Why AI-Driven Predictive Maintenance is the New Standard for Feed Mill Efficiency?

In the rapidly evolving landscape of feed manufacturing, the shift from reactive repairs to proactive management is becoming a necessity for operational survival. In this featured article, Dr. Dejan Miladinovic, Head of the Research Centre for Feed Technology at the Norwegian University of Life Sciences, explores how the integration of Artificial Intelligence (AI) and the Internet of Things (IoT) is transforming traditional feed mill operations. Published in Feed & Additive Magazine, July 2025 issue, the study details how embedded sensors and machine learning algorithms are now capable of detecting subtle deviations—such as irregular shaft movement or thermal increases—well before equipment failure occurs.

The practical application for producers and facility managers is immediate: by moving toward autonomous maintenance, mills can significantly reduce downtime and extend the lifespan of high-value assets like pellet presses and extruders. A standout technical achievement mentioned is the work at the Norwegian University of Life Sciences regarding moisture control. By using AI-controlled systems, mills can maintain moisture levels strictly between 8% and 14%, preventing the wild fluctuations (up to 18%) seen in uncontrolled environments. This precision directly translates to better energy efficiency and higher product consistency. Furthermore, the integration with Enterprise Resource Planning (ERP) systems allows for automated spare parts procurement, addressing the persistent industry challenge of labor shortages by reducing the need for manual inspections.

For technical experts and academics, the article raises a significant point of debate regarding the transition to fully autonomous "virtual assistants." While AI can currently recommend actions and optimize energy-intensive processes, the transition to systems that execute corrective actions without human oversight remains a frontier restricted by operational variability and safety requirements. The research suggests that while the ROI on sensor integration and cloud infrastructure is clear, the industry must still navigate the "human-in-the-loop" necessity, especially when dealing with the environmental stressors like dust and humidity typical of feed production environments.