Asset failures are costly and stressful. This is particularly true for mining operations, where a single hour of downtime can result in millions of dollars of lost revenue.
Some mining companies try to avoid these losses by stocking extra spare parts or through over-maintaining equipment. But these solutions often only add more financial burdens in CAPEX and maintenance costs.
But what if all of this extra cost could be avoided? What if the machines could warn their operators about impending breakdowns days, even weeks in advance? And what if this was possible without further instrumenting existing equipment?
Aspen Mtell® is an application that uses machine learning to monitor and analyse data across the entirety of the process, from any equipment or system in real-time to detect anomalies and predict failures, and their causes, before they occur. Using Aspen Mtell®, operators can address any abnormal behavior of the equipment before it becomes a serious problem.
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