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

Abstract

Hoteling's T2 control charts are widely used in industries to monitor multivariate processes. The classical estimators, sample mean, and the sample covariance used in T2 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 T2 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.

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