DETAILED DESIGN AND ANALYSIS FOR ADDITIVE MANUFACTURING OF TOPOLOGICALLY OPTIMIZED AND GENERATIVELY DESIGNED TI-6AL-4V HIP JOINT IMPLANT

In this paper, a comprehensive investigation of the design and analysis of Ti-6Al-4V hip joint implants using generative design and topology optimization, along with laser powder bed fusion (LPBF), an additive manufacturing technique, has been presented. The study employed the NSGA-II genetic algorithm for generative design, enabling the generation of diverse optimized designs and topology optimization with the solid isotropic material penalization approach, efficiently reducing implant mass of the design space by up to 75% while maintaining structural integrity. Finite element analysis revealed comparable von Mises stress and deformation levels between geometries obtained with generative design and topology optimization. However, the combined approach exhibited superior performance, namely, topology optimization followed by generative design, with a 40% reduction in deformation and a 15% reduction in von Mises stress compared to conventional models. LPBF simulations demonstrated the superiority of the optimized geometries, with a 30% reduction in thermal stress and a 66% reduction in deformation compared to conventional designs. It is observed that design input for generative design significantly impacts the output design. Also, geometry has a notable impact on the quality of the printed part.