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In this work, the effects of line (L-scanning strategy), stripe (S-scanning strategy), hollow square (H-scanning strategy) and chess board partition (C-scanning strategy) on the performances of graphene oxide reinforced Ti6Al4V matrix nanocomposites (GO/TC4) as fabricated by selective laser melting (SLM) were investigated. Numerical temperature field simulation of four different scanning strategies was utilized to investigate the effects of thermal concentration on SLM-processed GO/TC4 nanocomposites, linking to its micro-voids, surface roughness, porosity, microhardness and tribological properties. The proposed simulation scheme is validated by comparing the simulated thermal analysis with experimental results. Simulation results show that the thermal concentration effects of a part during SLM process is distinctive under different scanning strategies, with the slowest cooling rate of 64,977.5 °C/s that is achieved by C-scanning strategy specimen. The experimental results indicate that the performances of the L-scanning strategy or S-scanning strategy sample are seriously affected by the thermal concentration, causing a large number of micro-voids and defects. All the experimental results suggest that the sample using C-scanning strategy exhibits the optimal performance of all investigated specimens, which closely correlates with its lowest temperature gradients. This study highlights the importance of using a partition scanning strategy during SLM process, which can be easily extended to other powder bed fusion process.

Influence of Scanning Strategy on the Performances of GO-Reinforced Ti6Al4V Nanocomposites Manufactured by SLM