Ecological and economic process optimization in cement production through machine learning
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.
Key data
Projectlead
Project team
Peter Bolt, Raffael Künzi, Prof. Dr. Rudolf Marcel Füchslin, Matthias Bürki, Mohammed Motich, Dr. Mathieu Antoni, Marc-Aurèle Finger
Project partners
Ciments Vigier SA
Project status
completed, 09/2021 - 09/2024
Institute/Centre
Institute of Applied Mathematics and Physics (IAMP)
Funding partner
Innovationsprojekt / Projekt Nr. 54692.1 IP-ENG
Project budget
670'000 CHF
Publications
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Online thermal power estimation from oxygen measurement in cement industry
2026 Bolt, Peter; Ziebart, Volker; Jaeger, Christian; Künzi, Raffael; Motich, Mohammed; Antoni, Mathieu; Cristallini, Dimitri; Kaminsky, Jan C.; Buerki, Matthias; Füchslin, Rudolf M.
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Optimizing cement production by employing physics informed machine learning
2023 Bolt, Peter; Künzi, Raffael; Ziebart, Volker; Füchslin, Rudolf Marcel; Motich, Mohammed; Antoni, Mathieu; Finger, Marc-Aurèle; Bürki, Matthias
School of Engineering
Technikumstrasse 71
8400 Winterthur