Abstract
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 component being optimized. This is important in industrial workflows, where unwanted interference is costly to resolve. The gradient-based optimization framework 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 object should be able to be assembled with other components during the assembly process. The framework is demonstrated for the optimization of 2D and 3D parametric models created in CATIA V5.
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Acknowledgments
This work has been conducted within the IODA project (http://ioda.sems.qmul.ac.uk), funded by the European Union HORIZON 2020 Framework Programme for Research and Innovation under Grant Agreement No. 642959.
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Agarwal, D., Robinson, T.T., Armstrong, C.G. (2018). A CAD Based Framework for Optimizing Performance While Ensuring Assembly Fit. In: Wang, S., Price, M., Lim, M., Jin, Y., Luo, Y., Chen, R. (eds) Recent Advances in Intelligent Manufacturing . ICSEE IMIOT 2018 2018. Communications in Computer and Information Science, vol 923. Springer, Singapore. https://doi.org/10.1007/978-981-13-2396-6_7
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DOI: https://doi.org/10.1007/978-981-13-2396-6_7
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