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.