COMPUTER-AIDED KNOWLEDGE-BASED MONITORING AND DIAGNOSTIC SYSTEM FOR EMULSION POLYMERIZATION

摘要

A knowledge-based system (KBS) has been developed for an emulsion polymerization process. The reactor operation is carried out in batch and semi-batch modes. The system incorporates both quantitative and qualitative modelling framework. Mathematical models developed for the polymerization process includes partial and integro-partial differential equations. The model predictive control algorithm allows the manipulation of temperature, the flow rates of monomers (styrene and methyl methacrylate MMA), the surfactant and the initiator to control the particle size distribution (PSD) and the molecular weight distribution (MWD). The expert system provides continuous support, fault rectification, process monitoring and maintaining functionality with safety, as well as retaining process continuity. Process events such as particle growth stages and secondary nucleation are analysed by the rule-based expert system. The expert system provides diagnostic and decision support to the operator. The decision support system (DSS) incorporates several features such as intelligent polymer recipe input interface to pre-select optimal control operations. The expert system was put to test on the actual facility and has been aiding the operator running the facility. Multi-way principal component analysis (MPCA) provides intelligent statistical monitoring, which is integrated into our expert system. Multi-way partial least squares (MPLS) provides prediction for MWD, providing additional benchmark for optimal product quality control. The application of our integrated modelling and control system is described.