Quality-related prediction and monitoring of multi-mode processes using multiple PLS with application to an industrial hot strip mill

摘要

This paper is focused on the development of the quality prediction and fault detection schemes for the industrial hot strip mill process (HSMP). Considering that the pure partial least squares (PLS) model is based on the assumption of a single operating mode, in this paper, a multiple PLS based method is proposed. The new method address the multi-mode problem in HSMP with the Gaussian mixture model (GMM), then the advantage of original PIS is subsequently followed to achieve the quality prediction and monitoring goals. Meanwhile, a new probabilistic fault detection index called quality-related fault probability index is also developed for the fault detection purpose. Finally, the whole proposed scheme is exercised with the real industrial data, and performances are evaluated by comparing with other existing methods. (C) 2015 Elsevier B.V. All rights reserved.