A non-parametric double homogeneously weighted moving average control chart under sign statistic

  • Muhammad Riaz*
  • , Muhammad Abid
  • , Aroosa Shabbir
  • , Hafiz Zafar Nazir
  • , Zameer Abbas
  • , Saddam Akber Abbasi
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

In practical situations, the underlying process distribution sometimes deviates from normality and their distribution is partially or completely unknown. In that instance, rather than staying with/depending on the conventional parametric control charts, we consider non-parametric control charts due to their exceptional performance. In this paper, a new non-parametric double homogeneously weighted moving average sign control chart is proposed with the least assumptions. This chart is based on a sign test statistic for catching the smaller deviations in the process location. Run-length (RL) properties of the proposed chart are studied with the help of Monte Carlo simulations. Both in-control and out-of-control RL properties show that the proposed chart is a better contender as compared to some existing charts from the literature. A real-life application for practical consideration of the proposed chart is also provided.

Original languageEnglish
Pages (from-to)1544-1560
Number of pages17
JournalQuality and Reliability Engineering International
Volume37
Issue number4
DOIs
StatePublished - Jun 2021

Bibliographical note

Publisher Copyright:
© 2020 John Wiley & Sons Ltd.

Keywords

  • average run length
  • control chart
  • non-parametric
  • normality
  • sign statistic

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Management Science and Operations Research

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