Keywords: PPAP, benchmark, continual improvement, six sigma, minimum Cpk, Ppk, ISO-9000, QS-9000
Continuous improvement is a focal point of many quality standards including both ISO-9000 and QS-9000. The features described here can also serve to lock-in quality gains realized by Six Sigma projects. Establishing key statistical benchmarks can quantify quality gains and help maintain and enhance them over time, thereby fulfilling the continuing improvement requirements found in most quality standards. Just as importantly, key statistical benchmarks can be used as floors to prevent regressing below critical required levels and acting much like the AQLs (acceptable quality levels) of the past.
As an example of legal requirement for statistical benchmarks, automotive supplier sales cycle requires the supplier to initially submit documentation of compliance to Production Part Approval Process (PPAP – See AIAG PPAP Manual 3rd Edition, item I.1.2.2.9.1- I.2.2.9.4). In general, this process requires production sample parts to be run by the supplier through his production process (equivalent to 1-8 hours of processing, min. 300 pieces), and then a subset of samples are measured and analyzed (100+ consecutive pieces and could be more depending on the subgroup sample size required by the supplier’s control plan). If Cpk or Ppk values are high enough (1.67+), the supplier’s products may be considered for purchase in the future. As a condition of purchase, however, the supplier must warrant the Cpk or Ppk values of all future production parts supplied shall meet or exceed the Cpk or Ppk values certified in the original PPAP. The customer typically dictates whether Cpk or Ppk shall be used. We do not recommend using both statistics for PPAP validation. (Cpk should only be considered if process stability can be demonstrated).
Cpk and Ppk benchmark settings are available in software platforms registered with B5 in the registration code. To set global Cpk/Ppk benchmark values, select Setup/Preferences/Statistical Preferences from the DataLyzer® Spectrum main menu. To set Cpk/Ppk benchmarks by characteristic, open the desired characteristic, and select Preferences/Set Preferences.
Cpk and Ppk should be selected to appear in both control chart and Capability Histogram on the screen and in printed reports, but while useful, they are not necessary for the analysis. To make this setting in the control chart, open the settings window again and click the Control Chart Presentation tab. In the print options, select the capability indices you wish to display. For the histogram, click the Capability Presentation tab. Select the desired indices from the print options area. The Cpk calculation is not available for Inspection type characteristics.
DataLyzer® control charts default to use the last 25 subgroups for statistical analysis (including Cpk and Ppk).
The number of subgroups to be statistically analyzed can be changed for histograms. In the settings window, click the “Capability Calculations” tab. In the “number of subgroups to analyze” area, select the number of subgroups calculations should be based on. In order to meet requirements, this value must be set to match or exceed the number of subgroups to be collected for the PPAP Ppk or Cpk. If no changes are made, DataLyzer® will default to calculate based on the last 25 subgroups like the control chart, which may not be enough to analyze all the required data for smaller subgroup sizes.
The declared Cpk or Ppk values are used as reference in several areas:
The following graph is an example of a daily benchmark Ppk bar graph. The red line represents the benchmark Ppk value. The first bar on the graph (labeled “All”) represents the capability of the entire process.

The following graph is an example of a daily benchmark Ppk dot graph. The red line represents the benchmark Ppk value. The first bar on the graph (labeled “All”) represents the capability of the entire process.

Note: It is worth considering creation of a “PPAP” or “Benchmark” data group and create parts to be benchmarked or PPAPed in it. This way, the initial analysis can be done and maintained valid and “active” as long as you like. It can be easily excluded from the procedure of archiving SPC data by date, which would be done commonly to the rest of your in-process data.
Compliments of DataLyzer International, Inc.