Process Models in Design and Development
Read this article. It provides an overview of planning models. Pay particular attention to Figure 1 as it visually provides a global view of planning models. Then review Figures 2 -17 for more in-depth visual planning processes.
Micro-level models
Micro-level abstract models
To recap, abstract models of the DDP focus on presenting insights about the process without prescribing how it should be approached. On the micro-level, such models concern the forms of reasoning, the elementary activities, and/or the types, structures, and evolutions of knowledge that occur during design. Insights from such work are essentially domain-independent.
The foci of these models may be illustrated by considering the categorisation of design situations discussed by Gero. In routine designing, "all the necessary knowledge is available". Routine design problems can be seen as search problems and in principle can be solved using the conventional algorithms. Nonroutine designing, in contrast, is thought to be more difficult to automate. Gero argues that nonroutine situations can be further divided into two subcategories. First, in innovative designing, "the context that constrains the available ranges for the variables is jettisoned, so that unexpected values become possible". Second, in creative designing, new variables may be introduced during the design process allowing truly novel designs to be produced.
Models in this subsection focus mainly on nonroutine design processes including both subcategories. Researchers have identified important characteristics of such processes that are reflected in their models. These include:
- Designing starts with ill-defined problems Design problem specifications are often incomplete, inconsistent, and/or vague, because people do not fully understand the context, constraints, and possibilities before design begins. One factor separating nonroutine design from routine situations is that stakeholder needs may or must be interpreted, reformulated, renegotiated, and concretised.
- Design problems and solutions coevolve Considering possible solutions highlights new aspects of ill-defined problems and may lead to them being reframed. This may change the constraints on possible solutions and may change what is considered to be a good solution.
- Designing is partly solution-oriented Empirical research has indicated that designers prestructure problems to solve them. That is, existing knowledge and previous experiences are influential in the solution process. Models taking this view are often called solution-oriented. According to Kruger and Cross, they are usually considered to be more realistic representations of the designer's thought process than models which suggest the top–down and abstract-to-concrete strategy exemplified in Fig. 3.
- Designing creates new parameters and generates new knowledge Whereas routine processes involve finding suitable values for parameters whose existence is known, nonroutine designing involves modifying constraints and/or introducing new variables that were not originally anticipated. New knowledge relevant to the design process is also generated as design proceeds.
- Designing involves hierarchical structures Solving a design problem often generates new problems at a more detailed level. Problems lower in the hierarchy are defined and constrained by partial solutions higher up.
- Designing is situated Each step in the design process influences the design situation, including the designer's knowledge, which in turn influences and constrains future design activity.
- Designing is progressive and iterative As indicated above, a design solution is not generated in a single step but is approached progressively and iteratively. There are several perspectives on what gets revisited during micro-level iterations, and why.
The next subsections discuss selected process models that each emphasise some of these characteristics of nonroutine design. The models convey insights that might be useful for teaching design, as well for developing AI approaches to either assist or automate design reasoning. They might not all directly support working designers, but models discussed in this subsection have explanatory power and some have inspired the development of procedural and analytical work.