The part is the same. The operator is the same. Variation is simply a measure of how an operator can repeat the test on the same part. The source of the variation in this number is therefore the reproducibility of the test method – repeatability. It is a measure of the proximity of the operator to get the same result every time he measures the same part. Each set of tests for each part under each operator gives an additional estimate of repeatability. You should have similar parts – the idea of a batch described above – so that you can consider them as the same bar. It is a destructive test. When operator 1 executes both parts in lot 1, what are the sources of variation? Here too, it is the same operator. And we assume that Parts 1 and 2 are substantially identical. It is therefore the estimate of the repeatability of the test method.

It also contains variability within the batch. This applies to destructive testing, whether you use cross-referencing or nested R&R pledge design. In MSA studies for continuous measurements (e.g.B. weight, length, volume) by non-destructive testing, each part may be measured repeatedly. In this case, we may use cross-payment studies. However, sometimes we need to perform an MSA where the test needed for the measurement destroys the object or physically changes the property to be measured. Examples include shock testing and chemical analysis. Imagine frozen chickens thrown onto airplane windshields or testing the force needed to open a bag of potato chips. So what analysis do we use when the test is destructive? As with many of the questions that arise in statistics, the answer is, of course, “It all depends.” Aiden, I have the same problem. I have information about the destructive R&R and R attribute, but nothing that combines it.

Jim To perform an R&R measurement for a destructive measurement system, you need to make a critical assumption. You should assume that you are able to identify a batch of parts where the parts are so close to resembling each other that you can reasonably consider the parts in the batch to be “equal”. They think the lot is homogeneous. If you measure part of the lot for the same property, you will get the same result in the perfect world. Measurement Systems Analysis (MSA) is critical to the success of any data analysis. If you can`t rely on the tool you`re making measurements with, why should you bother collecting data first? It would be like trying to lose weight while relying on a scale that doesn`t work.