New five-axis machining method boosts industrial productivity and paves way for smarter manufacturing

Five-axis machining is one of the cornerstones of modern industry, supporting the production of aerospace engines, automotive dies, energy components, and biomedical implants. Despite its wide application, conventional strategies often face long machining times, uneven tool paths, and difficulties in handling surfaces with complex geometries. These limitations directly constrain productivity and increase costs for manufacturers.

In a recent article published in the Chinese Journal of Aeronautics, Dr. Jiancheng Hao and Prof. Pengcheng Hu from the Hong Kong University of Science and Technology and Hong Kong University of Science and Technology (GZ) reported a breakthrough approach: surface partitioning and iso-scallop field-based five-axis machining method with a non-spherical cutting tool. The team demonstrated that by dividing machining surfaces into multiple adaptive regions, tool orientations become smoother and cutting widths wider, leading to significantly shorter tool paths and higher efficiency.

“The idea was to address the inefficiencies caused by treating the whole surface as one region,” explained Dr. Hao. “By intelligently partitioning the surface and optimizing tool paths in each subregion, we can substantially reduce machining time while keeping the precision that industry demands.”

Experiments confirmed the value of the method. Compared with existing benchmarks, machining time was reduced by up to forty percent without compromising quality. This translates directly into higher throughput, lower production costs, and faster delivery schedules. For manufacturers producing turbine blades, molds, or medical implants, such improvements mean not only better efficiency but also stronger competitiveness in global markets.

The researchers emphasized that the benefits go beyond speed. The method enables tools to access intricate geometries that were previously difficult to machine, allowing engineers to realize lighter and more sophisticated designs. At the same time, smoother tool orientations reduce sudden mechanical loads, improving system stability and minimizing the need for costly secondary finishing. “Our results show that non-spherical tools, when paired with this strategy, unlock new levels of productivity and open possibilities for designs that were once out of reach,” said Dr. Hao.

Looking ahead, the team is determined to take the method further. Future work will integrate physical factors such as cutting force and tool wear, making the system more robust for real-world industrial use. The researchers are also planning to embed the method within intelligent manufacturing frameworks. “By combining machine learning with our partitioning strategy, the tool paths could be refined dynamically, adapting to changing conditions with respect to geometry indicators,” noted corresponding author Prof. Pengcheng Hu. “This will push efficiency even higher and bring us closer to the vision of smart manufacturing.”

Such developments have wide-reaching implications. In civilian production, higher efficiency ensures affordable, high-quality products, whether for energy systems, transport, or healthcare. By advancing both theory and practice, the study provides a foundation for the next generation of computer-aided manufacturing technologies. By linking advanced algorithms with industrial practice, the research shows how academic innovation can help to shape a new era of high-performance manufacturing.

Original Source

Jiancheng Hao, Pengcheng Hu, Dong He, Ke Cheng, Zhaoyu Li, Xiangyu Li, Haokun Chen, Bowen Du. Surface partitioning and iso-scallop field-based five-axis machining method with a non-spherical cutting tool [J]. Chinese Journal of Aeronautics, 2025, https://doi.org/10.1016/j.cja.2025.103676.

About Chinese Journal of Aeronautics 

Chinese Journal of Aeronautics (CJA) is an open access, peer-reviewed international journal covering all aspects of aerospace engineering, monthly published by Elsevier. The Journal reports the scientific and technological achievements and frontiers in aeronautic engineering and astronautic engineering, in both theory and practice. CJA is indexed in SCI (IF = 5.7, Q1), EI, IAA, AJ, CSA, Scopus.