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Pinpointing Problem Sources in Complex Manufacturing Processes

gail_massari — Tue, 04 Nov 2025 17:30:44 GMT

Video using JMP 18 was posted in July 2025.

Do you have a complex manufacturing process with many steps and tools that could contribute to poor yield or reduced quality? Do you have historical data about your yields that is tedious or time consuming to analyze and understand? Are you tasked with applying your understanding of your tools and processes to improve future yields? Are you facing production delays with causes that are hard to pinpoint?

In this session, we will demonstrate how to use your process history to quickly locate the exact combination of factors leading to poor yield, production problems, or time-consuming product changeovers. See two examples of how to:

Explore and analyze production tracking data to identity factors that seem to be associated with poor yield.
Analyze the time that units spend waiting between steps or tools in the process and see how that waiting time is related to yield.
Analyze the effect on yield and pinpoint troublesome changeovers.
Identify the sources of differing or unexpected results among your production lines.
Interactively visualize your data to get a high-level understanding of process activity.

Suggested Prerequisites:

An understanding of the tools and steps in your complex processes.
Basic familiarity with Stepwise Regression.

Resources

Documentation for Process History Explorer

Re: Pinpointing Problem Sources in Complex Manufacturing Processes

Vball247 — Tue, 22 Jul 2025 16:56:16 GMT

Added to JMP Wish List some enhancement requests for Process History Explorer, based on this webinar.

https://community.jmp.com/t5/JMP-Wish-List/Process-History-Explorer-enhancements-of-automatically-adding/idi-p/888514#M7550

Re: Pinpointing Problem Sources in Complex Manufacturing Processes

gail_massari — Tue, 22 Jul 2025 17:16:29 GMT

Thank you @Vball247 !

Re: Pinpointing Problem Sources in Complex Manufacturing Processes

PatrickGiuliano — Tue, 29 Jul 2025 19:40:51 GMT

Hello Attendees and JMP user community members!

I'd like to follow-up to address some questions that were brought to bear during this webinar (held in July of 2025):

Someone asked what happens with a continuous variable instead of categorical for the outcome variable.
- The platform may support continuous variables, but the current implementation and examples are designed for categorical variables.
Can we look at standard deviation with this tool to address sources of variation? Is it not meant for that?
- Given the current design/ functionality of the platform, we suggest looking that the mean only for analysis.
What happens if there is only one data table? The documentation says we need 2 tables.
- The platform is explicitly designed to be used with two tables, as stated in our support documentation.

Additional requests for further examples and statistical details in our support documentation have been captured and passed on to our development team for consideration.

-JMP Technical Support