Determining Sample Size for FDA Verification and Validation Activities

Bev D

Heretical Statistician
Staff member
Super Moderator
#41
Oh it make sense to me...but when you have an attribute characteristic, Option 1 is not viable. I agree if comparing levels or vendors during OQ then c=0 is inappropriate. So how do you determine a sample size for a PQ when I am testing if a product can withstand a certain pressure for 30 seconds. The test is basically to apply a fixed pressure to the device for 30 seconds. If it does not break it passes. We have very few if any parts that fail. So my only recourse is a c=0 plan, but if I understand you correctly there might be a better way of generating a sample size. Any help would be appreciated.
For PQ (as stated in 3. in my response) a c=0 plan is OK as PQ is a 'dress rehearsal' - if you will - of standard production prior to launch and release. The goal is to determine if the process will produce X number of sequential lots that met the quality/release criteria - that is what acceptance sampling plans are intended to do.


for validation in general, when faced with an acceptance test on a characteristic that rarely fails I tend towards some type of directed testing(test to failure, accelerated or worst case testing) for comparisons.



==========
my other issue is simply that c=0 plans were a deluded attempt to avoid the appearance accepting lots that knowingly had defects in them. c=0 plans don't guarantee or imply that the lot is defect free; which is what some people want to believe. c=0 plans have fairly flat OC curves leaving a lot of gray area between acceptable and unacceptable defect rates. If the plan is RQL based, the protection can be pretty decent but if the plan is AQL based it is quite deceptive. Acceptance sampling plans that use both an AQL and RQL have much steeper OC curves but have larger sample sizes and they often allow for one or more defects in the sample...
 
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Jojo63

#42
Hi,

I search some information on sample size to validate the functionality of a product. I read the previous posts and I concluded.

I use the simplest formula for a 99% confidence interval.

I perform a first statement of 30 measures and the results are : average 17.4 N.m and standard deviation : 1.3. I want a accuracy of 0.5. My real average not deviate more than 0.5 from my calculated average.

So I get a sample n=45. Is it correct?

Thanks you for your feedback.
 
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