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MOVUS White Papers

Want deeper insights? Our white papers dive into data accuracy, diagnostics, and real-world performance.

Adaptive AI Model Training and AI-Led Condition Monitoring

Industrial reliability is evolving beyond traditional maintenance. This paper explores how adaptive AI model training and real-time condition monitoring combine to deliver prescriptive, continuously improving insights across complex asset fleets. Learn how MOVUS’s Outcome Assistant AI achieves predictive accuracy through closed-loop learning, expert validation, and 24/7 monitoring.

AI-Driven Predictive Maintenance for Crushers in Industrial Applications

Crushers operate in some of the harshest industrial environments. This white paper explains how MOVUS combines rugged IoT sensors with AI analytics to prevent unplanned breakdowns and optimise maintenance for these mission-critical assets. Learn how predictive maintenance delivered zero unplanned failures across 142 crushers and over 1,500 hours of downtime avoided.

AI-Driven Predictive Maintenance for Belt Conveyors

Conveyors are the lifelines of bulk material handling. This paper details how MOVUS’s AI-driven monitoring technology detects faults across motors, pulleys, and gearboxes before they cause production losses. See how predictive insights from PlantOS improved uptime to over 99.9% across mining, ports, and power sites, to reduce manual inspections and enhance worker safety.

AI-Driven Predictive Maintenance for Pumps in Industrial Applications

Pumps are the heartbeat of process industries, yet failures can disrupt entire operations. This paper highlights how MOVUS’s AI-powered monitoring and analytics detect early-stage faults, reduce maintenance time, and improve safety across thousands of critical pumps. See the results and how 7,000+ hours of avoided downtime and near-perfect reliability was achieved.

AI-Driven Predictive Maintenance for Ball Mills

Ball mills are essential to cement, mining, and metals operations, yet remain some of the hardest assets to maintain. This paper demonstrates how AI-enabled vibration and temperature monitoring, powered by MOVUS PlantOS, prevents costly failures while improving availability and maintenance efficiency. Explore real-world deployments showing over 2,600 hours of downtime avoided.

The Role of AI in Blower Monitoring in Industrial Applications

Fans and blowers are vital to plant operations, but their harsh operating conditions make failures costly and dangerous. This paper examines how AI-driven predictive maintenance enables early fault detection, improved safety, and higher uptime across more than 3,000 monitored units. Discover how MOVUS’s PlantOS platform is transforming reliability for critical ventilation and process assets.

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