Premium
A nonparametric triple exponentially weighted moving average sign control chart
Author(s) -
Alevizakos Vasileios,
Chatterjee Kashinath,
Koukouvinos Christos
Publication year - 2021
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.2810
Subject(s) - ewma chart , control chart , cusum , nonparametric statistics , chart , moving average , statistics , sign test , sign (mathematics) , mathematics , exponential distribution , x bar chart , statistic , statistical process control , parametric statistics , computer science , process (computing) , wilcoxon signed rank test , mathematical analysis , mann–whitney u test , operating system
Nonparametric control charts are used in process monitoring when there is insufficient information about the form of the underlying distribution. In this article, we propose a triple exponentially weighted moving average (TEWMA) control chart based on the sign statistic for monitoring the location parameter of an unknown continuous distribution. The run‐length characteristics of the proposed chart are evaluated performing Monte Carlo simulations. We also compare its statistical performance with existing nonparametric sign charts, such as the cumulative sum (CUSUM), exponentially weighted moving average (EWMA), generally weighted moving average (GWMA), and double exponentially weighted moving average (DEWMA) sign charts as well as the parametric TEWMA‐ X ¯ chart. The results show that the TEWMA sign chart is superior to its competitors, especially for small shifts. Moreover, two examples are given to demonstrate the application of the new scheme.