Paper Title
Testing Weibull Process Yield using The Markov Chain Monte Carlo Method
Abstract
Process capability index pk C is a popular index used to make managerial decisions on quality assurance because
it provides bounds on the process yield of a normally distributed process. However, the normality assumption is often invalid,
so it has become challenging for quality managers to accurately assess pk C values. In this study, we provide an alternative
method for assessing the pk C value of a non-normal process. The Markov chain Monte Carlo method was integrated into a
Bayesian model and adapted to determine the empirical posterior distributions of pk C and thereby obtain the credible
intervals for testing pk C .
Keywords - Bayesian; Markov chain Monte Carlo; Process capability.