Engineering design is typically a team effort. Design teams frequently need to push technical boundaries to solve the most relevant challenges faced by our society. A significant area of research across multiple fields of investigation, including engineering, is the understanding and use of an individual’s cognitive attributes in the process of assembling productive teams. This research proposes an approach to assembling an engineering design team by first defining the desirable cognitive attributes in the team members. Subsequently, based on individual cognitive profile assessments along these attributes, an exhaustive list of possible design teams is investigated based on their cumulative attribute level. We compare the performance of two teams predicted to perform at different levels, and our results verify the differences between the observations of team interactions and the quality of designs produced. In addition to self-assessments, we also investigate the brain activity of the respondents using electroencephalography (EEG) to evaluate performance in an individual and a team setting. This analysis intends to highlight the characteristics of an individuals’ brain activity under different circumstances to reveal if these characteristics contribute to the success of a design team. EEG data revealed observations such as correlation between raw amplitude and level of team contribution, a higher variation in the channel power spectral density during individual versus team tasks, and a degradation of alpha activity moving from individual to group work. The results of this research can guide organizations to form teams with the necessary cognitive attributes to achieve the optimum design solution.
Effective Design Team Composition Using Individual and Group Cognitive Attributes
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Fritz, K, Deschenes, L, & Pandey, V. "Effective Design Team Composition Using Individual and Group Cognitive Attributes." Proceedings of the ASME 2018 International Mechanical Engineering Congress and Exposition. Volume 13: Design, Reliability, Safety, and Risk. Pittsburgh, Pennsylvania, USA. November 9–15, 2018. V013T05A030. ASME. https://doi.org/10.1115/IMECE2018-86888
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