Robustness to Non-normality of the Multivariate EWMA Control Chart

Article

Stoumbos, Zachary G.; Sullivan, Joe H.   (2002, ASQ)   Rutgers, The State University of New Jersey, Piscataway, NJ; Mississippi State University, Starksville, MS

Journal of Quality Technology    Vol. 34    No. 3
QICID: 18229    July 2002    pp. 260-276
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Article Abstract

[This abstract is based on the authors' abstract.] The effects of non-normality on the statistical performance of the multivariate exponentially moving average (MEWMA) control chart, and the Hotelling chi-squared chart in particular, is investigated when used in individual observations to monitor the mean vector of a multivariate process variable. It is demonstrated that performance is most sensitive to departures from multivariate normality with individual observations. With individual observations, and, by extension, with subgroups of any size, the MEWMA chart designed to be robust to non-normality can be very effective at detecting process shifts of any size or direction.

Keywords

Non-normality,Average run length (ARL),Exponentially weighted moving average control charts (EWMA),Multivariate control charts,Statistical process control (SPC)


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