Control charts for monitoring the mean vector and the covariance matrix of bivariate processes

被引：11

作者：

Machado, Marcela A. G. ^{[1
,2
]}

Costa, Antonio F. B. ^{[2
]}

Marins, Fernando A. S. ^{[2
]}

机构：

[1] Univ Estadual Paulista, Fac Engn, Dept Prod, BR-12516410 Sao Paulo, Brazil

[2] Univ Estadual Paulista, Sao Paulo State Univ, Prod Dept, BR-12516410 Sao Paulo, Brazil

来源：

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY | 2009年 / 45卷 / 7-8期

关键词：

Control charts; Mean vector; Covariance matrix; Bivariate processes; SYNTHETIC CONTROL CHART; MULTIVARIATE CONTROL CHART; DESIGN;

D O I：

10.1007/s00170-009-2018-7

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this article, we propose new control charts for monitoring the mean vector and the covariance matrix of bivariate processes. The traditional tools used for this purpose are the T (2) and the |S| charts. However, these charts have two drawbacks: (1) the T (2) and the |S| statistics are not easy to compute, and (2) after a signal, they do not distinguish the variable affected by the assignable cause. As an alternative to (1), we propose the MVMAX chart, which only requires the computation of sample means and sample variances. As an alternative to (2), we propose the joint use of two charts based on the non-central chi-square statistic (NCS statistic), named as the NCS charts. Once the NCS charts signal, the user can immediately identify the out-of-control variable. In general, the synthetic MVMAX chart is faster than the NCS charts and the joint T (2) and |S| charts in signaling processes disturbances.

引用

页码：772 / 785

页数：14

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