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.
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.
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.
In the old days, the design and production of a new product were a oneman's job. Consequently, decisions taken during design and production were inherently integrated and tuned to each other. Current design and production processes, however, involve many individuals from various disciplines. It is a major problem to integrate the decisions made by these individuals, especially if the members of the design team are in different locations or even in different enterprises [Cutkosky et al.]. In addition, as can be observed in practical situations, changes to a design description are often made in isolation by the various members of a design and production team.
On January 13-14, 1990, a workshop organized by EDRC was held to discuss the topic of creating a scientific community at the interface between engineering design and AI, in order to identify problems and methods in the area that would facilitate the transfer and reuse of results. This report summarizes the workshop and followup sessions and identifies major trends in the field. Since then, the subfield of artificial intelligence devoted to engineering design applications has blossomed, especially in the last decade. In order to form a genuine scientific community out of the group of researchers active in this area, it is reasonable to ask a hard question: What do we know? On January 13-14, 1990, twentythree researchers in the field participated in a workshop designed to produce at least the beginnings of an answer.