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Keywords:

  • breakdown point;
  • multivariate robust estimation of location and scatter;
  • multivariate control charts;
  • outliers;
  • Hotelling's T2

Abstract

Use of Hotelling's T2 charts with high breakdown robust estimates to monitor multivariate individual observations are the recent trend in the control chart methodology. Vargas (J. Qual. Tech. 2003; 35: 367-376) introduced Hotelling's T2 charts based on the minimum volume ellipsoid (MVE) and the minimum covariance determinant (MCD) estimates to identify outliers in Phase I data. Studies carried out by Jensen et al. (Qual. Rel. Eng. Int. 2007; 23: 615-629) indicated that the performance of these charts heavily depends on the sample size, amount of outliers and the dimensionality of the Phase I data. Chenouri et al. (J. Qual. Tech. 2009; 41: 259-271) recently proposed robust Hotelling's T2 control charts for monitoring Phase II data based on the reweighted MCD (RMCD) estimates of the mean vector and covariance matrix from Phase I. They showed that Phase II RMCD charts have better performance compared with Phase II standard Hotelling's T2 charts based on outlier free Phase I data, where the outlier free Phase I data were obtained by applying MCD and MVE T2 charts to historical data. Reweighted MVE (RMVE) and S-estimators are two competitors of the RMCD estimators and it is a natural question whether the performance of Phase II Hotelling's T2 charts with RMCD and RMVE estimates exhibits similar pattern observed by Jensen et al. (Qual. Rel. Eng. Int. 2007; 23: 615-629) in the case of MCD and MVE-based Phase I Hotelling's T2 charts. In this paper, we conduct a comparative study to assess the performance of Hotelling's T2 charts with RMCD, RMVE and S-estimators using large number of Monte Carlo simulations by considering different data scenarios. Our results are generally in favor of the RMCD-based charts irrespective of sample size, outliers and dimensionality of Phase I data. Copyright © 2010 John Wiley & Sons, Ltd.