OBJECTIVE: We propose a methodology for analyzing shared knowledge in engineering design teams. BACKGROUND: Whereas prior work has focused on shared knowledge in small teams at a specific point in time, the model presented here is both scalable and dynamic. METHOD: By quantifying team members' common views of design drivers, we build a network of shared mental models to reveal the structure of shared knowledge at a snapshot in time. Based on a structural comparison of networks at different points in time, a metric of change in shared knowledge is computed. RESULTS: Analysis of survey data from 12 conceptual space mission design sessions reveals a correlation between change in shared knowledge and each of several system attributes, including system development time, system mass, and technological maturity. CONCLUSION: From these results, we conclude that an early period of learning and consensus building could be beneficial to the design of engineered systems. APPLICATION: Although we do not examine team performance directly, we demonstrate that shared knowledge is related to the technical design and thus provide a foundation for improving design products by incorporating the knowledge and thoughts of the engineering design team into the process.
OBJECTIVE: We propose a methodology for analyzing shared knowledge in engineering design teams. BACKGROUND: Whereas prior work has focused on shared knowledge in small teams at a specific point in time, the model presented here is both scalable and dynamic. METHOD: By quantifying team members' common views of design drivers, we build a network of shared mental models to reveal the structure of shared knowledge at a snapshot in time. Based on a structural comparison of networks at different points in time, a metric of change in shared knowledge is computed. RESULTS: Analysis of survey data from 12 conceptual space mission design sessions reveals a correlation between change in shared knowledge and each of several system attributes, including system development time, system mass, and technological maturity. CONCLUSION: From these results, we conclude that an early period of learning and consensus building could be beneficial to the design of engineered systems. APPLICATION: Although we do not examine team performance directly, we demonstrate that shared knowledge is related to the technical design and thus provide a foundation for improving design products by incorporating the knowledge and thoughts of the engineering design team into the process.