Institute of Science and Technology, Federal University of Alfenas, Brazil.
Department of Mining Engineering, Federal University of Ouro Preto, Brazil.
J Environ Manage. 2016 May 1;172:177-85. doi: 10.1016/j.jenvman.2016.02.048. Epub 2016 Mar 3.
The mining operations of loading and haulage have an energy source that is highly dependent on fossil fuels. In mining companies that select trucks for haulage, this input is the main component of mining costs. How can the impact of the operational aspects on the diesel consumption of haulage operations in surface mines be assessed? There are many studies relating the consumption of fuel trucks to several variables, but a methodology that prioritizes higher-impact variables under each specific condition is not available. Generic models may not apply to all operational settings presented in the mining industry. This study aims to create a method of analysis, identification, and prioritization of variables related to fuel consumption of haul trucks in open pit mines. For this purpose, statistical analysis techniques and mathematical modelling tools using multiple linear regressions will be applied. The model is shown to be suitable because the results generate a good description of the fuel consumption behaviour. In the practical application of the method, the reduction of diesel consumption reached 10%. The implementation requires no large-scale investments or very long deadlines and can be applied to mining haulage operations in other settings.
装载和运输作业的采矿作业有一个高度依赖化石燃料的能源。在选择卡车进行运输的采矿公司中,这种投入是采矿成本的主要组成部分。如何评估露天矿运输作业中运营方面对柴油消耗的影响?有许多研究将燃油卡车的消耗与几个变量相关联,但在每种特定情况下,没有一种方法可以优先考虑高影响变量。通用模型可能不适用于矿业中呈现的所有运营环境。本研究旨在为露天矿运输卡车的燃油消耗相关变量创建一种分析、识别和优先级排序的方法。为此,将应用统计分析技术和使用多元线性回归的数学建模工具。该模型被证明是合适的,因为结果很好地描述了燃料消耗行为。在该方法的实际应用中,柴油消耗减少了 10%。该实施不需要大规模投资或很长的截止日期,并且可以应用于其他环境中的采矿运输作业。