Dynamic optimization for batch design and scheduling with process model uncertainty

Design and planning for multiproduct batch plants involves decisions from facility design, product scheduling, inventory planning, etc. These have been addressed for recipe-based processes with fixed stage processing times, although there is significant benefit in incorporating detailed dynamic process models while planning and addressing the overall problem simultaneously (Bhatia, T.; Biegler, L. T. Ind. Eng. Chem. Res. 1996, 35 (7), 2234-2246). However, incorporating processing decisions adequately requires sufficiently accurate nonlinear process models and methods that deal with process model uncertainty. This work simultaneously addresses dynamic processing and planning decisions for multiproduct batch plants, with uncertainty in process parameters. Instances of uncertain parameters are used to construct planning scenarios that are addressed through a multiperiod formulation. In addition, dynamic processing under uncertainty is addressed via a closed loop state feedback correction strategy. In addition, to provide an implementation advantage, parameters in the feedback law are determined in an open loop manner, as design variables that remain invariant across the scenarios in the multiperiod formulation.