A comprehensive study on surface quality in 5-axis milling of SLM Ti-6Al-4V spherical components

Surface quality is a significant factor in machining that affects the accuracy of spherical components. In this research, Ti-6Al-4V prosthetic acetabular shells have been printed using selective laser melting (SLM). Two post-processes, heat treatment and machining, have been carried out on the printed samples to improve the mechanical properties, dimensional deviations, and surface quality. Samples were printed based on Taguchi L32 design of experiment (DOE), and in order to predict the surface roughness multilayer perceptron (MLP) artificial neural networks (ANNs), Poisson and Taguchi methods have been used. The novelty of this work is in explaining the mechanical properties of as-built SLM parts such as hardness, ductility, and strength and their effect on machinability of spherical components. Characterising the effect of cutting conditions and heat treatment on the surface quality based on mechanics of cutting process and tool geometry is another contribution of this paper. Results showed that MLP ANN has high potential in the modelling of surface roughness in 5-axis machining of spherical components. To improve the surface quality of SLM parts, it is recommended to design appropriate tool paths, and machining parameters with lower scallop height, finishing allowance and higher spindle speed than normal and a higher annealing temperature.