Scientific evaluation of prototyping practices is an emerging field in design research. Prototyping is critical to the success of product development efforts, and yet its implementation in practice is often guided by ad hoc experience. To address this need, we seek to advance the study and development of prototyping principles, techniques, and tools. A method to repeatedly enhance the outcome of prototyping efforts is reported in this paper. The research methodology to develop this method is as follows: (1) systematically identify practices that improve prototyping; (2) synthesize these practices to form a guiding method for designers; and (3) validate that the proposed method encourages best practices and improves performance. Prototyping practices are represented as six key heuristics to guide a designer in planning: how many iterations to pursue, how many unique design concepts to explore in parallel, as well as the use of scaled prototypes, isolated subsystem prototypes, relaxed requirements, and virtual prototypes. The method is correlated, through experimental investigation, with increased application of these best practices and improved design performance outcomes. These observations hold across various design problems studied. This method is novel in providing a systematic approach to prototyping.

Prototyping may be simultaneously one of the most important and least formally explored areas of design. Over the last few decades, designers and researchers have developed many methodologies for ideation, product architecture, design selection, and many other aspects of the design process. However, there have been relatively few methodologies published regarding the efficient and effective development of prototypes for new products. This research explores a methodology for enhancing the prototyping process. It is founded on extensive literature review of the best practices of engineering prototype development. These findings have been aggregated and form the foundation of a methodology for formulating prototyping strategies. This methodology has then been experimentally evaluated in a controlled design environment, and its effect on the performance of prototypes has been demonstrated. The method consists of a set of guiding questions with corresponding flowcharts and foundational equations that assist the designer to make choices about how to approach the prototyping process in an efficient and effective manner.

This work seeks to introduce and evaluate effects of a novel method for designing prototyping strategies. This newly developed heuristics-based tool guides designers in planning a prototyping strategy based on answers to Likert-scale questions that embody empirically validated heuristics. We created this tool to augment prior work in the development of prototyping planning methods. The new tool guides designers through six critical prototype strategy choices: (1) How many concepts should be prototyped? (2) How many iterations of a concept should be built? (3) Should the prototype be virtual or physical? (4) Should subsystems be isolated? (5) Should the prototype be scaled? (6) Should the design requirements be temporarily relaxed? We assessed the new planning tool in two environments: (1) a controlled experiment in which volunteers completed a prototyping design challenge, and (2) a capstone design class with a diverse range of open-ended sponsored design projects. In both cases, students received training for the method and then employed it in their own efforts. In our study the new tool caused student teams to employ significantly more efficient and effective prototyping strategies, such as prototyping early and often. The results indicate a higher functional performance of prototypes from groups using the new planning tool compared to control groups. This paper describes the new prototyping strategy planning tool, details both sets of experiments, and discusses results.

His objective is to practice and promote engineering as a serving profession. His focus includes remote power generation, design methods for frontier environments, enhanced engineering learning, and assistive devices for persons with disabilities.

He completed his PhD in Mechanical Engineering from Texas A&M University in 2012. His research interests are engineering design innovation, creativity and engineering education.