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A spatial rank‐based multivariate EWMA control chart

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  • Changliang Zou
  • Zhaojun Wang
  • Fugee Tsung

Abstract

Nonparametric control charts are useful in statistical process control when there is a lack of or limited knowledge about the underlying process distribution, especially when the process measurement is multivariate. This article develops a new multivariate self‐starting methodology for monitoring location parameters. It is based on adapting the multivariate spatial rank to on‐line sequential monitoring. The weighted version of the rank‐based test is used to formulate the charting statistic by incorporating the exponentially weighted moving average control scheme. It is robust to non‐normally distributed data, easy to construct, fast to compute and also very efficient in detecting multivariate process shifts, especially small or moderate shifts which occur when the process distribution is heavy‐tailed or skewed. As it avoids the need for a lengthy data‐gathering step before charting and it does not require knowledge of the underlying distribution, the proposed control chart is particularly useful in start‐up or short‐run situations. A real‐data example from white wine production processes shows that it performs quite well. © 2012 Wiley Periodicals, Inc. Naval Research Logistics 59: 91–110, 2012

Suggested Citation

  • Changliang Zou & Zhaojun Wang & Fugee Tsung, 2012. "A spatial rank‐based multivariate EWMA control chart," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(2), pages 91-110, March.
    • Handle: RePEc:wly:navres:v:59:y:2012:i:2:p:91-110
    DOI: 10.1002/nav.21475
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    References listed on IDEAS

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    1. Longcheen Huwang & Yi‐Hua Tina Wang & Arthur B. Yeh & Ze‐Shiang Jason Chen, 2009. "On the exponentially weighted moving variance," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(7), pages 659-668, October.
    2. Thomas P. Hettmansperger, 2002. "A practical affine equivariant multivariate median," Biometrika, Biometrika Trust, vol. 89(4), pages 851-860, December.
    3. Chunguang Zhou & Changliang Zou & Yujuan Zhang & Zhaojun Wang, 2009. "Nonparametric control chart based on change-point model," Statistical Papers, Springer, vol. 50(1), pages 13-28, January.
    4. Zou, Changliang & Qiu, Peihua, 2009. "Multivariate Statistical Process Control Using LASSO," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1586-1596.
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    Cited by:

    1. Shu, Lei & Chen, Yu & Zhang, Weiping & Wang, Xueqin, 2022. "Spatial rank-based high-dimensional change point detection via random integration," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    2. Song, Zhi & Mukherjee, Amitava & Zhang, Jiujun, 2021. "Some robust approaches based on copula for monitoring bivariate processes and component-wise assessment," European Journal of Operational Research, Elsevier, vol. 289(1), pages 177-196.

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