image: By sparse-view irradiation processing volumetric additive manufacturing (SVIP-VAM) system, models successfully achieved high-quality reconstruction with only 15 projections under the OE irradiation mode.
Credit: By Huiyuan Wang, Fangyuan Gao, Yu Shi, Kai Wang, Xinbo Wei, Chunyang Ma, Xiewen Wen*, Xueli Chen* and Jiebo Li*
Traditional volumetric additive manufacturing (VAM) techniques rely on large sets of projection data, where the computation time for generating projection sets far exceeds the actual fabrication time, making the overall VAM process highly time-consuming.
Recently, researchers from Beihang University proposed the sparse-view irradiation processing volumetric additive manufacturing (SVIP-VAM) method, which reduces the required projection data by 60 times, cuts projection computation time by 10 times, and shortens the total manufacturing process by 10 times.
The work, reported in the International Journal of Extreme Manufacturing, suggests that such improvements will advance VAM technology, facilitating its broader application in rapid manufacturing fields, including tissue engineering, medical implants, and aerospace manufacturing.
Why is Traditional VAM Time-Consuming?
"The printing process itself is fast, but the projection dataset is too large, leading to excessive computational demands and lengthy pre-processing," said Jiebo Li, corresponding author on the paper and Professor in the School of Biological Science and Medical Engineering, Beihang University. "However, manufacturing structures are not like medical imaging—binary information is sufficient for spatial representation. Do we really need over 1,000 projections for fabrication?"
The VAM process typically requires numerous projections synchronized with resin vat rotation, resulting in low single-projection efficiency and potential vibrations from frequent rotations. Additionally, the extensive calculation time required to generate projection sets before printing significantly increased the overall production duration, thereby diminishing the rapid customization advantages of VAM.
Consequently, enhancing projection efficiency and reducing projection set calculation time are crucial for the rapid implementation of VAM.
The BUAA researchers propose sparse-view irradiation processing VAM (SVIP-VAM), enabling structure manufacturing with a reduced number of projections. Through theoretical analysis, they validated the minimal number of projections necessary to reconstruct structural contours (8 projections).
Subsequently, by examining the characteristics of both the VAM fabrication process and projection algorithms, the researchers developed an optimized irradiation approach—the odd-even (OE) irradiation mode—that significantly increases the feasibility of sparse-view printing in SVIP-VAM.
"Sparse-view irradiation leverages the low-entropy nature of VAM, drastically reducing projection computation time," said principal author Dr. Huiyuan Wang. “If combined with multi-source sparse projections—such as 15 projection sources—VAM fabrication could proceed without rotation, reaching speeds limited only by radical recombination timescales.”
The researchers are continuing the work, hoping to improve rotation-free VAM fabrication. This breakthrough provides a promising approach for in-situ manufacturing in complex environments, making it a strong candidate technology for applications in tissue engineering, medical implants, and aerospace manufacturing.
International Journal of Extreme Manufacturing (IJEM, IF: 21.3) is dedicated to publishing the best advanced manufacturing research with extreme dimensions to address both the fundamental scientific challenges and significant engineering needs.
- Maintain #1 in Engineering, Manufacturing for consecutive years
- Average time to First Decision after Peer Review: 34 days
- Open Access Publishing with APC Waivers
Visit our webpage, like us on Facebook, and follow us on Twitter and LinkedIn.
Journal
International Journal of Extreme Manufacturing
Article Title
Sparse-view irradiation processing volumetric additive manufacturing
Article Publication Date
14-Jul-2025