SOURCE-LINKED INTELLIGENCE
Integrated modelling for sustainable and optimized steel manufacturing processes
e processing steps in a steel manufacturing chain. The methodology includes intelligent coupling of interconnected processing steps by numerical simulation, soft sensors, process data and distributed machine learning. Integrated numerical modelling that captures the interactions, relations, and feedback loops between various processing stations enables prediction for smart optimization of energy efficiency and product quality in the steel manufacturing. Continuous casting, reheating, hot metal working, quenching and leveling processes are examples that are controlled separately but strongly interconnected in terms of parameters. These processes serve as objective functions in two parallel use cases at Celsa (ES) and SSAB (SW). It is well known that process optimization can have a significant effect on reducing carbon footprint in steel production, and implementing new digital tools will enable a faster transition towards sustainable industry. ProcTwin is divided in clear work packages to reach the objectives: one is adaption of existing physically based numerical models of each proce
Read original source ↗ Open in workspace
- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 4825924.55
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T03:21:21.440Z. This is not the publication date.