Productivity enhancement in top-down VPP via concurrent grayscaling and platform speed profile optimization for symmetrical parts having micro scale features

Abstract

Vat Photopolymerization (VPP), a widely adopted additive manufacturing technique, has revolutionized the domain of 3D printing by enabling the precise fabrication of complex structures, including intricate details. However, challenges remain in achieving optimal print quality while improving speed. Conventionally, grayscaling has been used to improve part accuracy in continuous VPP systems as the build platform speed remains constant. Considering a detailed photocurable resin solidification model, together with grayscaling, this study aims to improve productivity by optimizing platform speed profile while maintaining the build quality. While the optimization formulation presented here can be applied to any part, the computational limitations due to the employment of a voxel-based approach and the nonlinear nature of the resulting optimization problem are simplified by adopting a novel discretization methodology utilizing the symmetric properties of the target 3D part. By employing ring elements instead of voxels for cylindrical symmetrical parts, the computational load of the optimization algorithm is dramatically reduced. Experimental results show the proposed concurrent optimization reduces print time by 56% while maintaining superior print surface quality on an hourglass-shaped test part having micro scale features.