EWMA control charts for multivariate Poisson-distributed data

Busaba Laungrungrong, Connie M. Borror, Douglas Montgomery

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

Much of the research involving simultaneous monitoring of several related quality characteristics that follow a multivariate Poisson distribution has relied on using the normal approximation to the Poisson distribution in order to determine the appropriate control limits. In this paper, evaluation and implementation of MEWMA schemes for count rates using the multivariate Poisson framework itself are presented. We demonstrate that the multivariate EWMA chart-based directly on the multivariate Poisson distribution is superior to one based on normal-theory with respect to the in-control average run length. The proposed scheme performs similarly to one based on normal-theory for detecting an out-of-control process. We also illustrate a step-by-step numerical example on the practical use of the new control chart.

Original languageEnglish (US)
Pages (from-to)185-211
Number of pages27
JournalInternational Journal of Quality Engineering and Technology
Volume2
Issue number3
DOIs
StatePublished - 2011

Keywords

  • MEWMA chart
  • multivariate Poisson distribution

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality

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