Dr. Yang Xu Profile

Dr. Yang Xu

at Univ of Southern California

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Proceedings Article | 13 March 2024 Presentation + Paper

DMD-based additive manufacturing: spatiotemporal properties and motion-assisted image projection methods

Yong Chen, Han Xu, Yang Xu

Proceedings Volume 12900, 129000B (2024) https://doi.org/10.1117/12.3008289

KEYWORDS: Projection systems, Image processing, Fabrication, Mirrors, Printing, Additive manufacturing, Digital micromirror devices, Photopolymerization, Motion blur

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Additive manufacturing (AM) is a digital manufacturing process that can directly convert a computer-aided design model into a physical object layer-by-layer. Due to the additive and discrete nature of the digital manufacturing process, AM needs to find a tradeoff between process resolution, platform size, and production efficiency by tuning the process in the temporal or spatial domains. For the digital-micromirror-device (DMD) based vat photopolymerization (VPP, aka Stereolithography) AM process, I will present two motion-assisted image projection methods recently developed in our lab to improve resolution without sacrificing size and efficiency. First, I will discuss VPP’s energy input in the temporal and spatial domains and present an optimized pixel blending principle. Based on them, a mask image projection method based on subpixel shifting in a split second will be presented to tune the process in both temporal and spatial domains. I will then introduce a hopping light method by adding a complimentary motion of the projection image so the DMD can use a low refresh rate (< 100 Hz) without imaging blurring during the continuous movement of the light projection system. Compared with other AM processes, such as stop-and-go and moving light methods, the hopping light method can resolve the tradeoffs among printing speed, feature resolution, and part size. The challenges in developing the hopping light method and its potential use in metal additive manufacturing will also be discussed. Finally, conclusions will be drawn with thoughts on how the presented spatiotemporal strategy may shed light on future DMD-based AM research.

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