Abstract
A mixed-suspension, mixed-product removal (MSMPR) draft-tube-baffle crystallizer was used to estimate lactose crystallization kinetic rates under different processing conditions. The processing parameters investigated were the degree of supersaturation (S), agitation speed (rpm), the amount of seed (seed), and residence time (τ). Crystallization kinetic rates, including nucleation, growth, and aggregation rates, were calculated from the experimental crystal size distributions (CSD) via a moment transformation method. Two approaches were used to develop a correlation between the processing conditions and kinetic rates. The conventional power law approach estimated the model parameters of an assumed functional form via regression analysis. An artificial neural network (ANN) approach was also used. ANN does not require an assumed function, it develops a function by learning from the experimental processing conditions and kinetic pairs. The results showed that the ANN approach gave a much better prediction of...
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