Modern multivariate control chart using spatial signed rank for non-normal process

被引：11

作者：

Haanchumpol, Thidathip ^{[1
]}

Sudasna-na-Ayudthya, Prapaisri ^{[1
]}

Singhtaun, Chansiri ^{[1
]}

机构：

[1] Kasetsart Univ, Fac Engn, Dept Ind Engn, Bangkok, Thailand

来源：

ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH | 2020年 / 23卷 / 04期

关键词：

Spatial signed rank; Control chart; MEWMA; dMEWMA; ARL;

D O I：

10.1016/j.jestch.2019.12.001

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Modern multivariate control charts that use spatial signed rank are sensitive to the detection of small shifts under non-normal or gamma distributions. In this paper, Monte Carlo simulation is used to compare the performances of multivariate control charts based on the average run length. The results show that the spatial signed-rank multivariate exponentially weighted moving average (SSRM) control chart outperforms the multivariate exponentially weighted moving average (MEWMA) control chart, the double-MEWMA control chart, and the spatial signed-rank double multivariate exponentially weighted moving average control chart when detecting small shifts in the process mean. SSRM is appropriate for data from a non-normal distribution, which is valuable for the manufacturing industry when detecting waste. Moreover, SSRM is an excellent method suitable for most industrial processes, and therefore, is a very powerful tool. (C) 2019 Karabuk University. Publishing services by Elsevier B.V.

引用

页码：859 / 869

页数：11

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