Agent-based intelligent system development for decision support in chemical process industry |
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| Authors: | Ying Gao Zhigang Shang Antonis Kokossis |
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| Affiliation: | 1. Department of Chemical and Process Engineering, University of Surrey, Guildford, Surrey GU2 7XH, UK;2. Department of Process and Systems Engineering, School of Engineering, Cranfield University, Cranfield MK43 0AL, UK;1. Otto-Schott-Institut, Friedrich-Schiller-University Jena, Fraunhoferstr. 6, 07743 Jena, Germany;2. Fraunhofer Institute for Machine Tools and Forming Technology IWU, Reichenhainer Strasse 88, 09126 Chemnitz, Germany;1. Institute for Energy Technology, Physics Department, P.O. Box 40, NO-2027 Kjeller, Norway;2. SINTEF Materials and Chemistry, Forskningsveien 1, NO-0314 Oslo, Norway;1. High Temperature Energy Materials Research Center, Korea Institute of Science and Technology, Seoul 136-791, Republic of Korea;2. School of Chemical Engineering, Chonbuk National University, Jeonju 561-756, Republic of Korea |
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| Abstract: | This paper presents an agent-based intelligent system to support coordinate manufacturing execution and decision-making in chemical process industry. A multi-agent system (MAS) framework is developed to provide a flexible infrastructure for the integration of chemical process information and process models. The system comprise of a process knowledge base and a group of functional agents. Agents in the system can communicate and cooperate with each other to exchange and share information, and to achieve timely decisions in dealing with various scenarios in process operations and manufacturing management. Process simulation, artificial intelligent technique, rule-based decision supports are integrated in this system for process analysis, process monitoring, process performance prediction and operation suggestion. The implementation of this agent-based system was illustrated with two case studies, including one application in process monitoring and process performance prediction for a chemical process and one application in de-bottlenecking of a site utility system. |
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