Maximum Chi-Square Generally Weighted Moving Average Control Chart for Monitoring Process Mean and Variability

Abstract

Abstract In this article, we propose a new control chart called the maximum chi-square generally weighted moving average (MCSGWMA) control chart. This control chart can effectively combine two generally weighted moving average (GWMA) control charts into a single one and can detect both increases as well as decreases in the process mean and/or variability simultaneously. The average run length (ARL) characteristics of the MCSGWMA and maximum exponentially weighted moving average (MaxEWMA) charts are evaluated by performing computer simulations. The comparison of the ARLs shows that the MCSGWMA control chart performs better than the MaxEWMA control chart. Keywords: ARLGWMA control chartMaxEWMA control chartMCSGWMA control chartSimulationMathematics Subject Classification: Primary 62Secondary P30 Acknowledgments The authors would like to thank the referees for their valuable comments and suggestions which greatly enhanced the clarity of the article. All of the suggestions were incorporated directly in the text. Notes Note. Figures in boldface indicate the smallest ARL1 for the specific combinations of offset. Note. Figures in boldface indicate the smallest ARL1 for the specific combinations of offset. Note. Figures in boldface indicate the smallest ARL1 for the specific combinations of offset.