Monitoring of Location Parameters with a Measurement Error under the Bayesian Approach Using Ranked-Based Sampling Designs with Applications in Industrial Engineering

To detect sustainable changes in the production processes, memory-type control charts are frequently utilized. This study is conducted to assess performance of Bayesian adaptive exponentially weighted moving average (AEWMA) chart using ranked set sampling schemes following two different loss functions presence a measurement error for posterior and predictive distributions conjugate priors. based on covariate model multiple methods (ME). The proposed Bayesian-AEWMA with ME has been evaluated through run length standard deviation length. Finally, real-life application semiconductor manufacturing was evaluate effectiveness schemes. results demonstrate that chart, error, performed well detecting out-of-control signals compared existing chart. However, median scheme (MRSS) proved be better than other error.