RT Journal Article
T1 Optimizing cement kiln operation with expert systems
A1 Fernández Gassó, Raimundo
A1 Sevilla-Hurtado, Lorenzo
A1 Cañero-Nieto, Juan Miguel
K1 Hornos de cemento
K1 Industria del cemento
AB The optimization of cement kilns presents a significant challenge for the industry, where achieving operational efficiency and sustainability is paramount. This study introduces a Kiln Expert System (KES) that leverages symbolic artificial intelligence (AI), real-time data analysis, and adaptive algorithms to dynamically stabilize key variables such as calciner temperature and oxygen levels. By incorporating a higher proportion of alternative fuels (ATFs), KES not only reduces variable costs, but also minimizes the carbon footprint and strengthens the competitive positioning of operations. Deployed in a facility with a five-stage preheater and a multistage calciner, the KES fine-tunes combustion parameters in real time to maintain high production standards, improve performance, and adapt to changing operational conditions. This innovative approach demonstrates how AI-driven systems can transform process management by enabling precise control, optimizing resource use, and aligning industrial practices with environmental goals.
PB Springer Nature
YR 2025
FD 2025-09-20
LK https://hdl.handle.net/10630/41190
UL https://hdl.handle.net/10630/41190
LA eng
NO Fernández Gassó, Raimundo, Lorenzo Sevilla Hurtado, and Juan Miguel Cañero-Nieto. "Optimizing cement kiln operation with expert systems." The International Journal of Advanced Manufacturing Technology (2025): 1-13.
NO https://openpolicyfinder.jisc.ac.uk/id/publication/13456
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026