Research Projects   

Title: Advanced Predictive Analytics


Organisation: The University of Queensland


Duration: From 01–January–2016 To 21 – October – 2016



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:

  • Evaluate which Proactive Diagnostics are the best predictors of Haul Truck Equipment Damage unscheduled Maintenance.

  • Distinguish between “Real” versus “spurious “alarms.

  • Deep dive into two Mine Haul Truck Catastrophic Brake failure examples.