Abstract

Large-scale overland belt conveyor systems have been installed in mining to meet the increasing demand for higher capacity and longer distance continuous transport of bulk material. Currently, the Overall Equipment Effectiveness of belt conveyors (availability, utilization & load-factor) is a major concern for mining operators. The downtime of overland conveyors leads to the stoppage of bulk material handling, disrupting ore extraction and material processing. Root Cause Analysis shown that failures of rotating components such as idlers are the main responsible for unplanned shutdowns. Idler rollers are relatively simple and low reasonable running cost. However, their reliability has a large impact on the performance of long overland conveyors due to their large amount in service along the system (up to 26,500 idler rollers for a 10 km conveyor). The idler roller failures are stochastic. There is uncertainty in predicting its location, severity and time of occurrence. Since bearings have a limited lifespan, and a very large amount of idlers are operating under different conditions in a harsh environment, it is possible to estimate that a significant number of idler rollers are close to the fault condition, anytime. To meet cost per ton targets and zero harm goals, while reduce unplanned downtime, operators are installing different on-line condition based monitoring systems to continuously check on the health and provide early warning on problems with idler rollers. But, the deployment of idler monitoring systems presents several challenges in mining environments that must be addressed. This paper presents a technology review of idler condition monitoring systems for critical overland conveyors based on the operational key drivers claimed by personnel to upgrade their processes to predictive maintenance using a wireless-, smart-, and self-powered condition monitoring system. This includes initial investment, O&M costs, safety standards, instrumentation wiring issues, inexistence of power supply connections, and interference in wireless communications among other key design factors for mining.