| Over the last few decades design researchers have put forward theories and proposed methodologies that increase the chance that a design team will reliably arrive at the optimal solution to a given design problem. Studies, however, bear out that theories and methodologies alone will not guarantee an optimal or even good design solution. Instead, a breadth of knowledge across multiple engineering domains and the time and tools to thoroughly evaluate the design space are as important as any prescriptive design method. This work presents a set of underlying engineering technologies to define, archive and reuse product design knowledge to provide a breadth of domain knowledge for designers and to leverage artificial intelligence approaches to thoroughly, if not exhaustively, search the design space. Specifically, a database schema and entry application for a prototype design repository of product design knowledge is formulated and implemented. A real-time, knowledge base-driven, function-based conceptual design algorithm known as the morphological search is formulated to extract information from the design repository and support a thorough exploration of the design space for solutions. Currently, the Design Engineering Lab's prototype Design Repository contains design knowledge for over 125 products and has over 300 user accounts representing 17 different countries.;With the foundational repository elements in place, artificial intelligence methods are employed to generate a natural language to formal component naming terms thesaurus as part of a novel form-initiated concept generation approach. The approach, known as Form Follows Form, automatically generates a functional model based upon an initial component solution seed to a design problem. With a functional model in hand, established automated concept generation algorithms are employed to return more complete and varied solutions following a thorough search of the design space. |
