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Fusing data-mining and knowledge elicitation for the supervisory control of an aluminium plate mill

Browne, W.N., Yao, L., Postlethwaite, I., Lowes, S. and Mar, M. (2006) Fusing data-mining and knowledge elicitation for the supervisory control of an aluminium plate mill. Engineering Applications of Artificial Intelligence, 19 (3). pp. 345-359. ISSN 0952-1976

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To link to this item DOI: 10.1016/j.engappai.2005.09.005

Abstract/Summary

Knowledge-elicitation is a common technique used to produce rules about the operation of a plant from the knowledge that is available from human expertise. Similarly, data-mining is becoming a popular technique to extract rules from the data available from the operation of a plant. In the work reported here knowledge was required to enable the supervisory control of an aluminium hot strip mill by the determination of mill set-points. A method was developed to fuse knowledge-elicitation and data-mining to incorporate the best aspects of each technique, whilst avoiding known problems. Utilisation of the knowledge was through an expert system, which determined schedules of set-points and provided information to human operators. The results show that the method proposed in this paper was effective in producing rules for the on-line control of a complex industrial process.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science
ID Code:15157
Uncontrolled Keywords:Fusing data-mining methods; Metal rolling

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