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Jun 19, 2017 7:59 PM
(763 views)

Hi All,

I am planning to evaluate a new process which is supposed have a better defectivity performance (semiconductor industry). The question that I have is lets say that my process failure is not repeatable during a certain runs of experiment. For example in my 100 wafers run, i have observed that the failure happens on the 20th and 50th wafer run. A repeat on another 100 wafers run the failure happen on the 10th, 31st and 70th wafers. In this situation how do I design my experiment in order to determine whether my new process does indeed improves the defectivity of my baseline process

Hope someone is able to help me on this

Rgrds

Irfan

8 REPLIES

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Jun 20, 2017 1:12 AM
(745 views)

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Jun 20, 2017 1:25 AM
(737 views)

Are you able to direct me to the analysis option in JMP that is able to perform this cumulative probabillity?

Rgrds

Irfan

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Jun 20, 2017 4:54 AM
(727 views)

You can find the Kaplan-Meier reference in

Help==Statistics Index

Jim

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Jun 20, 2017 7:07 AM
(719 views)

Create, and open in JMP data file with columns (name):

Time: just a sequence of numbers from 1 to 100

Censor: with code 0 and 1 (failure "YES" – 0 (sic!), failure "NO" - 1)

Grouping: with code 1, 2 etc (comparison groups)

Then:

Analyze->Reliability and Survival->Survival

and activate (tick): "Plot Failure Instead of Survival"

Sorry for brevity (because of my weak English) :)

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Jun 21, 2017 12:11 AM
(691 views)

Hi Med,

Here is the data that I have

Able to explain to me the explanation of the numbers shown from the analysis above

Rgrds

Irfan

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Jun 21, 2017 11:44 AM
(674 views)

a process that has better defectivity performance has a lower curve.

Also need to consider (but not fetishization) p-value. But all this applies

to the theory of statistics.

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Jun 21, 2017 6:39 PM
(651 views)

Hi Med,

Able to share with me what does the number stands for, is the alpha also set at 0.05?which means in this case we are not able to reject the null hypothesis that the two groups are the same?

Rgrds

Irfan

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Jun 22, 2017 12:26 AM
(628 views)