Assessing Production Quality with Nonstandard Measurement Errors

Abstract

We consider the assessment of a manufacturing process's performance when a sample of parts produced by the process is measured with error. When the measurement error variance depends on the true characteristic of the part being measured, nonstandard variance components models are needed. We consider a Bayesian approach, showing how this methodology can be used to calculate tolerance intervals for the part distribution to assess the manufacturing process's performance and to determine other important quantities such as release specifications. In addition, we show how to handle censored data.

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