Improving Overall Equipment Effectiveness in Underground Mines with Newtrax

“Based on our benchmarking, we observe a global average overall equipment effectiveness (OEE) performance of 27 percent for underground mining, 39 percent for open-pit mining… compared with 92 percent for oil refining”

-McKinsey Global Institute 2016

The term “Overall Equipment Effectiveness (OEE)” draws its origin from the manufacturing industry, and its significance to the underground mining industry is easily transferable.

Measuring Overall Equipment Efficiency for underground mining equipment is becoming best practice in benchmarking progress, identifying losses, and improving the productivity of a fleet.

Most underground mines in the process of digitalizing their operation face similar challenges:

  •     Having a multi-OEM mix of mobile equipment; producing  unstandardized data
  •     The inability to collect real-time data from all the faces, including development faces
  •     Having data, but not knowing how to transform the information into actionable solutions

Newtrax has developed an array of OEE solutions to address these challenges.

The following highlight some of Newtrax OEE successes:

OEE Overall Equipment Effectiveness

Improved Hauling Efficiency: Case Study

A mining operation with a mixed fleet of mobile trucks, including CAT AD30s and Atlas MT436s, was looking for a solution to establish standardized payload monitoring systems.

Newtrax installed its Mobile Equipment Telemetry (MET) system, which interfaced with the original equipment manufacturer (OEM)’s existing sensor network. Newtrax also installed an availability switch, onboard payload scales, and an external/internal payload scoreboard. The payload information was retrofitted to display on the OEM’s load cells.

Four trucks were monitored closely for an eight week period with the approach to Measure, Manage, and Improve using the traditional OEE calculation.

OEE = Availability(A)% x Utilization(U)% x Haulage Efficiency(Q)%

After the eight week period of data collection and observation, it was reported that Availability Time (A) was 93% and the Utilization Time (U) was 52% of the mine’s standard production time calendar. Analysis of the equipment’s payload data over the same time period showed a Haulage Efficiency (Q) of 64% with 19.4 tons out of 30 tons capacity.

These passively measured data points showed the operations OEE being 31%.

Using the information collected, the haulage efficiency data point became a key area of focus in improving efficiencies within the workflow.

SOLUTION:

To improve truck effectiveness, Newtrax proposed an increase to the dumper bed wall height to accommodate extra buckets, as well as digital scoreboards on the trucks’ cab for LHD, and an alarm system on each truck to initiate an overloading situation warning.

Conclusion

  • You can’t improve what you can’t measure
  • Technology is available to overcome stumbling blocks, and enable the management of mixed equipment fleets, through the use of timely data from active areas
  • Offering actionable insight to both mine managers and operators will deliver significant value in a short period of time
  • Improved haulage efficiency will ensure UG mining effectiveness is increased above 27%