Shovel Performance

Truck haulage is the largest operational expense – constituting up to 60% of total running costs – of a typical open-pit mine. Proper management of the loading process is vital for cost control.

Under-loading leads to extra, unnecessary trips and lost productivity. Overloading increases fuel usage, reduces tyre life, compromises the performance of vehicle steering and braking systems, reduces component lifespan, and can impact on supplier warranties and repair/maintenance contracts.

As with most aspects of mining, the key to effective management of the truck / shovel mining process is comprehensive monitoring of key activities. And somewhat counter-intuitively, by making use of an advanced shovel monitoring solution, a mine can dramatically reduce their haulage costs.

Leading-edge mine operators are moving away from traditional truck-based payload monitoring systems towards shovel-based payload monitoring, as they deliver better shovel optimisation and performance, significant cost savings, more accurate data with fewer calibration requirements, and more consistent truck payloads.

Argus, from MineWare, is an advanced shovel-based monitoring system designed to manage payload, mine compliance and machine health for electric and hydraulic loaders of all makes and models. Argus boosts productivity, improves shovel performance, and lowers costs without compromising safety.

Some of the key benefits of using the Argus shovel-based payload monitoring system (from MineWare) are:

  • Productivity improvement through shovel optimisation of up to 16% — guaranteed
  • Average truck load improvement through elimination of under and overloading, leading to improved productivity
  • Dig to plan – Better shovel performance eliminates over and under-digging, which leads to costly and time-wasting remediation work
  • In-pit real-time grade control
  • Real-time alerts of overloads and equipment stress
  • Accurate payload count and reconciliation of production (Argus system vs. Survey)
  • Reduced operator performance variations by identifying the characteristics of the best operators, and then training and managing accordingly
  • Better management of operator performance and incentives
  • Overall safety and productivity improvement in the mine