use large samples, and the resultant standard deviation is represented by s. 3 = ocess USL LSL 6 Cp =
  • 7. However, in most cases, the process will not be centered on the specification as shown in Figure 2. The actual process capabili-ty Cpk then becomes X Nearest Specificat ion Limit X Nearest Specification Limit USL X − X LSL In Figure 2, the nearest specification limit is USL. An inspection of Figure 2 will show that the first step in increasing Cpk should be to take action to align the center of the process spread with the center of the specification spread. This assumes that the two spreads are close to equal, or the process spread is actually less than the specification spread. 4 s 3 − s 3 − s 3 Cpk = This is usually stated as Cpk = Min [ , ] FIG. 2
  • 8. Of course, if the process spread greatly exceeds the specifica-tion spread, steps must be taken to reduce the process spread. In Figure 2, Cpk would be about 0.5. However, if the process spread were aligned with the specification, Cpk would be about 1.0. Putting Cpk in Perspective For the sake of simplicity, let’s assume that the process is cen-tered on the product specification. How many defective parts per million (parts out of tolerance) would we expect for differ-ent values of Cpk? Table 1 lists some values: Table 1: Expected number of defective parts for values of Cpk Cpk Parts per million defective 1.00 2,700.0 1.10 967.0 1.20 318.0 1.30 96.0 1.40 26.0 1.50 6.8 1.60 1.6 1.70 0.34 1.80 0.06 2.00 0.0018 It should be noted that a Cpk of 2 equates to roughly two parts per billion defective! Such a number highlights the signifi-cance of sample size and the related issue of uncertainty associ-ated with the actual value of Cpk. 5
  • 9. Suppose we would like to start with a 90% confidence level that a calculated value of Cpk based on measured data is equal to or greater than a specified value. What value would we have to see based on various sample sizes? Table 2 provides some examples: Table 2: Required Test Cpk Values for 90% Confidence in Specified Value Specified Value for Cpk Sample Size 1.00 1.30 1.50 1.70 2.00 200 1.08 1.40 1.61 1.82 2.14 100 1.11 1.44 1.66 1.88 2.21 50 1.17 1.51 1.74 1.97 2.31 30 1.24 1.60 1.84 2.07 2.45 10 1.50 1.93 2.22 2.52 2.95 Most experts agree that the sample size should be at least 30. For derivation of how to calculate the values in Tables 1 and 2 above, see the referenced NIST/SEMATECH Handbook (noted on page 1), section 7.1.4. Things to Remember About Cpk Cpk is used to provide some expectation about the future capability of a process. However, the number calculated is based on a snapshot of the process at only one point in time. The calculated Cpk is only an estimate of how the process might be expected to perform. The confidence level we can assign to the calculated value is a function of sample size. 6
  • 10. We should not lose sight of the fact that establishing process capability gives us a benchmark for improvement. Continuous improvement is the ultimate goal of making the measurements. Factors to Consider in Improving Cpk Measurement The key element in establishing Cpk with a customer is reach-ing agreement on the measurement method and gauges to be used. The condition of the measurement equipment, and gauge reproducibility and repeatability (RR) should be stated. In fact, for tight tolerances, the conditions used to determine RR should be stated – such as the number of appraisers and the number of repeat measurements. In order to be able to analyze data for events that happen during a test run, make sure that measurements are recorded chronologically. See Section 2.4 in the NIST/SEMATECH referenced Handbook for a complete discussion on gauge RR. Machine Thermal deformation is one of the greatest contributors to change in the output of a machine tool. All elements respond-ing to temperature change should be understood and monitored. Machine accuracy and repeatability should be determined using statistical techniques. Factors such as alignment, spindle runout and balance, and dynamic stability should be accessed with respect to the contribution to desired workpiece parame-ters. Machine maintenance is useful to restore parameters that have deteriorated and are contributing to variations. Company pro-cedures should be established for maintaining machine calibra-tion. 7
  • 11. Tooling Changes in tool condition are a common source of shift in workpiece size or surface finish. These changes can best be analyzed from a histogram of data taken chronologically. Changes are not limited to tool wear, but may also be created by dirt on the toolholder, a balance condition, or repeatability when changing inserts. Workholding The ability of the workholding device to position each part con-sistently is critical to maintaining uniform output. Tests should be made to determine the repeatability of workholding devices. The rigidity of the workholding device in relation to the rigidity of the workpiece and process-induced forces can also influence size variation. Workpiece Variations in workpiece initial stock conditions are a common source of output variation. Workpieces should be checked for incoming size and hardness. Both parameters cause changes in process forces. Cpk of incoming parts would be desirable. 8