Industrial Internet of Things: (IIoT) applications in underground coal mines

Application of artificial intelligence in mine ventilation: a brief review

In recent years, there has been a notable integration of artificial intelligence (AI) technologies into mine ventilation systems. A mine ventilation network presents a complex system with numerous interconnected processes, some of which pose challenges for deterministic simulation methods. The utilization of machine learning techniques and evolutionary algorithms offers a promising avenue to address these complexities, resulting in enhanced monitoring and control of air parameter distribution within the ventilation network. These methods facilitate the timely identification of resistance faults and enable prompt calculation of ventilation parameters during emergency scenarios, such as underground explosions and fires. Furthermore, evolutionary algorithms play a crucial role in the advancement of methods for visual analysis of ventilation systems. However, it is essential to acknowledge that the current utilization of AI technologies in mine ventilation is limited and does not encompass the full spectrum of challenging-to-formalize problems. Promising areas for AI application include analyzing changes in air distribution caused by unaccounted thermal draft and gas pressure, as well as developing novel approaches for calculating shock losses. Moreover, the application of AI technologies in optimizing large-scale mine ventilation networks remains an unresolved issue. Addressing these challenges holds significant potential for enhancing safety and efficiency in mine ventilation systems.

Digital Innovations for Occupational Safety: Empowering Workers in Hazardous Environments

BACKGROUND

The quest to increase safety awareness, make job sites safer, and promote decent work for all has led to the utilization of digital technologies in hazardous occupations. This study investigated the use of digital innovations for safety and health management in hazardous industries. The key challenges and recommendations associated with such use were also explored.

METHOD

Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, a total of 48 studies were reviewed to provide a framework for future pathways for the effective implementation of these innovations.

FINDINGS

The results revealed four main categories of digital safety systems: wearable-based systems, augmented/virtual reality-based systems, artificial intelligence-based systems, and navigation-based systems. A wide range of technological, behavioral, and organizational challenges were identified in relation to the key themes.

CONCLUSION

Outcomes from this review can inform policymakers and industrial decision-makers about the application of digital innovations for best safety practices in various hazardous work conditions.

Bibliometric analysis and review of mine ventilation literature published between 2010 and 2023

To provide scholars with a quick understanding of the current status, research hotspots, and future trends in the field of mine ventilation, this paper conducted a visualized bibliometric analysis and a comprehensive review of mine ventilation-related literature from 2010 to 2023 using CiteSpace. A thorough analysis of the publication time, co-authorship, co-citation, keywords, and research topics of the literature was carried out. Based on this, through systematic literature reading and summarization, research topics in the field of mine ventilation were organized, analyzed, and classified. The results indicate that mine ventilation research from 2010 to 2023 went through three stages: stable development, slow growth, and rapid ascent. Nie Wen and China Univ Min & Technol were the most prolific authors and institutions in the field of mine ventilation. China had the highest number of publications during 2010-2023, while Canada and Poland exhibited the highest centrality, signifying their key roles in the mine ventilation domain. Deep mine ventilation and intelligent mine ventilation emerged as research hotspots and mainstream trends in the future. The analysis of multiple hazard coupling studies represents a research direction that mine ventilation needs to develop. Numerical simulation techniques should not be limited to static analysis, as dynamic simulation is a focal area of interest.

Use-Case-Oriented Evaluation of Wireless Communication Technologies for Advanced Underground Mining Operations

This work aims to give an overview of wireless communication technologies (WCT) for underground applications. Difficulties regarding the harsh mining environment and operational constraints for WCT implementation and use are discussed. Selected technologies are then classified regarding underground mining-specific use cases in advanced mining operations. Use-case-based application categories such as 'automation and teleoperation', 'tracking and tracing' and 'Long-Range Underground Monitoring (LUM)' are defined. The use cases determine requirements for the operational suitability and also quantify evaluation criteria for the evaluation of WCT. The result is a comparison by category of the wireless technologies, which underlines potentials of different technologies for defined use cases, but it can be concluded that the technology always has to be evaluated within the use case and operational constraints.

Emerging technologies in Indian mining industry: an exploratory empirical investigation regarding the adoption challenges

Purpose

Emerging technologies have been transforming most industries. A wide range of emerging technologies such as blockchain, internet of things (IoT), artificial intelligence (AI), machine learning (ML), robotics and many others have changed the way in which firm value chain activities or processes were executed traditionally. The mining industry has also witnessed the introduction of these emerging technologies in various processes from the exploration stage to the final processing of ores. The purpose of this paper is to understand the pace of adoption of emerging technologies in the Indian mining industry and identify the challenges that managers confront while adopting emerging technologies.

Design/methodology/approach

The authors undertook qualitative research. Data collection was done in two stages. Secondary research was conducted to arrive at a repository of use cases of the adoption of emerging technologies in the global mining industry. Primary data collection was also done. The insights on emerging technology adoption and challenges faced in the Indian mining industry were captured by in-depth interviewing of subject matter experts. The authors interviewed 21 mining subject matter experts with a semi-structured open-ended questionnaire. The responses were content analyzed by thematic content analysis. Technological-organizational-environmental (TOE) and diffusion of innovation (DOI) frameworks were applied to segregate different factors affecting the adoption of emerging technologies in the Indian mining industry.

Findings

Emerging technologies such as blockchain, IoT, AI, ML, robotics has been applied across various mining engineering value chain activities such as in drilling, blasting, excavation and ore hauling. However, emerging technologies adoption was hindered because of a lack of managerial awareness, cultural inertia, substantive upfront investments and the nature of intangible benefits in the short run.

Research limitations/implications

The research applied technology adoption frameworks in the mining industry. The authors used TOE and DOI frameworks to understand the challenges faced by Indian mining firms. The research findings, thus added to the conversation of TOE and DOI frameworks in the context of the Indian mining industry.

Practical implications

The research finding would help mining firm managers to anticipate the challenges with respect to technology adoption. This would allow mining executives to create a proper technology adoption plan and intervene proactively. The research would also provide information about the steps taken by competing firms with respect to emerging technologies adoption. The research would help managers to decide technology implementation steps in drilling, blasting, excavation and ore hauling to be undertaken for successful adoption of emerging technologies. Technology firms could gain insights into the issues faced by mining firms in adopting emerging technologies. This research would help managers to influence organizational technology policy and endorse the addition of pro-technology policies in mining activities. Policymakers involved in the mining sector could also incorporate industry-level policy decisions so as to facilitate the adoption of emerging technologies among mining firms and remove the barriers to the adoption of emerging technologies. This would create an opportunity for technology providers to redesign product offerings, which could be a good fit for Indian mining firms.

Originality/value

Indian mining industry contributed significantly to the Indian economy. Despite this, limited focus has been put regarding the adoption of emerging technologies in the mining industry. Mining managers did not have any framework to understand the challenges faced in the adoption of technologies across the mining value chain that is in drilling, blasting, excavation and ore hauling. This study focused on identifying those challenges through the use of technology adoption frameworks. This research was one of the first studies to gain insights on emerging technologies adoption in the context of the mining industry through the theoretical lens of TOE and DOI frameworks.

Review of Key Performance Indicators for Process Monitoring in the Mining Industry

The sustainable development of an organisation requires a holistic approach to the evaluation of an enterprise’s goals and activities. The essential means enabling an organisation to achieve goals are business processes. Properly managed, business processes are a source of revenue and become an implementation of business strategy. The critical elements in process management in an enterprise are process monitoring and control. It is therefore essential to identify the Key Performance Indicators (KPIs) that are relevant to the analysed processes. Process monitoring can be performed at various levels of management, as well as from different perspectives: operational, financial, security, or maintenance. Some of the indicators known from other fields (such as personnel management, finance, or lean manufacturing) can be used in mining. However, the operational mining processes require a definition of specific indicators, especially in the context of increasing the productivity of mining machines and the possibility of using sensor data from machines and devices. The article presents a list of efficiency indicators adjusted to the specifics and particular needs of the mining industry resulting from the Industry 4.0 concept, as well as sustainable business performance. Using the conducted research and analysis, a list of indicators has been developed concerning person groups, which may serve as a benchmark for mining industry entities. The presented proposal is a result of work conducted in the SmartHUB project, which aims to create an Industrial Internet of Things (IIoT) platform that will support process management in the mining industry.

Assessing the Feasibility of a Commercially Available Wireless Internet of Things System to Improve Conveyor Safety

Conveyor systems persist in being a source of injuries and fatalities in the mining industry. To reduce these incidents, better methods are needed to enhance the monitoring of probable hazards and improve situational awareness during the normal operation and maintenance of conveyor systems. To address these issues, researchers from the National Institute for Occupational Safety and Health (NIOSH) continue to investigate emerging technologies that show the potential to improve miner safety around conveyors. This paper presents a feasibility assessment by NIOSH researchers of a fully integrated, commercially available wireless Internet of Things (IoT) system to improve situational awareness around conveyor systems. Included are discussions of a full-scale laboratory test bed that was designed to simulate a working conveyor system as well as the challenges and successes of integrating the IoT system with the test bed.

Implementation of green chemistry principles in circular economy system towards sustainable development goals: Challenges and perspectives

Green chemistry principles (GCP) are comprehensively deployed in industrial management, governmental policy, educational practice, and technology development around the world. Circular economy always aims to balance the economic growth, resource sustainability, and environmental protection. This article offers a highlight on issues of significance within GCP and circular economy, and proposes the integrated strategies for GCP implementation from the aspects of governance, industry and education. At first, we developed a new categorizing system for GCP dividing to (i) pollution and accident prevention, (ii) safety and resource sustainability, and (iii) energy and resource sustainability. To assess the GCP practice towards the circular economy, the implementation of international movement of GCP in worldwide policy, especially those of Canada, China, Germany, Japan, South Korea, Sweden, Taiwan, United States and United Kingdom were reviewed. The policy implementation of GCP practices among governance, industries and education was analyzed. To integrate GCP into the circular economy concept, we also proposed five strategies of priority governance direction as follows: (i) establishment of cross-departmental collaboration, (ii) development of cleaner production and green product, (iii) provision of integrated chemical management system, (iv) implementation of green chemistry education program, and (v) construction of a business model. Finally, we discussed the prospects of disciplinary elements including the establishment of redesign-reduction-recovery-recycle-reuse (5R) practices for wastes reclamation, deployment of water-energy-food nexus with GCP to improve the food security and resource sustainability, and implementation of GCP in the green smart industrial park.

Leveraging IIoT to Improve Machine Safety in the Mining Industry

Each year, hundreds of mine workers are involved in machinery-related accidents. Many of these accidents involve inadequate or improper use of lockout/tagout (LOTO) procedures. To mitigate the occurrence of these accidents, new safety methods are needed to monitor access to hazardous areas around operating machinery, improve documentation/monitoring of maintenance that requires shutdown of the machinery, and prevent unexpected startup or movement during machine maintenance activities. The National Institute for Occupational Safety and Health (NIOSH) is currently researching the application of Internet of Things (IoT) technologies to provide intelligent machine monitoring as part of a comprehensive LOTO program. This paper introduces NIOSH's two phase implementation of an IoT-based intelligent machine monitoring system. Phase one is the installation of a proof-of-concept system at a concrete batch plant, while phase two involves scaling up the system to include additional sensors, more detailed safety/performance metrics, proximity detection, and predictive failure analysis.

Data transport over leaky feeder systems using Internet-Protocol-enabled land mobile radios

Mine monitoring through various sensors is a vital component of successful miner safety and health programs. Data from environmental, geotechnical, infrastructure and other types of sensors are increasingly used to discover and mitigate health and safety concerns in underground mines. In many smaller underground mines, as well as in the new development headings of larger underground mines, leaky feeder communication systems may be the only available means to transport crucial monitoring data. In addition, data transport is increasingly being delivered using Internet Protocol (IP), while older forms of serial communication are being retired. This paper presents the selection, configuration and testing methodologies employed by researchers from the U.S. National Institute for Occupational Safety and Health (NIOSH) to integrate commercially available land mobile data radios into an existing leaky feeder communication system to provide IP data transport.