Automating operating procedure synthesis for batch processes: Part I. Knowledge representation and planning framework

Abstract

Automating the synthesis of operating procedures for batch processes is very valuable as plant personnel often spend considerable amount of time and effort in preparing and verifying them for correctness and completeness. Towards this goal, a framework for automating operating procedure synthesis for batch processes is proposed in this paper. We propose an approach based on Grafcet, a discrete event modeling concept, to represent procedural knowledge combined with an object-oriented representation of the declarative knowledge. Grafcet is also used to model the information; called inferred knowledge, that is incrementally generated during operating procedure synthesis. The details of the basic components and the advanced features of Grafcet that make it a suitable technique for modeling the procedural and inferred knowledge are presented. A hierarchical planning strategy is proposed that uses the declarative and procedural knowledge to generate the inferred knowledge incrementally, which leads to the synthesis of the operating procedures. The implementation of this framework and its application to an industrial case study are presented in Part II.