Batch Polymerization Monitoring Using MEWA and MPCA

ALVAREZ MEDINA CARLOS RODRIGO; ADRIANA BRANDOLÍN; MABEL SÁNCHEZ

Salt Lake City- Utah- USA

Congreso; 2007 AIChE Annual Meeting; 2007

In this work a multivariate exponential weighted moving average (MEWMA) method is applied to take into account the batch history when the time-wise unfolding is applied. MEWMA method may be applied before or after obtaining the PCA model, resulting MEWMA-PCA and PCA-MEWMA respectively. By choosing an appropriate value of the weighting parameter of the MEWMA method, the batch history can be properly included. The system under study is the batch polymerisation of styrene using dibenzoyl peroxide as initiator. Based on a non-linear model of the process, an optimal temperature profile (set point) is designed that minimizes the batch time and ensures satisfaction of a number of constraints on the reactor and jacket temperature, monomer conversion, the product’s molecular weight and the coolant flow rate. The process is controlled by measuring the reactor temperature, and by manipulating the coolant flow rate. Results obtained by the proposed method are compared with the ones provided by the classical MPCA.