The daily activities of the maintenance team at Vale’s Fazendão Mine presented some difficulties, and even risks, for employees working in the field.
Data was collected manually, on a fortnightly basis, requiring an analyst to go to the machine site for collection and subsequent analysis.
No matter how careful and cautious the inspector was, and even with all the safety regulations in place, this method entailed risks, as the measurements had to be taken while the machines were in operation and required the inspector to be close by, as well as in postures that were often ergonomically incorrect. The activity also resulted in travel costs and the allocation of inspectors’ time.
Some of the challenges that were part of the maintenance team’s daily routine:
- Great distances between mines.
- Exposure to risks when traveling in areas with restricted access, with large equipment in transit (off-highway trucks).
- Equipment in hard-to-reach places (blind spots), with imminent risks for collecting condition monitoring parameters, such as vibration.
Vale was looking for solutions to help the predictive maintenance team improve its asset monitoring processes and Dynamox was the chosen company.
The use of wireless vibration and temperature sensors in the mine’s machinery has resulted in a considerable gain in production, reliability and asset availability.
Sensors were installed in all the equipment (conveyor belts, vibrating screens, vibrating feeders, jaw crushers, belt feeders, etc.) and their respective subsets (motors, gearboxes, conveyor bearing housings, exciter boxes and crusher jaw bearings).
Vale also chose to purchase gateways which, in direct communication with the sensors, collect data automatically.
The automated failure detection system was also used, which combines field experience with machine learning to identify failures, bringing agility and productivity to the analyst’s day-to-day work.
The results are shown in reports with the status and type of anomaly detected, on customized dashboards with a user-friendly interface.
According to Vale’s estimates, implementing the solution in the maintenance team’s daily routine prevented losses in the circuit estimated at 30,000 tons of ore, corresponding to R$ 3,438,000.00.
With the implementation of the remote monitoring and automated detection solution, the safety risks to employees have been considerably reduced.
As there was no need to travel to monitor the condition of the equipment, each analyst’s time was optimized, with a gain of 12.8 hours per month.
Failure identification
Many failures were detected using the detection and prognosis system.
With the sensing data collected by the gateways centralized in the cloud, decision-making is now more precise.
As an example, we can mention the failure on the LS drive pulley bearing housing. On the dashboard, the diagnosis evolved from “monitoring” to “critical”.
Using the automated detection tool, it was possible for the system to identify that the failure was looseness.
Based on this report, the team was able to intervene and replace the bearing that had rotation marks on the inner race above the adapter sleeve, thus confirming the accuracy of the diagnosis.
Learn how remote monitoring and data collection has helped Vale’s team in their mining processes, safety and asset life cycle.
The results provided eliminated the need for spot-by-spot analysis in the plant and also prevented several catastrophic failures in the mine.
Check out the original document prepared by Vale here.
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Source: Vale