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An improved Bayesian Modified-EWMA location chart and its applications in mechanical and sport industry

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  • Muhammad Aslam
  • Syed Masroor Anwar

Abstract

Control charts are popular tools in the statistical process control toolkit and the exponentially weighted moving average (EWMA) chart is one of its essential component for efficient process monitoring. In the present study, a new Bayesian Modified-EWMA chart is proposed for the monitoring of the location parameter in a process. Four various loss functions and a conjugate prior distribution are used in this study. The average run length is used as a performance evaluation tool for the proposed chart and its counterparts. The results advocate that the proposed chart performs very well for the monitoring of small to moderate shifts in the process and beats the existing counterparts. The significance of the proposed scheme has proved through two real-life examples: (1) For the monitoring of the reaming process which is used in the mechanical industry. (2) For the monitoring of golf ball performance in the sports industry.

Suggested Citation

  • Muhammad Aslam & Syed Masroor Anwar, 2020. "An improved Bayesian Modified-EWMA location chart and its applications in mechanical and sport industry," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-19, February.
    • Handle: RePEc:plo:pone00:0229422
    DOI: 10.1371/journal.pone.0229422
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    References listed on IDEAS

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    1. Nasir Abbas & Muhammad Riaz & Ronald J. M. M. Does, 2014. "An EWMA-Type Control Chart for Monitoring the Process Mean Using Auxiliary Information," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 43(16), pages 3485-3498, August.
    2. Josemar Rodrigues, 1994. "Bayesian estimation of a normal mean parameter using the Linex loss function and robustness considerations," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 3(2), pages 237-246, December.
    3. Jimoh Olawale Ajadi & Muhammad Riaz, 2017. "Mixed multivariate EWMA-CUSUM control charts for an improved process monitoring," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(14), pages 6980-6993, July.
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    Cited by:

    1. Fatimah Alshahrani & Ibrahim M. Almanjahie & Majid Khan & Syed M. Anwar & Zahid Rasheed & Ammara N. Cheema, 2023. "On Designing of Bayesian Shewhart-Type Control Charts for Maxwell Distributed Processes with Application of Boring Machine," Mathematics, MDPI, vol. 11(5), pages 1-20, February.

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