KNOWLEDGE REPRESENTATION AND REASONING IN THE PRESENCE OF UNCERTAINTY IN AN EXPERT SYSTEM FOR LABORATORY REACTOR SELECTION

This paper is concerned with modeling and computer implementation of the process of selecting multiphase reactors for a given application. The qualitative reasoning process is modeled using an expert system architecture. Uncertainty in the input data is handled using the theory of fuzzy sets. Uncertainty in the decision-making process is modeled using the analytic hierarchy process (AHP) adapted from the field of economics. The system is implemented using a commercial expert system shell. The work demonstrates the feasibility and utility of creating expert systems to encapsulate knowledge used by experts in chemical process and reaction engineering.