In an Australian technical paper titled, “Haul truck fuel consumption and CO₂ emission under various engine load conditions”, the researchers determined that overloading a large mining truck (CAT 797B) by as little as a 10% could increase fuel consumption and costs by nearly US$367,000 per annum and add 900mt CO₂ emissions per truck.

(Based on bulk density factor of 1.5)

With big mining trucks, fuel is a major cost contributor. Analysis carried out by the University of Queensland into fuel consumption relative to load size shows some interesting facts.

Based on an analysis of CAT 793D trucks (250 tonne rated capacity), it was found that when underloaded, fuel consumption increased at a similar rate to when overloaded! It became evident that there is an optimal loading ‘sweet spot’ where fuel consumption (and resulting CO₂ emissions) are optimized.

The Mine Payload Scanner (MPS) enables mines to identify sub-optimal loading in real time and to take immediate corrective action. The MPS is a key weapon in helping to reduce unnecessary fuel consumption and CO₂ emissions.

DATA SOURCE: University of Queensland, “Reducing Fuel Consumption of Haul Trucks in Surface Mines Using Artificial Intelligence Models”

The MPS is a reliable and consistently accurate truck scale alternative, and a powerful tool for helping to reduce unnecessary fuel consumption and CO₂ emissions.

The correlation between P, S, TR and FC Index is based on an Artificial Neural Network model

Operator console and message board indicate overloading with bold visual warning indicators.