Initial Process Study Cpk Worksheet for PPAP
PPAP asks for initial process study results on characteristics the customer designates, usually special characteristics. This worksheet keeps the summary in one table: enter mean, standard deviation and limits and it calculates the capability indices and flags anything below 1.67.
| Characteristic | LSL | USL | Mean | Std dev (sigma) | Upper index | Lower index | Cpk / Ppk | Meets 1.67 (1 = yes) | |
|---|---|---|---|---|---|---|---|---|---|
1.9444 | 1.9444 | 1.9444 | 1 | ||||||
1.3333 | 1.697 | 1.3333 | 0 | ||||||
1.28 | 1.3867 | 1.28 | 0 | ||||||
1.8571 | 1.9524 | 1.8571 | 1 |
Enter sigma from your study: use overall (long term) sigma for Ppk and within-subgroup sigma for Cpk. For one-sided limits such as surface finish, set the unused limit so it cannot limit the index, or ignore the unused column. Capability targets come from your customer, not from this page.
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How to use it
Collect data from a significant production run, commonly at least 25 subgroups and 100 readings, from the production process with production tooling. Compute mean and standard deviation in your SPC tool and enter them with the specification limits. The sheet calculates the upper and lower indices as (USL minus mean) over 3 sigma and (mean minus LSL) over 3 sigma. The lower of the two is the Cpk or Ppk value reported.
- Use readings in time order from one stable run
- Check the data is stable on a control chart first
- Use within-subgroup sigma for Cpk
- Use overall sigma for Ppk
Acceptance targets
The AIAG PPAP manual's common guidance is that an index of 1.67 or higher is acceptable, between 1.33 and 1.67 may be acceptable with customer agreement, and below 1.33 needs corrective action and a 100 percent inspection plan until capability improves. Your customer's specific requirements win, and some use 1.33 for Cpk and 1.67 for Ppk. The sheet flags against 1.67, so read results in light of your own agreement.
Reading the example
In the example the bore diameter has a mean close to the middle of a narrow tolerance and a small sigma, giving a high index. Length is centred in a wide band. Flange thickness has a lower index because sigma is larger relative to tolerance. Surface Ra is one-sided with the lower limit at zero, so the lower index here is not meaningful and the upper index drives the result. Replace all rows with your data.
Common mistakes
Calculating capability on unstable data, mixing multiple cavities or machines in one study, and using a gage that is not capable are the usual errors. Check measurement system variation first, because gage noise inflates sigma. For non-normal characteristics such as flatness or position, use a method suitable for the distribution agreed with your customer.
Frequently Asked Questions
What is the difference between Cpk and Ppk?
Cpk uses within-subgroup variation and describes potential capability when the process is stable. Ppk uses overall variation including shifts and drift, so it describes actual performance in the study. Ppk is usually used for initial studies.
Why does my one-sided characteristic show a strange lower index?
Features like surface roughness have only an upper limit. The lower index uses an LSL of zero here, which is not a real requirement, so report only the upper index for these characteristics.
How many parts do I need?
A common PPAP expectation is at least 100 consecutive parts from a significant production run, but your customer may require more or use subgroup data. Follow the customer-specific requirement.
Can this replace my SPC software?
No. It summarises results you already calculated. Use SPC software for charts, normality tests and subgroup calculations, then use this sheet as a clean summary for the PPAP file.
If your measurement data sits in an MES or an ERP inspection module, Netray can help build a read-only summary of capability by characteristic.
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