Our client, a leading manufacturers of off-highway equipment, had approached us to help them reduce the cost of operations and improve the asset longevity through informed and effective decision-making in the maintenance of the asset and its components. They wanted to reduce downtime and production losses by effectively prioritizing maintenance activities and proactively replacing components before failure.
We designed an ensemble of advanced analytics solutions that could predict when asset components will fail and align replacements with planned maintenance schedules. We built predictive algorithms, which evaluate a machine’s repair history, operating and maintenance practices, etc. to predict the catastrophic premature failure risk before planned maintenance.
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