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An adaptive chart for multivariate process monitoring and diagnosis

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  • Yongzhong Zhu
  • Wei Jiang

Abstract

Hotelling's T2 chart is one of the most popular multivariate control charts for monitoring multiple variables simultaneously. The identification of response variables from T2 charts is an area that is currently receiving considerable attention. This paper proposes an adaptive T2 chart that combines process monitoring and diagnosis in a unified manner. The proposed procedure has a close relationship with the U2 chart, but it is data oriented and does not have a priori knowledge of the potential shifts space. It can adaptively capture shift information from the sample data to construct the U2 test statistic and is shown to be very competitive with other alternative charts for multivariate statistical process control in terms of both mean monitoring and fault diagnosis.

Suggested Citation

  • Yongzhong Zhu & Wei Jiang, 2009. "An adaptive chart for multivariate process monitoring and diagnosis," IISE Transactions, Taylor & Francis Journals, vol. 41(11), pages 1007-1018.
    • Handle: RePEc:taf:uiiexx:v:41:y:2009:i:11:p:1007-1018
    DOI: 10.1080/07408170902942675
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    Cited by:

    1. Jinho Kim & Myong K. Jeong & Elsayed A. Elsayed, 2017. "Monitoring multistage processes with autocorrelated observations," International Journal of Production Research, Taylor & Francis Journals, vol. 55(8), pages 2385-2396, April.
    2. Lee, Pei-Hsi, 2013. "Joint statistical design of X¯ and s charts with combined double sampling and variable sampling interval," European Journal of Operational Research, Elsevier, vol. 225(2), pages 285-297.

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