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Economic design of charts when signals may be misclassified and the bounded reset chart

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  • Changsoon Park

Abstract

In monitoring manufacturing processes, mistakes made by statisticians can lead to Type I and Type II errors. Process engineers also commit action errors, such as search and judgment errors, when following the out-of-control action plan. These errors arise because process engineers are not always successful in searching for special causes or judging search results correctly. Action errors committed by process engineers have not been considered in the control chart literature; however, they exist in most manufacturing processes. They degrade the process quality as well as increase the control cost. The efficiency of a Traditional Control Chart (TCC) procedure is re-evaluated considering the action errors in terms of the economic context. It is shown that the efficiency of the TCC procedure is overestimated when these errors are present. The Bounded Reset Chart (BRC) procedure is proposed as an alternative to the TCC procedure. The BRC procedure is to reset the process upon a signal instead of searching for special causes so that action errors are not committed. An example and an extensive comparison of the economic design of the TCC and BRC procedures are presented and it is shown that the BRC procedure is more effective than the TCC procedure for cases where action errors are considered.

Suggested Citation

  • Changsoon Park, 2013. "Economic design of charts when signals may be misclassified and the bounded reset chart," IISE Transactions, Taylor & Francis Journals, vol. 45(4), pages 436-448.
  • Handle: RePEc:taf:uiiexx:v:45:y:2013:i:4:p:436-448
    DOI: 10.1080/0740817X.2012.695101
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    Cited by:

    1. Chenglong Li & Amitava Mukherjee & Qin Su & Min Xie, 2016. "Optimal design of a distribution-free quality control scheme for cost-efficient monitoring of unknown location," International Journal of Production Research, Taylor & Francis Journals, vol. 54(24), pages 7259-7273, December.
    2. Chenglong Li & Qin Su & Min Xie, 2016. "Economic modelling for statistical process control subject to a general quality deterioration," International Journal of Production Research, Taylor & Francis Journals, vol. 54(6), pages 1753-1770, March.

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