Over the past four decades since the reform and opening-up policy was launched, while the mining industry has created enormous social wealth, it has also faced significant challenges and been under multiple pressures—including energy, resource, and environmental concerns. Traditional industries such as mining must promptly address a series of pressing issues, including extensive development practices, low production efficiency and energy utilization rates, and a low level of mineral resource utilization, thereby accelerating the pace of transformation and upgrading. The mining industry needs to leverage modern, intelligent technologies to drive profound changes in its resource-development approaches, achieving intensive, efficient, and sustainable development. The construction of smart mines has become an essential path for realizing high-quality development in the mining sector.
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　　Current Status of Smart Mine Development
　　During the First Industrial Revolution, humanity entered the Steam Age. The rapid development of industry ushered in mining’s true emergence onto the historical stage; at that time, mining operations were predominantly carried out by manual labor. During the Second Industrial Revolution, humanity entered the Electric Age, placing higher demands on mining development. As a result, mechanized and automated mining became the mainstream approach. In the Third Industrial Revolution, humanity entered the Technological Age, and demand for mineral resources reached unprecedented levels. Meanwhile, the concept of green development in mining and the idea of intelligent mining have both matured, leading to rapid progress in the construction of green mines and smart mines. With the advent of the Fourth Industrial Revolution—the Intelligent Era—automation, digitalization, and intelligent technologies have received increasing attention within the mining industry. Mining enterprises have begun conducting extensive practical experiments in the process of intelligent transformation, each tailored to their specific application goals. Based on the primary focus of technological applications, these efforts can be categorized into automated mines, digital mines, and intelligent (smart) mines. Currently, the generally accepted view is that an intelligent mine is a modern, safe, efficient, and intensive mine that achieves digital planning and design, automated operation, unmanned operations, and intelligent management across various aspects—including geological surveying, resource management, mining design, scheduling, mining production, ore processing, tailings disposal, and mining and beneficiation equipment.
　　1.1 Current Status of Smart Mine Development Abroad
　　Starting from the 1960s, some developed mining nations abroad began researching automated, digitalized, and intelligent mining technologies. Entering the 1990s, in order to gain a competitive edge in the mining industry, these developed mining nations launched smart mine research programs and started formulating development plans for “intelligent mines” and “unmanned mines.” Today, it is possible to achieve geological modeling, three-dimensional digitization of the mining process, large-scale mining equipment, and partial intelligence in certain equipment. Moreover, centralized control has been established through the creation of integrated mining and beneficiation operation centers, resulting in fewer frontline workers, higher production efficiency, and significantly fewer safety accidents. For example, Canada Nickel Company has long been committed to researching automated mining technologies and plans to achieve unmanned mining at one of its mines by 2050, using satellite control to operate all mine equipment and realize fully automated mechanical mining. Anglo American plc’s latest technological system, dubbed “Future Smart Mining,” encompasses four key areas: concentrated mines, waterless mines, modern mines, and intelligent mines. Future Smart Mining places greater emphasis on resource conservation and intensive use as well as ecological and environmental protection; advanced technologies have greatly reduced reliance on fossil fuels and conventional energy sources. The Kiruna Iron Ore Mine in Sweden has now essentially achieved unmanned, intelligent mining. In underground working areas, apart from maintenance workers conducting inspections, nearly all operations are controlled remotely via centralized computer systems, achieving an extremely high degree of automation. This is largely attributable to the introduction of large-scale machinery, intelligent remote-control systems, and modern management practices. Highly automated and intelligent mine systems and equipment have made mining operations much more efficient. Rio Tinto’s “Mine of the Future” initiative focuses primarily on driverless trucks, driverless trains, automated drilling rigs, automated excavators, and bulldozers—all controlled from a central computer control center. This project will incorporate over 70 innovative technologies, including digital simulation systems for processing plants, fully integrated automated mines and simulation systems, advanced automation technology applications, and cutting-edge production analysis systems.
　　With the rapid development of digital technologies, information technologies, and artificial intelligence technologies, countries around the world are accelerating the innovation and widespread adoption of intelligent technologies in mining equipment, operations, and management. The supporting industrial ecosystem is developing rapidly. Intelligent mining technology systems, leveraging smart technologies and intelligent services, integrate mining equipment, products, processes, and personnel in ways never seen before, thereby enhancing mine safety, reducing operational costs, and boosting efficiency. Intelligent mine management systems can connect operators, dispatchers, site managers, and central control room supervisors onto a single platform, enabling end-to-end control of mining processes through system integration, optimizing production workflows, and improving both mining efficiency and mine safety. These systems provide mining enterprises with powerful IoT, advanced analytics, and AI technologies, significantly enhancing safety, productivity, and operational efficiency. Meanwhile, to strengthen their capabilities in intelligent mining systems, companies in the underground mining automation sector are also stepping up their mergers and acquisitions.
　　Overall, in many countries and mining companies abroad, the construction of smart mines has gone beyond the realms of mechanization and automation, integrating the concepts of green, safe, intelligent, and efficient operations into every stage of mining production.
　　1.2 Current Status of Smart Mine Development in China
　　Over the past four decades since the reform and opening-up policy was launched, China’s mining industry has not only provided abundant basic raw materials for economic and social development but has also faced multiple pressures related to energy, resources, and the environment. As a traditional industry, the mining sector urgently needs to address a series of challenges, including extensive development practices, low production efficiency and energy utilization rates, and suboptimal resource utilization levels. The continuous attention and support from the state for the mining industry call for vigorously promoting coordinated digital and green transformation and development. In particular, “leveraging digital technologies to empower the green transformation of the mining industry” has been identified as an important task for mining enterprises seeking to upgrade and accelerate their development. In recent years, as efforts have been stepped up to promote “efficiency, safety, and environmental protection” in mine construction and mining operations, the adoption rate of digital design tools and the CNC rate of key process flows have both improved to some extent among many domestic mining enterprises. Meanwhile, the level of intelligence in mines has been steadily rising, especially with the widespread application of technologies such as big data, automatic control, the Internet of Things, and 5G, which have enabled some mines to achieve breakthrough progress in intelligent construction.
　　China’s intelligent mining development exhibits distinctive features across different regions. For example, the Sanshandao Gold Mine of Shandong Gold has leveraged new networks, technologies, and applications to unlock a new growth engine for mine development, pioneering a new model for mine construction and operations and achieving industrial digitalization. At the Pulang Copper Mine in Yunnan, the 5G-based smart mining industrial application has been successfully implemented, enabling automated and intelligent operations—including loading, hauling, and dumping of ore within underground vein systems—and establishing a comprehensive, intelligent solution for minimally manned and unmanned production processes. The Dahongshan Iron Mine in Yuxi integrates more than 30 subsystems, providing integrated control over intelligent mining and beneficiation, data-driven decision-making, energy management, and safety management. Mining production now features three-dimensional geological modeling of geology, surveying, and mining, as well as driverless haulage vehicles; beneficiation processes benefit from remote centralized control of key equipment and real-time dynamic adjustment of production parameters; and surface operations include automated dust suppression via road spraying and online monitoring. In Zhejiang, Jiaotou Puxin Mining has established a decision-making command and dispatch center, along with a three-dimensional geological twin model of mineral resources, and has developed six major systems: early warning for over-boundary mining, real-time online monitoring of mine dust, real-time positioning and tracking of personnel and vehicles, all-around video surveillance, intelligent vehicle scheduling, and online quality inspection of aggregates. Baowu Resources has comprehensively upgraded its smart mines; in 2022, its indices for unmanned and centralized operations reached 60.2% and 54.2%, respectively. At Ma Steel Zhangzhuang Mine, the intelligent beneficiation system achieves fully automated operation throughout the entire process, increasing concentrate production capacity by more than 10%. The intelligent filling system enables fully intelligent control over the entire filling process and one-click filling operations. At Wugang Daye Mine, based on “ore flow”-oriented full-process management, an integrated intelligent control platform has been built that combines mining, beneficiation, and filling processes. To address the hazards posed by blast waves in mining areas, power grid technology has been introduced, establishing an intelligent decision-making and remote control system for mine ventilation, while also integrating aerial photography, monitoring points in collapsed areas, and 3D reconstruction technologies. At the Yulong Copper Mine in Tibet, intelligent truck scheduling, smart ore blending, high-precision positioning of electric shovels, and automatic drilling pattern setting have been implemented, alongside high-precision online detection of grade in raw ore, concentrate, and tailings, as well as intelligent control over crushing and grinding-flotation processes. Through a production, safety, environmental protection, and energy monitoring platform and an MES system, cost and process management are realized, supported by comprehensive mobile applications. Western Mining’s Xitie Shan Lead-Zinc Mine has carried out a complete architectural design covering mining, beneficiation, and management, enabling driverless locomotives, remote ore loading, integrated mining data collection, and intelligent ventilation. Additionally, it has achieved centralized control over the entire beneficiation process, as well as expert control systems for grinding and flotation. Mine data is automatically collected and intelligently analyzed, ensuring comprehensive process cost management. Tongmei Datang Tashan Coal Mine has undertaken intelligent construction and renovation of 10 major systems—covering mining, excavation, machinery, transportation, ventilation, geological hazard prevention and water control—as well as 27 specialized sub-systems. It has created a smart decision-making platform known as the “Mine Cloud Map,” leveraging modern communication and control technologies to achieve remote, collaborative, and automated control across the entire safe production process. Luoyang Molybdenum’s Sandaozhuang Open-Pit Mine has adopted a new generation of IoT, big data, artificial intelligence, and other advanced technologies, integrating unmanned aerial vehicle dynamic modeling, multi-metal multi-objective ore blending, intelligent scheduling of loading and unloading, and intelligent analysis and management of production data into a comprehensive, next-generation smart production control and decision-making system for open-pit mines.
　　1.3 Issues in the Construction of Smart Mines
　　First, the concept of smart mines remains unclear. Currently, the understanding of smart mines is still rather one-sided—often viewed simply as the digitalization, automation, and unmanned operation of every stage in mining production, thereby enhancing management efficiency and achieving resource intensification. However, the true significance of smart mines lies more in the digitalization, automation, and coordinated management of all key elements. Moreover, the operational systems of smart mines must also possess capabilities for sensing, analyzing, reasoning, judging, and making decisions.
　　Second, the concept behind smart mine development is outdated. China boasts a wide variety of mineral resources with enormous total reserves, yet large-scale mines are relatively few, while small- and medium-sized mines are abundant. Open-pit mining is less common, whereas underground mining prevails; independent mines are rare, while co-produced (or associated) minerals are prevalent. Given the significant regional differences, smart mine development must be tailored to local conditions and adopt appropriate approaches and methods to achieve intelligent mine operations. However, many mines, in their efforts to undergo intelligent transformation and upgrading, simply copy and paste existing models without formulating customized smart mine development plans that take into account their specific circumstances.
　　Third, the construction system for smart mines is still immature. There is a lack of coordination among various stages of smart mine development, resulting in isolated information and data that fail to form an integrated system. Consequently, the benefits of intelligent upgrades at individual stages are significantly diminished. A smart mine is a comprehensive system that closely integrates digital, automated, and intelligent technologies with mining production and operational processes, thereby achieving intelligent production and management in mines. For most mines in China, building such a system has become the greatest challenge and pain point.
　　Fourth, the policy support for smart mines is insufficient. The state has identified “leveraging digital technologies to drive the green transformation of the mining industry” as a key task for mining enterprises seeking transformation, upgrading, and accelerated development. However, overall, the supporting policies and the level of support remain somewhat inadequate. For most small- and medium-sized mining enterprises, the benefits derived from systematic smart infrastructure development are still insufficient to cover the associated construction costs. Meanwhile, the uncertain prospects for survival and growth faced by mining enterprises also hinder their decision-making and progress in upgrading and transforming their operations.
　　Fifth, the supporting industries for smart mines are incomplete. Currently, most of these industries rely on third-party technology companies that provide information-based services. Aside from 5G mining technologies, there is a lack of sufficiently robust technology enterprises to support the development of smart mines domestically. Moreover, industries such as intelligent mine equipment manufacturing and production services remain incomplete, uncoordinated, and unsystematic.
　　Overall, China's research and development of intelligent mining technologies started relatively late. Compared with the advanced international standards, most Chinese mining enterprises have low levels of production automation, fragmented systems, and poor information integration—particularly in terms of the three-dimensional geological modeling used for resource reserve management, which remains at a relatively low level. With the rapid advancement of digital communication technologies in China, the construction of smart mines has been greatly accelerated, and some aspects have even reached an internationally leading position. However, there is still a certain gap in terms of systematic and comprehensive approaches.
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　　Trends in the Development of Smart Mines
　　To guide and standardize the mining industry in accelerating the development of smart mines, the Ministry of Natural Resources has, over more than two years of concerted effort involving numerous automation design firms, research institutes, universities, and mining enterprises, compiled and released the industry standard “Specification for Smart Mine Construction” (DZ/T 0376—2021), which has become a crucial guideline for promoting the automated and intelligent application across all stages of mineral exploration and development. At the same time, the ministry has stepped up efforts to implement and enforce this industry standard; 16 enterprises have been designated as pilot units under the Ministry’s “Smart Mine Construction Specification.” The practical demonstrations carried out by these pilot enterprises will undoubtedly serve as exemplary models for smart mine development with Chinese characteristics. Furthermore, in the “Catalog of Advanced and Applicable Technologies for Conservation and Comprehensive Utilization of Mineral Resources (2022 Edition)” issued by the Ministry of Natural Resources, digital and information technologies have been identified as a key area. Many innovative digital and intelligent technological equipment developed and applied by various research institutions and mining enterprises have been included in this catalog. Overall, the development trend of smart mines is reflected in the following aspects.
　　First, the core objective is to achieve safe, green, and efficient exploration and utilization of mineral resources. Starting from the realities of mine production, we must leverage cutting-edge modern technologies to empower resource development, with the ultimate goal of enhancing mining efficiency and optimizing resource utilization. Mining enterprises need to strengthen their sense of responsibility and promote the intelligent transformation of mines—a key component of the nation’s drive toward coordinated digital and green transformation. In advancing the intelligent development of mines, it is crucial to stay firmly focused on the right direction and adhere to the principles of improving efficiency, conserving resources, pursuing green development, and prioritizing safety.
　　Second, empower resource development with cutting-edge modern technologies. Relying on the “ore flow” generated throughout the resource extraction process, we will standardize the intelligent construction of the entire workflow—including mine geological surveying, reserve management, mining operations, ore dressing, resource conservation and comprehensive utilization, and ecological restoration. We will also place great emphasis on the innovative integration of new technologies such as artificial intelligence, big data, the Internet of Things, industrial internet, cloud computing, 3D technology, and virtual reality into the mining industry. This will lay a solid foundation for mine data and promote the automated and intelligent application of all stages of mine development.
　　Third, we will enhance the level of intelligent control in the mineral extraction process. By leveraging next-generation technologies such as networking, navigation, high-definition video, and cloud computing—common enabling platforms—we will achieve precise exploration and geological modeling, intelligent identification of ore layers, and accurate positioning of mineral resources. We will vigorously develop smart applications such as unmanned vehicles and mining robots, enabling remote control and autonomous driving for underground operations including rock drilling, loading, and transportation—all without human presence. Furthermore, we will carry out geological modeling of the extraction process to improve resource recovery rates, optimize fault monitoring in the transportation phase, and reduce energy consumption during downtime.
　　Fourth, we will strengthen the intelligent and efficient utilization of mineral resources as well as ecological protection in mining areas. We will promote the intelligent upgrading and transformation of mines, enhance the intelligence level of ore processing, advance the comprehensive development and utilization of co-produced (or associated) resources, achieve energy conservation and emission reduction, realize clean mineral production, and effectively utilize mineral waste, thereby improving the environmental friendliness of mining operations. We will actively leverage various sensing devices and digital intelligence technologies to conduct ecological monitoring of mining areas and their surrounding environments, enhancing the effectiveness of ecological protection and restoration efforts. We will also strengthen geological environment exploration, employ integrated remote sensing monitoring technologies to assess slope stability, and bolster our capacity for early warning of geological hazards such as landslides and debris flows along mountain slopes.
　　Fifth, we will comprehensively strengthen the construction of a digital industrial chain and supply chain system for the mining sector. We will build digital operation platforms for mines, seamlessly integrating intelligent management across all stages—from production exploration and mining excavation to ore beneficiation and processing, as well as mineral sales—thereby enhancing the overall reserve and regulation capabilities of mineral resources and creating new models and networks for mineral production and marketing. Focusing on the key links of “production, transportation, storage, and sales,” we will leverage digital platforms to connect with downstream industries such as metallurgy, construction, and chemical engineering, continuously improving the level of collaborative sales.
　　Sixth, we must fully take into account the actual conditions and needs of mines and adopt a tiered approach to their development. Mines in different regions and of different types vary significantly in terms of geological conditions, resource endowments, and development methods. Therefore, there is no one-size-fits-all model for advancing smart mine development, and the degree of智能化 (intelligentization) cannot be uniformly standardized across all mines. Smart mines can be categorized into different levels based on the extent of intelligent applications. Mine enterprises should focus on holistic consideration and comprehensive planning, carefully assess their own foundational capabilities and strengths, and, in light of their existing process levels and actual needs, choose an intelligent development path that best suits them. This will ensure that mining enterprises achieve a win-win outcome in terms of resources, efficiency, and safety through intelligent transformation.
　　Seventh, the pace of intelligent construction in mines is accelerating. Facts have proven that promoting intelligent mine development and enhancing enterprises’ independent innovation capabilities and resource exploitation efficiency has become an indispensable path for achieving high-quality development in the mining industry. Mine enterprises with the necessary conditions should take the initiative in advancing intelligent construction, carrying out intelligent upgrades and transformations in areas such as smart oilfields, smart mines, and intelligent mining operations, and strive to become pilot demonstration enterprises that can drive and lead innovation and intelligent development in the mining industry.
　　Eighth, the construction of smart mines involves achieving intelligence across various aspects—including geology and surveying, reserves of mineral resources, mineral resource development, ore dressing, resource conservation and integrated utilization, ecological and environmental protection, and intelligent collaborative management. This goes beyond mere automation and unmanned operations in the mining process, enabling miners to maximize their economic benefits, rationalize resource utilization, make environmental protection more sustainable, and optimize production safety. Moreover, by analyzing downstream market trends, smart mines can even automatically adjust production and development strategies, thereby allowing mining enterprises to reap greater returns.
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　　Analysis of the Development Path for Smart Mines
　　A smart mine is a modern mining operation that achieves digital, automated, informational, and collaborative management of all key elements—including mine geology and surveying, mineral resource reserves, mining, ore dressing, resource conservation and comprehensive utilization, ecological and environmental protection, and production and business operations. Moreover, its operational system possesses the capabilities of sensing, analyzing, reasoning, judging, and making decisions. It is a comprehensive system that integrates digital, automated, and intelligent technologies with mining production and business processes, enabling intelligent production and management in mines and demonstrating the application of new intelligent technologies, concepts, and methods in the mining industry.
　　The construction of smart mines should fully reflect the industry-specific characteristics arising from the cross-integration of new technologies—including big data, modern information technology, the Internet of Things, the Industrial Internet, and artificial intelligence—with the mining sector. It should also fully meet the requirements for the continuous and deepening application of digital and intelligent technologies and equipment in both production and management processes. The massive, diverse, and heterogeneous data generated by digitizing information throughout the entire mine lifecycle—from exploration and construction to production and closure—will be aggregated into a rich big data resource. After data mining and advanced processing, this resource will be leveraged for mine production management and decision-making. By harnessing big data and machine learning, we can achieve real-time, intelligent monitoring of mineral resource production processes, as well as the selective sorting, classification, and recycling of waste materials, thereby reducing environmental pollution and further promoting the development of green mines. Through the integrated convergence of modern communication and information technologies, computer science, automatic control technologies, artificial intelligence, and advanced mining technologies, we can build a practical, intelligent mine system platform that enables full-process visualization and controllability of mine operations, as well as intelligent management, thus enhancing production efficiency and improving safety. At the same time, we must place great emphasis on building a skilled workforce for mine intelligence, cultivating a team of professionals with high-tech expertise and profound knowledge of the mining industry, and continuously driving the transformation and upgrading of mines, fostering technological innovation, and ensuring sustainable development.
　　3.1 Intelligentization of Geological and Surveying Work
　　The primary focus is on enhancing the intelligentization of geological and surveying work in mining operations. By leveraging specialized software, we will develop geological models and manage geological data related to ore deposits, hydrology, engineering, and the environment, thereby promptly acquiring and consolidating various exploration and mining data generated throughout the mineral exploration and development process. The geological models should adopt standardized data exchange formats to meet the requirements for intelligent management and control in mining operations. Furthermore, we will employ digital engineering surveying and void-space measurement technologies to carry out three-dimensional engineering acceptance inspections and support multi-dimensional engineering mapping functions. We will establish an integrated information management system for geological and surveying data, enabling the digitalization, vectorization, and storage of exploration reports, verification reports, surveying data, production exploration reports, and annual mine reserve reports according to specified formats. All operations—including updates, additions, and retrievals—will be accompanied by traceable records. Measurement results pertaining to mine terrain, geological structures, underground excavation projects, and mined-out areas shall be interconnected with the production management system and the dynamic reserve management system, allowing for secure and efficient sharing of geological and surveying data through workflow and access control mechanisms. This will facilitate integrated, dynamic management of technology, planning, and production processes.
　　3.2 Intelligent Management of Mineral Resource Reserves
　　The primary goal is to implement intelligent applications for mine reserve estimation, evaluation, and resource management. In line with the actual needs of mine production, comprehensive three-dimensional digital geological models should be established for geological entities directly related to mine resource estimation, mine design, and mining and beneficiation processes. These models should intuitively depict the distribution, morphology, occurrence, and grade characteristics of ore bodies, country rocks, structures, and mineral components. Based on the latest classification standards for mineral resource reserves, the system should enable accurate estimation and dynamic updating of mineral resource reserves, thereby achieving information-based, dynamic, three-dimensional visualized, and intelligent management of mineral resources. At the same time, intelligent algorithms should be employed to delineate resource boundaries, and reserve estimation should be carried out using geological models and estimation software. Mine reserve data should be integrated with and synchronized with operational and production data. The data should be updated promptly in response to changes in the latest surveying, mining, technological, market, and policy conditions. Furthermore, the system should allow retrospective analysis of the dynamic changes in resource quantities and reserves over time, along with corresponding production technology parameters, thus enabling dynamic tracking and management. The relevant systems should be equipped with data exchange interfaces to provide up-to-date dynamic data on mineral resource reserves to the relevant management authorities in a synchronized manner.
　　3.3 Intelligentization of the Mineral Resource Extraction Process
　　The primary focus is on achieving intelligent control and management of both the mining production process and auxiliary production processes. Mine excavation design and planning should be digitized and managed through three-dimensional visualization. Priority should be given to selecting highly intelligent equipment for key mine machinery, thereby reducing the number of personnel required on-site. Such equipment should be equipped with network connectivity features to enable online collection of equipment location, status, and operational data, and should be integrated into a centralized monitoring platform to facilitate unified dispatching, command, or remote visual control. The scope of mining operations should be regulated and made controllable through the use of three-dimensional virtual electronic fences. The mining transportation system should be comprehensively integrated with the ore quality inspection system to establish an ore tracking and blending control framework, enabling real-time assessment of mined ore quality. Auxiliary production systems should support remote control, data acquisition, and intelligent management.
　　The specialized equipment used in open-pit mining—such as rock drills, drilling rigs, and loaders—should be equipped with automatic positioning, dynamic tracking, and online fault monitoring and diagnostics. Crushing equipment should feature automated control, enabling remote operation and coordinated work with the transportation system. Transportation equipment with remote control or autonomous driving capabilities should be selected, along with features such as collision avoidance and early warning systems, as well as blind-spot monitoring. Conveyor belts should be capable of automatic start-stop operations and intelligent safety protection. Robots should be employed for routine inspections along the conveyor lines.
　　In underground mining, tunneling, extraction, and hoisting & transportation primarily rely on automated and intelligent equipment, significantly reducing the number of workers required. Real-time collection of operational data from various equipment and remote monitoring are implemented. The loading, transportation, and unloading processes are fully automated. Vehicles are equipped with functions for roadway space detection, collision avoidance, and early warning. Linked equipment should feature interlocked emergency stop mechanisms and automated centralized control capabilities.
　　3.4 Intelligentization of Mineral Processing and Beneficiation Processes
　　Intelligent control and management are implemented across all production stages, including ore dressing—crushing and screening, grinding and classification, beneficiation processing, concentrate handling, tailings thickening and transportation. Through technologies such as process modeling, data analysis, expert decision-making, and machine learning, the beneficiation process systematically summarizes operational rules, enabling adaptive, self-decisive intelligent control throughout the entire beneficiation workflow. The raw materials selected for processing are subjected to ore blending measures and optimized blending control, ensuring stable grade and properties of the feed ore. A recovery component balance analysis system is established in the beneficiation process to enable dynamic management, with online monitoring and process diagnosis capabilities, thus facilitating prediction and early warning and enhancing resource utilization.
　　The crushing and screening system should feature automated centralized control, employing intelligent recognition technology for online detection and smart decision-making to reduce energy consumption. The grinding and classification process should be equipped with automatic control capabilities, enabling real-time optimization and adjustment of product particle size, as well as an automated media storage and addition system. The control system for beneficiation processing should autonomously select control parameters and strategies based on process conditions and raw material characteristics, thereby enhancing beneficiation efficiency and recovery rates. Each process stage should implement online monitoring to provide data support for parameter optimization. Auxiliary production facilities—including transportation systems, hydrothermal systems, raw ore bins, fine ore bins, and stockyards—should all be equipped with automated detection and control functions and integrated into a unified control platform.
　　3.5 Intelligent Resource Conservation and Comprehensive Utilization
　　Intelligent control is primarily implemented in areas such as tracking and evaluating the utilization of mineral resources, recovering co-produced (or associated) minerals, and utilizing waste materials. An information-based and intelligent management system for resource conservation and comprehensive utilization will be established to enhance the capacity for assessing, developing, and transforming co-produced (or associated) mineral resources and waste materials. A database for the utilization and management of co-produced (or associated) minerals and waste materials will be created, providing statistical analysis functions for metrics such as yield and utilization rate. This database will enable an analysis and evaluation of the value of co-produced (or associated) mineral utilization and waste reuse from the perspectives of industrial and supply chains. It will also facilitate online management of the entire process—from mining and storage to processing and utilization of co-produced (or associated) minerals—and integrate emission control measures for wastewater, exhaust gases, tailings, and waste rock with production control systems, thereby reducing emissions through optimized production control strategies. The comprehensive utilization process will be integrated with the primary production and processing flow, enabling automated integrated control, unified information-based management, intelligent and scientific matching, and ultimately, reduced costs for comprehensive utilization.
　　3.6 Intelligent Approaches to Ecological Environmental Protection and Restoration
　　The focus is on achieving intelligent standards in areas such as ecological environment monitoring, governance, and remediation. Following the principle of prevention first and giving equal weight to production and governance, we aim to reduce the impact of environmental pollution by establishing an information-based management platform that centrally manages online environmental monitoring data and inspection and analysis results. The platform will also provide dynamic data analysis and early-warning functions, enabling centralized, integrated, and real-time monitoring and management.
　　Establish a digital, visual management system for ore stockpiles and stockpile volumes, dynamically monitoring the operational status of ore stockpiles, conducting waste sorting, reducing emissions, and enhancing the level of reuse—particularly by implementing automated detection and control for water-based dust suppression. Develop an integrated management platform for spoil yards and waste rock sites, covering production operations, water and soil conservation, and land reclamation and greening efforts. This platform will visually display the implementation status of ecological protection measures, as well as the progress and effectiveness of land reclamation and greening, and will also enable historical traceability.
　　3.7 Intelligent Integrated Coordination and Control
　　Intelligent transformation is primarily achieved in areas such as mine infrastructure, data acquisition, data application, data storage, scheduling and management, as well as production and operations, computer-aided decision-making analysis, and information dissemination. Through data integration and information fusion technologies, centralized control of production and online intelligent analysis are realized. Moreover, by leveraging big data from mines and intelligent decision-making technologies, coordinated and intelligent management and operations are enabled.
　　Integrate the planning and construction of network infrastructure to support information-based applications such as data collection, information management, and security monitoring. Furthermore, centrally deploy and build operational terminals—including automated systems and centralized control platforms—within the dispatch and control center, thereby achieving centralized management of information throughout the mining and beneficiation production process and comprehensive control over auxiliary production data. Leveraging digital application technologies such as data integration, data flow, query, statistical analysis, prediction, and forecasting, we will implement all-domain, all-element, and full-process information-based management of mine production and processes. Establish a unified data service system that provides centralized management and access services for real-time data, relational data, and other types of data. Through the mine operation and management system, we will enable collaborative management of enterprise operations—including supply chain, finance, and human resources—and leverage the enterprise data center and data service system to integrate data and functionalities, thereby supporting decision-making analysis and information dissemination for mining enterprises.
　　3.8 Levels of Intelligent Mining Construction
　　The construction of smart mines should adhere to the principles of adapting to local conditions and integrated planning. Based on the mine’s specific circumstances, as well as the depth and breadth of application of intelligent technologies and products within mining enterprises, an appropriate level of intelligence should be selected to formulate a construction plan. The development of smart mines should proceed in a tiered manner, starting with individual applications, followed by integrated and collaborative applications, and ultimately culminating in comprehensive, holistic implementation. Specifically: Individual applications are characterized by the widespread adoption of basic automation control and information management systems. In this stage, one or more standalone intelligent systems are developed, each operating independently without integration or fusion with existing basic automation or information systems. Integrated and collaborative applications are marked by the integration of intelligent systems with foundational information systems, making them integral components of an overall information integration framework. Moreover, multiple interconnected intelligent systems can achieve autonomous collaboration, enabling interactive operations and coordinated functioning, thus realizing localized integration effects. Comprehensive, holistic applications are characterized by the pervasive use of intelligent technologies throughout the entire production process. All intelligent systems are networked and work collaboratively, allowing for extensive collection of production and operational data. This data is then fully leveraged through intelligent decision-making systems.
　　For smaller mines with relatively low ore grades, maximizing benefits in smart mine development can be achieved by focusing on the implementation of individual, targeted applications—meaning that intelligent technologies can be deployed effectively in specific projects to better support mine production. For mines that meet certain conditions and possess adequate scale and strength, interconnected intelligent systems can achieve interactive operations and coordinated workflows through autonomous collaboration, thus realizing localized integration and enabling integrated, synergistic applications. As for large and medium-sized mines with strong capabilities and favorable conditions, it is essential to integrate smart technologies throughout the entire upstream-to-downstream value chain, connecting all intelligent systems for networked collaboration and achieving a comprehensive, enterprise-wide application level that significantly enhances production efficiency and competitiveness.
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　　Conclusions and Recommendations
　　1) Internationally advanced mining companies have taken smart mine development beyond the realms of mechanization and automation, integrating the concepts of green, safe, intelligent, and efficient operations into every stage of mining production. In recent years, China’s smart mining initiatives have seen rapid progress; however, challenges remain, including unclear conceptual frameworks, outdated construction philosophies, an immature construction system, insufficient policy support, and an incomplete supporting industrial ecosystem.
　　2) The development of smart mines should take as its core objective the safe, green, and efficient exploration and utilization of mineral resources. It should fully reflect the industry’s unique characteristics—namely, the cross-fusion of new technologies such as big data, the industrial internet, and artificial intelligence with the mining sector—and adequately meet the requirements for the continuous and deepening integration of digital and intelligent technologies and equipment into production and management processes. This will enable full-process visualization and controllability of mine operations, as well as intelligent management, thereby enhancing both production efficiency and safety.
　　3) The content and approach for smart mine development encompass geology and surveying, management of mine resource reserves, mining and ore dressing, resource conservation and comprehensive utilization, ecological environment protection and restoration, and integrated collaborative management. It involves establishing a highly user-friendly decision-support system and building an implementable smart mine system platform. Fully taking into account the actual conditions and needs of mines, we will advance smart mine development in an orderly manner.
　　4) Establish and improve a comprehensive system of technical specifications and standards for intelligent applications in mining, accelerate the cultivation and development of a specialized talent pool, intensify support through various policies and measures, and effectively ensure the sustained advancement of intelligent mining development, thereby promoting high-quality growth of China’s mining industry.
Original link: https://mp.weixin.qq.com/s/oEpWmVf7dnEp_WWrwbnvSg