An adaptive nonparametric exponentially weighted moving average control chart with dynamic sampling intervals. (15th December 2020)

• Record Type: Journal Article
• Authors: Liu, Liu; Peng, Qing; Lai, Xin; Deng, Zepei
• Is Part Of: Statistical analysis and data mining. Volume 14:Number 1(2021)
• Page Start: 74
• Page End: 87
• Publication Date: 2020-12-15
• Subjects: aluminum manufacturing capacitor -- dynamic link function -- EWMA -- nonparametric control chart -- variable sampling interval; Data mining -- Statistical methods -- Periodicals; 006.312
• DOI: 10.1002/sam.11490
• Languages: English
• ISSNs: 1932-1864

Abstract

Abstract: Nonparametric statistical control charts have been widely studied over the past decade. The variable sampling intervals (VSIs) methods have been found to exhibit superior performance compared to the traditional fixed sampling policy in this area. In previous VSI studies, the sampling interval function d (·) realized only two distinct values. Limiting the selection of the sampling interval to two fixed values may not be reasonable, especially when the monitoring statistic value is at the edge or near the middle of these two intervals so that the advantages of VSI methods cannot be fully reflected. Therefore, we propose a nonparametric exponentially weighed moving average control chart with a dynamic sampling interval in this article, in which the dynamic sampling interval is an extension of two fixed sampling intervals. The dynamic sampling interval can be continuous valued and is determined by an indicator of the magnitude of the unknown shift. This chart can efficiently detect various magnitudes of shifts and performs robustly for different distributions according to simulation studies. The small computational cost indicates that the method is applicable for monitoring large data streams. Data from an aluminum electrolytic capacitor manufacturing process are used to illustrate the implementation of this chart.