Special Issue "Advances in Mining Technology: The Digital Mine"

A special issue of Resources (ISSN 2079-9276).

Deadline for manuscript submissions: closed (31 October 2019).

Special Issue Editor

Dr. Jonathon Ralston
E-Mail Website
Guest Editor
Integrated Mining Team Leader | CSIRO Energy
Interests: mining automation; sensing; systems integration; navigation; robotics; remote operations

Special Issue Information

Dear Colleagues,

The ongoing need to deliver improved safety, productivity, and environmental benefits in the mining industry presents an open challenge, as well as a powerful incentive, to develop new and improved solutions. Critical to the success of this initiative is the ability to identify approaches that led to high-value processes across the entire mining value chain to improve resource quality and mining productivity, increase personnel safety, and achieve effective environmental stewardship. This Special Issue invites new contributions in mining sensing, automation and knowledge management advances, with a special emphasis on digitally-enabled technologies towards a fully digital mining ecosystem.

Submissions are welcome in all areas of mining technology, but not limited to the following topics:

  • Smart sensing—mining situational awareness through integrated sensor networks
  • Automation—sensing, processing and control leading to high-integrity mining equipment operating at peak efficiency with trusted autonomy
  • Data-driven decision-making—integrating next-generation analytics and decision making with current mining process, culture and experience
  • Exploring the physical-digital interaction—digital technology applications in mining contexts
  • Human–technology interaction— distributed, collaborative and remote operations to deliver the digitally enabled mining workforce
  • Integrated enterprise—systems interoperability, maximising value from information, managing uncertainty in data and processes

Submission scopes can include:

  • Early technology development—sensors, systems and software
  • Case studies of digital technology in mining contexts
  • Related applications and success in analogous domains
  • Industry-focused developments and applications
  • Technology roadmaps and future directions

Dr. Jonathon Ralston
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Resources is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Mining
  • automation
  • sensing
  • systems integration
  • decision support
  • technology development
  • interoperability
  • ecosystem

Published Papers (9 papers)

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Research

Article
Development of a Protective Enclosure for Remote Sensing Applications—Case Study: Laser Scanning in Underground Coal Mines
Resources 2020, 9(5), 56; https://doi.org/10.3390/resources9050056 - 11 May 2020
Cited by 2 | Viewed by 1756
Abstract
Sensing for equipment location and mapping in explosion risk zones such as underground coal mines is a difficult proposition due to the regulatory requirement for certified protective enclosures to safely house the required complex electrical equipment. This paper provides a case study for [...] Read more.
Sensing for equipment location and mapping in explosion risk zones such as underground coal mines is a difficult proposition due to the regulatory requirement for certified protective enclosures to safely house the required complex electrical equipment. This paper provides a case study for the process involved in creating and implementing an optical-grade enclosure for use in these environments. The result of this process has been the creation of ExScan®, a 3D laser mapping system that is providing step-change capability for remote operations and automation in the underground coal mining industry. Full article
(This article belongs to the Special Issue Advances in Mining Technology: The Digital Mine)
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Article
Development of Digital Subterranean Models for Real-Time Open Cut Horizon Control
Resources 2020, 9(4), 50; https://doi.org/10.3390/resources9040050 - 24 Apr 2020
Viewed by 1923
Abstract
A reliable coal seam sensing system is required to improve the productivity of selective mining in open-cut mining operations. A prototype system based upon commercial ground penetrating radar equipment, which measures coal thickness from the top of an exposed surface down to an [...] Read more.
A reliable coal seam sensing system is required to improve the productivity of selective mining in open-cut mining operations. A prototype system based upon commercial ground penetrating radar equipment, which measures coal thickness from the top of an exposed surface down to an underlying coal-interburden interface and generates digital subterranean models of the subsurface seam boundaries, was developed for this purpose. The models can be deployed to commercially available in-cab assistive guidance systems for bulldozers and other mining machinery in existing production processes, and can further contribute to the databases required for remote operation and control in a complete digital mine scenario. The system was evaluated at a production open cut coal mine in Queensland, Australia, with promising results. The benefits reported by operational personnel who evaluated the digital surface model in the mining environment provide strong motivation for ongoing technology development. Full article
(This article belongs to the Special Issue Advances in Mining Technology: The Digital Mine)
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Article
Remnant Coal Detection System
Resources 2020, 9(4), 45; https://doi.org/10.3390/resources9040045 - 17 Apr 2020
Viewed by 1716
Abstract
This paper describes the development and successful implementation of a system designed to detect coal deposits remaining in coal train wagons after unloading (dumping). These undesirable coal deposits constitute both small residual amounts of “carryback”, but also larger “hang-ups” of significant volume that [...] Read more.
This paper describes the development and successful implementation of a system designed to detect coal deposits remaining in coal train wagons after unloading (dumping). These undesirable coal deposits constitute both small residual amounts of “carryback”, but also larger “hang-ups” of significant volume that have failed to discharge. The system was originally developed simply to detect and record volumes of carryback, as part of an effort to characterise the extent of the problem for the coal transport industry, but was then enhanced to provide real-time feedback of large hang-ups so that they could be discharged prior to the wagons exiting the dump station. The paper describes the hardware and processing systems used in the system, including the different strategies employed to ensure a reliable detection system. The system has now been installed and operated in a production environment at three dump stations across two different coal terminals, and a case study of the results from one of these dump stations is presented. Automating remnant coal detection at dump stations provides short interval control to minimise potential hazards and downtime, and historical data that may be integrated into existing data platforms and analysed for productivity, environmental, and safety planning insights. Full article
(This article belongs to the Special Issue Advances in Mining Technology: The Digital Mine)
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Article
Systems Engineering Approach to Slope Stability Monitoring in the Digital Mine
Resources 2020, 9(4), 42; https://doi.org/10.3390/resources9040042 - 15 Apr 2020
Cited by 1 | Viewed by 1979
Abstract
Slope stability monitoring in open cut mining is increasingly based on the use of a variety of different sensors and associated analytics, each capable of providing part of the understanding required to manage complex geotechnical environments. Designing an integrated monitoring system that is [...] Read more.
Slope stability monitoring in open cut mining is increasingly based on the use of a variety of different sensors and associated analytics, each capable of providing part of the understanding required to manage complex geotechnical environments. Designing an integrated monitoring system that is both attainable and fit for purpose can therefore be particularly challenging. In this paper, a systems engineering approach based on a novel methodology is presented to design the slope monitoring system. The methodology uses the rock engineering systems (RES) approach to system decomposition for geotechnical engineering problems, to determine the critical rock mass behaviours requiring monitoring. It follows this with the application of the system theoretic process analysis (STPA) approach, to design the control system for the monitoring system and identify and mitigate sub-optimal configurations. We demonstrate that the approach is practical to implement and supports transparent and defensible decision making for designing and implementing slope monitor systems. We apply the method to the design of a monitoring system for an Australian coal mine and demonstrate how the approach can facilitate the identification and design of new sensing modalities. Full article
(This article belongs to the Special Issue Advances in Mining Technology: The Digital Mine)
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Article
Cousins, Siblings and Twins: A Review of the Geological Model’s Place in the Digital Mine
Resources 2020, 9(3), 24; https://doi.org/10.3390/resources9030024 - 04 Mar 2020
Viewed by 2509
Abstract
Digital mining is a broad term describing the enhancement of the physical mining method through the use of digital models, simulations, analytics, controls and associated feedbacks. Mining optimisation will be improved through increased digitisation and real-time interactions via a “digital twin”, however digitisation [...] Read more.
Digital mining is a broad term describing the enhancement of the physical mining method through the use of digital models, simulations, analytics, controls and associated feedbacks. Mining optimisation will be improved through increased digitisation and real-time interactions via a “digital twin”, however digitisation of the rock mass component of this system remains problematic. While engineered systems can be digitally twinned, natural systems containing inherent uncertainties present challenges, especially where human-intensive procedures are required. This is further complicated, since the mining system is designed not only to interact with, but to substantially and continually alter its surrounding environment. Considering digital twin requirements and geological modelling capabilities, we assess the potential for a mine’s synchronised digital twin to encompass the complex, uncertain, geological domain within which it interacts. We find that current geological (and indeed hydro-geological) models and simulations would support digitisation that could be considered to provide, at best, a digitised ‘cousin’. Based on this assessment, the digital twin’s value for medium term forecasting of mining operations may be limited and we discuss technological advancements that can mitigate this. Full article
(This article belongs to the Special Issue Advances in Mining Technology: The Digital Mine)
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Article
Data Analytic Approaches for Mining Process Improvement—Machinery Utilization Use Case
Resources 2020, 9(2), 17; https://doi.org/10.3390/resources9020017 - 07 Feb 2020
Cited by 5 | Viewed by 3192
Abstract
This paper investigates the application of process mining methodology on the processes of a mobile asset in mining operations as a means of identifying opportunities to improve the operational efficiency of such. Industry 4.0 concepts with related extensive digitalization of industrial processes enable [...] Read more.
This paper investigates the application of process mining methodology on the processes of a mobile asset in mining operations as a means of identifying opportunities to improve the operational efficiency of such. Industry 4.0 concepts with related extensive digitalization of industrial processes enable the acquisition of a huge amount of data that can and should be used for improving processes and decision-making. Utilizing this data requires appropriate data processing and data analysis schemes. In the processing and analysis stage, most often, a broad spectrum of data mining algorithms is applied. These are data-oriented methods and they are incapable of mapping the cause-effect relationships between process activities. However, in this scope, the importance of process-oriented analytical methods is increasingly emphasized, namely process mining (PM). PM techniques are a relatively new approach, which enable the construction of process models and their analytics based on data from enterprise IT systems (data are provided in the form of so-called event logs). The specific working environment and a multitude of sensors relevant for the working process causes the complexity of mining processes, especially in underground operations. Hence, an individual approach for event log preparation and gathering contextual information to be utilized in process analysis and improvement is mandatory. This paper describes the first application of the concept of PM to investigate the normal working process of a roof bolter, operating in an underground mine. By applying PM, the irregularities of the operational scheme of this mobile asset have been identified. Some irregularities were categorized as inefficiencies that are caused by either failure of machinery or suboptimal utilization of the same. In both cases, the results achieved by applying PM to the activity log of the mobile asset are relevant for identifying the potential for improving the efficiency of the overall working process. Full article
(This article belongs to the Special Issue Advances in Mining Technology: The Digital Mine)
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Article
Mine Machine Radar Sensor for Emergency Escape
Resources 2020, 9(2), 16; https://doi.org/10.3390/resources9020016 - 04 Feb 2020
Cited by 1 | Viewed by 2397
Abstract
This paper presents the results of recent work to develop and trial a mine machine radar sensor for underground coal mine vehicles. There is an urgent industry need for an integrated solution to the problem of operating an underground vehicle in conditions of [...] Read more.
This paper presents the results of recent work to develop and trial a mine machine radar sensor for underground coal mine vehicles. There is an urgent industry need for an integrated solution to the problem of operating an underground vehicle in conditions of dense ambient dust and/or smoke, such as may occur in underground coal mines after a fire or explosion. Under these conditions, sensors such as cameras and lidar offer limited assistance due to their inability to penetrate thick dust. Thermal infrared can penetrate dust but still results in poor vision, as there is insufficient temperature contrast between the tunnel walls and the ambient air. Microwave radar sensors are able to penetrate the dust, and suitable radar sensors have been developed for use in the automation industry. Adapting such sensors for use in an underground coal mining environment was the focus of this research effort, and involved trialing a suitable sensor in dust and smoke chambers as well as trials in an underground coal mine with introduced dust. Data processing and the development of a suitable user interface were key aspects of the research. Since any sensor would have to operate in an explosive atmosphere, a related research work developed a flameproof dielectric enclosure to allow the use of the radar in the mine environment. Full article
(This article belongs to the Special Issue Advances in Mining Technology: The Digital Mine)
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Article
Applications of Geophysical Logs to Coal Mining—Some Illustrative Examples
Resources 2020, 9(2), 11; https://doi.org/10.3390/resources9020011 - 22 Jan 2020
Viewed by 2428
Abstract
Geophysical logs can be used not only for qualitative interpretation such as strata correlation but also for geotechnical assessment through quantitative data analysis. In an emerging digital mining age, such a use of geophysical logs helps to establish reliable geological and geotechnical models, [...] Read more.
Geophysical logs can be used not only for qualitative interpretation such as strata correlation but also for geotechnical assessment through quantitative data analysis. In an emerging digital mining age, such a use of geophysical logs helps to establish reliable geological and geotechnical models, which reduces safety and financial risks due to geological and geotechnical uncertainty for new and existing coal mining projects. This paper presents some examples of geological and geotechnical characterizations from geophysical logs at various coal mines in Australia and India. The applications include rock strength and coal quality estimations, automated lithological/geotechnical interpretation and geophysical strata rating, all based on geophysical logs. These derived parameters could provide input to modelling, control, even ‘digital twin’ generation in a form of geological and geotechnical models as part of the future digital mining. The outcomes can be visualized in 3D space and used for identifying the key geotechnical strata units that are responsible for caving behaviors during longwall mining. This could assist site geologists and planning and production engineers predict and manage mining conditions on an ongoing basis. Both conventional logs such as density, natural gamma and sonic and less common logging data, such as full waveform sonic, televiewer and SIROLOG spectrometric natural gamma logging data are examined for their potential applications. The geotechnical strata classification and rock strengths predicted from the geophysical logs match the laboratory tests, drill core geotechnical strata classification, core photos and the mining condition/behavior observed. These illustrate the usefulness and effectiveness of using geophysical logs for geological and geotechnical characterizations. Full article
(This article belongs to the Special Issue Advances in Mining Technology: The Digital Mine)
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Article
Preliminary Investigation into Measurement While Drilling as a Means to Characterize the Coalmine Roof
Resources 2020, 9(2), 10; https://doi.org/10.3390/resources9020010 - 21 Jan 2020
Cited by 2 | Viewed by 2604
Abstract
The variable nature of the coalmine roof poses a challenge to roadway stability during underground coal mining. There have been fatalities and financial losses in the coal mining industry due to roadway failures and roof falls. Generally, the geotechnical and geological data gathered [...] Read more.
The variable nature of the coalmine roof poses a challenge to roadway stability during underground coal mining. There have been fatalities and financial losses in the coal mining industry due to roadway failures and roof falls. Generally, the geotechnical and geological data gathered from exploration boreholes, which are drilled at considerable distances from each other, are used to characterize the thickness and quality (including strength) of the coalmine roof. This process provides a limited number of samples that cannot represent the discontinuous nature of the strata in the coalmine roof nor can they form reliable inputs to a digital model of the rock mass component of the digital mine. Gaining confidence in the strata properties of the coalmine roof is necessary for the modelling, design, and maintenance of roadways. The paper describes the progress of the ongoing work to investigate the monitoring while drilling (MWD) concept for characterizing coalmine roofs. Large-scale drilling experiments in synthesized sandwiched rock samples without interfaces were carried out. The drilling response data were analyzed to identify whether the drill data differentiates the various strengths associated with the rock samples. The initial results show that the drilling data can differentiate the synthesized rock samples. Full article
(This article belongs to the Special Issue Advances in Mining Technology: The Digital Mine)
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