A nonparametric double generally weighted moving average signed‐rank control chart for monitoring process location. (10th July 2020)

• Record Type: Journal Article
• Authors: Alevizakos, Vasileios; Koukouvinos, Christos; Chatterjee, Kashinath
• Is Part Of: Quality and reliability engineering international. Volume 36:Number 7(2020)
• Page Start: 2441
• Page End: 2458
• Publication Date: 2020-07-10
• Subjects: average run‐length -- double generally weighted moving average -- generally weighted moving average -- nonparametric control chart -- signed‐rank statistic; Reliability (Engineering) -- Periodicals; Quality control -- Periodicals; High technology -- Periodicals; 620.00452
• DOI: 10.1002/qre.2706
• Languages: English
• ISSNs: 0748-8017

Abstract

Abstract: 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.