This paper explores optimization techniques for support structures in Vat Photopolymerization Additive Manufacturing (VPP AM), addressing challenges posed by overhangs and inclined edges less than 45°. This research aims to overcome manufacturing optimization limitations in situations where the support structure is needed, by generating a benchmark methodology for further automated industrial mass production. Success criteria include ensuring part attachment to the support structure, minimal scarring after support removal, and high fabrication fidelity. Experiments are focused on a worst-case scenario involving a simple bar geometry positioned at 0° to the surface with support attached underneath. This setup facilitated precise control of process parameters and mask optimization per layer. Tests were conducted using the open-architecture ultra-high resolution VPP system, developed by the AM group at Technical University of Denmark (DTU), and commercial photopolymer resin. The study investigated the impact of Support-Free Factor (SFF) value, and Process Parameters (PP) for different support generation techniques. Variations in UV light intensity at the point of contact between the support tip and the part revealed correlations with final surface quality. Notably, a decrease in Z-axis dimensional error from 20% to 6.9% was observed during the study. The minimum required SFF for the VPP AM system was identified being equal to 65.19, corresponding to 1.51% of the supported area of the part. Furthermore, the study found that increased support structure and early part removal before post-processing resulted in finished part dimensions closest to the CAD model. Additionally, under-curing within the part structure improved the surface finish and achieved thicknesses closer to nominal values. These findings contribute to the advancement of VPP AM by providing insights into support structure optimization and process parameter adjustments for enhanced part quality and manufacturing efficiency.
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