Sorting Results of Automated Concept Generators Based on Design for Manufacture and Assembly

Early in the design process, it is desirable to produce a large number of potential solutions. Completely exploring a problem’s solution space is an unreasonable expectation for an unaided designer or design team. Computational tools have emerged to help designers more fully explore possible solutions. These automated concept generators use knowledge from existing designs and the desired functionality of the new product to suggest solutions. Existing automated concept generation methods produce many candidate solutions, but often provide unmanageably large sets of solutions. Techniques are needed to organize the set of concepts into smaller groups, more easily parsed by the human designer. This work proceeds from the hypothesis that the utility of automated concept generators can be enhanced if their output is sorted based on design for manufacture and assembly heuristics. Data to sort concepts is collected and a sorting method is proposed. Finally a case study is presented to demonstrate the method.