Why Your JMP Cpk Calculations Might Be Wrong
Did you know that JMP’s default method for calculating Cpk on non-normal data can lead to inconsistent engineering decisions?
In this video, we dive deep into the two main methods for generalizing capability indices to non-normal distributions: the ISO Percentiles method and the Z-Score method. I'll explain why JMP defaults to the Percentile method, the math behind it, and why switching to the Z-Score method provides a much more consistent relationship between your Cpk value and actual process non-conformance metrics.
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⏱️ Timestamps / Chapters:
00:00 - Intro: Normal vs. Non-Normal Process Capability
00:50 - JMP’s Default: Percentile Method
02:10 - The Formula and Effective Width (W)
03:25 - Replicating JMP's Percentile Calculation
04:36 - The Problem with the Percentile Method
05:15 - Inconsistent Non-Conformance Rates
06:46 - The Solution: Z-Score Method in JMP
07:58 - Key Takeaways for Engineers
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