J. Mech. Des. May 2020, 142(5): 051702
John K. Ostrander, Conrad S. Tucker, Timothy W. Simpson, Nicholas A. Meisel
J. Mech. Des. May 2020, 142(5): 051702
Additive manufacturing (AM) is becoming more prevalent in the classroom. Most AM education, though, is limited to desktop-scale material extrusion printers since they are relatively safe, easy to use, and inexpensive. However, industry demand continues to rise for students skilled in more advanced forms of AM, such as laser-based, metal powder bed fusion. Unfortunately, the cost, infrastructure, and training necessary for using these complex systems in education present challenges for classroom implementation. This research proposes using virtual reality (VR) as a medium for teaching introductory concepts of AM without the need for a physical printing system located in the classroom. Changes in student knowledge are identified using a pre-/post-AM lesson evaluation and student-reported changes in self-efficacy. Results showed no overall significant difference between knowledge gained in the physical AM environment and knowledge gained in the VR environment. This suggests that VR could be used as a successful approach for teaching AM concepts if cost, space, or infrastructure make it difficult to implement a physical industrial-scale AM system. There was also no significant difference found in knowledge gained in a passive VR environment when compared with an interactive VR environment. This suggests that even simple, accessible, low-cost VR solutions (such as Google Cardboard) could be used to educate the future AM workforce.
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Christine A. Toh, Andrew A. Strohmetz and Scarlett R. Miller
J. Mech. Des 138(10), 101105; doi: 10.1115/1.4034107
Concept selection is a critical stage of the engineering design process because of its potential to influence the direction of the final design. While formalized selection methods have been developed to increase its effectiveness and reduce human decision-making biases, research that understands these biases in more detail can provide a foundation for improving the selection process. One important bias that occurs during this process is ownership bias, or an unintentional preference for an individuals’ own ideas over the ideas of others. However, few studies have explored ownership bias in a design setting and the influence of other factors such as the gender of the designer or the “goodness” of an idea. In order to understand the impact of these factors in engineering design education, a study was conducted with 110 engineering students. The results from this study show that male students tend to show ownership bias during concept selection by selecting more of their own ideas while female students tend to show the opposite bias, the Halo Effect, by selecting more of their team members’ concepts. In addition, participants exhibited ownership bias for ideas that were considered good or high quality, but the opposite bias for ideas that were not considered good or high quality. These results add to our understanding of the factors that impact team concept selection and provide empirical evidence of the occurrence of ownership bias and the effects of gender and idea goodness in engineering design education.
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Seda Yilmaz, Colleen Seifert, Shanna R. Daly and Richard Gonzalez
J. Mech. Des 138(7), 071102; doi: 10.1115/1.4032219
Current design theory lacks a systematic method to identify what designers know that helps them to create innovative products. In the early stages of idea generation, designers may find novel ideas come readily to mind, or may become fixated on their own or existing products. This may limit the ability to consider more, and more varied candidate concepts that may potentially lead to innovation. To aid in idea generation, we sought to identify “design heuristics,” or “rules of thumb,” evident in award-winning designs. In this paper, we demonstrate a content analysis method for discovering heuristics in the designs of innovative products. Our method depends on comparison to a baseline of existing products so that the innovative change can be readily identified. Through an analysis of key features and functional elements in the designs of over 400 award-winning products, forty heuristic principles were extracted. These Design Heuristics are outlined according to their perceived role in changing an existing product concept into a novel design, and examples of other products using the heuristics are provided. To demonstrate the ease of use of these Design Heuristics, we examined outcomes from a classroom study, and found that concepts created using Design Heuristics were rated as more creative and varied. The analysis of changes from existing to innovative products can provide evidence of useful heuristic principles to apply in creating new designs.
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This section includes brief descriptions of articles soon to be or recently published by the Journal of Mechanical Design. These featured articles highlight recent research developments and emerging trends in mechanical design. For Abstracts and Full Articles please see ASME's Digital Collection.