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Jan 27, 2016 9:07 AM
(1336 views)

Hello. I was wondering best practices for proving tool to tool matching with many factors.

For instance I have 3 tools, 2 heads per tool (a left and a right). I want to match 4 conditions for 10 parts per condition measured 10 times each.

I would normally do a GRR if it only had 3 factors. Should I just do fit model and use the variance components as metrics?

Should I just do a separate GRR for each condition then compare them?

The information I'm really trying to glean from this is if the gauges match and are capable at each condition (to some spec).

In reality, the part isn't measured at the same spot for the repeats of the measurement as it is moving. And L&R won't line up exactly to the same spots either from tool to tool. I think I can just nest those but I don't know if another method is preferred.

I attached a mock table in case it's not clear what I'm asking.

Even just recommended reading would be appreciated.

Thanks,

Vince

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Solution

Vince: You may also want to take a look at Don Wheeler's EMP algorithm for analyzing data in this regard. I like Wheeler's method over the traditional Gage R & R approach primarily because there are many different graphical means by which Wheeler's method answers the various traditional questions around repeatability, resolution, reproducibility, interactions, etc. Here's a link in the JMP online documentation that illustrates the EMP approach as deployed in JMP:Measurement Systems Analysis

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Jan 27, 2016 2:27 PM
(924 views)

Vince,

You've got a couple of options here... First is just to use the components of variance analysis (under variability study). Another option with multiple matching criteria is to build a model in Fit Model with the conditions and see if any of them are significant at some level of alpha. If they aren't significant, then the tools are effectively matched.

Best,

M

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Jan 28, 2016 11:13 AM
(924 views)

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Jan 28, 2016 12:21 PM
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Jan 28, 2016 1:14 PM
(924 views)

I like it. That helps me get the information I'm looking for. Thanks for the help.