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A functional representation for aiding biomimetic and artificial inspiration of new ideas

Published online by Cambridge University Press:  17 August 2005

AMARESH CHAKRABARTI ,
PRABIR SARKAR ,
B. LEELAVATHAMMA  and
B.S. NATARAJU
AMARESH CHAKRABARTI
Affiliation:
Centre for Product Design and Manufacturing, Indian Institute of Science, Bangalore 560012, India
PRABIR SARKAR
Affiliation:
Centre for Product Design and Manufacturing, Indian Institute of Science, Bangalore 560012, India
B. LEELAVATHAMMA
Affiliation:
Centre for Product Design and Manufacturing, Indian Institute of Science, Bangalore 560012, India
B.S. NATARAJU
Affiliation:
Indian Space Research Organisation Satellite Centre, Bangalore 560017, India
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Abstract

Inspiration is useful for exploration and discovery of new solution spaces. Systems in natural and artificial worlds and their functionality are seen as rich sources of inspiration for idea generation. However, unlike in the artificial domain where existing systems are often used for inspiration, those from the natural domain are rarely used in a systematic way for this purpose. Analogy is long regarded as a powerful means for inspiring novel idea generation. One aim of the work reported here is to initiate similar work in the area of systematic biomimetics for product development, so that inspiration from both natural and artificial worlds can be used systematically to help develop novel, analogical ideas for solving design problems. A generic model for representing causality of natural and artificial systems has been developed, and used to structure information in a database of systems from both the domains. These are implemented in a piece of software for automated analogical search of relevant ideas from the databases to solve a given problem. Preliminary experiments at validating the software indicate substantial potential for the approach.

Keywords

Behavioral LanguageBiomimicryDesign by AnalogyIdea GenerationInspiration
Type
Research Article
Information
AI EDAM , Volume 19 , Issue 2 , May 2005 , pp. 113 - 132
Copyright
© 2005 Cambridge University Press

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References

REFERENCES

Andreasen, M.M. (1980). Syntesemetoder pa systemgrundlag. PhD Thesis. Lund Technical University, Lund, Sweden.
Bhatta, S., Goel, A., & Prabhakar, S. (1994). Innovation in analogical design: A model-based approach. Proc. AI in Design, pp. 57–74. Dordrecht: Kluwer Academic.
Chakrabarti, A. (2001). Towards hybrid methods for synthesis. International Conference on Engineering Design (ICED 01), pp. 379–386, Glasgow.
Chakrabarti, A. & Blessing, L. (1996). Representing functionality in design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 10(4), 251–253.Google Scholar
Chakrabarti, A. & Bligh, T.P. (1993). Towards a theory for functional reasoning. Proc. Int. Conf. Engineering Design (ICED 93), Vol. 1, pp. 1–8, The Hague.
Chakrabarti, A. & Bligh, T.P. (2001). A scheme for functional reasoning in conceptual design. Design Studies 22(6), 493–517.Google Scholar
Chakrabarti, A. & Regno, R. (2001). A new approach to structure sharing. Int. Conf. Engineering Design (ICED 01), pp. 155–162, Glasgow.
Chakrabarti, A., Johnson, A.L., & Kiriyama, T. (1997). An Approach to automated synthesis of solution principles for micro-sensor designs. Proc. Int. Conf. Engineering Design, Vol. 2, pp. 125–128, Tampere.
Chandrasekaran, B. (1994). Functional representation and causal processes. In Advances in Computers (Yovits, M.C., Ed.), pp. 73–143. New York: Academic.
Deng, Y.M. (2002). Function and behavior representation in conceptual mechanical design. Artificial intelligence for Engineering Design, Analysis and Manufacturing 16(4), 343–362.Google Scholar
French, M.J. (1998). Invention and evolution. Design in Nature and Engineering New York: Cambridge University Press.
Goel, A.K. (1997). Design, analogy and creativity. IEEE Expert: Intelligent Systems and Their Applications 12(3), 62–70.Google Scholar
Gordon, W.J.J. (1961). Synthesis: The Development of Creative Capacity. New York: Harper & Row.
Hansen, C.T. & Andreasen, M.M. (2002). Two approaches to synthesis based on domain theory. In Engineering Design Synthesis (Chakrabarti, A., Ed.), pp. 93–108. New York: Springer–Verlag.
Hubka, V. (1976). Theorie der Konstruktionsprozesse. Berlin: Springer–Verlag.
IDEA-INSPIRE. (2004). Idea-Inspire User's Manual. Bangalore, India: Centre for Product Design and Manufacturing, Indian Institute of Science.
Kletke, M.G., Mackay, J.M., Barr, S.H., & Jones, B. (2001). Creativity in the organization: the role of individual creative problem solving and computer support. International Journal of Human–Computer Studies 55, 217–237.Google Scholar
MacCrimmon, K.R. & Wagner, C. (1994). Stimulating ideas through creative softwares. Management Science 40, 1514–1532.CrossRefGoogle Scholar
Murakami, T. & Nakajima, N. (1997). Mechanism concept retrieval using configuration space. Research in Engineering Design 9, 9–11.Google Scholar
Pahl, G. & Beitz, W. (1988). Engineering Design: A Systematic Approach. Berlin: Springer–Verlag.
Qian, L. & Gero, J.S. (1996). Function–behavior–structure paths and their role in analogy-based design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 10(3), 289–312.Google Scholar
Umeda, Y., Ishii, M., Yoshioka, M., Shimomura, Y., & Tomiyama, T. (1996). Supporting conceptual design based on the function–behavior–state modeler. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 10(3), 275–288.Google Scholar
Vogel, S. (1998). Cat's Paws and Catapults: Mechanical Worlds of Nature and People. New York: W.W. Norton.
Watson, D.L. (1989). Enhancing creative productivity with the Fisher associated lists. The Journal of Creative Behavior 23, 51–58.Google Scholar
Yoshioka, M. & Tomiyama, T. (1997). Pluggable metamodel mechanism: A framework of an integrated design object modelling environment. In Computer Aided Conceptual Design '97, Proc. 1997 Lancaster Int. Workshop on Engineering Design CACD '97 (Bradshaw, A. & Counsell, J., Eds.), pp. 57–70. Lancaster, UK: Lancaster University.