Sensor-Based Diagnostics for Conveyor Belt Condition Monitoring and Predictive Refurbishment

Rising raw material costs and complex global supply chains have reduced the durability and availability of conveyor belts. In response, condition-based maintenance (CBM) with in situ diagnostics has become essential. This case study from a Polish lignite mine shows how subjective visual inspections were replaced with objective, repeatable measurements of belt core condition and thickness. Shifting refurbishment decisions from the plant to the conveyor improved success rates from 70% to over 90% and optimized belt lifecycle management. Sensor-based monitoring enables predictive maintenance, reduces premature or delayed replacements, increases belt reuse, lowers costs, and supports the circular economy by extending belt core life and reducing raw material demand. The study demonstrates how real-time, sensor-based diagnostics using inductive and ultrasonic technologies supports predictive maintenance of conveyor belts, improving refurbishment efficiency and lifecycle management.