Engineering conceptual design is a knowledge-intensive process that generates solutions to a product specification. It is a process that can benefit from past experience of similar designs. In reality however, designers often have limited time to build up the necessary experience and are, in any event, unlikely to become experts in all relevant fields. Hence there is a need to capture, store and reuse valuable knowledge. Currently available conventional CAD systems offer limited possibilities for the re-use of existing designs. Techniques from the field of Artificial Intelligence (Al) may be applied to aid the conceptual design phase, which is known as the area of intelligent computer-aided design. The aim of this work is to identify and externalise design knowledge using a fractal-like model, to understand the role of design knowledge in conceptual design and to use design knowledge as a guide for every stage of concept development. This research provides a framework for supporting conceptual design, which uses the techniques of Case-Based Reasoning (CBR) and fractal theory, for reasoning about the design and development of computer-based design aids. The framework is comprised of three parts. The first is case representation. This research proposes a new representation technique, Fractal-like Design Modelling (FDM), which integrates design knowledge in a graph-based form and has fractal-specific characteristics. The second is case retrieval. Based on FDM, the similarity between a new design and the existing designs is assessed by concurrently applying a feature-based similarity measure and a structure-based similarity measure. The third is case adaptation. With the help of fractal characteristics, an approach of adaptive design is developed by performance revision and by goal-oriented substitution. These three parts work together to achieve an automated, case-based, conceptual design method: Fractal-Based Re-design.
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