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Optimising Payloads

 

Context
Our client, a Gold mine in Western Australia operated by a large multinational miner, was suffering from a high degree of variation in haul truck payloads across the operation. This resulted in lower than target average payloads and lower total material movement, while still triggering a number of overloading events, which impacted not only the health of the trucks themselves, but also their productivity.

 

MaxMine Application
Together with the site engineers and maintenance team, MaxMine was able to complete an “optimal payload” study for the site, which indicated that the site’s payload target could be increased significantly. However, to prevent an increase in the frequency of overload events, we first rolled out MaxMine’s operator scoring metrics for the shovel operators. MaxMine automatically and objectively measures each operator on their conformance to payload targets (both over and underloads) as well as loading bias and loading time. This helped to reduce the payload variation between loads and allowed the site to increase payload targets. Once variation was suitably controlled, we worked with the site team and the OEM to further increase payload targets in line with the optimal payload study results.

 

Client Results and Discussion
  • 8% increase in average payload
  • Improved operator conformance to loading metrics, including loading time and load bias
  • Improved visibility on site around overload events and reduced the frequency of these events

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Excavator Loading Truck Loads in Range
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