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Building Control Charts to Identify and Eliminate Unnecessary Process Variation

Presented in English
Published on ‎05-15-2026 10:38 AM by Community Manager Community Manager | Updated on ‎08-05-2026 02:17 PM

Video using JMP 19 was posted in August 2026.

Control charts are useful to quantify the common-cause variation in a process and identify and eliminate special-cause variation. See how to interactively select and drag variables into zones where JMP automatically chooses an appropriate chart type based on the data and interactively  change the chart settings or create another chart type.

This webinar covers: Control Chart Builder, interactive charting options, using control limits, understanding when to use and how to interpret several types of control charts, process screening, process performance graph, and a view of control chart capabilities in JMP Live.

Suggested Prerequisites:

  • Understanding of process variation
  • Familiarity with using control limits

NOTE: The techniques in the video use semiconductor process data and are relevant to most industries.

Questions ansered by @MarilynWheatley and  @cweisbart  at the live webinar.

Q: How do I access and use Process Screening?
A: Analyze > Quality and Process > Process Screening. See below.

Q: How do I interpret the Process Performance Graph? What does the red line mean? And do I need to have Spec Limits to see it?
A:  When you look at the X and Y axis, you are looking at the PPK.  And when we're looking at the stability index, something to note here is there is no CPK, and that's where that red line comes. There are differences between the CPK and PPK. …CPK is using a within sigma value, while the PPK is using an overall sigma value. Yes, to get the process performance graph, must you have the spec limits, which are necessary to evaluate the performance against your needs/goals. See below.

Q: What is the difference between CPK and PPK?
A: CPK is Within Sigma and PPK Overall Sigma. See below.

Q: What is stability index?
A: It's the ratio of the overall sigma to the within sigma. If they are similar, the ratio is close to 1 and the process is stable. If there's a big difference, JMP flags that as an unstable process to look at.

Q: Is there anything in Process Screening that differentiates between normal vs non-normal distributions?
A: You could set the column property Distribution in the data table, and pick the distribution from the drop-down list before running process screening. That way when you run process screening and right-click to see the capability analysis you'll see the capability relative to the distribution you selected.

Resources:

 

 

 



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Start:
Fri, Jul 31, 2026 02:00 PM EDT
End:
Fri, Jul 31, 2026 03:00 PM EDT
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