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Mining
Special Issues
Envisioning the Future of Mining
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Envisioning the Future of Mining

A special issue of Mining (ISSN 2673-6489).

Deadline for manuscript submissions: closed (1 August 2023) | Viewed by 55857

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Prof. Dr. Juan M Menéndez-Aguado

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Guest Editor
Escuela Politécnica de Mieres, Universidad de Oviedo, 33600 Mieres, Spain
Interests: comminution; energy efficiency; mineral processing; mineral waste streams; critical raw material production; process technoeconomic analysis; sustainability; circular economy of minerals
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Oscar Jaime Restrepo Baena

E-Mail Website
Guest Editor
Department of Materials and Minerals, School of Mines, Universidad Nacional de Colombia, Medellín 65-223, Colombia
Interests: extractive metallurgy; materials science; mineral processing; sustainability in extractive process; circular economy of minerals; humanitarian topics in engineering
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jessica M. Smith

E-Mail Website
Guest Editor
Department of Engineering, Design & Society, Colorado School of Mines, Golden, CO 80401, USA
Interests: gender in mining; engineering education; humanitarian engineering; sustainability in artisanal mining; engineering ethics

Special Issue Information

Dear Colleagues,

To date, the production of mineral raw materials has faced many challenges to provide necessary supplies which are involved in almost any production chain. In addition to the traditional search for more efficient processes, cleaner and safer operations, and higher levels of social acceptance, there is a need for the mining industry to become a major actor in the circular economy, decarbonization, and digital transformation processes. Following the precepts of the sustainable development principles, further insight must be gained in order to foresee potential challenges with regard to mineral raw material production in the future. This issue will cover technical aspects such as future urban mining, submarine mining, ultradeep mining, extraterrestrial mining, and innovative advances in raw material processing, and will cover scales from artisanal to large-scale mining activities. It will also include integrated sociotechnical approaches to addressing future challenges in sustainable and socially responsible ways.

Prof. Dr. Juan M Menéndez-Aguado
Prof. Dr. Oscar Jaime Restrepo Baena
Prof. Dr. Jessica M. Smith
Guest Editors

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 submissions that pass pre-check are 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. Mining is an international peer-reviewed open access quarterly 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 1000 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.

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Related Special Issue

Published Papers (11 papers)

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Editorial

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6 pages, 196 KiB  
Editorial
Editorial for Special Issue “Envisioning the Future of Mining”
by Juan M. Menéndez-Aguado, Oscar Jaime Restrepo Baena and Jessica M. Smith
Mining 2024, 4(1), 1-6; https://doi.org/10.3390/mining4010001 - 21 Dec 2023
Viewed by 1161
Abstract
According to the International Energy Agency, clean energy transitions significantly increase strategic minerals demand [...] Full article
(This article belongs to the Special Issue Envisioning the Future of Mining)

Research

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14 pages, 7935 KiB  
Article
Toward Automatic Monitoring for Anomaly Detection in Open-Pit Phosphate Mines Using Artificial Vision: A Case Study of the Screening Unit
by Laila El Hiouile, Ahmed Errami and Nawfel Azami
Mining 2023, 3(4), 645-658; https://doi.org/10.3390/mining3040035 - 20 Oct 2023
Cited by 2 | Viewed by 1689
Abstract
Phosphorus is a limited resource that is non-replaceable worldwide. Its significant role as a fertilizer underlines the necessity for prudent and strategic management. The adequate monitoring of the phosphate extraction process mitigates anything that can influence the quantity or quality of the product. [...] Read more.
Phosphorus is a limited resource that is non-replaceable worldwide. Its significant role as a fertilizer underlines the necessity for prudent and strategic management. The adequate monitoring of the phosphate extraction process mitigates anything that can influence the quantity or quality of the product. The phosphate extraction process’s most important phase is the screening unit, which can be used to separate phosphate minerals from unwanted materials. Nevertheless, it encounters several anomalies and malfunctions that influence the performance of the whole chain. This unit requires continuous automated control to avoid any blockages or risks caused by malfunctions. Using artificial intelligence and image processing techniques, the main goal of the investigations described in this paper was to evaluate the performances of machine-learning and deep-learning models to detect the screening unit malfunction in the open pit of the phosphate mine in Benguerir-Morocco. These findings highlight that the CNN and HOG-based models are the most suitable and accurate for the given case study. Full article
(This article belongs to the Special Issue Envisioning the Future of Mining)
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12 pages, 454 KiB  
Article
Sociotechnical Undergraduate Education for the Future of Natural Resource Production
by Jessica Smith, Carrie McClelland and Oscar Jaime Restrepo
Mining 2023, 3(2), 387-398; https://doi.org/10.3390/mining3020023 - 18 Jun 2023
Cited by 1 | Viewed by 1446
Abstract
The greatest challenges for contemporary and future natural resource production are sociotechnical by nature, from public perceptions of mining to responsible mineral supply chains. The term sociotechnical signals that engineered systems have inherent social dimensions that require careful analysis. Sociotechnical thinking is a [...] Read more.
The greatest challenges for contemporary and future natural resource production are sociotechnical by nature, from public perceptions of mining to responsible mineral supply chains. The term sociotechnical signals that engineered systems have inherent social dimensions that require careful analysis. Sociotechnical thinking is a prerequisite for understanding and promoting social justice and sustainability through one’s professional practices. This article investigates whether and how two different projects enhanced sociotechnical learning in mining and petroleum engineering students. Assessment surveys suggest that most students ended the projects with greater appreciation for sociotechnical perspectives on the interconnection of engineering and corporate social responsibility (CSR). This suggests that undergraduate engineering education can be a generative place to prepare future professionals to see how engineering can promote social and environmental wellbeing. Comparing the different groups of students points to the power of authentic learning experiences with industry engineers and interdisciplinary teaching by faculty. Full article
(This article belongs to the Special Issue Envisioning the Future of Mining)
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20 pages, 619 KiB  
Article
Inclusive Urban Mining: An Opportunity for Engineering Education
by Sofia L. Schlezak and Jaime E. Styer
Mining 2023, 3(2), 284-303; https://doi.org/10.3390/mining3020018 - 18 May 2023
Cited by 1 | Viewed by 2758
Abstract
With the understanding that the mining industry is an important and necessary part of the production chain, we argue that the future of mining must be sustainable and responsible when responding to the increasing material demands of the current and next generations. In [...] Read more.
With the understanding that the mining industry is an important and necessary part of the production chain, we argue that the future of mining must be sustainable and responsible when responding to the increasing material demands of the current and next generations. In this paper, we illustrate how concepts, such as inclusiveness and the circular economy, can come together in new forms of mining—what we call inclusive urban mining—that could be beneficial for not only the mining industry, but for the environmental and social justice efforts as well. Based on case studies in the construction and demolition waste and WEEE (or e-waste) sectors in Colombia and Argentina, we demonstrate that inclusive urban mining could present an opportunity to benefit society across multiple echelons, including empowering vulnerable communities and decreasing environmental degradation associated with extractive mining and improper waste management. Then, recognizing that most engineering curricula in this field do not include urban mining, especially from a community-based perspective, we show examples of the integration of this form of mining in engineering education in first-, third- and fourth-year design courses. We conclude by providing recommendations on how to make inclusive urban mining visible and relevant to engineering education. Full article
(This article belongs to the Special Issue Envisioning the Future of Mining)
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24 pages, 5660 KiB  
Article
Environmental and Work Factors That Drive Fatigue of Individual Haul Truck Drivers
by Elaheh Talebi, W. Pratt Rogers and Frank A. Drews
Mining 2022, 2(3), 542-565; https://doi.org/10.3390/mining2030029 - 26 Aug 2022
Cited by 1 | Viewed by 2557
Abstract
Many factors influence the fatigue state of human beings, and fatigue has a significant adverse effect on the health and safety of the haulage operators in the mine. Among various fatigue monitoring systems in mine operations, currently, the Percentage of Eye Closure (PERCLOS) [...] Read more.
Many factors influence the fatigue state of human beings, and fatigue has a significant adverse effect on the health and safety of the haulage operators in the mine. Among various fatigue monitoring systems in mine operations, currently, the Percentage of Eye Closure (PERCLOS) is common. However, work and other environmental factors influence the fatigue state of haul truck drivers; PERCLOS systems do not consider these factors in their modeling of fatigue. Therefore, modeling work and environmental factors’ impact on individual operations fatigue state could yield interesting insights into managing fatigue. This study provides an approach of using operational data sets to find the leading indicators of the operators’ fatigue. A machine learning algorithm is used to model the fatigue of the individual. eXtreme Gradient Boosting (XGBoost) algorithm is chosen for this model because of its efficiency, accuracy, and feasibility, which integrates multiple tree models and has stronger interpretability. A significant number of negative and positive samples are created from the available data to increase the number of datasets. Then, the results are compared with other existing models. A selected algorithm, along with a big data set was able to create a comprehensive model. The model was able to find the importance of the individual factors along with work and environmental factors among operational data sets. Full article
(This article belongs to the Special Issue Envisioning the Future of Mining)
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24 pages, 4872 KiB  
Article
Development of a Smart Computational Tool for the Evaluation of Co- and By-Products in Mining Projects Using Chovdar Gold Ore Deposit in Azerbaijan as a Case Study
by Anvar Mammadli, George Barakos, Md Ariful Islam, Helmut Mischo and Michael Hitch
Mining 2022, 2(3), 487-510; https://doi.org/10.3390/mining2030026 - 30 Jul 2022
Cited by 8 | Viewed by 4231
Abstract
Despite their significance in numerous applications, many critical minerals and metals are still considered minor. Since most of them are not found alone in mineral deposits, their co- or by-production depends on the production of base metals and other major commodities. In many [...] Read more.
Despite their significance in numerous applications, many critical minerals and metals are still considered minor. Since most of them are not found alone in mineral deposits, their co- or by-production depends on the production of base metals and other major commodities. In many cases, the concentration of the minor metals is low enough not to be considered part of the production. Hence, their supply is not always secured, their availability decreases, and their criticality increases. Many researchers have addressed this issue, but no one has set actual impact factors other than economic ones that should determine the production of these minor commodities. This study identified several parameters, the number and diversity of which gave birth to developing a computational tool using a multi-criteria-decision analysis model based on the Analytical Hierarchical Process (AHP) and Python. This unprecedented methodology was applied to evaluate the production status of different commodities in a polymetallic deposit located in Chovdar, Azerbaijan. The evaluation outcomes indicated in quantifiable terms the production potentials for several commodities in the deposit and justified the great perspectives of this tool to evaluate all kinds of polymetallic deposits concerning the co- and by-production of several minor critical raw materials. Full article
(This article belongs to the Special Issue Envisioning the Future of Mining)
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15 pages, 2057 KiB  
Article
Rock Fragmentation Prediction Using an Artificial Neural Network and Support Vector Regression Hybrid Approach
by Richard Amoako, Ankit Jha and Shuo Zhong
Mining 2022, 2(2), 233-247; https://doi.org/10.3390/mining2020013 - 24 Apr 2022
Cited by 32 | Viewed by 5948
Abstract
While empirical rock fragmentation models are easy to parameterize for blast design, they are usually prone to errors, resulting in less accurate fragment size prediction. Among other shortfalls, these models may be unable to accurately account for the nonlinear relationship that exists between [...] Read more.
While empirical rock fragmentation models are easy to parameterize for blast design, they are usually prone to errors, resulting in less accurate fragment size prediction. Among other shortfalls, these models may be unable to accurately account for the nonlinear relationship that exists between fragmentation input and output parameters. Machine learning (ML) algorithms are potentially able to better account for the nonlinear relationship. To this end, we assess the potential of the multilayered artificial neural network (ANN) and support vector regression (SVR) ML techniques in rock fragmentation prediction. Using geometric, explosives, and rock parameters, we build ANN and SVR models to predict mean rock fragment size. Both models yield satisfactory results and show higher performance when compared with the conventional Kuznetsov model. We further demonstrate an automated means of analyzing a varied number of hidden layers for an ANN using Bayesian optimization in the Keras Python library. Full article
(This article belongs to the Special Issue Envisioning the Future of Mining)
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17 pages, 4484 KiB  
Article
A High-Fidelity Modelling Method for Mine Haul Truck Dumping Process
by Aaron Young and William Pratt Rogers
Mining 2022, 2(1), 86-102; https://doi.org/10.3390/mining2010006 - 11 Feb 2022
Cited by 1 | Viewed by 3713
Abstract
Dumping is one of the main unit operations of mining. Notwithstanding a long history of using large rear dump trucks in mining, little knowledge exists on the cascading behavior of the run-of-mine material during and after dumping. In order to better investigate this [...] Read more.
Dumping is one of the main unit operations of mining. Notwithstanding a long history of using large rear dump trucks in mining, little knowledge exists on the cascading behavior of the run-of-mine material during and after dumping. In order to better investigate this behavior, a method for generating high fidelity models (HFMs) of dump profiles was devised and investigated. This method involved using unmanned aerial vehicles with mounted cameras to generate photogrammetric models of dumps. Twenty-eight dump profiles were created from twenty-three drone flights. Their characteristics were presented and summarized. Four types of dump profiles were observed to exist. Factors that influence the determination of these profiles include the location of the truck relative to the dump crest, the movement of the underlying dump material during the dumping process and the differences in the dump profile prior to dumping. The HFMs created in this study could possibly be used for calibrating computer simulations of dumps to better match reality. Full article
(This article belongs to the Special Issue Envisioning the Future of Mining)
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17 pages, 1837 KiB  
Article
Safe Mining Assessment of Artisanal Barite Mining Activities in Nigeria
by David Oluwasegun Afolayan, Azikiwe Peter Onwualu, Carrick McAfee Eggleston, Adelana Rasak Adetunji, Mingjiang Tao and Richard Kwasi Amankwah
Mining 2021, 1(2), 224-240; https://doi.org/10.3390/mining1020015 - 18 Sep 2021
Cited by 5 | Viewed by 7756
Abstract
Barite, used in mud formulation, is mined in several places to support the industry. However, there is insufficient literature on the downside of mining and associated hazards, especially in the artisanal barite mining sector. This paper contains three parts. The initial section reviews [...] Read more.
Barite, used in mud formulation, is mined in several places to support the industry. However, there is insufficient literature on the downside of mining and associated hazards, especially in the artisanal barite mining sector. This paper contains three parts. The initial section reviews major causes of mining accidents and health hazards in Nigeria. The second section examines existing but weak institutional frameworks and policies for artisanal and small-scale mining (ASM) in Nigeria. In the third part, data from questionnaires and heavy metal contamination assessment are compared with health and environmental standards to identify and characterize hazards. It was observed that 54% had health challenges traceable to illicit drugs, and 54% were ignorant about the use of safety kits. The UV-Vis, AAS, and ICP-MS analyses confirmed lead, barium, zinc, copper, and iron in the water samples. Index of geoaccumulation (Igeo) and contamination factor (CF) show that water samples are moderate to highly polluted by Pb2+, Ba2+, and highly contaminated. The chronic daily intake assessment and health quotient analysis revealed that the accumulation of lead and barium is possible and can initiate chronic diseases in humans over a long time. Certain safe mining protocols and controls are recommended. Full article
(This article belongs to the Special Issue Envisioning the Future of Mining)
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13 pages, 4435 KiB  
Article
Optimising Productivity and Safety of the Open Pit Loading and Haulage System with a Surge Loader
by Ignacio Andrés Osses Aguayo, Micah Nehring and G. M. Wali Ullah
Mining 2021, 1(2), 167-179; https://doi.org/10.3390/mining1020011 - 2 Aug 2021
Cited by 7 | Viewed by 12478
Abstract
The open pit mining load and haul system has been a mainstay of the mining industry for many years. While machines have increased in size and scale and automation has become an important development, there have been few innovations to the actual load [...] Read more.
The open pit mining load and haul system has been a mainstay of the mining industry for many years. While machines have increased in size and scale and automation has become an important development, there have been few innovations to the actual load and haul process itself in recent times. This research highlights some of the potential productivity and safety benefits that the incorporation of a surge loader may bring to the load and haul system through an analysis of the system, discussion of component characteristics, and mine planning aspects. The incorporation of the surge loader into open pit loading and haulage operations also enables improved safety. This is a result of a reduction in shovel–truck interactions and the reduced likelihood of truck overfilling and uneven loading. This paper details the number of mine worker deaths that a surge loader may have prevented within the Peruvian and Chilean mining industries. Full article
(This article belongs to the Special Issue Envisioning the Future of Mining)
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Review

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25 pages, 6826 KiB  
Review
Electrification Alternatives for Open Pit Mine Haulage
by Haiming Bao, Peter Knights, Mehmet Kizil and Micah Nehring
Mining 2023, 3(1), 1-25; https://doi.org/10.3390/mining3010001 - 1 Jan 2023
Cited by 9 | Viewed by 7785
Abstract
Truck-Shovel (TS) systems are the most common mining system currently used in large surface mines. They offer high productivity combined with the flexibility to be rapidly relocated and to adjust load/haul capacity and capital expenditure according to market conditions. As the world moves [...] Read more.
Truck-Shovel (TS) systems are the most common mining system currently used in large surface mines. They offer high productivity combined with the flexibility to be rapidly relocated and to adjust load/haul capacity and capital expenditure according to market conditions. As the world moves to decarbonise as part of the transition to net zero emission targets, it is relevant to examine options for decarbonising the haulage systems in large surface mines. In-Pit Crushing and Conveying (IPCC) systems offer a smaller environmental footprint regarding emissions, but they are associated with a number of limitations related to high initial capital expenditure, capacity limits, mine planning and inflexibility during mine operation. Among the emerging technological options, innovative Trolley Assist (TA) technology promises to reduce energy consumption for lower carbon footprint mining systems. TA systems have demonstrated outstanding potential for emission reduction from their application cases. Battery and energy recovery technology advancements are shaping the evolution of TAs from diesel-electric truck-based patterns toward purely electrified BT ones. Battery Trolley (BT) systems combined with autonomous battery-electric trucks and Energy Recovery Systems (ERSs) are novel and capable of achieving further significant emission cuts for surface mining operations associated with safety, energy saving and operational improvements. This article reviews and compares electrification alternatives for large surface mines, including IPCC, TA and BT systems. These emerging technologies provide opportunities for mining companies and associated industries to adopt zero-emission solutions and help transition to an intelligent electric mining future. Full article
(This article belongs to the Special Issue Envisioning the Future of Mining)
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