Improve the Energy Efficiency of Haul Trucks in Surface Mines

The Application of AI in Mining Industry

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Truck haulage is responsible for a majority of cost in a surface mining operation. Diesel fuel, which is costly and has a significant environmental footprint, is used as a source of energy for haul trucks in surface mines. Reducing diesel fuel consumption would lead to a reduction in haulage cost and greenhouse gas emissions. The determination of fuel consumption is complex and requires multiple parameters including the mine, fleet, truck, fuel, climate and road conditions as input. Data analytics is used to simulate the complex relationships between the input parameters affecting truck fuel consumption. This technique is also used to optimize the input parameters to minimize fuel consumption without losing productivity or further capital expenditure for a specific surface mining operation. The aim of this research work is to develop an advanced data analytics model to improve the energy efficiency of haul trucks in surface mines.


Ali Soofastaei


Dr. Ali Soofastaei is a Research Developer at the Artificial Intelligence Centre, Vale. Dr. Soofastaei uses innovative models based on Artificial Intelligence (AI) methods to improve safety, productivity, energy efficiency, and to reduce maintenance costs.

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Publishing House:

LAP LAMBERT Academic Publishing


Artificial Inteligence, Mining, analytics, Energy, Optimization, Simulation, prediction

Product category:

TECHNOLOGY / Engineering / General