Prospects and Progress of Intelligent Technology in Hard Rock Underground Mining

 Intelligent technology is driving remarkable advancements in underground mining, particularly in hard rock mines. As mineral resources are increasingly found at greater depths, there is a growing shift towards underground mining methods. Conventional techniques often face challenges like high rock strength and increased depth, which can lead to operational disruptions and safety concerns. Recent technological advancements aim to address these through intelligent systems.

In a review published in the KeAi journal Green and Smart Mining Engineering, the authors note that key production processes such as drilling, blasting, transportation, ventilation, support and filling are being enhanced with technologies like deep learning, big data and Internet-of-Things (IoT). These innovations are improving both efficiency and safety. For example, intelligent drilling systems can now sense rock properties and automate drilling rigs. In blasting, smart systems optimize design, charging and detonation, allowing real-time adjustment of parameters to predict and manage effects.

In the transportation, the industry is seeing the introduction of unmanned, autonomous vehicles and real-time positioning, while vertical transportation is exploring innovations like magnetic levitation. Ventilation systems benefit from intelligent sensing, fault diagnosis and adaptive control, ensuring a safe working environment.

The authors also highlighted that support and filling technologies are evolving. Intelligent evaluation of rock quality, advanced support equipment and continuous monitoring of rock deformation ensure stability and safety. Meanwhile, intelligent filling systems optimize material use and process control, contributing to the goal of fully automated and self-regulating mining environment.

In conclusion, these technological advancements are transforming the mining industry, making operations safer, more efficient and more sustainable.

Contact author details: Xiaobo Liu, School of Civil and Resource Engineering, University of Science and Technology Beijing, email: liuxiaobo@ustb.edu.cn

Funder: This work was financially supported by the National Natural Science Foundation of China (No. U21A20106) and the Chinese Academy of Engineering project (Nos. 2022-33-29 and 2023-XY-44). 

Conflict of interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. 

See the article: X. Liu, X. Zhang, L. Wang et al., Research progress and prospects of intelligent technology in underground mining of hard rock mines, Green and Smart Mining Engineering, Volume 1, Issue 1, 2024, Pages 12-26, https://doi.org/10.1016/j.gsme.2024.03.007