Feature Recognition and Parameterization Methods for Algorithm-Based Product Development Process

The algorithm-based product development process applies mathematical optimization tools in the conceptual steps of the product development process. It relies on formalized data such as initial loads and boundary conditions to find the best product solution for optimized bifurcated sheet metal parts. Previous research efforts focused on the automation of CAD modeling steps. Current algorithms are able to generate the CAD models of optimized bifurcated sheet metal products automatically, however, they are rough with low-level of detail and abstraction. Consequently, CAD models are embodied and detailed manually in a partly iterative and time-consuming process to include parameters, constraints and design features. Hence, this paper introduces feature recognition and parametrization methods for the algorithm-based product development of bifurcated sheet metal products. It proposes the inclusion of a pre-processor to analyze the solution graph resulted from topology optimization before the generation of CAD models. Algorithms that derive the geometric shape from the solution graph by recognizing features as well as assigning parameters are introduced. Then, feature-based CAD models of bifurcated sheet metal products are automatically generated. The proposed methods and algorithms are implemented with Python and validated with a use-case. Benefits and limitations of the proposed methods are discussed.