Markov chain Monte Carlo in Bayesian models for testing gamma and lognormal S-type process qualities

作者：Liao Mou Yuan^*

来源：International Journal of Production Research, 2016, 54(24): 7491-7503.

DOI：10.1080/00207543.2016.1198055

• Bayesian
• Markov chain Monte Carlo
• process capability
• quality control

The process capability index C-pu is widely used to measure S-type process quality. Many researchers have presented adaptive techniques for assessing the true C-pu assuming normality. However, the quality characteristic is often abnormal, and the derived techniques based on the normality assumption could mislead the manager into making uninformed decisions. Therefore, this study provides an alternative method for assessing C-pu of non-normal processes. The Markov chain Monte Carlo, an emerging popular statistical tool, is integrated into Bayesian models to seek the empirical posterior distributions of specific gamma and lognormal parameters. Afterwards, the lower credible interval bound of C-pu can be derived for testing the non-normal process quality. Simulations show that the proposed method is adaptive and has good performance in terms of coverage probability.

• 出版日期2016