Greenhouse Gas (Ghg) Reduction Potential In The Mineral Industry Through Smart Fleet Management - SME Annual Meeting 2022

Greenhouse gas (GHG) emissions from primary mineral and metal production account for ~10% of global GHG emissions. One of the main sources of GHG emissions in mining operations is fuel consumption by haul trucks. Given their size and carrying capacity, the fuel consumption of haul trucks can approach 250 liters per hour. An average of 30% of the idle time of the trucks is spent while waiting in the queue. Inefficient truck dispatch planning can waste resources, cause dilution and elevate GHG emissions. In this research, a machine learning based truck dispatch approach was developed to dynamically route the haul trucks based on the loaded material, the road traffic, the estimated wait time, and the maintenance needs of the trucks. The GHG reduction potential of this smart fleet management approach was estimated by calculating and comparing the related carbon emissions versus scenarios using traditional fleet allocation approaches. Results suggest that this dynamic fleet allocation approach can significantly reduce GHG emissions at mineral production sites by optimizing waiting times and the overall distance travelled while achieving the same production levels.