Computers have the capability to support human designers in a variety of tasks including releasing the human designer from routine tasks via design automation as well as sparking and supporting innovation and creativity. To support the concept phase effectively, a wide range of possible concepts, which are quantitatively evaluated, should be considered to enable designers to explore the solution space and choose advantageous concepts. To enable automated solution space exploration and evaluation, this research presents a method that uses automated model transformations based on a graph-based object-oriented knowledge representation. The approach combines previous research with automated generation of variable assignments for generated concepts and optimization using simulated annealing. The variable assignments are generated by automatically setting up and solving constraint satisfaction problems and evaluated using automatically generated simulation models. The main contributions of this research are an integrated and fully automated approach starting with task definition and ending with a solution space of optimized product concepts and generic model transformations that enable automated use of Boolean satisfiability, constraint satisfaction and bond graph-based simulation methods. The method is validated on the case studies of automotive powertrains.

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