Challenge
A leading oil sands producer had fragmented CBM data across multiple systems and poor reporting that inhibited timely action.
The company needed help to move from reactive to predictive maintenance by leveraging real-time analytics and creating dashboards from its autonomous mine fleet.
Approach
- Uncovered key pain points across the current CBM process
- Identified data flow and automation improvements to the work screening / work prioritization processes using new CBM failure models and data visualization tools
- Executed zero-cost Health Equipment Insights CBM trial across mine fleet
- Validated HEI as an effective real‑time analytics and data visualization tool to identify early‑stage component failures
Results
Projected a 120 day/year reduction in unplanned downtime
Avoided $39M in annual failure and repair costs
Reduced reliance on rental equipment and reactive work
Projected a 120 day/year reduction in unplanned downtime
