Scientific fields typically have meta-heuristics that help scientists select appropriate modeling, analysis, or testing procedures based on problem parameters. For instance, the Reynolds number calculation dictates to fluid dynamicists the classification of the flow and subsequent modeling and analysis tools most appropriate to use. As engineering design matures into a field defined by scientific principles, there is a need for similar meta-heuristics to help designers select appropriate design tools and methods. There has been significant work developing design methods to support product development including robust design, product platforms, and reconfigurable design, among others. Many of these methods have matured into design paradigms but are still undergoing validation, exercise, and extension. However, when faced with a new product design (or re-design) problem, it is a challenging task to determine what methods or paradigms to subscribe to and implement; part of this decision involves whether to design a single product or a set of similar products (i.e., a product line). This is fundamentally a metadesign problem — the design of the design method. This paper proposes an approach to support this meta-design decision using market segmentation data and appropriate contextual information.

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