DOIONLINE 
DOIONLINE Publish In |
International Journal of Management and Applied Science (IJMAS)-IJMAS |
 Journal Home Volume Issue |
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Issue |
Volume-4,Issue-10 ( Oct, 2018 ) | |||||||||
Paper Title |
Testing Weibull Process Yield using The Markov Chain Monte Carlo Method | |||||||||
Author Name |
Mou-Yuan Liao | |||||||||
Affilition |
Department of Statistics and Informatics Science, Providence University, Taichung, Taiwan | |||||||||
Pages |
13-15 | |||||||||
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. | |||||||||
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