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Decision-making in preliminary engineering design

Published online by Cambridge University Press:  27 February 2009

S. P. Joshi ,
J. R. Umaretiya  and
Sanjay B. Joshi
S. P. Joshi
Affiliation:
Department of Aerospace, The University of Texas at Arlington, Arlington, TX 76019, U.S.A.
J. R. Umaretiya
Affiliation:
Structural Analysis Technology, 4677 Old Ironsides Drive, Santa Clara, CA 95054, U.S.A.
Sanjay B. Joshi
Affiliation:
Industrial and Management System Engineering, The Pennsylvania State University, University Park, PA 16802, U.S.A.
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Abstract

A designer often has to deal with complex and ill-structured situations during specification synthesis and preliminary engineering design. To assist in the development of computer-aided design systems, it is desirable to capture the designers decision-making process during these design states. The research presented in this paper is towards this direction. Based on the conceptual understanding of the process, three postulates are presented. The following two postulates; (1) the decisions are neither optimum nor just satisfying but retain certain characteristics of both, (2) the design is driven by the important objective(s) among all the specified objectives, at the preliminary design, although the remaining objectives do have a weak influence on the preliminary design; are used to develop a compensatory and a non-compensatory model of the decision-making. These models are formulated with the help of fuzzy set theory and they implicitly or explicitly follow the two postulates. These models are suitable for discrete decision situations where the above mentioned postulates apply. Examples of material selection during a preliminary structural design are used to illustrate the effectiveness of these models.

Type
Research Article
Information
AI EDAM , Volume 5 , Issue 1 , February 1991 , pp. 21 - 30
Copyright
Copyright © Cambridge University Press 1991

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References

Diaz, A. R. 1989. A strategy for optimal design of hierarchical system using fuzzy sets. NSF Engineering Design Research Conference, University of Massachusetts, Amherst, June 11–14.Google Scholar
Dong, Z. 1987. Evaluating design alternatives and fuzzy operations. International Conference on Engineering Design, Boston, MA, August 17–20, 322–329.Google Scholar
Goicoechea, A., Hansen, D. R. and Duckstein, L. 1982. Multiobjective Decision Analysis with Engineering and Business Applications. New York: John Wiley.Google Scholar
Hwang, C. and Yoon, K. 1981. Multiple Attribute Decision Making: A Slate-of-the-Art Survey. New York: Springer-Verlag.CrossRefGoogle Scholar
Kacprizyk, J. 1983. Multistage Decision-Making Under Fuzziness. Cologne: Verlag Tüv Rheinland GmbH.Google Scholar
Kickert, W. J. M. 1981. Organization of Decision-Making: A Systems Theoretical Approach. Amsterdam: North Holland.Google Scholar
Lewin, K., Dembo, T.Festinger, L., Sears, P. S. 1944. Levels of aspiration. In: Hunt, J. M. (Ed.) Personality and the Behavior Disorder. New York: The Ronald Press.Google Scholar
Lindblom, C. E. 1959. The science of muddling through. Public Administration Review 9, 79–88.CrossRefGoogle Scholar
Simon, H. A. 1945. Administrative Behavior. New York: Free Press.Google Scholar
Umaretiya, J. R., Joshi, S. P. and Joshi, S. B. 1990. An intelligent specifications extraction interface for structural design. Engineering with Computers, 6, 153–165.CrossRefGoogle Scholar
Wood, K. L. and Antonsson, E. K. 1987. Engineering design-computational tools in the SYNTHESIS domain. The Study of the Design Process: A Workshop, Ohio State University, February 8–10, 1987.Google Scholar
Zadeh, L. A. 1965. Fuzzy sets. Information and Control 8, 338–353.CrossRefGoogle Scholar
Zeleny, M. 1980. Descriptive decision making and its application. Applications of Management Science 1, 327–388.Google Scholar
Zeleny, M. 1982. Multiple Criteria Decision Making. New York: McGraw-Hill.Google Scholar