Use of Artificial Intelligence in cement grinding control: impacts on operational performance and industrial efficiency

Elison Lopes Pereira; Elmer Rolando Llanos Villarreal; Ednardo Pereira da Rocha; Andrés Ortiz Salazar · Derecho y cambio social. (2026) · DOI: 10.54899/dcs.v23i89.5227

Resumen

The cement industry faces the challenge of balancing high production demand with the mitigation of environmental impacts and the optimization of energy efficiency. In this context, the cement grinding stage is one of the most critical and complex processes, historically operated by reactive systems that depend on human sensitivity and experience. This article presents a case study conducted in an industrial unit located in the state of Ceará, Brazil, aiming to analyze the impacts of implementing Artificial Intelligence (AI) in the operational control of cement mills. The study was carried out in a cement industry facility in Ceará, where the grinding process is performed in vertical mills controlled by supervisory systems integrated with Programmable Logic Controllers (PLCs). The implemented AI system acted as decision-support for operational control, analyzing multiple process variables and proposing real-time adjustments in order to optimize process stability and productive performance. The results demonstrate that the application of Artificial Intelligence contributed to increased process productivity, as well as to a significant reduction in specific energy consumption per ton produced. This new operational behavior suggests that the intelligent system was able to optimize the mills’ operating conditions, reducing energy losses and improving the utilization of installed power. The research adopted a comparative approach to investigate how the transition from conventional methods to AI-based control affects process stability and performance.

Instituciones: Universidad Nacional de Ingeniería