AI Monitors Mine Truck Loading at Russian Diamond Deposit
Loading efficiency of ALROSA’s underground haul trucks has increased by 11%.
ALROSA’s Center for Innovation and Technology has completed the rollout of a machine vision system at one of the company’s key production sites – the Udachny underground mine in Yakutia, north of the Arctic Circle. The algorithms are designed to monitor the loading of underground haul trucks, the world’s largest diamond producer told IT Russia.
Tracks Volume, Weight, and Residual Build-Up
Machine vision refers to artificial intelligence technologies that capture and analyze images to solve industrial tasks. At ALROSA, the deployed system evaluates the overall load level of each underground haul truck, determines the volume and weight of the extracted rock, and automatically calculates the load utilization ratio. It can also assess the percentage of material left sticking to the truck bed after unloading.
All data is transmitted in real time to the control center, where dispatchers analyze the information and adjust equipment operators’ work as needed.
According to Andrei Nasekaylov, director of ALROSA’s innovation center, the machine vision system increased the load utilization ratio by 11.3%. As a result, ore transportation became more efficient, and overall productivity of the underground mobile mining fleet improved during each shift.
Hundreds of Millions of Rubles in Savings
Earlier, we reported that ALROSA is migrating its business processes to 1C:ERP. Some core modules are set to be implemented by the end of 2026, with full transition expected in 2028.
