Zheng presented additive manufacturing research at 2026 AIAA SciTech

Jan 16, 2026 · 1 min read

At the 2026 AIAA SciTech conference, Zheng presented Support-Free Additive Manufacturing via Multi-Axis Digital Light Processing, introducing a robotic, multi-axis DLP 3D-printing framework aimed at eliminating sacrificial supports for complex geometries. The approach dynamically reorients the build platform so overhang directions align with the gravity vector, reducing or avoiding support formation but creating new hurdles in non-planar layer generation and projection. To overcome these, Zheng described a modified slicing workflow for non-planar interfaces, paired with a variable layer-thickness strategy that uses pixel-level grayscale modulation to precisely control curing depth. The presentation also detailed a collision-free path-planning method for the submerged vat environment, including safe entry/exit trajectories and compensation for robot repeatability errors. Together, these advances connect multi-axis robot kinematics with vat photopolymerization and were demonstrated to achieve 90° self-supporting structures while saving more than 15% resin.

Zheng Liu
Authors
Zheng Liu
Assistant Professor
Zheng Liu joined the University of Michigan-Dearborn Industrial and Manufacturing Systems Engineering Department as an Assistant Professor. His research bridges theoretical and applied aspects of AI in manufacturing and energy systems. He focused on physics-based modeling, physics-informed machine learning, and generative design for manufacturing and energy storage applications. He also evaluated the manufacturing processes through life cycle assessment and techno-economic analysis, helping the team win $1M Department of Energy’s (DOE) inaugural American-Made Geothermal Lithium Extraction Prize. He has collaborated on multiple projects funded by the National Science Foundation (NSF) through the Future Manufacturing Research Grant (FMRG) program, as well as the Office of Naval Research (ONR). In addition, he served as a graduate fellow and STEM outreach coordinator at the NSF Engineering Research Center for Power Optimization for Electro-Thermal Systems (POETS). Zheng has received the Sharp Outstanding Graduate Student Award and the Tau Beta Pi Outstanding Graduate Student Award in recognition of his research contributions. He has published more than 15 peer-reviewed journal articles and 15 conference proceedings, and has served as a track chair for the IEEE Transportation Electrification Conference. Through his work, he continues to push the frontiers of AI-driven innovation in manufacturing and energy systems.