Knowledge-based systems are a special class of computer programs that purport to perform, or to assist humans in performing, specified intellectual tasks. This paper describes how knowledge-based programs are special; that is, how they differ from other computer programs. A structure for understanding the use of knowledge-based programs in engineering design is presented, together with an example. The role of knowledge-based systems in design research is discussed.

Issue Section:
Research Papers
Topics:
Design, Computer software, Engineering design
1.
Antonsson
E.
, and
Otto
K.
,
1991
, “
Trade-off Strategies in Engineering Design
,”
Research in Engineering Design
, Vol.
3
, No.
2
, pp.
87
–
104
.
2.
Barr, A., and Fiegenbaum, E., 1981, The Handbook of Artificial Intelligence, Vols. 1, 2, and 3, Wm Kaufman, Inc., Los Altos, CA.
3.
Brown, D., 1985, “Capturing Mechanical Design Knowledge,” Proceedings of the ASME Computers in Engineering Conference, Boston, MA, August 4–8.
4.
Dixon, J. R., and Simmons, M. K., 1984, “Computers that Design: Expert Systems for Mechanical Engineers,” Computers in Mechanical Engineering, November.
5.
Dixon, J., Jones, C, Nielsen, E., Luby, S., and Libardi, E., 1986, “Knowledge Representation in Mechanical Design Systems,” SAE Technical Paper Series 860335, SAE International Conference, Detroit, MI, February 24–27.
6.
Dixon, J. R., and Poli, C, 1995, Engineering Design and Design for Manufacturing—A Structured Approach: Text and Reference for Mechanical Engineers, in press.
7.
Hayes-Roth, F., Waterman, D. A., and Lenat, D. B., 1983, Building Expert Systems, Addison-Wesley.
8.
Howe, A., Cohen, P. R., Dixon, J. R., and Simmons, M. K., 1986, “Dominic: A Domain Independent Program for Mechanical Engineering Design,” Artificial Intelligence in Engineering, Vol. 1, No. 1.
9.
Mistree, F., Karandikar, H., and Kamal, S., 1985, “Knowledge-Based Mathematical Programming: A Hybrid Approach for Decision Making in Design,” Proceedings of the I.F.I.P. Working Group 5.2, Working Conference for Design Theory for Computer-Aided-Design, Tokyo, Japan, October.
10.
Nicklaus, D., Tong, S., and Russo, D., 1987, “Engineous, A Knowledge Directed Computer Aided Design Shell,” Proceedings of the Third IEEE Conference on Artificial Intelligence Applications, February 22–28.
11.
Nielsen, E. H., Dixon, J. R., and Simmons, M. K., 1986, “GERES: A Knowledge-Based Material Selection Program for Injection Molded Resins,” Proceedings 1986 ASME Computers in Engineering Conference, Chicago, IL, July 20–24.
12.
Orelup, M. F., Dixon, J. R., Cohen, P. R., and Simmons, M. K., 1987, “Dominic II: Meta-Level Control in Iterative Resign,” Proceedings, Intelligent and Integrated Manufacturing Analysis and Synthesis, ASME PED-Vol. 25, Boston, MA, December 13–18.
13.
Orelup, M. F., 1992, “Dominic III: Incorporating Taguchi Philosophy, Material Choice, and Memory in the Design of Mechanical Components,” Ph.D. Dissertation, University of Massachusetts, Amherst, May.
14.
Otto, K., and Antonsson, E., 1991, “Tuning Parameters in Engineering Design,” Proceedings of the 1991 ASME DTM Conference, DE Volume 31, Miami, FL.
15.
Pugh, S., 1990, Total Design, Addison-Wesley.
16.
Thurston, D., and Crawford, C., 1991, “Integration of Utility Analysis and Rule Based Systems for Design Evaluation,” Proceedings of the 1991 NSF Design and Manufacturing Systems Conference, University of Texas, Austin, TX, January 9–11.
17.
Thurston, D., and Tian, Y., 1991, “A Method for Integrating Utility Analysis into an Expert System for Design Evaluation Under Uncertainty,” Proceedings of the Seventh Conference on Uncertainty in AI, UCLA, Los Angeles, July 13–15.
18.
Ward, A., and Seering, W., 1989, “Quantitative Inference in a Mechanical Design Compiler,” Proceedings of the First International Conference on Design Theory and Methodology, Montreal, Canada.
This content is only available via PDF.
Copyright © 1995
 by The American Society of Mechanical Engineers
You do not currently have access to this content.