Abstract
In this paper, engineering design is considered from the point of view of modeling i.e. the construction and manipulation of models of (possible) physical realities. Consequently, the design activity has been analysed in terms of patterns of inference called model transmutations. Three categories of transmutations namely, transformations, combinations and retrievals, have been discussed with reference to the Multimodeling approach for representing physical systems. The major goal of the paper is to provide a conceptual framework for analysing existing design systems and for addressing questions concerning their competence such as what types of inference patterns underlie different design strategies e.g. top-down, compositional and analogical design; what kind of design solutions a design system is able to generate from what kind of input specification and prior design knowledge; what is the logical relationship between specification and prior design knowledge. A second goal is to provide a basis for the development of a general theory for task adaptive multistrategy design that aims at combining a range of different design strategies dynamically, in order to take advantage of their respective strengths and address a wider range of practical problems.
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References
Beltrame A. and Toppano E. (1995). Prototype-based conceptual design: the SECS system. In Applications of AI in Engineering X, R.A. Adey, G.Rzevski, and C.Tasso (Eds.), Comp. Mechanics Pub., Boston, pp. 502–512.
Borst P., Akkermans H., Pos A., and Top J. (1995). The PhysSys Ontology for Physical Systems. Proc. QR Workshop, Amsterman, the Netherlands, pp. 11–21.
Bose P. and Rajamoney S.A. (1993). Compositional model-based design. Proc. IJCAI93, Chambery, France, pp. 1445–1450.
Chandrasekaran B. (1990). Design problem solving: a task analysis, AI Magazine, Winter 1990, pp. 59–71.
Chittaro L., Guida G., Tasso C. and Toppano E. (1993). Functional and teleological knowledge in the Multimodeling approach for reasoning about physical systems: a case study in diagnosis. In IEEE Transactions on Systems, Man, and Cybernetics, vol. 23, No. 6, pp. 1718–1751.
Falkenhainer B., and Forbus K.D. (1991). Compositional Modeling: Finding the Right Model for the Job, Artificial Intelligence 51, pp. 95–143.
Gero J.S. (1990). Design prototypes: a knowledge representation schema for design. In AI Magazine 11 (4), Winter 1990, pp. 26–36.
Goel A., and Chandrasekaran B. (1989). Functional Representation of Designs and Redesign Problem Solving. Proc. IJCAI-89, Detroit, MI, USA, pp. 1388–1394.
Greiner R. (1988). Learning by understanding analogies. Artificial Intelligence, vol. 35, pp. 81–125.
Iwasaki Y., and Levy A.Y. (1994). Automated model selection for simulation. In Proc. AAAI-94, Seattle, WA, USA, pp. 1183–1190.
Kannapan S.M. (1993). Metrics for functional evaluation of engineered devices. In Proc. of the Reasoning about Function Workshop, July 1993, Washington, D.C., pp. 53–59.
Michalski R.S. (1991). Inferential learning theory as a basis for multitrategy task-adaptive learning. In Proc. First International Workshop on Multistrategy Learning, November 1991, Harpers Ferry, West Virginia, pp. 3–18.
Michalski R.S., and Hieb, M.R. (1993). Knowledge representation for Multistrategy Task-Adaptive Learning: Dynamic Interlaced Hierarchies. In Proc. Second International Workshop on Multistrategy Learning, Harpers Ferry, West Virginia, pp. 3–17.
Murthy S. (1988). Qualitative reasoning at multiple resolutions. In Proc. AAAI-88, Saint Paul, MN, USA, pp. 296–300.
Nayak P.P. (1994). Causal approximations. Artificial Intelligence, vol. 70, pp. 277–334.
Navinchandra D., Sriram D., and Kedar Cabelli S.T. (1987). Analogy-based engineering problem solving: an overview. In AI in Engineering: Tools and Techniques, Sriram Adey (Eds.), Computational Mechanics Pub., pp. 273–285.
Neville D., and Weld D.S. (1993). Innovative design as systematic search. In Proc. AAAI-93, Washington, D.C., USA, pp. 737–742.
Pahl G., and Beitz W. (1984).Engineering Design,The Design Council, London,.
Rajamoney S.A. and Lee H. (1991). Prototype-Based reasoning. In Proc. AAAI-91, Anaheim, CA, USA, pp. 34–39.
Riesbeck, C.K. and Schank R.C. (1989). Inside Case-Based Reasoning. Lawrence Erlbaum Associates Pulishers, Hillsdale, New Jersey.
Toppano E. (1996). Multistrategy modeling: a case study in design. In Proc. 6th European-Japanese Seminar on Information Modeling and Knowledge Bases, Hornbaek, Denmark, pp. 35–48.
Toppano E. (1996). Rational Model Selection in Large Engineering Knowledge Bases. Applied Artificial Intelligence Journal 10, No. 3, pp. 191–224.
Umeda Y., Takeda H., Tomiyama T., and Yoshikawa H. (1990). Function, Behaviour, and Structure. In Applications of Artificial Intelligence in Engineering V, vol. 1, J.S.Gero Ed. Springer-Verlag, pp. 177–193.
Williams B C (1990). Interaction-based invention: designing novel devices from first principles. In Expert Systems in Engineering: Principles and Applications. Proc. Int. Workshop, Vienna, Austria, pp. 119–134.
Wills L.M., and Kolodner J.L. (1994). Towards more creative case-based design systems. In Proc. AAAI-94, Seattle, Washington, pp. 50–55.
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Toppano, E. (1998). Model Transmutations for Conceptual Design of Technical Systems. In: Tasso, C., de Arantes e Oliveira, E.R. (eds) Development of Knowledge-Based Systems for Engineering. International Centre for Mechanical Sciences, vol 333. Springer, Vienna. https://doi.org/10.1007/978-3-7091-2784-1_10
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DOI: https://doi.org/10.1007/978-3-7091-2784-1_10
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