Robust optimization framework for process parameter and tolerance design

Abstract

This article introduces a framework for including different uncertainties at the chemical plant design stage. Through an integrated robust optimization approach and problem formulation, equipment, operating, control, and quality costs are simultaneously taken into account, leading to system, parameter, and tolerance design. Rather than using single pointwise solutions in the decision space, operating windows leading to overall best performance are identified and defined. Such windows and their width allow us to point out control needs and goals at a very early stage of plant design. Two small-scale case studies (for a CSTR and a batch distillation column) provide enough evidence to support the practicality of the optimization framework: the robust solutions found are different and much better than the corresponding solutions obtained with the fully deterministic optimization paradigms.