Application of artificial intelligence and the future of big data analytics in the mining industry

Q4 Engineering
M. Rylnikova, D. Klebanov, M. Makeev, M. V. Kadochnikov
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引用次数: 2

Abstract

The article identifies factors that indicate the relevance of creating new tools for efficient and safe mining of solid minerals based on advances in predictive analytics methods. These methods take into account the trends in big data analysis in subsoil management. An example is given on implementation of a new class of information systems, i.e. the "digital advisers", which use information from dispatching systems, MES, ERP of the mining operations as the input data to create such systems. Cases of practical implementation of the digital advisers are analyzed. A reference economic assessment of implementing the digital adviser for mine dump truck drivers is provided. Trends in development of such analytical systems are identified based on the Big Data analysis.
人工智能的应用和大数据分析在采矿业的未来
本文确定了基于预测分析方法的进步,表明创造有效和安全的固体矿物开采新工具的相关性的因素。这些方法考虑了底土管理大数据分析的发展趋势。举例说明了实施一类新的信息系统,即“数字顾问”,它使用采矿作业调度系统、MES、ERP的信息作为创建这类系统的输入数据。对数字顾问的实际实施案例进行了分析。为矿用自卸车司机实施数字顾问系统提供了经济评价参考。这种分析系统的发展趋势是基于大数据分析确定的。
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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来源期刊
Gornaya Promyshlennost
Gornaya Promyshlennost Engineering-Industrial and Manufacturing Engineering
CiteScore
1.10
自引率
0.00%
发文量
100
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