Document Type

Conference Paper

Publication Date


Publication Details

Ali Soofastaei, Saiied Mostafa Aminossadati, Mehmet Siddik Kizil and Peter Knights, Simulation of Payload Variance Effects on Truck Bunching to Minimise Energy Consumption and Greenhouse Gas Emissions, 15th Coal Operators' Conference, University of Wollongong, The Australasian Institute of Mining and Metallurgy and Mine Managers Association of Australia, 2015, 337-346.


Data collected from truck payload management systems at various surface mines shows that the payload variance is significant and must be considered in analysing the mine productivity, energy consumption and greenhouse gas emissions. Payload variance, causes significant differences in gross vehicle weights. Heavily loaded trucks travel slower up ramps than lightly loaded trucks. Faster trucks are slowed by the presence of slower trucks, resulting in ‘bunching’, production losses and increasing fuel consumptions. This paper simulates the truck bunching phenomena in large surface mines to improve truck and shovel systems’ efficiency, minimise energy consumption and reduce greenhouse gas emissions. The study concentrated on completing a practical simulation model based on a discrete event method which is most commonly used in this field of research in other industries. The rate of greenhouse gas emissions corresponding to diesel consumption by haul trucks is calculated according to global warming potential guidelines. The simulation model has been validated by a dataset collected from a large surface mine in Arizona state, USA. The results have shown that there is a good agreement between the actual and estimated values of investigated parameters. The validated model has been utilised in a real mine site in central Queensland, Australia as a case study. The focus of this case study has been on the relationship between the trucks bunching due to payload variance with average cycle time, average hauled mine materials, fuel consumption and greenhouse gas emissions. The results have indicated that there is a non-linear correlation between the payload variance and the mentioned parameters. In this case study, the simulation results indicate that a reduction of up to 15 minutes on average cycle time is possible if the standard deviation of payload is reduced from 30 down to 5 tonnes. By reducing the payload variance, the average of hauled mine materials can be increased up to 35 kt per day. Moreover, the fuel consumption and greenhouse gas emissions can be reduced dramatically by reducing the payload variance.