DEVELOPMENT OF DIGITAL MONITORING SYSTEMS AND SMART MINE TECHNOLOGIES IN UNDERGROUND COAL MINING

УДК 622.33:622.6:681.518

Abstract

The rapid digital transformation of the mining industry has created new opportunities for improving the efficiency, safety, and sustainability of underground coal mining. The aim of this study is to investigate the possibilities of implementing digital monitoring systems and Smart Mine technologies in underground coal mining and to evaluate their impact on production efficiency, equipment reliability, and occupational safety. To achieve this objective, the study employs a comparative analysis of recent scientific publications, a review of international experience in mining digitalization, and a systematic analysis of the functional capabilities of SCADA systems, sensor networks, and intelligent monitoring technologies. Particular attention is given to the integration of real-time data acquisition, fault diagnostics, predictive maintenance, and artificial intelligence into underground mining operations. The results demonstrate that digital monitoring systems enable continuous assessment of equipment condition, early detection of potential failures, optimization of maintenance activities, and improvement of operational decision-making. The proposed Smart Mine framework contributes to enhanced equipment utilization, reduced operational risks, and improved workplace safety through intelligent process control and data-driven management. The findings provide a scientific and methodological basis for the digital transformation and technical modernization of underground coal mining enterprises, supporting sustainable, reliable, and economically efficient mining operations.

Аннотация

Стремительная цифровая трансформация горнодобывающей промышленности открывает новые возможности для повышения эффективности, безопасности и устойчивости подземной добычи угля. Целью настоящего исследования является изучение возможностей внедрения систем цифрового мониторинга и технологий «Smart Mine» в подземной добыче угля, а также оценка их влияния на производственную эффективность, эксплуатационную надёжность оборудования и безопасность труда. Для достижения поставленной цели использованы методы сравнительного анализа современных научных публикаций, обзора международного опыта цифровизации горнодобывающей промышленности, а также системного анализа функциональных возможностей SCADA-систем, сенсорных сетей и интеллектуальных технологий мониторинга. Особое внимание уделено интеграции технологий сбора данных в режиме реального времени, диагностики неисправностей, прогнозного технического обслуживания и искусственного интеллекта в процессы подземной добычи угля. Полученные результаты показывают, что системы цифрового мониторинга обеспечивают непрерывный контроль технического состояния оборудования, раннее выявление потенциальных неисправностей, оптимизацию технического обслуживания и повышение эффективности принятия производственных решений. Предлагаемая концепция «Smart Mine» способствует более эффективному использованию оборудования, снижению эксплуатационных рисков и повышению безопасности труда благодаря интеллектуальному управлению технологическими процессами и принятию решений на основе анализа данных. Полученные результаты формируют научно-методическую основу для цифровой трансформации и технической модернизации предприятий подземной угледобычи, обеспечивая их устойчивое, надёжное и экономически эффективное функционирование.

Keywords: Smart mine, digital monitoring, shearer automation, mining safety, artificial intelligence.

Ключевые слова: умная шахта, цифровой мониторинг, автоматизация очистного комбайна, безопасность горных работ, искусственный интеллект.

Introduction

The mining industry is undergoing rapid digital transformation driven by the need to improve production efficiency, occupational safety, and sustainable resource utilization. Underground coal mining remains one of the most hazardous industrial activities because of complex geological conditions, equipment failures, gas emissions, and the continuous interaction between personnel and mining machinery. Therefore, the implementation of digital technologies has become one of the key priorities for modern mining enterprises.

Conveyor transport plays a crucial role in underground coal mining by ensuring continuous material transportation. Previous studies have focused on improving conveyor reliability, optimizing technological parameters, and increasing the efficiency of transport systems [1–7]. However, conventional maintenance is mainly based on periodic inspections and manual diagnostics, which do not provide continuous equipment condition monitoring or early fault detection.

The concept of the Smart Mine has emerged as an integrated approach to mining digitalization by combining Industrial Internet of Things (IIoT), sensor networks, SCADA systems, artificial intelligence, big data analytics, and digital twin technologies into a unified production management platform. These technologies enable continuous equipment monitoring, predictive maintenance, automated process control, and intelligent decision-making based on real-time operational data.

International studies indicate that digital transformation significantly improves equipment reliability, production efficiency, and occupational safety through intelligent monitoring and predictive maintenance [8–15]. Nevertheless, the practical implementation of Smart Mine technologies in many underground coal mines remains limited, making the development of integrated digital monitoring systems an important scientific and engineering challenge.

The aim of this research is to investigate the principles of implementing digital monitoring systems and Smart Mine technologies in underground coal mining and to evaluate their potential impact on equipment reliability, production efficiency, and occupational safety. To achieve this objective, the study analyzes the architecture of modern digital monitoring systems, examines the operating principles of SCADA-based intelligent control, and summarizes international experience in the application of Smart Mine technologies. Among the various Smart Mine subsystems, conveyor transport monitoring is considered a representative example because uninterrupted material transportation directly affects the continuity and efficiency of underground mining operations.

The scientific novelty of this work lies in the systematization of modern approaches to digital monitoring for underground coal mining and in the development of a conceptual framework integrating sensor technologies, SCADA systems, and intelligent decision-support tools into a unified Smart Mine architecture. The proposed approach provides a methodological basis for improving equipment reliability and supporting the digital transformation of underground coal mining enterprises.

Materials and methods

Leading global mining companies, including Rio Tinto, BHP, and Caterpillar, have been actively implementing this concept in practice by utilizing autonomous equipment, digital control systems, and artificial intelligence. This has laid the foundation for the development of the “unmanned mine” concept. In conclusion, the “Smart Mine” concept represents a logical continuation of mechanization, automation, and digitalization stages in the mining industry and serves to ensure efficient, safe, and sustainable production based on modern technologies. The general structural scheme of the “Smart Mine” concept is presented in Figure 1.

The proposed digital monitoring architecture consists of several interconnected functional modules responsible for data acquisition, processing, transmission, and intelligent decision support. Their functions are summarized in Table 1.

Table 1. Functional components of the proposed digital monitoring system

Figure 1. Structural scheme of the intelligent control system for production processes in an underground mining operation.

The proposed architecture provides continuous monitoring of production processes and forms the technological basis for implementing Smart Mine technologies in underground coal mines.

The productivity of underground coal mining combines largely depends on the technical condition of machines and equipment as well as the operator’s skills. However, the human factor and the lack of real-time data often lead to unexpected downtime and economic losses. In particular, the absence of digital monitoring systems in the mining industry limits the optimization of equipment operation.

Mining combines used in underground mines are highly productive and complex technical systems. Their efficient operation requires continuous monitoring of multiple technical parameters. Digital monitoring systems consist of the following main components: sensor and detection systems; real-time data transmission networks; dispatching centers; automated control systems.

With the help of these systems, parameters such as combine load level, cutting speed, engine temperature, vibration indicators, and other variables can be continuously monitored. This enables early detection of equipment malfunctions. According to industrial analyses and studies by scholars such as Sh. Ge, the implementation of digital monitoring systems can reduce equipment failures in mining operations by 20–25% and decrease operational costs by 10–15% [11].

The development of the Smart Mine concept in the mining industry has progressed through several stages [11–15]:

Stage 1 – Automation. At this stage, individual processes of mining equipment are automated. For example, shearers, conveyors, and ventilation systems are controlled through automatic control systems.

Stage 2 – Digital monitoring. In this stage, production processes are monitored in real time using sensors and information systems.

Stage 3 – Integrated control. All technological processes are integrated into a unified digital platform and managed in a centralized manner.

Stage 4 – Smart mine. This is the highest stage, where mining processes are optimized using artificial intelligence, big data, and predictive algorithms.

For example, the automated control of conveyor systems is considered. The continuous operation of conveyor systems is directly dependent on constant monitoring and analysis of their technical condition. Currently, these processes are monitored using modern SCADA systems (Figure 2). SCADA is a system that enables real-time monitoring and control of production processes via a central computer.

The study employed a comparative analysis of international scientific publications on mining digitalization, a systematic review of Smart Mine technologies, and functional analysis of SCADA-based monitoring systems. The conceptual architecture of the proposed monitoring system was developed using systems engineering principles and generalized industrial experience reported in recent publications.

Results and discussion

Among the various subsystems of a Smart Mine, conveyor transport monitoring represents one of the most critical components because uninterrupted material transportation directly affects production continuity. Therefore, the conveyor monitoring system is considered in this study as a representative example of implementing Smart Mine technologies.

SCADA typically consists of four main levels:

1) Lower level — sensors and measuring devices. At this level, devices that measure the technical condition of the conveyor are installed. These devices measure physical parameters such as vibration, temperature, current, etc.: Vibration sensors (rollers, bearings); Temperature sensors (infrared or contact type);  Current and voltage sensors (for electric motors); Speed and belt displacement sensors

2) Middle level — PLC (Programmable Logic Controller). At this level, PLC controllers operate (the “brain” that makes rapid decisions): Receives signals from sensors; Performs initial data processing; Compares values with threshold limits; Sends alarms or automatically shuts down the conveyor in emergency situations.

3) Communication system. Data is transmitted through the following channels: Ethernet (Modbus) Profibus protocols; Optical fiber or wireless communication.  This system ensures continuous data exchange between sensor → PLC → central computer.

4) Upper level — operator panel (HMI/SCADA server). At this level, the operator controls the system (the “eyes and control center”): Computer or dispatcher panel (HMI); Graphical interface (diagrams, trends); Alarm system; Database (archiving system).

Working Principle of the SCADA System

The SCADA system operates in the following sequence:

Stage 1: Data acquisition

Sensors measure the conveyor condition: Vibration → mm/s ; Temperature → °C ; Current → A.

Stage 2: Signal processing

The PLC performs the following operations: Filters the incoming signals; Compares them with threshold values.

For example: If V > 4.5 mm/s → potential fault condition; If T > 70°C → overheating condition.

Stage 3: Transmission and visualization

The collected data is transmitted to the SCADA system, where it is: Displayed in graphical form; Presented as real-time trends; Used to generate operator alerts.

Stage 4: Decision-making

The system operates in two modes:

1. Automatic mode: The conveyor is stopped; Load is reduced; Alarm signals are generated.

2. Operator mode: The operator makes decisions; Maintenance actions are scheduled.

Stage 5: Data storage and analysis: All data is stored in a database; Fault statistics are maintained; System reliability R(t) is calculated; Preventive maintenance scheduling is optimized.

The implementation of SCADA-based monitoring systems and intelligent diagnostic technologies significantly improves the operational performance of underground mining equipment. Continuous acquisition and analysis of real-time operational parameters, including vibration, temperature, motor current, and belt speed, enable early fault detection and predictive maintenance scheduling. As reported by Ge [11], intelligent monitoring technologies implemented in fully mechanized coal mining systems substantially reduce unexpected equipment failures and improve production continuity. Similar conclusions were presented by the World Economic Forum [9], which identified predictive maintenance and real-time monitoring as key factors for reducing operational costs and increasing equipment utilization in the mining industry.

According to Bellamy and Pravica [14], the application of digital monitoring technologies allows mining companies to reduce maintenance costs, improve equipment availability, and optimize energy consumption through condition-based maintenance strategies. Furthermore, the International Energy Agency [15] notes that digital technologies contribute to higher energy efficiency and better utilization of industrial assets by enabling continuous performance assessment and operational optimization.

Based on the analysis of these studies and the operating principles of SCADA systems, the implementation of digital monitoring in underground conveyor transport can reasonably be expected to increase equipment reliability, reduce unplanned downtime, extend component service life, and improve overall production efficiency. These improvements are achieved through continuous condition monitoring, automatic alarm generation, predictive diagnostics, and timely maintenance planning rather than corrective maintenance after equipment failure.

The implementation of SCADA-based monitoring systems contributes to reduced equipment downtime, improved operational reliability, lower maintenance costs, and increased energy efficiency, as demonstrated in previous studies on intelligent mining technologies [9,11,14,15].

In general, the implementation of Smart Mine technologies leads to the following outcomes: increased production efficiency; reduced maintenance costs; improved occupational safety for miners; more efficient use of energy and resources; prevention of emergency situations.

In addition, digital monitoring systems extend the service life of mining equipment and reduce unplanned stoppages.

The transition from conventional underground mining systems to Smart Mine technologies represents a fundamental shift in production management, equipment monitoring, and occupational safety. Based on the analysis of international scientific publications, the key technological differences between these approaches are summarized in Table 2 [8–15].

Table 2. Comparative characteristics of conventional mining systems and Smart Mine technologies

As shown in Table 2, Smart Mine technologies integrate digital monitoring, intelligent diagnostics, and predictive maintenance into a unified management system. These technologies improve production efficiency, reduce operational risks, and provide a scientific basis for data-driven decision-making in underground mining operations [8–15].

Figure 2. Schematic diagram of an SCADA-based automated monitoring system for a belt conveyor

The reviewed studies consistently indicate that Smart Mine technologies contribute not only to production efficiency but also to sustainable mining practices through intelligent monitoring, predictive maintenance, and integrated process management [8–15].

Conclusion

In conclusion, it should be noted that the implementation of digital monitoring and Smart Mine technologies in underground coal mining using shearers not only increases production efficiency but, more importantly, enables remote control of processes without endangering miners’ lives. Digital transformation is the only strategic pathway ensuring the long-term sustainability of the coal mining industry. In the future, artificial intelligence, robotic mining equipment, and autonomous transport systems will further advance the Smart Mine concept. Future research should focus on developing digital twin technologies, machine learning algorithms for predictive diagnostics, and autonomous control systems adapted to the geological and technological conditions of underground coal mines in Uzbekistan.

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