Integrated approach for an artificial intelligence-based generative product design Online publication date: Tue, 12-Jul-2022
by Prasad Umakant Bhad; Rajesh B. Buktar
International Journal of Design Engineering (IJDE), Vol. 10, No. 2, 2021
Abstract: Generative design is an artificial intelligence-based technology that provides solution with less human intervention. In this research study, we have adopted an integrated approach of convolutional neural network, topology optimisation and autoencoder for generating multiple novel outcomes for one design problem. To showcase the research work, we initially generated bicycle frame designs by providing a reference design to topology optimisation tool to generate optimised designs based on applied constraints, support conditions, loading conditions and environmental conditions. Generated design outcomes were then provided to CNN for image processing. Processed images from CNN were further provided to autoencoder for error less results and dimensional mapping of design domain. Generated outcomes were then converted to 3D models and analysed. Generated designs were validated with yield or critical values of material. The results obtained were within the critical limits of yield values of applied material.
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