Data-Driven Monitoring and Characterization of Thermal Energy Losses in Cement Clinker Production

Cement clinker production is a highly energy-intensive process in which variations in fuel properties, raw-meal feed, excess air, heat recovery, and exhaust-gas conditions cause substantial fluctuations in specific thermal energy consumption. Conventional energy audits provide only periodic and aggregated assessments and may therefore fail to identify short-term inefficient operating regimes. This study presents a data-driven monitoring methodology for characterizing thermal energy consumption and major heat-loss pathways in a dry-process rotary kiln system. The methodology combines a simplified process energy balance with statistical analysis of multivariable operational data. The considered variables include fuel feed and lower heating value, raw-meal and clinker production rates, kiln and calciner temperatures, preheater outlet temperature, exhaust-gas temperature, oxygen concentration, secondary-air temperature, and clinker discharge temperature. Data preprocessing comprises operating-state screening, outlier removal, missing-value reconstruction, time synchronization, and normalization. Specific thermal energy consumption and individual heat-loss indicators are subsequently calculated and analyzed using correlation, mutual information, and feature-importance methods. The evaluated operating data indicated a specific thermal energy consumption of 960–1000 kcal/kg clinker, with an average value of approximately 980 kcal/kg clinker. Total thermal losses accounted for approximately 40–45% of the fuel heat input. Exhaust gases represented the dominant loss pathway, contributing 45–50% of total losses, followed by kiln-shell radiation and convection at 20–25%, clinker sensible heat at 15–20%, and incomplete-combustion losses at 5–8%. Exhaust-gas temperatures of 320–350 °C were associated with the highest-energy operating periods. Exhaust-gas temperature, fuel feed, excess-air conditions, raw-meal feed, and clinker production rate were identified as the most influential variables.