The optimization of an individual component usually happens in isolation of the components it will interface with or be surrounded by in an assembly. This means that when the optimized components are assembled together fit issues can occur. This paper presents a CAD-based optimization framework, which uses constraints imposed by the adjacent or surrounding components in the CAD model product assembly, to define the limits of the packaging space for the com-ponent being optimized. This is important in industrial workflows, where un-wanted interference is costly to resolve. The gradient-based optimization frame-work presented uses the parameters defining the features in a feature-based CAD model as design variables. The two main benefits of this framework are: (1) the optimized geometry is available as a CAD model and can be easily used in the manufacturing stages, and (2) the resulting manufactured should be able to be as-sembled with other components during the assembly process. The framework is demonstrated for the optimization of 2D and 3D parametric models created in CATIA V5.
|Name||Communications in Computer and Information Science|
|Conference||International Conference on Intelligent Manufacturing and Internet of Things, Intelligent Computing for Sustainable Energy and Environment|
|Abbreviated title||IMIOT-ICSEE 2018|
|Period||21/09/2018 → 23/09/2018|