Ecological and economic process optimization in cement production through machine learning
At a glance
- Project leader : Dr. Volker Ziebart
- Project team : Dr. Mathieu Antoni, Peter Bolt, Matthias Bürki, Marc-Aurèle Finger, Prof. Dr. Rudolf Marcel Füchslin, Raffael Künzi, Mohammed Motich
- Project budget : CHF 670'000
- Project status : completed
- Funding partner : Innosuisse (Innovationsprojekt / Projekt Nr. 54692.1 IP-ENG)
- Project partner : Ciments Vigier SA
- Contact person : Volker Ziebart
Description
The goal of this Industry 4.0 project is to stabilize and optimize the clinker burning process in a cement plant using machine learning and improved process analytics. This significantly reduces emissions of carbon dioxide, ammonia and nitrogen oxides, improves clinker quality and reduces the consumption of thermal and electrical energy. The project makes a significant contribution to climate and environmental protection.
Publications
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Bolt, Peter; Künzi, Raffael; Ziebart, Volker; Füchslin, Rudolf Marcel; Motich, Mohammed; Antoni, Mathieu; Finger, Marc-Aurèle; Bürki, Matthias,
2023.
Optimizing cement production by employing physics informed machine learning [poster].
In:
Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023.
ZHAW Zürcher Hochschule für Angewandte Wissenschaften.
Available from: https://doi.org/10.21256/zhaw-26666