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Multivariate variability monitoring using EWMA control charts based on squared deviation of observations from target

Memar, A. O ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1002/qre.1196
  3. Abstract:
  4. Recent research works have shown that control statistics based on squared deviation of observations from target have the ability to monitor variability in both univariate and multivariate processes. In the current research, the properties of the control statistic S t that has been proposed by Huwang et al. (J. Quality Technology 2007; 39:258-278) are first reviewed and three new S t-based multivariate schemes are then presented. Extensive simulation experiments are performed to compare the performances of the proposed schemes with those of the multivariate exponentially weighted mean squared deviation (MEWMS) and the L 1-norm distance of the MEWMS deviation from its expected value (MEWMSL 1) charts. The results show that one of the proposed schemes outperforms the others in detecting shifts in correlation coefficients and another has the best general performance among the compared charts in detecting shifts in which at least one of the variances changes
  5. Keywords:
  6. Multivariate variability monitoring ; Correlation coefficient ; EWMA control ; Expected values ; Extensive simulations ; Individual observations ; Multivariate exponentially weighted mean squared deviation ; Multivariate process ; Multivariate schemes ; Univariate ; Variability monitoring ; Weighted mean ; Safety engineering ; Quality assurance
  7. Source: Quality and Reliability Engineering International ; Volume 27, Issue 8 , 2011 , Pages 1069-1086 ; 07488017 (ISSN)
  8. URL: http://onlinelibrary.wiley.com/doi/10.1002/qre.1196/abstract