Understanding how designers think is core to advancing design methods, tools, and outcomes. Engineering researchers have effectively turned to cognitive science approaches to studying the engineering design process. Empirical methods used for studying designer thinking have included verbal protocols, case studies, and controlled experiments. Studies have looked at the role of design methods, strategies, tools, environment, experience, and group dynamics. Early empirical studies were casual and exploratory with loosely defined objectives and informal analysis methods. Current studies have become more formal, factor controlled, aiming at hypothesis testing, using statistical design of experiments (DOE) and analysis methods such as analysis of variations (ANOVA). Popular pursuits include comparison of experts and novices, identifying and overcoming fixation, role of analogies, effectiveness of ideation methods, and other various tools. This paper first reviews a snapshot of the different approaches to study designers and their processes. Once the current basis is established, the paper explores directions for future or expanded research in this rich and critical area of designer thinking. A variety of data may be collected, and related to both the process and the outcome (designs). But there are still no standards for designing, collecting and analyzing data, partly due to the lack of cognitive models and theories of designer thinking. Data analysis is tedious and the rate of discoveries has been slow. Future studies may need to develop computer based data collection and automated analyses, which may facilitate collection of massive amounts of data with the potential of rapid advancement of the rate of discoveries and development of designer thinking cognitive models. The purpose of this paper is to provide a roadmap to the vast literature for the benefit of new researchers, and also a retrospective for the community.
Design for additive manufacturing (DFAM) gives designers new freedoms to create complex geometries and combine parts into one. However, it has its own limitations, and more importantly, requires a shift in thinking from traditional design for subtractive manufacturing. There is a lack of formal and structured guidelines, especially for novice designers. To formalize knowledge of DFAM, we have developed an ontology using formal web ontology language (OWL)/resource description framework (RDF) representations in the Protégé tool. The description logic formalism facilitates expressing domain knowledge as well as capturing information from benchmark studies. This is demonstrated in a case study with three design features: revolute joint, threaded assembly (screw connection), and slider–crank. How multiple instances (build events) are stored and retrieved in the knowledge base is discussed in light of modeling requirements for the DFAM knowledge base: knowledge capture and reuse, supporting a tutoring system, integration into cad tools. A set of competency questions are described to evaluate knowledge retrieval. Examples are given with SPARQL queries. Reasoning with semantic web rule language (SWRL) is exemplified for manufacturability analysis. Knowledge documentation is the main objective of the current ontology. However, description logic creates multiple opportunities for future work, including representing and reasoning about DFAM rules in a structured modular hierarchy, discovering new rules with induction, and recognizing patterns with classification, e.g., what leads to “successful” versus “unsuccessful” fabrications.
Problem formulation is an important part of the design process that has been largely underexplored. Similarly, the relationship between how designers formulate problems and creative outcome is not well understood. To shed light on what the process of problem formulation can tell us about creativity in design, we use the problem map model — a flexible, domain-independent ontology for modeling the design formulation process — to analyze protocols from eight expert designers. In this paper, we discuss the effectiveness of using problem maps for coding design protocols and what the problem map model can tell us about the protocols of designers. In this exploratory study, we use the problem map model to code and analyze the problem formulation stage of the design process.
Studies on design, show that problem formulation plays a major role in creative design. We plan to construct an interactive computer system that aids problem formulation. In the current stage, to improve our understanding of problem formulation, we have conducted exploratory protocol studies of novice designers and collected data from an expert designer in the form of a depositional interview. A formal representation of the design problem is needed to improve our empirical investigation. We propose a preliminary framework for such a model and we call it a problem map. It provides a basis for comparing how different designers perceive a problem. Our study is based on the design of a model aircraft for the AIAA student design competition. This preliminary analysis shows the evolution of the problem and the solution spaces in the elaboration of the problem maps through time. The problem maps also show a richer representation of attended attributes and relations for the expert and more attributes left in vacuum for the novices.
Conceptual design is a high-level cognitive activity that draws upon distinctive human mental abilities. An early and fundamental part of the design process is problem formulation, in which designers determine the structure of the problem space they will later search. Although many tools have been developed to aid the later stages of design, few tools exist that aid designers in the early stages. In this paper, we describe Problem Formulator, an interactive environment that focuses on this stage of the design process. This tool has representations and operations that let designers create, visualize, explore, and reflect on their formulations. Although this process remains entirely under the user's control, these capabilities make the system well positioned to aid the early stages of conceptual design. [DOI: 10.1115/1.4024714] Keywords: problem formulation, conceptual design, design representation, requirement analysis, computer-aided conceptual design Background and MotivationDesign is one of the most complex cognitive activities in which humans engage, involving sophisticated reasoning about specifications, functional devices, and how the latter satisfy the former. As such, design has long been recognized as standing to benefit from computational aids, and there have been many success stories in the general area of computer-aided design.However, nearly all work in this arena has focused on later stages of the design process, which involve determining the detailed structure of designed artifacts or deciding on specific values for their parameters. In contrast, the earlier, and equally important, stage of conceptual design, or problem formulation, has received relatively little attention. This phase plays a key role in the design enterprise, since it focuses on how one formulates the problem, which in turn constrains the alternatives considered during later stages. Thus, helping users generate promising conceptual designs early on will increase their chances of finding useful detailed designs later.One reason is that design tasks, as typically stated by customers or marketing departments, are incompletely and ambiguously specified. To make them operational, designers must often add requirements, clarify goals, identify trade-offs, and otherwise refine the specifications they have been provided. In other cases, to make the problem solvable they may even need to reject some facets of the specification. These activities occur largely during the conceptual period, although they may well incorporate feedback from later stages, especially when the designer encounters problems that lead him to reconsider earlier choices.There is also reason to believe that the formulation phase is the primary locus of creativity in the design process, particularly for nonroutine problems. Howard [1], in a review of both the design and psychology literature, provides evidence for this claim and identifies conceptual design and task analysis as the phases where the most creative output is produced. Furthermore, Christiaans [2] has discove...
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