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Study of a Markov model for a high-quality dependent process

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  • C. D. Lai
  • M. Xie
  • K. Govindaraju

Abstract

For high-quality processes, non-conforming items are seldom observed and the traditional p (or np) charts are not suitable for monitoring the state of the process. A type of chart based on the count of cumulative conforming items has recently been introduced and it is especially useful for automatically collected one-at-a-time data. However, in such a case, it is common that the process characteristics become dependent as items produced one after another are inspected. In this paper, we study the problem of process monitoring when the process is of high quality and measurement values possess a certain serial dependence. The problem of assuming independence is examined and a Markov model for this type of process is studied, upon which suitable control procedures can be developed.

Suggested Citation

  • C. D. Lai & M. Xie & K. Govindaraju, 2000. "Study of a Markov model for a high-quality dependent process," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(4), pages 461-473.
    • Handle: RePEc:taf:japsta:v:27:y:2000:i:4:p:461-473
    DOI: 10.1080/02664760050003641
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    References listed on IDEAS

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    1. Layth C. Alwan & Harry V. Roberts, 1995. "The Problem of Misplaced Control Limits," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 44(3), pages 269-278, September.
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    Cited by:

    1. Sueli Mingoti & Julia De Carvalho & Joab De Oliveira Lima, 2008. "On the estimation of serial correlation in Markov-dependent production processes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(7), pages 763-771.

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