Towards a framework for acquisition of design knowledge

Engineering design is a knowledge-intensive process driven by various design objectives. Design is an iterative process where the objectives evolve together with the solutions in order to deliver an artefact with the desired properties and functions. Many design theories developed so far suggest more or less efficient ways for finding a suitable solution to the given goals. However, they often leave open the issue of ‘solution talkback’. Discovery of new design objectives and amendment of the existing ones is as important as the development of design solutions. The biggest issue with solution talkback is the presence of tacit knowledge in addition to the explicit one. This paper draws on a theory that incorporates some typical features of design problems, and transfers theoretical findings about reflection on the design actions to a tool for acquisition of design knowledge. First, key terms are defined and theoretical framework is introduced. Afterwards we look at the means for capturing explicit and tacit design knowledge more in depth.

[1]  Srinath Perera,et al.  Case-based design: A review and analysis of building design applications , 1997, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[2]  G. Altshuller Creativity as an exact science : the theory of the solution of inventive problems , 1984 .

[3]  Martin Dzbor,et al.  TOWARDS LOGICAL FRAMEWORK FOR SEQUENTIAL DESIGN , 2001 .

[4]  Tetsuo Tomiyama,et al.  From general design theory to knowledge-intensive engineering , 1994, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

[5]  Hans Hermes,et al.  Introduction to mathematical logic , 1973, Universitext.

[6]  Herbert A. Simon,et al.  The Structure of Ill Structured Problems , 1973, Artif. Intell..

[7]  P. M. Wognum,et al.  Introduction to TIPS: a theory for creative design , 1995, Artif. Intell. Eng..

[8]  R. J. Bogumil,et al.  The reflective practitioner: How professionals think in action , 1985, Proceedings of the IEEE.

[9]  David Poole,et al.  Explanation and prediction: an architecture for default and abductive reasoning , 1989, Comput. Intell..

[10]  D. Schoen,et al.  The Reflective Practitioner: How Professionals Think in Action , 1985 .

[11]  J. Brown,et al.  Bridging epistemologies: The generative dance between organizational knowledge and organizational knowing , 1999, STUDI ORGANIZZATIVI.

[12]  Nigel Cross,et al.  Descriptive models of creative design: application to an example , 1997 .

[13]  Raymond Reiter,et al.  Characterizing Diagnoses , 1990, AAAI.

[14]  B. Chandrasekaran,et al.  Design Problem Solving: A Task Analysis , 1990, AI Mag..

[15]  Ming Xi Tang A knowledge-based architecture for intelligent design support , 1997, Knowl. Eng. Rev..

[16]  Richard Fikes,et al.  How Things are Intended to Work: Capturing Functional Knowledge in Device Design , 1993, IJCAI.

[17]  Johan de Kleer,et al.  An Assumption-Based TMS , 1987, Artif. Intell..

[18]  Elliott Mendelson,et al.  Introduction to Mathematical Logic , 1979 .

[19]  Brian Logan,et al.  Design as intelligent behaviour: An AI in design research programme , 1990, Artif. Intell. Eng..

[20]  Hideaki Takeda,et al.  Towards multi-aspect design support systems , 1994 .

[21]  John S. Gero,et al.  Design Prototypes: A Knowledge Representation Schema for Design , 1990, AI Mag..