Process Models in Design and Development

A possible criticism of some models discussed above is their highly conceptual nature. This may cause difficulties interpreting them for application to real design problems. Although certain insights have been embedded in research prototypes, the objective of some authors to establish a mathematical basis for designing that allows its implementation in mainstream CAD does not seem to have been achieved yet.

Other authors approach the challenge of decomposing designing into elementary activity by focusing on more concrete operators and the specific knowledge structures or domains they operate on. For instance, Ullman et al. develop the Task–Episode–Accumulation (TEA) model to explain nonroutine mechanical design by analysing protocol recordings of designers working on such problems. Their model describes design as a series of tasks, each comprised from episodes that are undertaken to achieve goals. In turn, the episodes are decomposed into series of primitive operators falling into three categories: select, evaluate, and decide. The primitive operators are applied to the design state, which comprises all information about the emerging design. Key features of the TEA model include: design alternatives exist only within episodes, and as such, the design is incrementally reached through an accumulation of operators' results; the designer's working memory is explicitly modelled alongside operators to manage its limitations by loading and unloading relevant information; and goals are managed on a step-by-step basis, not in response to an overall plan. TEA, therefore, reflects observed designer behaviour in which an initial concept is "developed and gradually extended to accomplish the design goals". In common with other micro-level abstract models, this differs substantially from the systematic decomposition approaches exemplified by Fig. 3.

Situated FBS views designing as a series of steps that are triggered by, and affect, emerging models of function (F), behaviour (B), structure (S), and requirements (R). The emerging models exist in three worlds and 20 types of step are possible, as shown. Key:  Xe$X^e$  = external representation of X (where X is F, B, or S).  Xi$X^i$  interpreted representation.  Xei$X{e}^i$  expected representation.

Finally, other models in this category were derived from the literature with a view to integrating key insights. For example, Chandrasekaran argues that AI approaches to design can be viewed as an iterative cycle of propose, critique, and modify. They review ways to approach each step. For example, the first step of solution proposal can be approached by algorithmic methods such as decomposition and recombination, constraint satisfaction, and so forth. A design process involves a mixture of approaches according to the characteristics of each subproblem encountered. Chandrasekaran argues that appropriate approaches can be selected dynamically by a controller which structures the task and chooses methods appropriate to each subgoal. Sim and Duffy develop a model of designing as a cycle of activity that is executed by a situated agent operating on input knowledge and producing output knowledge, in the context of individual objectives. They show that elementary activities described in the design literature can be categorised into three groups: design definition activities; design evaluation activities; and design management activities. Srinivasan and Chakrabarti also review elementary task models in the literature and argue that they can be mapped onto "a general problem finding and solving cycle" comprising the four activity types of generate, evaluate, modify, and select (GEMS). The outcomes of each activity are represented in terms of constructs that describe the emerging design and its operating principles. These constructs, namely State change, Action, Parts, Phenomenon, Input, oRgans, and Effects (SAPPhIRE) were developed by Chakrabarti et al. based on the review and synthesis of earlier work.