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Performance of new nonparametric Tukey modified exponentially weighted moving average—Moving average control chart

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  • Khanittha Talordphop
  • Saowanit Sukparungsee
  • Yupaporn Areepong

Abstract

Control charts are an amazing and essential statistical process control (SPC) instrument that is commonly used in monitoring systems to detect a specific defect in the procedure. The mixed Tukey modified exponentially weighted moving average - moving average control chart (MMEM-TCC) with motivation detection ability for fewer shifts in the process mean under symmetric and non-symmetric distributions is proposed in this paper. Average run length (ARL), standard deviation of run length (SDRL), and median run length (MRL) were used as efficiency criteria in the Monte Carlo simulation, and their efficiency was compared to existing control charts. Furthermore, the expected ARL (EARL) is a method for evaluating the performance of control charts beyond a specific range of shift sizes. The distinguishing feature of the proposed chart is that it performs efficiently in detecting small to moderate shifts. There are applications for PM 2.5 and PM 10 data that demonstrate the performance of the proposed chart.

Suggested Citation

  • Khanittha Talordphop & Saowanit Sukparungsee & Yupaporn Areepong, 2022. "Performance of new nonparametric Tukey modified exponentially weighted moving average—Moving average control chart," PLOS ONE, Public Library of Science, vol. 17(9), pages 1-16, September.
    • Handle: RePEc:plo:pone00:0275260
    DOI: 10.1371/journal.pone.0275260
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    Cited by:

    1. Umair Khalil & Tahira Saeed Khan & Walaa Ahmad Hamdi & Dost Muhammad Khan & Muhammad Hamraz, 2024. "A robust cusum control chart for median absolute deviation based on trimming and winsorization," PLOS ONE, Public Library of Science, vol. 19(5), pages 1-21, May.

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