Decision support for process development in the chemical industry

Process development in chemical industry is a multiobjective optimization problem. Objectives of this optimization are for example product quality, raw material and investment cost, energy efficiency, reliability or health, safety, and environmental issues. Parameters for this optimization are, e.g., feed stock, utilities, process configuration, equipment, operating parameters, and site. In process design, the developer usually generates a certain number of process variants by varying process parameters intuitively. The process is usually stopped if a solution is found that is acceptable regarding all or at least most criteria, optimality cannot be guaranteed. The present paper describes a feasible alternative approach, which is a real multiobjective optimization based on the Pareto optimality concept. The Pareto front describes a set of solutions where no improvement in one objective can be reached without at least getting worse in another objective. The Pareto front a llows investigating the trade-offs between different objectives, but the final choice of the design is left to the user. In the present work the multiobjective optimization is used together with a decision support system, which allows navigating within the Pareto front and thereby finding the best compromise between the objectives in a rational and efficient way.