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Apr 21, 2015 9:48 AM
(700 views)

I am such a novice in JMP and statistics. I have basic questions for experts here.

The data I have is product dimension. I have ‘min’ dimension data, and ‘max’ dimension data around 30 points for each. And with these data, I need to propose to team min and max dimension specification.

In JMP11, I used Analyze>Distrubution and found most of the data are slightly skewed, and there are some with a few outlier points. I checked continuous fit – normal – fitted normal - goodness of fit: which shows Prob<W less than 0.05.

Traditionally I was told that we just take mean/average then +- 3 STDEV, which I don’t find it appropriate in this case.

If I could be pointed out proper analysis of my data, and how I should be setting specification, or JMP article I should read, I would appreciate very much.

Thank you,

Nan

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Apr 21, 2015 12:51 PM
(534 views)

Nan, an alternate approach is to use the data to create a control chart for each potential specification item. The published specification [e.g. to an internal or external customer] is then based on +/- 3 Sigma [Hence 6 Sigma quality].

Update the chart as new data becomes available and use the charts to not only set specifications but to, more significantly, control the process.

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Apr 22, 2015 9:51 AM
(534 views)

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Apr 21, 2015 1:24 PM
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Apr 22, 2015 9:52 AM
(534 views)

Thank you very much for your suggestion Karen. And the e-Handbook looks very useful.