Mixed multivariate EWMA-CUSUM control charts for an improved process monitoring

  • Jimoh Olawale Ajadi
  • , Muhammad Riaz*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

62 Scopus citations

Abstract

Multivariate exponential weighted moving average and cumulative sum charts are the most common memory type multivariate control charts. They make use of the present and past information to detect small shifts in the process parameter(s). In this article, we propose two new multivariate control charts using a mixed version of their design setups. The plotting statistics of the proposed charts are based on the cumulative sum of the multivariate exponentially weighted moving averages. The performances of these schemes are evaluated in terms of average run length. The proposals are compared with their existing counterparts, including HotellingT2, MCUSUM, MEWMA, and MC1 charts. An application example is also presented for practical considerations using a real dataset.

Original languageEnglish
Pages (from-to)6980-6993
Number of pages14
JournalCommunications in Statistics - Theory and Methods
Volume46
Issue number14
DOIs
StatePublished - 18 Jul 2017

Bibliographical note

Publisher Copyright:
© 2017 Taylor & Francis Group, LLC.

Keywords

  • Average run length
  • HotellingT
  • MCUSUM chart
  • MEC charts
  • MEWMA chart
  • Multivariate control charts

ASJC Scopus subject areas

  • Statistics and Probability

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