Ameliorating the diagnostic power of combined shewhart-memory-type control chart strategies for mean

Aqeel ur Rehman, Javid Shabbir, Tahir Munir, Shabbir Ahmad*, Muhammad Riaz

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

A great deal of research in statistical process control (SPC) involves the integration of different ideas to achieve the optimal detection of anomalies in the location parameter of a process. Likewise, the prime rationale of the combined (Shewhart-Memory-type) strategies is to promptly detect the shift of any size: small, moderate or large. An effort, along the same lines, is made to detect shifts in the mean of a normally distributed process. The usual difference estimator of the process mean instead of the sample mean is employed in the Mixed EWMA-Crosier CUSUM Combined Shewhart Mixed EWMA-CUSUM and Combined Shewhart Mixed EWMA-Crosier CUSUM charts to make their upgraded versions. This enhances the sensitivity of these charts against any shift size. The performance of the charts is appraised and compared with some notable charts of the same ilk, with reference to the average run length (ARL), relative average run length, extra quadratic loss and performance comparison index. An illustrative example is also provided.

Original languageEnglish
Pages (from-to)2564-2595
Number of pages32
JournalJournal of Statistical Computation and Simulation
Volume94
Issue number11
DOIs
StateAccepted/In press - 2024

Bibliographical note

Publisher Copyright:
© 2024 Informa UK Limited, trading as Taylor & Francis Group.

Keywords

  • combined Shewhart-CUSUM
  • Crosier’s CUSUM
  • Memory-type charts
  • statistical process monitoring

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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