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School of Engineering

Ecological and economical process optimization in the cement production with machine learning

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.