The design of Bayesian generalized likelihood ratio control chart for monitoring the normal process mean

摘要

This paper develops a Bayesian generalized likelihood ratio (BGLR) control chart to monitor the mean of a normally distributed process. The proposed chart statistic is based on the maximum a posteriori estimator and moving window of past observations. Simulation scheme is used to evaluate the performance of this chart for different window sizes, and the best window size according to the sample size is provided. Furthermore, the performance of BGLR control chart is compared with the Bayesian cumulative sum (BCUSUM) control chart and a combination of two BCUSUM charts (2BCUSUM) in terms of the steady-state average time to signal (SSATS). Simulation results show that the overall performance of the BGLR chart is better than its competitors.