Publication details

Title Machine learning applications and process intelligence for cement industries
Document Type Article
Year 2021
Authors C. Chatzilenas, T. Gentimis, T. Dalamagas, A. Kokossis, A. Katsiaboulas, I. Marinos
Source Computer Aided Chemical Engineering, Volume 50, pp. 711-716, 2021
Keywords machine learning; energy consumption; prediction; cement industry
Abstract 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.
More info Publication link