Immersive Technologies has been working with iron ore miners in Western Australia to boost the capability of heavy equipment operators.  One of the mining companies, which operates several iron ore mines, uses a simulation-based workforce development solution to address the variance in operator capability to improve haul-cycle productivity. After investing in a PRO5 Equipment Simulator, their operations now are able to train their people in a safe and highly realistic virtual environment proven to improve heavy equipment operator skill and behavior.

Installed at a centrally located training facility, the PRO5 will simulate Caterpillar and Liebherr excavators loading a fleet of autonomous trucks. The training solution develops mine-ready operators via a targeted training approach for experienced personnel and a structured and inclusive approach for new skill development.

“Autonomy has successfully addressed risk to truck fleet safety and productivity; however, this has created greater cognitive, socio-emotional and technology skills required to get the job done. The need to balance productive material movement, radio communication skill and software literacy also extends to ancillary machines such as dozers and graders,” said Simon Vellianitis, Regional Vice President Australia Pacific at Immersive Technologies.

With deployments on dozens of autonomous haulage sites around the world, Immersive Technologies said it has global experience addressing workforce challenges arising from the introduction of autonomous systems. For example, system inputs from the operator affect the approach paths for autonomous trucks, often introducing additional wait time into the truck exchange. These paths were previously determined by operators within the trucks themselves, however within an autonomous haulage operation this part of the haul cycle becomes the responsibility of the loading machine operator. Immersive Technologies’ simulation solutions monitor the human variables enabling equipment operators to build familiarity with the system, understand its complexities and practice the best methods for consistent cycles.