Multiobjective temperature trajectory optimization for unseeded batch cooling crystallization of aspirin

Abstract

Batch cooling crystallization is a type of crystallization wherein supersaturation is brought about by reducing the temperature of the crystallization system with time. It is commonly used in the chemical and pharmaceutical industries to manufacture a wide variety of crystalline products. This work deals with multiobjective optimization of unseeded batch cooling crystallization of Aspirin. A novel method involving temperature changes rather than temperatures of the crystallization mixture over time has been discussed in this study. Optimization studies were carried out to minimize the coefficient of variation and maximize mean size. Optimization was carried out using the benchmark NSGA-II and NSGA-II hybrid optimizers available in MATLAB. A standard algorithm to select a trade-off point on the Pareto front is also discussed. Rigorous simulation studies were carried out to determine the best temperature trajectory by inspecting the crystal size distributions generated using the method of characteristics.