Intelligent Manufacturing Technology Of Polyvinyl Chloride

Data mining, a rising technique nowadays, combines many advanced techniques, such as artificial intelligence, computational intelligence, pattern recognition, statistic etc., to mine and discover valuable and hidden knowledge from databases. Vinyl chloride suspension polymerization is widely studied by making full use of data mining in this paper. Many achievements about quality modeling of polyvinyl chloride (PVC), dynamic modeling of polymerization and optimization of initiation system are gained, and intelligent manufacturing technology (IMT) of PVC based on technology integration is presented.Firstly, the status of research and major achievements in the research of data mining technique in the chemical process are reviewed. Some primary methods in data mining are introduced including methods of artificial neural network (ANN), genetic algorithm (GA), genetic programming (GP), principal component analysis (PCA), partial least square (PLS), rough set (RS), etc. The application prospect, existing problems which needed solving for further developing are analyzed.Aimed at the importance of PVC particle feature, the regression model of the mean grain diameter is developed by using multiple nonlinear regression. The optimum operational conditions about the concentration of dispersant and nano-CaCO3 microemulsion is attained by using trend surface analysis.Inferential estimation of PVC quality using stacked neural networks - ridge regression (SNNs-RR) approach is studied, and determination of appropriate weights for combining individual networks using ridge regression is proposed. Neural network generalization capacity can be improved by combining several neural networks. The results obtained demonstrate significant improvements in model accuracy and robustness, as a result of using SNNs model, compared to using single neural network model.Based on heat transfer process form the reactants to the reactor wall and from the inner wall to the coolant in the jacket, the dynamic heat balances for the PVC reactor is developed. Since the changes in both the mass of the reactants in the reactor and its specific heat are considered, the model can be used to exactly describe the dynamic characteristic of vinyl chloride suspension polymerization. The analysis of the reactionrate, conversion and the rate of water draining is provided.In order to take full advantage of the PVC reactor cooling capacity, the polymerization rate must be kept approximately constant at a level which yields a reaction rate equal to the common maximum cooling capacity of the system. The common solution to this problem is to use a combination of rapid and slow initiators. The optimal formulation of initiation system is studied as an optimization problem based on reaction kinetics. The optimization model of initiation system is developed, and optimization of initiation system containing two initiators is successfully implemented.IMT of PVC based on technology integration is presented. Its objective is the harmonious integration of the dynamic model of vinyl chloride suspension polymerization, advanced sensors, multivariable statistical approaches and advanced process control strategy. It relates to dynamic simulation technique of vinyl chloride suspension polymerization, advanced control and soft sensor technique, process performance monitoring and diagnosis, etc.An effective research approach about improving quality of PVC by using information technology is provided. The results might be helpful to correlative study (advanced control, on-line optimization, diagnosis, etc.) in vinyl chloride suspension polymerization. The achievements also provide a basis for the further application of IMT in the production of others polymer, and provide an instantiation for the application of data mining in chemical process.