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http://dx.doi.org/10.7465/jkdi.2017.28.4.937

Multivariate control charts based on regression-adjusted variables for covariance matrix  

Kwon, Bumjun (Department of Statistics, Kyungpook National University)
Cho, Gyo-Young (Department of Statistics, Kyungpook National University)
Publication Information
Journal of the Korean Data and Information Science Society / v.28, no.4, 2017 , pp. 937-945 More about this Journal
Abstract
The purpose of using a control chart is to detect any change that occurs in the process. When control charts are used to monitor processes, we want to identify this changes as quickly as possible. Many problems in quality control involve a vector of observations of several characteristics rather than a single characteristic. Multivariate CUSUM or EWMA charts have been developed to address the problem of monitoring covariance matrix or the joint monitoring of mean vector and covariance matrix. However, control charts tend to work poorly when we use the highly correlatted variables. In order to overcome it, Hawkins (1991) proposed the use of regression adjustment variables. In this paper, to monitor covariance matrix, we investigate the performance of MEWMA-type control charts with and without the use of regression adjusted variables.
Keywords
Average run length; covariance matrix; multivariate control chart; regression adjusted variables;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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