Online Monitoring of Batch Process using Sub-phase based Principal Component Analysis

Methods based on multivariate statistical projection analysis have been widely applied for batch processes monitoring. However, conventional methods are linear ones that can only model linear combinations of variables and most batch processes are non-linearity. Traditionally, in process modeling, two solutions for non-linearity have been implemented: non-linear models and local linear models. In this paper, a novel methodology named Sub-phase based Principal Component Analysis (SPPCA), which integrates methods of operation phase detection and a novel multi-way principal component analysis (MPCA), is approached. A case study from a simulated fed-batch penicillin cultivation process indicates the efficacy of approach.