How to choose Samples for a Gage R&R (GR&R) study

#21
Hi, I think the question is simple: Why 3 op x 10 p x 2 or 3 trials statistically-wise? I cannot find an answer in the entire internet hitherto.
 
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Miner

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#22
I would be very surprised had you been able to do so. There are many statistical flaws with the approach, specifically the use of non-additive standard deviations in the calculation of the metrics (i.e., %SV, %Tol) instead of variances. This results in an overly conservative method that makes up for possible shortcomings in sample size by rejecting potentially good gages and never accepting bad gages. If you want a statistically sound approach, see Dr. Wheeler's An Honest Gauge R&R Study.
 

Bev D

Heretical Statistician
Staff member
Super Moderator
#23
Miner has hit on the dilemma: the "common" (AIAG) approach is 'accepted' by almost every auditor because it has been codified in the quality standards for many industries. It is so accepted - without critical thought - that the use of a statistically valid approach often results in a lot of grief from QA groups, Customer's SQEs and auditors simply because it's different.
 
#24
Thank you! This is for sure a great plus on the help to find that magic (but still unwritten) sentence that explains in simple words why 3 op x 10 p x 2 or 3 trials.
 

Bev D

Heretical Statistician
Staff member
Super Moderator
#25
Perhaps I am misinterpreting what you are saying? there is no statement that can justify the 3X10X3 'popular' approach; it is not statistically - or mathematically justifiable. (If there is a 'magic' statement it's going to be black magic).

In addition to the article from Dr. Wheeler, you might my critique of the popular approach (along with an alternative approach) and further references valuable. You can find my paper on MSA in the resources section of this site.
 

Jim Wynne

Staff member
Admin
#26
Thank you! This is for sure a great plus on the help to find that magic (but still unwritten) sentence that explains in simple words why 3 op x 10 p x 2 or 3 trials.
To put it simply, you're looking for a logical and statistically sound justification when none exists.
 
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