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Optimal design of the synthetic chart for the process mean based on median run length

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  • Michael Khoo
  • V. Wong
  • Zhang Wu
  • Philippe Castagliola

Abstract

Control charts are usually designed using average run length as the criterion to be optimized. The shape of the run length distribution changes according to the shift in the mean, from highly skewed for an in-control process to approximately symmetric when the mean shift is large. Since the shape of the run length distribution changes with the mean shift, the Median Run Length (MRL) provides a more meaningful interpretation for in-control and out-of-control performances of the charts, and it is readily understood by practitioners. This article presents an optimal design procedure for a synthetic chart able to monitor the mean based on the MRL under the zero- and steady-state modes. The synthetic chart integrates and conforming run length charts. Pseudocodes and Mathematica programs are presented for the computation of the optimal parameters of the synthetic chart based on a desired in-control MRL (MRL(0)), a given sample size, and a specified mean shift for which a quick detection is needed. [Supplementary materials are available for this article. Go to the publisher's online edition of IIE Transactions for additional example, additional performance study, proof, tables, and figures.]

Suggested Citation

  • Michael Khoo & V. Wong & Zhang Wu & Philippe Castagliola, 2012. "Optimal design of the synthetic chart for the process mean based on median run length," IISE Transactions, Taylor & Francis Journals, vol. 44(9), pages 765-779.
  • Handle: RePEc:taf:uiiexx:v:44:y:2012:i:9:p:765-779
    DOI: 10.1080/0740817X.2011.609526
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    Cited by:

    1. Moi Hua Tuh & Cynthia Mui Lian Kon & Hong Siang Chua & Man Fai Lau & Yee Hui Robin Chang, 2023. "Evaluating the Performance of Synthetic Double Sampling np Chart Based on Expected Median Run Length," Mathematics, MDPI, vol. 11(3), pages 1-23, January.
    2. Yeong, Wai Chung & Khoo, Michael B.C. & Lee, Ming Ha & Rahim, M.A., 2013. "Economic and economic statistical designs of the synthetic X¯ chart using loss functions," European Journal of Operational Research, Elsevier, vol. 228(3), pages 571-581.
    3. Lei Yong Lee & Michael Boon Chong Khoo & Sin Yin Teh & Ming Ha Lee, 2015. "A Variable Sampling Interval Synthetic Xbar Chart for the Process Mean," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-18, May.

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