Reduce operating expenses for mining equipment with machine learning.
Operating expenses for maintenance and repair of quarry equipment are expensive in and of themselves, but they become even higher due to the human factor and suboptimal operation parameters (excessive fuel consumption, tire wear, inefficient and untimely forecasting of purchases and repairs).
A family of digital advisors for drivers, mechanics, engineers, etc. powered by artificial intelligence and predictive analytics. The platform ensures real-time processing of key parameters, design of optimal models, and recommendation systems for operation and maintenance of quarry equipment with visual and audible alerts.
Specific fuel consumption reduced by up to 7–10% per year;
A 10–15% increase in tire running life;
Repair and maintenance costs reduced by 5-10% per year
Discussion of goals and objectives, solution demonstration (1–3 days)
Feasibility study based on the discovered customer issues (1–3 days)
Pilot implementation of the solution (1–2 months)
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