Perspectives on model based integration of process operations

Abstract The chemical process industry has increasingly been pursuing the use of computing technology to gather, organize, disseminate and exploit enterprise information and to closely coordinate the decisions made at the various levels of the process operational hierarchy so as to optimize overall corporate objectives. The thesis advanced in this paper is that mathematical programming models and solution methods offer the most effective tools for integration of the tactical and strategic levels of the operational hierarchy. To that end, existing strategies for implementing model-based integrated applications are reviewed. Four classes of examples of integration are presented: scheduling of multiproduct plants, large-scale model predictive control, integration of planning and scheduling across single and multiple plant sites and design of multipurpose batch plants under uncertainty. The methodology used to address these model-based integration instances successfully accomodates the key features of process operations: diverse time scale, multiple reference frameworks, spatial and organizational aggregation/disaggregation and uncertainty in the enterprise information. The applications further demonstrate that for the foreseeable future no single model or reference framework will be sufficient and efficient for treating all aspects of the process operations hierarchy.