A joint monitoring of the process mean and variance with a generally weighted moving average maximum control chart

Abstract

Single control charts are widely used to control assignable causes that shift the process due to variations in the mean and the dispersion. In the present article, the exponentially weighted moving average maximum (EWMA-Max) control chart is extended to the new single generally weighted moving average maximum (referred as GWMA-Max) control chart for joint monitoring of the process mean and variability. The proposed chart is compared with the EWMA-Max and DEWMA-Max charts in terms of the run-length performance measures. The results reveal that the GWMA-Max chart is very efficient in detecting small shifts in the process mean and variability concurrently. Finally, a practical implementation of the GWMA-Max chart is displayed using real and simulated datasets.

Keywords:

• Average run–length
• Exponentially weighted moving average maximum chart
• Generally weighted moving average maximum chart
• Single control chart
• Standard deviation of run–length

Mathematical Subject Classification:

• 62P30

Acknowledgments

The authors would like to thank the Editor and the referees for their useful comments which resulted in improving the quality of this article.