Monitoring location and scale of multivariate processes subject to a multiplicity of assignable causes

Abstract

This paper presents a fully adaptive multivariate statistical process control scheme for processes where multiple assignable causes may occur. The assignable causes affect both the mean vector and the covariance matrix, monitored by a T2 chart and a control chart based on entropy, respectively. Markov chain theory is employed to model the stochastic operation of the proposed scheme and optimize its economic-statistical operation. A numerical investigation and a sensitivity analysis are conducted in order to evaluate the performance and investigate the robustness of the model. A real example is employed to illustrate the operation of the scheme.

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