The integration of simulation-driven design tools into additive manufacturing (AM) technologies offers new pathways for producing lightweight structures. In addition, some simulation tools enable the prediction of potential defects and failures caused by residual stresses prior to manufacturing. In this study, a systematic workflow combining topology optimization (TO), laser powder bed fusion (PBF-LB/M), and hybrid post-processing is presented for the development of a robotic arm gripper. Using finite element (FE)-based TO, the original gripper geometry was redesigned to achieve a 65% mass reduction, decreasing the component weight from 570 to 192 g, while maintaining structural integrity. Residual stress accumulation and potential distortion occurring during PBF-LB/M were predicted using inherent-strain-based simulations, including the stress relief achieved by post–heat treatment scenario. The optimized design was manufactured using AlSi10Mg powder via PBF-LB/M, followed by 300°C for 2 h annealing, and subsequently refined through drilling, tapping, and surface finishing as part of a hybrid AM approach. Post-processing reduced the surface roughness from 3.4 (as-built) to 0.035 µm on functional contact regions, enabling precise joint compatibility. This study provides a transferable engineering framework that integrates computational design, distortion prediction, and hybrid manufacturing to realize lightweight, functionally efficient structures for robotic applications.
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