Abstract
Intelligent process control requires theoretical and experimental knowledge of physical processes combined with the judgement and experience of experts in plant operations and management. An effective integration of these components depends on effective communication.
The objective of this paper is to propose visual modelling as a knowledge acquisition tool for eliciting, integrating and formalizing the three different types of knowledge into a knowledge base for intelligent process control. The approach is illustrated by the manufacturing processes in the annealing of copper wire and the galvanizing of steel.
Research partly supported by the High Temperature Project at Rensselaer Polytechnic Institute sponsored by the New York State Energy and Development Authority.
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© 1992 Springer-Verlag Berlin Heidelberg
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Schmidt, D., Haddock, J., Wallace, W.A., Wright, R. (1992). Visual modelling: A knowledge acquisition method for intelligent process control systems. In: Belli, F., Radermacher, F.J. (eds) Industrial and Engineering Applications of Artificial Intelligence and Expert Systems. IEA/AIE 1992. Lecture Notes in Computer Science, vol 604. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0024981
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DOI: https://doi.org/10.1007/BFb0024981
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