Many design problems are too difficult to solve all at once; therefore, design teams often decompose these problems into more manageable subproblems. While there has been much interest in engineering design teams, no standard method has been developed to understand how teams solve design problems. This paper describes a method for analyzing a team’s design activities and identifying the subproblems that they considered. This method uses both qualitative and quantitative techniques; in particular, it uses association rule learning to group variables into subproblems. We used the method on data from ten teams who redesigned a manufacturing facility. This approach provides researchers with a clear structure for using observational data to identify the problem decomposition patterns of human designers.

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