A BEHAVIOURAL MODEL FOR REPRESENTING BIOLOGICAL AND ARTIFICIAL SYSTEMS FOR INSPIRING NOVEL DESIGNS

Inspiration is useful in problem solving. Our aim is to develop an integrated approach for systematic idea generation in product design using inspiration from natural as well as artificial systems. A new, generic model has been developed for representing causality of how functionality in natural and artificial systems is achieved; this is implemented in a piece of software for automated, analogical search of relevant ideas from large databases of natural and artificial systems, annotated with the constructs of the model, to solve a given problem. Two search strategies, consisting of three different search types have been formulated to facilitate designers with the necessary flexibility to search the databases, as per requirements of a given problem. In house design experiments, conducted for evaluating effectiveness of the support, showed a clear indication that the software enhances designers' ability to generate a large number of solutions, even after their own ideas are exhausted.

[1]  Tamotsu Murakami,et al.  Mechanism Concept Retrieval Using Configuration Space. , 1994 .

[2]  David L. Watson.  Enhancing Creative Productivity with the Fisher Association Lists , 1989 .

[3]  Vladimir Hubka.  Theorie der Konstruktionsprozesse , 1976 .

[4]  Amaresh Chakrabarti,et al.  A New Approach to Structure Sharing , 2004, J. Comput. Inf. Sci. Eng..

[5]  H. Berg,et al.  Cats' Paws and Catapults: Mechanical Worlds of Nature and People , 1998 .

[6]  Tetsuo Tomiyama,et al.  Supporting conceptual design based on the function-behavior-state modeler , 1996, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[7]  Michael C. Quick,et al.  Invention and evolution — design in nature and engineering , 1995 .

[8]  Y.-M. Deng,et al.  Function and behavior representation in conceptual mechanical design , 2002, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[9]  Takashi Kiriyama,et al.  An approach to automated synthesis of solution principles for micro-sensor designs , 1997 .

[10]  Amaresh Chakrabarti,et al.  Special Issue: Representing functionality in design , 1996, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[11]  A Chakrabarti,et al.  Towards a theory for functional reasoning in design , 1993 .

[12]  Christian Wagner,et al.  Stimulating ideas through creativity software , 1994 .

[13]  Larry W. Zimmerman,et al.  Value Engineering : A Practical Approach For Owners, Designers And Contractors , 1988 .

[14]  John S. Gero,et al.  Function–behavior–structure paths and their role in analogy-based design , 1996, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[15]  Ashok K. Goel,et al.  Innovation in Analogical Design: A Model-Based Approach , 1994 .

[16]  Ashok K. Goel.  Design, Analogy, and Creativity , 1997, IEEE Expert.

[17]  Jane M. Mackay,et al.  Creativity in the organization: the role of individual creative problem solving and computer support , 2001, Int. J. Hum. Comput. Stud..

[18]  B. Chandrasekaran,et al.  Functional Representation and Causal Processes , 1994, Adv. Comput..

[19]  Tamotsu Murakami,et al.  Mechanism concept retrieval using configuration space , 1997 .

[20]  Crispin Hales,et al.  Engineering design: a systematic approach , 1989 .

[21]  Amaresh Chakrabarti,et al.  A scheme for functional reasoning in conceptual design , 2001 .

[22]  Masaharu Yoshioka.  Pluggable Metamodel Mechanism : A Framework of an Integrated Design Object Modeling Environment , 1998 .

[23]  Amaresh Chakrabarti.  Towards hybrid methods for synthesis , 2001 .

[24]  W. Gordon.  Synectics: The Development of Creative Capacity , 1961 .

[25]  Michael French,et al.  Invention and evolution : design in nature and engineering, 2nd ed. , 1988 .