An optimal bivariate Poisson field chart for controlling high-quality manufacturing processes

被引：8

作者：

Aebtarm, Surath ^{[1
]}

Bouguila, Nizar ^{[1
]}

机构：

[1] Concordia Univ, Concordia Inst Informat Syst Engn, Fac Engn & Comp Sci, Montreal, PQ H3G 2W1, Canada

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2010年 / 37卷 / 07期

关键词：

Attribute chart; Control chart; Count data; Poisson distribution; Poisson field; Bivariate Poisson;

D O I：

10.1016/j.eswa.2010.02.060

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Shewhart C-chart is a widely accepted control chart for monitoring number of defects in a given process. This chart is based on normal approximations. Normal assumption is, however, impractical in many cases especially for count data. This assumption becomes stronger when correlation between characteristics exists. In this article, we propose an optimal bivariate Poisson field chart to monitor two correlated characteristics of count data for both industrial and non-industrial purposes. Our chart is based on optimization of bivariate Poisson confidence interval and projection of bivariate Poisson data in Poisson field. The performance of our proposed algorithm is presented using both real case study and simulations. The experimental results demonstrate improved performances regarding visualization and false alarm rate. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：5498 / 5506

页数：9

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