This article discusses building a computable design process model, which is a prerequisite for realizing intelligent computer-aided design systems. First, we introduce general design theory, from which a descriptive model of design processes is derived. Second, we show a cognitive design process model obtained by observing design processes using a protocol analysis method. In the computable model, a design process is regarded as an iterative logical process realized by abduction, deduction, and circumscription.
One of the major problems in developing so-called intelligent computer-aided design (CAD) systems (ten Hagen and Tomiyama 1987) is the representation of design knowledge, which is a two-part process: the representation of design objects and the representation of design processes. We believe that intelligent CAD systems will be fully realized only when these two types of representation are integrated. Progress has been made in the representation of design objects, as can be seen, for example, in geometric modeling; however, almost no significant results have been seen in the representation of design processes, which implies that we need a design theory to formalize them. According to Finger and Dixon (1989), design process models can be categorized into a descriptive model that explains how design is done, a cognitive model that explains the designer's behavior, a prescriptive model that shows how design must be done, and a computable model that expresses a method by which a computer can accomplish a task. A design theory for intelligent CAD is not useful when it is merely descriptive or cognitive; it must also be computable.
What important research issues require further investigation? Perhaps the key research problem in AI-based design for the 1980's is to develop better models of the design process. A comprehensive model of design should address the following aspects of the design process:the state of the design; the goal structure of the design process;design decisions; rationales for design decisions; control of the design process; and the role of learning in design. This article presents some of the most important ideas emerging from current AI research on design especially ideas for better models design.
This paper presents an introduction to a model of a collaborative working environment which supports distributed team argumentation, negotiation, consensus building and rationalecapture. Based on a natural model of team deliberation, this model is the basis for the development of a system which enables team support and the capture of the design rationale in value added activities. The consensus model is the result of over fifteen years of studying and modeling design engineers by the authors and the integration of research results from the fields of negotiation and argumentation modeling, design rationale capture, decision theoretics, and engineering best practices.
Studies in design methodology provide various structured approaches to the design process. Many books provide definitions and elaborations of the design process: In the structural engineering field, such books include Holgate (1986) and Lin and Stotesbury (1981). More generally, various design methods and techniques are described in Alexander (1964) and Jones (1970). These design methods share the characteristic of prescribing a general set of tasks to be performed by the designer. One problem with design methodologies is that such approaches prescribe what a designer should do but not how.