I absolutely agree that the process should be stable so you dont fool your self.
What I am trying to achieve are to have a general internal SOP (Standard Operation Procedure) to estimate a process capability for a given process. The scope is that it shall be written to use additional no software (than perhaps Excel or equal) an be able to used of persons with almost no or little experience of statistics. It shall also provide recommended sample sizes in order for what they try to achieve.
My basic idea are to use estimates of CI for the indexes based on sample size using a target for 1,33 or 1,66 and what you can allow in CI lower to determine the sample size.
As you mention in your book Implementing SixSigma-Smarter Solutions using statistical methods (standing firm on my bookshelf, in a true 5S sprit as an easy tool to reach) Ch 11 Process capability and process performance metrics about Cp and Pp indexes that how to form the sampling criteria are crucial (Ch 11.23 page 297).
My initial thoughts are in the first step break down the metric in focus to plausible things that can have an effect using CTQ breakdown, Ishikawa diagram and/or other tools and from that score top xs.
From that make a sample plan that takes in consideration the xs of (estimated) significance.
Say for a example raw material are assumed to be a critical x. Sampling should be done over # lots of material calculating Cpk for etch lot. After all samples are done calculate Ppk and compare Cpk and Ppk.
If they all checks out as normal (all Cpk and Ppk) with a reasonable difference and Ppk checks out to given limit the process gets go ahead.
In case non normal data or to large shift in process the analysis are taken to the next level using transformations, non normal distributions, lurking factors etc (not included in this SOP)
I dont know how big pitfalls there is in the approach (glad for comments) but it sure is a struggle (and a challenge) to write a SOP in laymans terms on this topic. =)
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