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An efficient multivariate control charting mechanism based on SPRT

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  • Yanjing Ou
  • Nan Chen
  • Michael B.C. Khoo

Abstract

This article devises a feasible multivariate Sequential Probability Ratio Test chart (MSPRT chart) to monitor the mean of the multivariate normal distribution. To reduce the time required by the MSPRT chart to detect shifts of a wide range, the charting parameters are optimised to minimise the Average Extra Quadratic Loss (AEQL). The comparative study reveals that the MSPRT chart can improve the performance of the typical Hotelling’s T2 chart and the multivariate synthetic (Msynthetic) chart. It also shows that the MSPRT chart outperforms the multivariate Exponentially Weighted Moving Average (MEWMA) chart for moderate and large shifts but the latter prevails in detecting small shifts. For ease of use, we also provide two design tables for the quality engineers to adopt the MSPRT and Hotelling’s T2 charts more conveniently. Finally, we used an example concerning the white wine production process to demonstrate the application of the proposed scheme.

Suggested Citation

  • Yanjing Ou & Nan Chen & Michael B.C. Khoo, 2015. "An efficient multivariate control charting mechanism based on SPRT," International Journal of Production Research, Taylor & Francis Journals, vol. 53(7), pages 1937-1949, April.
    • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:7:p:1937-1949
    DOI: 10.1080/00207543.2014.925601
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    Cited by:

    1. Pamela Chiñas-Sanchez & Ismael Lopez-Juarez & Jose Antonio Vazquez-Lopez & Abdelkader El Kamel & Jose Luis Navarro-Gonzalez, 2020. "Stable and Unstable Pattern Recognition Using D 2 and SVM: A Multivariate Approach," Mathematics, MDPI, vol. 9(1), pages 1-12, December.

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