Optimal Designs of EWMA Charts for Monitoring the Coefficient of Variation Based on Median Run Length and Expected Median Run Length

W. L. Teoh, J. Y. Lim, Michael B. C. Khoo, Z. L. Chong, W. C. Yeong

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


The shape of run-length distribution changes with process shifts. This leads to complexity in interpreting the average run length performance. In this article, we show that the percentiles of the run-length distribution, especially the median run length (MRL), are more intuitive. The 5th and 95th percentiles of the run-length distribution are also provided in order to investigate the variation and spread of the run length. We develop two new optimal-design procedures for the exponentially weighted moving average (EWMA) charts, for monitoring the coefficient-of-variation (CV) squared (EWMA-γ2). These include minimization of the out-of-control MRL and the out-of-control expected MRL for deterministic and unknown shift sizes, respectively. Both the zero and steady states are discussed in this article. The optimal EWMA-γ2 chart is illustrated with real industrial data obtained from a metal sintering process. A comparative study reveals the superiority of the EWMA-γ2 charts for certain ranges of shifts in the CV.
Original languageEnglish
Pages (from-to)459-479
Number of pages21
JournalJournal of Testing and Evaluation
Issue number1
Publication statusPublished - 1 Jan 2019


  • Coefficient of variation
  • Deterministic
  • Expected median run length
  • Exponentially weighted moving average chart
  • Median run length
  • Steady states
  • Unknown shift sizes
  • Zero

ASJC Scopus subject areas

  • Materials Science(all)
  • Mechanics of Materials
  • Mechanical Engineering

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