Alrosa introduces machine vision to improve diamond mining efficiency

2025: Implementation of the Dump Truck Load Control System

ALROSA, together with Russian software and digital equipment developers, is introducing an innovative system for monitoring the loading of dump trucks based on machine vision technologies. Tests have shown that the use of artificial intelligence can increase production efficiency at the field by up to 10%. The company announced this on September 2, 2025.

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Фото: Alrosa

Traditional methods of determining the volume of mined ore - both in underground mines and in open pits - do not provide an opportunity to monitor and adjust the load of dump trucks in real time. As a result, the technique does not work at full capacity: tests have shown that the load is 10% lower than the optimal level.

The system, which has been tested at the Udachny underground mine and in the Yubileiny quarry of ALROSA, uses machine vision to determine the loading of the dump truck body. The laser locator lidar builds a 3D model of the body of the dump truck, and then the neural network analyzes the model and accurately calculates the volume of loaded rock mass and the degree of filling of each machine. This data comes in real time to the control center, where the dispatcher can quickly adjust the work of equipment operators: operators of loading and delivery machines in mines and excavator drivers in quarries.

Tests carried out at one of the ore runs of Udachny made it possible to increase the productivity of mine dump trucks by 10% - this is almost 12 thousand tons of additionally transported diamond-bearing ore. We obtained similar results on the surface, in conditions of open mining. In the next two years, we expect to implement this system at all production sites. It is also important that in order to reduce risks, we simultaneously tested two different technological platforms - one in the mine, the other in the quarry - and both showed the necessary result, - said Andrei Nasekailov, head of the ALROSA Center for Innovation and Technology.