TECHNOLOGY FEED & ADDITIVE MAGAZINE July 2025 85 TRANSFORMING DATA INTO STRATEGIC INSIGHTS Modern feed mills generate large volumes of data, often stored in Enterprise Resource Planning (ERP) systems. Without intelligent tools, much of this data remains underutilized. AI bridges this gap by analyzing both historical and real-time data to forecast equipment failures, optimize maintenance schedules, and streamline operations. When integrated with ERP platforms, AI can automate spare parts procurement, simulate maintenance scenarios, and support data-driven decision-making that enhances reliability and efficiency. INDUSTRY EXAMPLES: PRACTICAL AI INTEGRATION Several companies are already demonstrating how AI can be effectively integrated into feed and pet food production: • AGI SureTrack: This system monitors critical equipment like pellet presses. When early signs of wear, such as bearing degradation are detected, it alerts the maintenance team and checks inventory levels. If the required part is low in stock, the system automatically triggers a reorder through the ERP, ensuring timely delivery and preventing unplanned downtime. • Bühler Insights: In pet food manufacturing, Bühler’s AI platform monitors energy usage in extruders. If abnormal consumption is detected, the system compares it with historical maintenance data, schedules a service window, and updates the ERP system to adjust production planning and spare parts logistics accordingly. The Center for Feed Technology at the Norwegian University of Life Sciences is trying to integrate AI technology into the moisture control and management with small steps (Figure 1). SOLVING KEY INDUSTRY CHALLENGES Predictive maintenance addresses several persistent challenges in the feed and grain sector: • Labor shortages: Automated monitoring reduces reliance on manual inspections, easing the burden on limited technical staff. • Asset longevity: Early detection of wear extends the lifespan of expensive machinery and improves return on investment. Figure 1. AI-controlled moisture (blue line) strictly between 8% and 14% moisture; Uncontrolled moisture (red dashed line): Fluctuating up to 18% in the feed drying process AI-Controlled vs Uncontrolled Moisture Levels in Feed Products Time (seconds) Moisture Level (%) Uncontrolled Moisture AI-Controlled Moisture AI Intervention Points 0 20 40 60 80 100 18 16 14 12 10 8
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