This study focuses on Metal Additive Manufacturing (AM), an emerging method known for its ability to create lightweight components and intricate designs. However, Laser Powder Bed Fusion (LPBF), a prominent AM technique, faces a major challenge due to the development of high residual stress, resulting in flawed parts and printing failures. The study’s goal was to assess the thermal behaviour of different support structures and optimised designs to reduce the support volume and residual stress while ensuring high-quality prints. To explore this, L-shaped specimens were printed using block-type support structures through an LPBF machine. This process was subsequently validated through numerical simulations, which were in alignment with experimental observations. In addition to block-type support structures, line, contour, and cone supports were examined numerically to identify the optimal solutions that minimise the support volume and residual stress while maintaining high-quality prints. The optimisation approach was based on the Design of Experiments (DOE) methodology and multi-objective optimisation. The findings revealed that block supports exhibited excellent thermal behaviour. High-density supports outperformed low-density alternatives in temperature distribution, while cone-type supports were more susceptible to warping. These insights provide valuable guidance for improving the metal AM and LPBF processes, enabling their broader use in industries like aerospace, medical, defence, and automotive.

Laser Powder Bed Fusion (LPBF) is one of the most commonly used and rapidly developing metal Additive Manufacturing (AM) technologies for producing optimized geometries, complex features, and lightweight components, in contrast to traditional manufacturing, which limits those characteristics. However, this technology faces difficulties with regard to the construction of overhang structures and warping deformation caused by thermal stresses. Producing overhangs without support structures results in collapsed parts, while adding unnecessary supports increases the material required and post-processing. The purpose of this study was to evaluate the various support and process parameters for metal LPBF, and propose optimized support structures to minimize Support Volume, Support Removal Effort, and Warping Deformation. The optimization approach was based on the Design of Experiments (DOE) methodology and multi-response optimization, by 3D printing and studying overhang geometries from 0° to 45°. For this purpose, EOS Titanium Ti64 Grade 5 powder was used, a Ti6Al4V alloy commonly employed in LPBF. For 0° overhangs, the optimum solution was characterized by an average Tooth Height, large Tooth Top Length, low X, Y Hatching, and high Laser Speed, while for 22.5° and 45° overhangs, it was characterized by large Tooth Height, low Tooth Top Length, high X, Y Hatching, and high Laser Speed.

Powder bed fusion—laser beam (PBF-LB), a prevalent and rapidly advancing additive manufacturing (AM) technology nowadays, serves the industry by producing thin, complex, and lightweight components for various sectors, including healthcare, automotive, defence, and aerospace. However, this technology encounters challenges related to the construction of critical parts and the high overall process costs. Equally significant is the role of support structures in metal laser powder bed fusion (PBF-LB/M). The absence of supports can lead to defective and collapsed parts, while the incorrect selection of a support type or the addition of unnecessary supports results in increased material usage and additional post-processing efforts. Therefore, there is a pressing need for advanced software capable of generating appropriate support structures and predicting the thermomechanical behaviour of a part under PBF-LB/M printing conditions. Such software would be beneficial for the industry to avoid printing defects caused by high thermal stresses, minimise material usage, reduce printing time, and ensure high-quality prints. In this study, we introduce a web-based support generation and optimisation platform for PBF-LB/M. Through this platform, among other features, users can import three-dimensional (3D) parts and generate block-type support structures with diamond perforations based on the PySLM library, all within a user-friendly web environment. The first release of the platform (v0.6) is fully interactive and accessible online at no cost.