Maximizing Mining Operations: Unlocking the Crucial Role of Intelligent Fleet Management Systems in Surface Mining’s Value Chain

Mining Pub Date : 2023-12-22 DOI:10.3390/mining4010002
Arman Hazrathosseini, A. Moradi Afrapoli
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引用次数: 0

Abstract

On the one side, the operational expenses of mining enterprises are showing an upward trend; and on the other side, conventional mining fleet management systems (FMSs) are falling short in addressing the high-dimensionality, stochasticity, and autonomy needed in increasingly complex operations. These major drivers for change have convinced researchers to search for alternatives including artificial-intelligence-enabled algorithms recommended by Mining 4.0. The present study endeavors to scrutinize this transition from a business management point of view. In other words, a literature review is carried out to gain insight into the evolutionary trajectory of mining FMSs and the need for intelligent algorithms. Afterward, a holistic supply chain layout and then a detailed value chain diagram are depicted to meticulously inspect the effect of technological advancements on FMSs and subsequently the profit margin. The proposed value-chain diagram is advantageous in explaining the economic justification of such intelligent systems, illustratively, for shareholders in the industry. Moreover, it will show new research directions for mining scholars.
最大化采矿作业:揭示智能车队管理系统在露天采矿价值链中的关键作用
一方面,采矿企业的运营费用呈上升趋势;另一方面,传统的采矿车队管理系统(FMS)无法满足日益复杂的运营所需的高维度、随机性和自主性。这些变革的主要驱动因素促使研究人员寻找替代方案,包括采矿 4.0 推荐的人工智能算法。本研究试图从企业管理的角度来审视这一转变。换句话说,通过文献综述,我们可以深入了解 FMS 采矿的发展轨迹以及对智能算法的需求。随后,通过描绘整体供应链布局和详细的价值链图,细致考察技术进步对 FMS 的影响以及随之而来的利润率。所提出的价值链图有利于向业界股东说明此类智能系统的经济合理性。此外,它还将为采矿学者指明新的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
2.80
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0.00%
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