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Multivariate Statistical Process Control Charts and the Problem of Interpretation: A Short Overview and Some Applications in Industry

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  • Bersimis, Sotiris
  • Panaretos, John
  • Psarakis, Stelios

Abstract

Woodall and Montgomery in a discussion paper, state that multivariate process control is one of the most rapidly developing sections of statistical process control. Nowadays, in industry, there are many situations in which the simultaneous monitoring or control, of two or more related quality - process characteristics is necessary. Process monitoring problems in which several related variables are of interest are collectively known as Multivariate Statistical Process Control (MSPC). This article has three parts. In the first part, we discuss in brief the basic procedures for the implementation of multivariate statistical process control via control charting. In the second part we present the most useful procedures for interpreting the out-of-control variable when a control charting procedure gives an out-of-control signal in a multivariate process. Finally, in the third, we present applications of multivariate statistical process control in the area of industrial process control, informatics, and business

Suggested Citation

  • Bersimis, Sotiris & Panaretos, John & Psarakis, Stelios, 2005. "Multivariate Statistical Process Control Charts and the Problem of Interpretation: A Short Overview and Some Applications in Industry," MPRA Paper 6397, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:6397
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    File URL: https://mpra.ub.uni-muenchen.de/6397/1/MPRA_paper_6397.pdf
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    1. Bersimis, Sotiris & Psarakis, Stelios & Panaretos, John, 2006. "Multivariate Statistical Process Control Charts: An Overview," MPRA Paper 6399, University Library of Munich, Germany.
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    Cited by:

    1. Chen, Yikai & Durango-Cohen, Pablo L., 2015. "Development and field application of a multivariate statistical process control framework for health-monitoring of transportation infrastructure," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 78-102.
    2. Nasir Abbas & Muhammad Riaz & Shabbir Ahmad & Muhammad Abid & Babar Zaman, 2020. "On the Efficient Monitoring of Multivariate Processes with Unknown Parameters," Mathematics, MDPI, vol. 8(5), pages 1-32, May.

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    More about this item

    Keywords

    Quality Control; Process Control; Multivariate Statistical Process Control; Hotelling's T²; CUSUM; EWMA; PCA; PLS; Identification; Interpretation;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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