About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
Advances in Pyrometallurgy: Pyrometallurgical Off Gas Handling, Processing and Cleaning
|
| Presentation Title |
Hybrid Modeling for Gas Cleaning Optimization in Non-Ferrous Furnace Systems |
| Author(s) |
Jia Zhang, Dmitry Kravchenko, David Louwagie, Tinne De Staercke, Tim Van Rompaey, Karolien Vasseur |
| On-Site Speaker (Planned) |
Jia Zhang |
| Abstract Scope |
Umicore is a global leader in precious metal refining, recognized for its advanced and sustainable technologies that enable the efficient recovery of valuable metals from complex industrial and end-of-life materials. Building on deep expertise in pyrometallurgy, furnace operations, such as the lead blast furnace, are highly efficient and allow for proactive adjustments. However, gas cleaning systems still present opportunities for improvement due to their complex configurations and control challenges. To enhance process understanding and operational reliability, we are developing a hybrid modeling approach that integrates physics-based models with advanced data analytics, including machine learning, to optimize gas cleaning performance. This model combines thermodynamic modeling, process know-how, and real-time data analysis to detect anomalies, and support predictive control. Implemented through a real-time dashboard, the system improves operator support, enhances gas quality, and reduces downtime. This work advances digital process intelligence and lays the foundation for industrial-scale deployment. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Modeling and Simulation, Machine Learning, Recycling and Secondary Recovery |