Determination of the relative importance of process factors on particle size distribution in suspension polymerization using a Bayesian experimental design technique

The use of a Bayesian experimental design technique to determine the relative importance of factors that control particle size distribution (PSD) in suspension copolymerization of styrene and divinylbenzene is reported. Six factors and two responses are considered in this study. The experimental trials are of the two-level factorial type designed with a Bayesian method. The experiments were carried out in a 5-L pilot plant reactor. The matrix of variances of the parameter means (the prior knowledge) was estimated with the use of a preliminary compartment-mixing (CM) model for PSD in suspension polymerization and our subjective judgement (process understanding). The responses, mean particle size and coefficient of variation, were calculated from distributions obtained with a Coulter particle counter. The results of this study provided the criteria needed to guide the future improvement of our CM-PSD model in a balanced and effective way. (c) 2006 Wiley Periodicals, Inc.