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A new statistical process control method to monitor and diagnose bivariate normal mean vectors and covariance matrices simultaneously

Akhavan Niaki, T ; Sharif University of Technology | 2009

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  1. Type of Document: Article
  2. DOI: 10.1007/s00170-008-1774-0
  3. Publisher: 2009
  4. Abstract:
  5. In this paper, in order to find an adequate method of monitoring the mean vector and covariance matrix of a production process simultaneously, first, some available univariate control methods were reviewed and evaluated. Then, the maximum exponentially weighted moving average method with a better potential application and good performances in terms of average time to signal (ATS) criterion was selected to be extended to the bivariate case. In the extended procedure, by proper transformation of the control parameters, the primary control space is transformed such that all control elements have the same probability distributions. In this case, only the maximum absolute value of the transformed elements is monitored to control both the mean vector and the covariance matrix simultaneously. Moreover, a heuristic procedure is proposed to interpret and diagnose the out-of-control parameter(s). Finally, not only the performances of the proposed method are evaluated and compared to the ones from the two recent methods in terms of ATS but also the percentage of correct classification of the proposed method was estimated by extensive simulation experiments. © 2008 Springer-Verlag London Limited
  6. Keywords:
  7. Maximum exponentially weighted moving average method ; Multivariate quality control ; Signal diagnosing ; Simultaneous control of mean and variance ; Statistical quality control ; Control system analysis ; Covariance matrix ; Heuristic methods ; Probability density function ; Probability distributions ; Quality assurance ; Quality function deployment ; Robustness (control systems) ; Statistical process control ; Total quality management ; Quality control
  8. Source: International Journal of Advanced Manufacturing Technology ; Volume 43, Issue 9-10 , 2009 , Pages 964-981 ; 02683768 (ISSN)
  9. URL: https://link.springer.com/article/10.1007/s00170-008-1774-0