Ever wonder how digital technology is changing metal forming?
We'd love to share insights from our research, which was selected as one of "The Editors' Highlights" in Nature Communications.
This research combines the implementation of digital characteristics (DC) of the target forming process, data-guided lubricant testing and mechanism-based accurate theoretical modelling, enabling the development of data-centric lubricant limit diagrams (LLDs) and intuitive and quantitative evaluation of the lubricant performance.
Why it matters:
- Enables smart, physics-informed selection of lubricants tailored to the transient contact conditions in hot stamping process.
- Bridges the gap between simulation-driven design and real-world industrial application.
- Paves the way toward AI‑augmented tribology, elevating quality and sustainability in manufacturing.
Check the full article here:Digitally-enhanced lubricant evaluation scheme for hot stamping applications
2025
90% of metal products rely on forming processes - yet their data is often information absent and fragmental. Our latest research, published in JMSY, cracks the code!
Using an information absent data processing framework enabled by Evolutionary Binary algorithm, we achieved:
- Over 90% accuracy in recognising missing features of metal forming processes with sparsely labelled data.
- Mapped the ‘DNA’ of manufacturing processes - digital characteristics (DC) - to trace data origins with over 90% accuracy.
- Paving the way for DC-aided engineering, diagnostics, and DC-aided sustainable manufacturing.
Check the full article here: ‘Genetic exploration’ of metal forming processes through information absent and fragmental data processing - ScienceDirect
Vacancies
6 PhD Studentships in Mechanics and Characterisation of Next Generation EAF Recycled Steels for Forming and Welding Applications.
Contact details
For any questions regarding our work, please contact: