The performance of double exponentially weighted moving average control charts for monitoring the coefficient of variation

Abstract

The coefficient of variation (CV) is one of the most important quality characteristics in industrial applications. There have been some control charts for monitoring this dimensionless and normalized characteristic. This paper presents three double exponentially weighted moving average (DEWMA) charts for monitoring the CV. Many numerical simulations are performed and the results are given in several tables to show the properties of the proposed DEWMA CV charts. Through comparisons with other existing exponentially weighted moving average (EWMA) CV charts using the average run length (ARL) metric, it is shown that the proposed DEWMA CV charts perform better than the existing EWMA CV charts for small shifts, especially when the smoothing parameter increases. In addition, a detailed comparison among the proposed three DEWMA CV charts is also presented. A real date example from industry is used to show the implementation of the proposed charts.

Keywords:

• Coefficient of variation
• DEWMA chart
• EWMA chart
• Average run length

Disclosure statement

There are no relevant financial or non-financial competing interests to report.

Acknowledgement

The authors are grateful to the AE and the anonymous reviewers for their useful suggestions, which enabled the quality of the present manuscript to be improved from the original version. This work is supported by the National Natural Science Foundation of China (No. 71802110, 71872088, 72101123), Natural Science Foundation of JiangSu Province (No. BK20200750), Postgraduate Research and Practice Innovation Program of Jiangsu Province (No. KYCX21_0840), Key Research Base of Philosophy and Social Sciences in Jiangsu-Information Industry Integration Innovation and Emergency Management Research Center, The Excellent Innovation Teams of Philosophy and Social Science in Jiangsu Province (No. 2017ZSTD022).