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An enhanced nonparametric EWMA sign control chart using sequential mechanism

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  • Muhammad Riaz
  • Muhammad Abid
  • Hafiz Zafar Nazir
  • Saddam Akber Abbasi

Abstract

Control charts play a significant role to monitor the performance of a process. Nonparametric control charts are helpful when the probability model of the process output is not known. In such cases, the sampling mechanism becomes very important for picking a suitable sample for process monitoring. This study proposes a nonparametric arcsine exponentially weighted moving average sign chart by using an efficient scheme, namely, sequential sampling scheme. The proposal intends to enhance the detection ability of the arcsine exponentially weighted moving average sign chart, particularly for the detection of small shifts. The performance of the proposal is assessed, and compared with its counterparts, by using some popular run length properties including average, median and standard deviation run lengths. The proposed chart shows efficient shift detection ability as compared to the other charts, considered in this study. A real-life application based on the smartphone accelerometer data-set, for the implementation of the proposed scheme, is also presented.

Suggested Citation

  • Muhammad Riaz & Muhammad Abid & Hafiz Zafar Nazir & Saddam Akber Abbasi, 2019. "An enhanced nonparametric EWMA sign control chart using sequential mechanism," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-15, November.
  • Handle: RePEc:plo:pone00:0225330
    DOI: 10.1371/journal.pone.0225330
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    References listed on IDEAS

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    1. Mukherjee, Amitava & Sen, Rudra, 2018. "Optimal design of Shewhart–Lepage type schemes and its application in monitoring service quality," European Journal of Operational Research, Elsevier, vol. 266(1), pages 147-167.
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    Cited by:

    1. Tokelo Irene Letshedi & Jean-Claude Malela-Majika & Sandile Charles Shongwe, 2022. "New extended distribution-free homogenously weighted monitoring schemes for monitoring abrupt shifts in the location parameter," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-25, January.

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