Machine learning applications and process intelligence for cement industries
C. Chatzilenas, T. Gentimis, T. Dalamagas, A. Kokossis, A. Katsiaboulas, I. Marinos
Computer Aided Chemical Engineering, Volume 50, pp. 711-716, 2021
machine learning; energy consumption; prediction; cement industry
Estimating energy consumption in cement mills is critical for the cement industry. Following data science practices and adopting machine learning (ML) technologies, we developed energy consumption prediction models for a cement mill of TITAN SA plant in Kamari Viotia. The models exploit historical sensor measurements and operational data and give predictions for energy consumption with accuracy better than almost one order of magnitude compared to existing baseline methods.