Organisation: Vale – The University of Queensland
Start and Estimated Duration: From 12–Jun–2015 To 20 – November – 2017
Summary: In the current [mining] economic climate, minimising costs is critical. Equipment reliability must be stepped up to increase production and to reduce delays. Equipment reliability requires effective maintenance. Maintenance expenses in the mining industries are commonly between 30% -50% of mine site total operating costs. The overall goal is the application of Advanced Analytics to reduce unscheduled maintenance delays, prevent equipment machine damage, avoid catastrophic failures, and provide a platform for ongoing predictive maintenance. Outcomes and benefits can be categorised in deep dive into two mine haul truck catastrophic brake failure examples; distinguish between “Real” versus “Spurious” alarms; and evaluating which proactive diagnostics are the best predictors of haul truck equipment damage and unscheduled maintenance.
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