Accounting for Variability on High Side of Specification

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pmccain47

#1
Hello All,

I have a statistics question that I was hoping someone might have some insight into. For one of our design criteria (pull force) we have a minimum pull force of 1.12 lbf. In design verification, we typically perform a 95% confidence/99% reliability analysis to demonstrate that the lower bound is above our minimum specification.

Usually we have no issues with that, but in a data set we are analyzing, we have a relatively consistent mean of ~2.5 lbf, but two samples that pulled significantly above that (3.3 lbf and 3.5 lbf). There is no max spec, the higher the pull force the better. But this variation to the high side increases the standard deviation significantly and causes our lower bound to fall at 1.05, which is below the min spec.

If the samples are excluded, the LTL is ~2.0 which would meet our acceptance criteria. There is no immediately assignable special cause for the variation, the units look identical to the ones that were closer to the mean. Are there any other strategies to account for variation above the mean of a one sided spec?

Thanks for any help or thoughts!

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#2
Hello All,

I have a statistics question that I was hoping someone might have some insight into. For one of our design criteria (pull force) we have a minimum pull force of 1.12 lbf. In design verification, we typically perform a 95% confidence/99% reliability analysis to demonstrate that the lower bound is above our minimum specification.

Usually we have no issues with that, but in a data set we are analyzing, we have a relatively consistent mean of ~2.5 lbf, but two samples that pulled significantly above that (3.3 lbf and 3.5 lbf). There is no max spec, the higher the pull force the better. But this variation to the high side increases the standard deviation significantly and causes our lower bound to fall at 1.05, which is below the min spec.

If the samples are excluded, the LTL is ~2.0 which would meet our acceptance criteria. There is no immediately assignable special cause for the variation, the units look identical to the ones that were closer to the mean. Are there any other strategies to account for variation above the mean of a one sided spec?

Thanks for any help or thoughts!

Please - SCAN the attachment for viruses or whatever.
.
i think your assessment on ' assignable special cause' is right step; further,
* is there a dependent parameter/attribute which gets affected because of higher pull force?;
* is there a possibility of the 'some' un/assignable special cause to bring the the pull force to the lower side?
* is the probable cause (correlation) (beyond the 'identical' observation noted) with the process parameters, material attributes?
* is the instrument/method validated?
* did we perform further samples to explore similar phenomenon?

I do not have direct-experience with devices per say...but here are :2cents: from a generic/logical approach...

....as we are in design verification stage, its appropriate to put reasonable efforts in establishing the source of variation; atleast an action point & timeframe to resolve same...moving ahead purely depends on the 'criticality' of the parameter; and its affect on the functionality/acceptability with the customer!
 
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