Multivariate exponentially weighted moving covariance matrix

    Authors

    D. M. Hawkins;E. M. Maboudou-Tchao

    Comments

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    Abbreviated Journal Title

    Technometrics

    Keywords

    average run length; average run length bias; regression adjustment; QUALITY-CONTROL; CONTROL SCHEMES; CONTROL CHARTS; VARIABLES; EWMA; Statistics & Probability

    Abstract

    Multivariate exponentially weighted moving average (MEWMA) charts are among the best control charts for detecting small changes in any direction. The well-known MEWMA is directed at changes in the mean vector. But changes can occur in either the location or the variability of the correlated multivariate quality characteristics, calling for parallel methodologies for detecting changes in the covariance matrix. This article discusses an exponentially weighted moving covariance matrix for monitoring the stability of the covariance matrix of a process. Used together with the location MEWMA, this chart provides a way to satisfy Shewhart's dictum that proper process control monitor both mean and variability. We show that the chart is competitive, generally outperforming current control charts for the covariance matrix.

    Journal Title

    Technometrics

    Volume

    50

    Issue/Number

    2

    Publication Date

    1-1-2008

    Document Type

    Article

    Language

    English

    First Page

    155

    Last Page

    166

    WOS Identifier

    WOS:000256420500004

    ISSN

    0040-1706

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