A team with the right characteristics can exceed the sum of their individual efforts. However, a team having the wrong characteristics may perform more poorly than the sum of its individuals. Therefore, it is crucial that teams are assembled and managed properly in order to maximize performance. This work examines how the properties of a design problem can be used to select the best values for team characteristics. Two characteristics are considered: team size and interaction frequency. A computational model of design teams that has been shown to effectively emulate human team behavior is leveraged to pinpoint optimized team characteristics for solving a variety of fluid and structural design problems. The nature of each design problem is characterized with respect to local and global behavior of the design space, alignment between objective functions, and the resources allotted for solving the problem. Regression analysis is used to create equations for predicting optimized team characteristics based on problem properties. These equations, which enable the informed design of design teams based on those characteristics, describe statistically significant relationships and are found to have useful levels of accuracy. Further analysis reveals insights about how the properties of a design problem can influence a team’s search for solutions.

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