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A network based expert system for intelligent design of mechanisms

Published online by Cambridge University Press:  27 February 2009

Sridhar Kota,
Arthur G. Erdman,
Donald R. Riley,
Albert Esterline and
James R. Slagle
Sridhar Kota
Affiliation:
Department of Mechanical Engineering and Applied Mechanics, University of Michigan, Ann Arbor, U.S.A.
Arthur G. Erdman
Affiliation:
Department of Mechanical Engineering, University of Minnesota, U.S.A.
Donald R. Riley
Affiliation:
Department of Mechanical Engineering, University of Minnesota, U.S.A.
Albert Esterline
Affiliation:
Department of Computer Science, University of Minnesota, U.S.A.
James R. Slagle
Affiliation:
Department of Computer Science, University of Minnesota, U.S.A.
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Abstract

Linkage-type mechanisms have numerous applications in industry especially for automation Unfortunately, they are less popular due to lack of proper design tools. This paper describes our efforts to remove the technological barrier in mechanisms design automation. Although the ideas presented apply to automation of mechanisms design in general, the paper discusses the development of an expert system for a particular sub-set of mechanisms called Dwell mechanisms.

Many essential and desirable motion characteristics of mechanisms are so implicit that they are difficult to control by analytical methods. By systematically and extensively studying the entire motion characteristics of hundreds of linkages, a comprehensive classification system and heuristics were developed. This qualitative classification scheme led to a finite set of linkage models that cover the entire design space in the sense that any possible design falls under one or more of the models. Our system, called Dwell-Expert, incorporates this design expertise to select the best linkage model for a given set of design specifications and to compare that model against alternatives. The new design methodology and its implementation in AGNESS (A Generalized Network-based Expert System Shell) are explained. A design example is also presented. Our system can reduce even an experienced designer’s initial-design time from a day or more to a minute or less, assuming specifications have already been formulated. Such results motivate extension of this design methodology to other areas of mechanical design and engineering design in general.

Information

Type
Research Article
Information
AI EDAM , Volume 2 , Issue 1 , February 1988, pp. 17 - 32
Copyright
Copyright © Cambridge University Press 1988

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