Abstract
In order to achieve satisfactory monitoring, multivariate statistical process models should well reflect process nature. In manufacturing systems, many batch processes are inherently multiphase. Usually, different phases have different characteristics, while gradual transitions are often observed between phases. Another important feature of batch processes is the unevenness of operation durations. Especially, in multiphase batch processes, the situation becomes more complicated. In this study, a batch process modelling and monitoring strategy is proposed based on Gaussian mixture model (GMM), which can automatically extract phase and transition information for uneven-duration batch processes. The application results verify the effectiveness of the proposed method. © 2011 Canadian Society for Chemical Engineering.