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A nonparametric double generally weighted moving average signed‐rank control chart for monitoring process location
Author(s) -
Alevizakos Vasileios,
Koukouvinos Christos,
Chatterjee Kashinath
Publication year - 2020
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.2706
Subject(s) - ewma chart , control chart , nonparametric statistics , chart , statistics , location parameter , mathematics , statistic , rank (graph theory) , x bar chart , moving average , statistical process control , parametric statistics , shewhart individuals control chart , process (computing) , computer science , probability distribution , combinatorics , operating system
Most control charts have been developed based on the actual distribution of the quality characteristic of interest. However, in many applications, there is a lack of knowledge about the process distribution. Therefore, in recent years, nonparametric (or distribution‐free) control charts have been introduced for monitoring the process location or scale parameter. In this article, a nonparametric double generally weighted moving average control chart based on the signed‐rank statistic (referred as DGWMA‐SR chart) is proposed for monitoring the location parameter. We provide the exact approach to compute the run‐length distribution, and through an extensive simulation study, we compare the performance of the proposed chart with existing nonparametric charts, such as the exponentially weighted moving average signed‐rank (EWMA‐SR), the generally weighted moving average signed‐rank (GWMA‐SR), the double exponentially weighted moving average signed‐rank (DEWMA‐SR), and the double generally weighted moving average sign (DGWMA‐SN) charts, as well as the parametric DGWMA‐ X ¯ chart for subgroup averages. The simulation results show that the DGWMA‐SR chart (with suitable parameters) is more sensitive than the other competing charts for small shifts in the location parameter and performs as well as the other nonparametric charts for larger shifts. Finally, two examples are given to illustrate the application of the proposed chart.