Support structure design in additive manufacturing

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Additive manufacturing (AM) offers significant design freedom, particularly in laser-based powder bed fusion of metals, where support structures are often necessary for printability and process reliability. However, there is insufficient knowledge regarding the design of these support structures, which can lead to build failures and excessive material use. This study aimed to develop a method for designing tree-like support structures to optimize the mechanical performance of AM parts. Experimental investigations were conducted on the printability, geometrical accuracy, and strength of thin struts, complemented by an AM process simulation model for four generic overhang geometries. This model facilitated parameter optimization to identify design parameters, yielding Pareto optimal support designs in terms of support volume and part deformation. Printed sample measurements validated simulation results and the effectiveness of tree-like supports. Additionally, two case studies on the additive manufacturing of discontinued spare parts provided initial validation of the approach. This research uniquely integrated thermal and structural loads in parameter optimization to enhance part mechanical behavior. A successful print on the first attempt demonstrated the approach's potential, laying the groundwork for automated support generation tools that require minimal user input.