On designing a robust double exponentially weighted moving average control chart for process monitoring

Ishaq Adeyanju Raji, Nasir Abbas*, Muhammad Riaz

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

A double exponentially weighted moving average chart has been proven more efficient for monitoring process mean in comparison to the classical exponentially weighted moving average chart. We, in this article, made a careful investigation on how well this scheme performs with the presence of disturbances in the process under consideration. This investigation was motivated in exploring the scheme with some robust statistic, as the mean estimator performs woefully. We also evaluated the effects of parameter estimation on the phase II assuming the parameters are unknown. Adopting a 20% trimmed mean of trimeans (robust) reveals the effect of parameter estimations. We substantiated these claims by applying the scheme on a real-life data set. The findings of the study pronounced the trimean estimator to be the best of all the five estimators used, including the mean.

Original languageEnglish
Pages (from-to)4253-4265
Number of pages13
JournalTransactions of the Institute of Measurement and Control
Volume40
Issue number15
DOIs
StatePublished - 1 Nov 2018

Bibliographical note

Publisher Copyright:
© The Author(s) 2018.

Keywords

  • Average run length
  • DEWMA
  • quality control
  • robustness
  • trimmed mean

ASJC Scopus subject areas

  • Instrumentation

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