Smoothing versus repeated measurements
Smoothing versus repeated measurements
(OP)
hi folks
the problem is the following:
we collected many measurements under certain conditions and create a "golden signature reference". Subsequent parts results are compared to the golden for dispositioning. This golden can be generated after a curve fitting or by averaging all measurements. At this stage, metrology noise is not an issue. Customer "A" insists in multiple measurements and argue that fitting is not acceptable as we use a monotonic function (residuals after fitting are normal, which would indicate the model is adequate). Well, multiple measurements would be a burden on certain fabs and we would like to avoid that as much as possible.
If someone could help me with some ideas or different approaches, it will be very much appreaciated
the problem is the following:
we collected many measurements under certain conditions and create a "golden signature reference". Subsequent parts results are compared to the golden for dispositioning. This golden can be generated after a curve fitting or by averaging all measurements. At this stage, metrology noise is not an issue. Customer "A" insists in multiple measurements and argue that fitting is not acceptable as we use a monotonic function (residuals after fitting are normal, which would indicate the model is adequate). Well, multiple measurements would be a burden on certain fabs and we would like to avoid that as much as possible.
If someone could help me with some ideas or different approaches, it will be very much appreaciated





RE: Smoothing versus repeated measurements
Another way is to select some discrete points, make a set of calibration measurements at each point, make a statistics for each set and then compare a measurement of a tested item, mesured at the same independent variables values, to the previously done "golden signature reference statistics".
You do not need to make replications of your tested item, but results will be miserable and unreliable. Replications increase time consumption, money and reliability on the other side.
It is my impression that your customer does not know much about quality control or better, he (or she)is totaly ignorant. It may be a good idea to persuade him(her) to
build up a quality control relations together.
m777182
RE: Smoothing versus repeated measurements
RE: Smoothing versus repeated measurements
I did a fitting on my data usinga monotonic function and the residuals are normally distributed, mean ~ 0, constant sigma. So I assume that my function describes the data very well. Now a colleague did Principal Components Analysis and found bumps. Now, do we have other systematics or not?
RE: Smoothing versus repeated measurements
Your statement, "the residuals are normally distributed," begs lots of questions, because what you've written as apparent confirmation, "mean ~ 0, constant sigma," doesn't PROVE that your distribution is normal. It merely suggests that your distribution can be APPROXIMATED by a normal distribution.
TTFN
RE: Smoothing versus repeated measurements
Back to PCA: I have one variable and multiple data sets. Can I do a PCA in such situation? Does PCA requires we have more than one variable?
RE: Smoothing versus repeated measurements
m777182