Table of Contents
Journal of Quality and Reliability Engineering
Volume 2013, Article ID 542305, 14 pages
Research Article

Robust Control Charts for Monitoring Process Mean of Phase-I Multivariate Individual Observations

Department of Mathematics and Statistics, Memorial University of Newfoundland, St. John's, NL, Canada A1C 5S7

Received 22 November 2012; Revised 22 March 2013; Accepted 2 April 2013

Academic Editor: Adiel Teixeira de Almeida

Copyright © 2013 Asokan Mulayath Variyath and Jayasankar Vattathoor. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Hoteling's control charts are widely used in industries to monitor multivariate processes. The classical estimators, sample mean, and the sample covariance used in control charts are highly sensitive to the outliers in the data. In Phase-I monitoring, control limits are arrived at using historical data after identifying and removing the multivariate outliers. We propose Hoteling's control charts with high-breakdown robust estimators based on the reweighted minimum covariance determinant (RMCD) and the reweighted minimum volume ellipsoid (RMVE) to monitor multivariate observations in Phase-I data. We assessed the performance of these robust control charts based on a large number of Monte Carlo simulations by considering different data scenarios and found that the proposed control charts have better performance compared to existing methods.