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.
