Multi-objective optimization of selective laser sintering processes for surface quality and energy saving

Selective laser sintering (SLS) is one of the most widely used additive manufacturing technologies and represents a valuable manufacturing process in the aerospace, automotive, and medical industries. Owing to the preheating requirement for the SLS of polymer materials, one of the main challenges is to reduce the energy required for the part-building process and at the same time maintain the surface quality of the parts, represented by surface roughness, as this has aesthetic and functional importance for industrial applications. These objectives are competing criteria and are significantly influenced by the build orientation of the parts in the SLS process. This study investigates a computational methodology for the simultaneous minimization of surface roughness and energy consumption in the SLS process, to locate the optimal trade-off set between these objectives, known as the Pareto set; thus, it provides a consistent decision support system for the identification of optimal build orientations for SLS.