Influence of SLM block support design on geometrical quality of AISI 316 l cantilever features and its impact on post-processing

Abstract

Abstract In Selective Laser Melting, the design of efficient support structures is the key to enable the production of high-quality functional parts exhibiting complex shapes with improved geometrical accuracy. Nonetheless, from a process point of view, supports are waste material that must be minimized to reduce production costs and post-processing. Despite the recent technological advances, support optimization is based on time- and resource-consuming trial-and-error experimental campaigns, while support removal is primarily a manual operation which requires a consistent human effort and consumable consumption. Nowadays, the industry is demanding a tool capable to optimize support design and placement based on part geometry and building orientation, by ensuring high part geometrical accuracy along with reduced timing for post-processing operations. Specifically, the purpose of this experimental campaign, is to evaluate the influence of support thickness and tooth length on the dimensional accuracy of AISI 316 l cantilever specimens in order to form a solid baseline of knowledge for the future realization of an automated algorithm for optimized support structure generation based on both part and process requirements. The experimental results show that the support thickness strongly affects the final part distortion, reducing the as-built geometrical deviation by 72.6% when wall thickness increases up to 0.7 mm, whereas tooth length has a higher impact on post-processing when decreased from 0.7 mm to 0.3 mm, reducing support time removal and consumables usage respectively up to 40.5% and 72.7%. The achieved results highlight that the implementation of optimized support structures ensuring low geometrical deviation and involving reduced resource consumption in post-processing is feasible. These findings provide the starting design rules for the engineering of an empirical methodology, based on thermomechanical modelling, enabling optimized design and implementation of SLM support structures.