Statistical monitoring of the covariance matrix in multivariate processes: A literature review

被引：19

作者：

Ebadi, Mohsen ^{[1
]}

Chenouri, Shojaeddin ^{[1
]}

Lin, Dennis K. J. ^{[2
]}

Steiner, Stefan H. ^{[1
]}

机构：

[1] Univ Waterloo, Dept Stat & Actuarial Sci, Waterloo, ON, Canada

[2] Purdue Univ, W Lafayette, IN 47907 USA

来源：

JOURNAL OF QUALITY TECHNOLOGY | 2022年 / 54卷 / 03期

关键词：

covariance matrix; multivariate control charts; Phase I and Phase II; statistical process monitoring (SPM); BAR CONTROL CHART; DISPERSION CONTROL CHARTS; PROCESS VARIABILITY; MEAN VECTOR; CHANGE-POINT; INDIVIDUAL OBSERVATIONS; SAMPLE VARIANCES; NEURAL-NETWORKS; CONTROL SCHEMES; DIMENSION;

D O I：

10.1080/00224065.2021.1889419

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Monitoring several correlated quality characteristics of a process is common in modern manufacturing and service industries. Although a lot of attention has been paid to monitoring the multivariate process mean, not many control charts are available for monitoring the covariance matrix. This paper presents a comprehensive overview of the literature on control charts for monitoring the covariance matrix in a multivariate statistical process monitoring (MSPM) framework. It classifies the research that has previously appeared in the literature. We highlight the challenging areas for research and provide some directions for future research.

引用

页码：269 / 289

页数：21

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