One of the hallmarks of engineering design is the design synthesis phase where the creativity of the designer most prominently comes into play as solutions are generated to meet underlying needs. Over the past decades, methodologies for generating concepts and design solutions have matured to the point that computation-based synthesis provides a means to explore a wider variety of solutions and take over more tedious design tasks. This paper reviews advances in function-based, grammar-based, and analogy-based synthesis approaches and their contributions to computational design synthesis research in the last decade.

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.

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The objective of this paper is to present experimental results of a specific ideation method TRIZ (an abbreviation of a Russian acronym of “Teoriya Resheniya Izobretatelskikh Zadatch” meaning theory of inventive problem solving) as compared to ad hoc methods used by students. It is critical to understand how and why TRIZ works as it can lead to improvements on how to teach this method, and also how to analyze ideation methods in general. Our hypothesis is that TRIZ improves the creativity level of subjects using it as observed in the produced design outcomes. The experiments were conducted simultaneously at two institutions: University of Texas at El Paso (UTEP) and University of Maryland (UMD). The results were analyzed as part of an existing research partnership with Pennsylvania State University (PSU). The ideation task present here has been used in all three institutions; it is the redesign of a traffic light that uses light-emitting diodes (LED) instead of incandescent bulbs leading to snow build-up on the lights in certain climates as LED's generate less heat to melt the snow. UTEP and UMD student groups were tasked with redesigning the LED traffic lights to resolve this issue. The assessment was performed on the outcome (i.e., ideas generated) using quantity, novelty and variety as metrics. Numerical results of these metrics are shown along with conclusions based on observations of the experimental process. Data presented in this paper conclude that TRIZ does improve the ideation effectiveness metrics Novelty and Variety while slightly reducing Quantity when compared to a control group using ad hoc ideation methods.

The value of sketching in engineering design has been widely documented. This paper reviews trends in recent studies on sketching in engineering design and focuses on the encouragement of sketching. The authors present three experimental studies on sketching that look at (1) sketching assignments and their motivation, (2) the impact of a sketching lesson, and (3) the use of Smartpen technology to record sketching; overall these studies address the research question: Can sketching frequency be influenced in engineering education? Influencing sketching frequency is accomplished through motivation, learning, and use of technology for sketching, respectively. Results indicate that these three elements contribute to the encouragement of sketching in engineering design.