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Multivariate variability monitoring using EWMA control charts based on squared deviation of observations from target
Author(s) -
Memar Ahmad Ostadsharif,
Niaki Seyed Taghi Akhavan
Publication year - 2011
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.1196
Subject(s) - ewma chart , multivariate statistics , univariate , statistics , standard deviation , statistic , control chart , mathematics , multivariate analysis , mean squared error , statistical process control , computer science , process (computing) , operating system
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. Copyright © 2011 John Wiley & Sons, Ltd.