Mining ventilation fans are critical pieces of equipment, used to supply adequate oxygen to personnel, dilute and exhaust dangerous gasses in the underground mine and are required to extract smoke and fumes from equipment. Improper underground ventilation creates health problems and can reduce the efficiency of personnel and cause an increase in the frequency of accidents.
The ventilation fans at the mine were monitored by VROC AI. Predictive maintenance models were built on the platform to ensure high reliability and to predict any degradation or potential failures before they happen.
In this case, a Ventilation Fan started showing moderate and then severe degradation in the fan outlet pressure. Shortly following the outlet pressure degradation, the fan started showing severe degradation on the fan vane position feedback, which is representative of the actual vane position.
The reliability was alerted to the issue by the platform, and with the information from the AI models, the engineers investigated the Fan vanes and positioner to determine the cause of the degradation. They found that the linkage between the actuator and the vanes themselves had rusted and was preventing the fan vanes from being adjusted to the correct position. Maintenance personnel ordered the replacement parts and planned a shutdown to replace the faulty parts. After replacing the faulty linkage, the ventilation fan went back into normal operation.
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The efficient deployment, continuous retraining of models with live data and monitoring of model accuracy falls under the categorisation called MLOps. As businesses have hundreds and even.
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