A Digital Twin Approach for Agile Additive Manufacturing of Automotive Components

This study aims to develop a digital twin framework for fabricating automotive components through additive manufacturing (AM) technology. The framework comprises topology optimization (TO), finite element analysis (FEA), and fabrication analysis using Simufact Additive, which ensures the first-time-right fabrication of the component. Using TO-FEA, the component is designed with reduced overall weight without compromising the structural and functional performance. After the successful design of the component, it is analyzed for fabrication feasibility before undergoing the actual fabrication process. In the present study, an automotive flange fork is designed and fabricated through AM laser powder-bed fusion technology using Inconel-718 material. The optimized process parameters of 180 W laser power, 600 mm/s scan speed, 100 µm hatch spacing, and 30 µm layer thickness were used for the fabrication of the flange. The Simufact analysis revealed that the optimized design's out-of-tolerance was reduced from 18% to 6.1%. In addition, the surface deviation of the optimized design was increased by 2%, compared to the original design. Furthermore, the optimized design showed better thermal characteristics, resulting in reduced residual stress and distortion. Precision analysis of the component showed the dimensional discrepancy between the 3D model and printed part to be less than 1%. The fabricated component showed it can withstand a torque of 300 Nm, which is generated in 4-wheel automobiles. The torque analysis successfully demonstrated the component’s performance, showing no signs of damage or cracks. This study shows the potential of integrating digital twins and additive manufacturing to promote Sustainable Development Goals (SDG) goals across many industries.