BelAZ has introduced digital solutions and artificial intelligence tools into the production process to improve the accuracy and speed of mining equipment production. The launch of the integrated system was announced by the company's press service.
Virtual copies of real technological chains — so-called digital twins — now allow you to model assembly stages in advance, find bottlenecks and test changes without stopping real production. This reduces setup time and reduces the risk of errors when launching new modifications of equipment.
More than 500 pieces of equipment have been integrated into a single digital circuit. Sensors and software modules transmit data on machine load, temperature, vibration and other parameters in real time. If the indicators go beyond the permissible limits, the system signals this before the deviation leads to defects or downtime.
At the same time, the plant is testing neural network algorithms for analyzing large arrays of production data and automating work with technical documentation. AI assistants are learning to extract the necessary information from drawings, regulations and reports, saving the time of engineers and technologists.
The predictive quality control system records the slightest deviations in the parameters of parts processing. This makes it possible to prevent the release of defective components at an early stage, and not at the final check.
BelAZ calls the current stage not a point modernization, but a systemic restructuring of production management. The goal is to create a flexible, self-learning ecosystem where data, algorithms and people work in a single rhythm.