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

Authors :
Hu, XueLong
Zhang, SuYing
Zhou, XiaoJian
Tang, AnAn
Xie, FuPeng
Source :
Communications in Statistics: Simulation & Computation. 2024, Vol. 53 Issue 4, p1779-1798. 20p.
Publication Year :
2024

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03610918
Volume :
53
Issue :
4
Database :
Academic Search Index
Journal :
Communications in Statistics: Simulation & Computation
Publication Type :
Academic Journal
Accession number :
176146860
Full Text :
https://doi.org/10.1080/03610918.2022.2057539