Applying analogical problem solving to mechanical design

Abstract Design automation holds great benefits for mechanical-product development. In addition to saving engineers from having to carry out redundant tasks, mechanical design automation can also provide embodiment of knowledge, reduced dowstream manufacturing costs, reduced manual errors and more reliable designs. Most of the approaches to mechanical design automation, thus far, have required a large amount of domain-specific knowledge (e.g. expert systems), and/or have had to presume a particular style of design problem solving (e.g. top-down decomposition, bottom-up constructive). The paper proposes analogical problem solving as an approach for alleviating some of these inherit problems in mechanical design automation. Analogical problem solving is based on the fundamental principle that problem solving can be assisted by the review of solutions to past problems that have been attempted. The technique and issues related to the application of analogical problem solving to mechanical design are presented.

[1]  J S Arora,et al.  Uses of artificial intelligence in design optimization , 1986 .

[2]  Steven Hyung Kim,et al.  A General Model of Design: Formalization and Consequences , 1988 .

[3]  Jack Mostow.  Why are design derivations hard to replay , 1986 .

[4]  J Rinderle.  Function and form relationships : a basis for preliminary design , 1987 .

[5]  Clive L. Dym,et al.  PRIDE: An Expert System for the Design of Paper Handling Systems , 1986, Computer.

[6]  Kristian J. Hammond,et al.  Chapter 8 – Case-based Planning , 1989 .

[7]  Rogers P. Hall,et al.  Computational Approaches to Analogical Reasoning: A Comparative Analysis , 1989, Artif. Intell..

[8]  John R. Dixon,et al.  A review of research in mechanical engineering design. Part I: Descriptive, prescriptive, and computer-based models of design processes , 1989 .

[9]  David C. Brown,et al.  Knowledge and Control for a Mechanical Design Expert System , 1986, Computer.

[10]  Nam P. Suh,et al.  Application of symbolic logic to the design axioms , 1985 .

[11]  Richard Fikes,et al.  Learning and Executing Generalized Robot Plans , 1993, Artif. Intell..

[12]  Saul Amarel,et al.  Artificial intelligence and design , 1990, Proceedings of the 5th Jerusalem Conference on Information Technology, 1990. 'Next Decade in Information Technology'.

[13]  David C. Brown,et al.  Design Problem Solving: Knowledge Structures and Control Strategies , 1989 .

[14]  Jaime G. Carbonell,et al.  An Overview of Machine Learning , 1983 .

[15]  Jack Mostow,et al.  Design by Derivational Analogy: Issues in the Automated Replay of Design Plans , 1989, Artif. Intell..

[16]  Janet L. Kolodner,et al.  Retrieval and organizational strategies in conceptual memory: a computer model , 1980 .

[17]  Richard Fikes,et al.  STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving , 1971, IJCAI.