1S3: Continuous Monitoring Solution over the Internet for Heavy Earth Moving Equipment

David Dick, Condition Monitoring Technician, Rio Tinto Paulo Cipriano, Global CBM Services CoE Cluster Manager, SKF


Heavy earth moving equipment play a vital role in the achieving of production targets for any open cut mine. To ensure safe operation and increase the availability of these assets, effective reliability and condition monitoring program is mandatory. The operating dynamics of these heavy earth moving equipment pose certain challenges for vibration analysis specialists to produce accurate prognostics of its critical components. This paper provides continuous (online) condition monitoring over the Internet, remote data analysis and prognostic solutions for heavy earth moving equipment including draglines and electric rope shovels in particular. In the proposed solution, the data acquisition is optimized by mitigating the impact of machine’s dynamics, i.e., variable speed, load and direction into the vibration data. The discussion also comprises of technical cases on diagnosing bearing and gearmesh faults on these critical assets.

Bio - David Dick

David served 10 years as a Fitter Machinist in the Australian Defence Force and has a further 20 years’ experience in condition monitoring and NDT.
He is currently responsible for the coordination of vibration analysis and NDT at Rio Tinto’s Hail Creek coal mine. This includes variable speed; variable direction equipment being monitored remotely by on-line technology.

Bio - Paul Cipriano

Paulo has over 20 years of experience in condition-based maintenance services including vibration analysis, infrared thermography, lubricant analysis, electrical motor testing and non-destructive testing.
He is currently responsible for SKF’s Global Condition-Based Maintenance Service Standards. These standards outline the know-how for local capability set-up and delivery of CBM Services. The standardization helps SKF to maximize efficiency, safety, repeatability and quality while enabling SKF Smart Analytics Digitalization.