Strategies for the simultaneous optimization of the structure and the process variables of a protein production plant

Abstract

Process performance models for a multiproduct batch protein plant are used to exploit alternative strategies in the optimization of both the process variables and the structure of the plant. Simple process performance models are used to describe the unit operations, which renders explicit expressions for the size and time factor model in the design of batch plants. In the proposed approach the process variables are optimized regardless the plant structure constraints, which are left as a posterior decision. This optimization is done in a single product-free intermediate storage (SP-FIS) scenario, unbiased with any plant structure. The approach is compared to the case of recipe values for the process variables and to the best optimal solution for the nonconvex mixed integer nonlinear program (MINLP), which arises when simultaneously optimizing the structure and the process variables. This last optimization model is hard to solve and its global solution remains as an open problem. The proposed approach generates solutions very close to the ones obtained from nonconvex MINLP and is quite superior than simply resorting to recipes. We also study the role of process variables in this approach. It is found that they behave as in continuous processes by trading off cost components, with a smooth dependence on the overall cost. Moreover, for feasible designs that include the size and time constraints that correspond to the plant structure, the process variables accommodate the size and time factors to reduce idle times and equipment under-occupancy.