Exponentially weighted moving average control charts for monitoring increases in Poisson rate

被引：24

作者：

Shu, Lianjie

Jiang, Wei ^{[1
]}

Wu, Zhang ^{[2
]}

机构：

[1] Shanghai Jiao Tong Univ, Antai Coll Econ & Management, Shanghai 200030, Peoples R China

[2] Nanyang Technol Univ, Sch Mech & Aerosp Engn, Div Syst & Engn Management, Singapore, Singapore

来源：

IIE TRANSACTIONS | 2012年 / 44卷 / 09期

关键词：

Poisson distribution; average run length; statistical process control; Markov chain; SPC-Q-CHARTS; EWMA CONTROL CHARTS; LONG RUNS; CONTROL SCHEMES; CUSUM; SURVEILLANCE; VARIANCE; LENGTH; START;

D O I：

10.1080/0740817X.2011.578609

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The Exponentially Weighted Moving Average (EWMA) control chart has been widely studied as a tool for monitoring normal processes due to its simplicity and efficiency. However, relatively little attention has been paid to EWMA charts for monitoring Poisson processes. This article extends EWMA charts to Poisson processes with an emphasis on quick detection of increases in Poisson rate. Both cases with and without normalizing transformation for Poisson data are considered. A Markov chain model is established to analyze and design the proposed chart. A comparison of the results obtained indicates that the EWMA chart based on normalized data is nearly optimal.

引用

页码：711 / 723

页数：13

共 31 条

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