Abstract
In industrial manufacturing, most batch processes are inherently multistage/multiphase in nature. To ensure both quality consistency of the manufactured products and safe operation of this kind of batch process, different multivariate statistical process control (MSPC) methods have been proposed in recent years. This paper gives an overview of multistage/multiphase statistical process control methods used for process analysis, monitoring, quality prediction and online quality improvement. Different types of phase divisions and modeling strategies are introduced and the method properties are discussed. For comparisons, a selection guide to these methods for different application purposes is provided. Finally, some promising research directions are suggested based on existing works. © 2009 Elsevier Ltd. All rights reserved.