A HIERARCHICAL APPROACH TO SIMULTANEOUS DESIGN OF PRODUCTS AND PROCESSES

Product and process design involve algorithmic and heuristic processin g of symbolic and numeric data. Therefore, for such a design task, a h ybrid approach that interweaves numerical and heuristic paradigms is w arranted. The increasing rigor in modeling along with the necessary kn owledge feedback results in a generalized system architecture that for ms the basis of this paper. The approach is implemented using KAPPA on a Sun SPARC 5 station. The superstructure developed using the heurist ic method is optimized with respect to the choice of technology, opera ting conditions, the technology sequencing, and the stream flows using Mixed Integer (Non) Linear Programming (MI(N)LP). Product design invo lves relating product mix and processing conditions to various product characteristics. The multi-objective approach called for this type of problem is addressed through relative weighing of the objectives in t he objective function. The lumped parameters used are derived from det ailed distributed models using a two-tier approach. The first example used is porous matrix-polymer composite design through impregnation an d surface treatment. A second example on catalyst design is also used. The rigorous models utilize a genetic algorithm for search in the dis crete variable space. Learning from the rigorous models is used to upd ate the process flowsheets as well as the knowledge bases.