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An EWMA-Type Control Chart for Monitoring the Process Mean Using Auxiliary Information

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  • Nasir Abbas
  • Muhammad Riaz
  • Ronald J. M. M. Does

Abstract

Statistical process control (SPC) is an important application of statistics in which the outputs of production processes are monitored. Control charts are an important tool of SPC. A very popular category is the Shewhart's X‾$\bar X $ -chart used to monitor the mean of a process characteristic. Two alternatives to the Shewhart's X‾$\bar X $ -chart are the cumulative sum and exponentially weighted moving average (EWMA) charts which are designed to detect moderate and small shifts in the process mean. Targeting on small and moderate shifts in the process mean, we propose an EWMA-type control chart which utilizes a single auxiliary variable. The regression estimation technique for the mean is used in defining the control structure of the proposed chart. It is shown that the proposed chart is performing better than its univariate and bivariate competitors which are also designed for detecting small shifts.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:lstaxx:v:43:y:2014:i:16:p:3485-3498
    DOI: 10.1080/03610926.2012.700368
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    Cited by:

    1. Maroua Said & Khaoula ben Abdellafou & Okba Taouali, 2020. "Machine learning technique for data-driven fault detection of nonlinear processes," Journal of Intelligent Manufacturing, Springer, vol. 31(4), pages 865-884, April.
    2. Su-Fen Yang & Li-Pang Chen & Cheng-Kuan Lin, 2023. "Adjustment of Measurement Error Effects on Dispersion Control Chart with Distribution-Free Quality Variable," Sustainability, MDPI, vol. 15(5), pages 1-19, February.
    3. Jen-Hsiang Chen & Shin-Li Lu, 2022. "Economic-Statistical Performance of Auxiliary Information-Based Maximum EWMA Charts for Monitoring Manufacturing Processes," Mathematics, MDPI, vol. 10(13), pages 1-15, July.
    4. Vasileios Alevizakos & Arpita Chatterjee & Kashinath Chatterjee & Christos Koukouvinos, 2024. "The exponentiated exponentially weighted moving average control chart," Statistical Papers, Springer, vol. 65(6), pages 3853-3891, August.
    5. 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.

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