The triple exponentially weighted moving average control chart

ABSTRACT

Quality control charts are extensively used to monitor processes. The EWMA chart is a good alternative to the Shewhart chart to quickly detect small and moderate shifts in the process mean. The DEWMA charting procedure is an enhanced approach for the EWMA chart and performs much better, especially for small and moderate shifts. In this article, we propose the triple EWMA (TEWMA) chart in an effort to improve much more the detection ability of the classical EWMA chart. Monte Carlo simulations are used to evaluate the run-length characteristics of the proposed chart. A comparison study versus the DEWMA, EWMA and GWMA charts indicates that the TEWMA chart with time-varying control limits is more effective in detecting small shifts while it is comparable with the other charts in moderate and large shifts. Moreover, the proposed chart has better inertia properties than the competing charts and is also shown to be in-control robust for small values of the smoothing parameter. Finally, two examples are given to display the application of the TEWMA chart.

KEYWORDS:

• Average run-length
• control chart
• DEWMA chart
• EWMA chart
• TEWMA chart

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.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Vasileios Alevizakos

Vasileios Alevizakos is a PhD canditate of the Department of Mathematics at the National Technical University of Athens, Greece. His research interests include statistical process control, process capability analysis, and robust parameter design.

Kashinath Chatterjee

Kashinath Chatterjee is a former Professor of the Department of Statistics at the Visva-Bharati University, India. His research interests include experimental and optimal designs, statistical quality control, reliability analysis, and robust parameter design.

Christos Koukouvinos

Christos Koukouvinos is a Professor of the Department of Mathematics at the National Technical University of Athens, Greece. His research interests include statistical experimental and optimal designs, statistical quality control, biostatistics, and combinatorial designs.