An Interactive Web-Based Platform for Support Generation and Optimisation for Metal Laser Powder Bed Fusion.

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.

Support Structures Optimisation for High-Quality Metal Additive Manufacturing with Laser Powder Bed Fusion: A Numerical Simulation Study.

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.