A multivariate exponentially weighted moving average control chart for monitoring process variability

Arthur B. Yeh, Dennis K.J. Lin, Honghong Zhou, Chandramouliswaran Venkataramani

Research output: Contribution to journalArticle

62 Scopus citations

Abstract

This paper introduces a new multivariate exponentially weighted moving average (EWMA) control chart. The proposed control chart, called an EWMA V-chart, is designed to detect small changes in the variability of correlated multivariate quality characteristics. Through examples and simulations, it is demonstrated that the EWMA V-chart is superior to the S-chart in detecting small changes in process variability. Furthermore, a counterpart of the EWMA V-chart for monitoring process mean, called the EWMA M-chart is proposed. In detecting small changes in process variability, the combination of EWMA M-chart and EWMA V-chart is a better alternative to the combination of MEWMA control chart (Lowry et al., 1992) and S-chart. Furthermore, the EWMA M-chart and V-chart can be plotted in one single figure. As for monitoring both process mean and process variability, the combined MEWMA and EWMA V-charts provide the best control procedure.

Original languageEnglish (US)
Pages (from-to)507-536
Number of pages30
JournalJournal of Applied Statistics
Volume30
Issue number5
DOIs
StatePublished - Jun 1 2003

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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