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Mining still plays a vital role in providing various sectors with essential materials since many industries depend heavily on mined minerals. Moreover, the mining industry is the primary driver for many economies worldwide. On the other hand, new mining projects face many challenges, the most important of which are risks related to the economic aspects, e.g., the significant uncertainty about mineral resources compared to other engineering projects. Therefore, many jurisdictions worldwide depend on detailed engineering studies conducted according to internationally recognized standards to assess the new mining projects from an economic and technical perspective. In the same context and due to the significant lack of published research in this field, as the literature review revealed, this article reviewed and discussed the different main stages of engineering studies to evaluate new potential mining projects, including scoping, pre-feasibility, and feasibility studies, to ensure that the engineering study report complies with all the recognized main requirements. Results indicated the necessity of adhering to the needs of the engineering tasks while preparing reports of evaluation studies for new mining projects to reduce potential uncertainty risks and thus raise the level of confidence in these types of projects. Furthermore, they showed direct progress between the investigation details conducted in the evaluation studies and the value of the new mining project.

The present study aimed to investigate the environmental consequences of mining activities in boke bauxite mining areas and the Kerouane iron mining project in Guinea using a mixed-methods approach that combines quantitative and qualitative data. A reference matrix was used to evaluate the impact of the mining activities, classifying them as negligible, moderate, or significant. Data were collected from October 2022 to January 2023 by assessing their impact on water pollution, soil, noise, air quality, vegetation, fauna, and flora. These findings indicate concerns regarding the water pH, electrical conductivity, and turbidity in both the Boke and Kerouane regions. The soil composition analysis revealed the presence of Cr, Cu, Ni, and Zn in both the Boke and Kerouane project areas. Noise levels exceeded the guideline levels and substantial amounts of particulate matter (PM) were detected, with high levels of PM10 in mining operations. The Kerouane Iron Project resulted in the direct loss of 2929 ha of natural habitats and 466 ha of modified habitats, with the extraction of approximately 1.291 billion tons of ore anticipated over a 22-year mine lifespan. This study proposes an environmental threat assessment framework that integrates technical and human activity data to evaluate the environmental impacts of mining activities comprehensively. To promote sustainable development and minimize the negative impacts of mining, an integrated index of economic and environmental performance in the mining sector is recommended, along with collaboration between researchers and policymakers to develop effective climate-change mitigation strategies.

PurposeIt is well known in the mining industry that the increase in failures and breakdowns is due mainly to a poor maintenance policy for the equipment, in addition to the difficult access that specialized personnel have to combat the breakdown, which translates into more machine downtime. For this reason, this study aims to propose a remote assistance model for diagnosing and repairing critical breakdowns in mining industry trucks using augmented reality techniques and data analytics with a quality approach that considerably reduces response times, thus optimizing human resources.Design/methodology/approachIn this work, the six-phase CRIPS-DM methodology is used. Initially, the problem of fault diagnosis in trucks used in the extraction of material in the mining industry is addressed. The authors then propose a model under study that seeks a real-time connection between a service technician attending the truck at the mine site and a specialist located at a remote location, considering the data transmission requirements and the machine's characterization.FindingsIt is considered that the theoretical results obtained in the development of this study are satisfactory from the business point of view since, in the first instance, it fulfills specific objectives related to the telecare process. On the other hand, from the data mining point of view, the results manage to comply with the theoretical aspects of the establishment of failure prediction models through the application of the CRISP-DM methodology. All of the above opens the possibility of developing prediction models through machine learning and establishing the best model for the objective of failure prediction.Originality/valueThe original contribution of this work is the proposal of the design of a remote assistance model for diagnosing and repairing critical failures in the mining industry, considering augmented reality and data analytics. Furthermore, the integration of remote assistance, the characterization of the CAEX, their maintenance information and the failure prediction models allow the establishment of a quality-based model since the database with which the learning machine will work is constantly updated.

Wymagania stawiane przez międzynarodowe instytucje finansowe w zakresie raportowania wyników prac geologicznych, klasyfikacji zasobów kopalin oraz oceny rentowności projektów górniczych dla potrzeb ich finansowania wymuszają w tym zakresie konieczność stosowania jednolitych standardów. Podstawowym celem tej standaryzacji jest umożliwienie porównania wartości ekonomicznej zasobów kopaliny według jednolitych zasad i traktowania tych zasobów jako składnika aktywów przedsiębiorstwa górniczego. Potrzeba takiej standaryzacji pojawia się również w Polsce. Obecnie na świecie najczęściej jest stosowany australijski system raportowania wyników rozpoznania złoża oraz oceny jego zasobów znany pod nazwą JORC Code. Złożoność projektów górniczych (surowcowych) oraz wielostronne czynniki ryzyka związane z ich oceną i wdrożeniem wymuszają w fazie przedinwestycyjnej projektu konieczność przygotowania optymalnej koncepcji zagospodarowania złoża – Bankowego Studium Wykonalności (BSW). Celem BSW jest optymalizacja decyzji inwestora o najmniejszym ryzyku w świetle posiadanej wiedzy na temat technicznej i finansowej wykonalności danego projektu górniczego. BSW jest zatem narzędziem (instrumentem) wykorzystywanym do podjęcia obiektywnych (najlepiej trafnych) i obarczonych możliwie niskim ryzykiem decyzji inwestycyjnych. Kompleksowa ocena rentowności projektu górniczego z uwzględnieniem wszelkich czynników geologiczno-górniczych, technicznych, ekonomicznych, marketingowych, prawnych, środowiskowych oraz istotnych względów społecznych i administracyjnych podjęta na etapie koncepcyjnym (studium), pozwala na ograniczenie ryzyka w fazie wykonania projektu (budowa zakładu górniczego). Tym samym BSW jest instrumentem oceny rentowności projektu oraz efektywnym narzędziem minimalizacji ryzyka przyjęcia do realizacji projektu, który jest niewykonalny albo nieracjonalny.

A fundamental aspect in the evaluation of mining projects is the classification of mineral resources, as it directly influences the definition of mineral reserves and affects both the planning and operational phases of the mine. Traditional methods employed in the industry are based on geometric or geostatistical criteria which, while constituting the fundamental basis of the process, may prove insufficient when applied in isolation to reflect the uncertainty inherent in the databases used for the evaluation of mineral deposits. As discussed throughout the article, this limitation can lead to an incorrect or imprecise assignment of resource categories. This work presents a methodology to integrate variables related to sample quality as an additional criterion in resource classification. This allows for the identification of areas with greater uncertainty and the adjustment of their categories more consistently with data reliability. The effectiveness of the proposed method is demonstrated through its application to a real case study, complemented by a comprehensive analysis of its implications and results.

Mining projects are intricate, requiring significant time and investment for feasibility studies, despite a low likelihood of reaching execution. Accurate project factors can optimize costs across the study, execution, and operation phases. This work proposes a strategic approach to define the production rate in conceptual projects of critical raw materials, based on well-established formulae from Taylor, Long, and Singer, focusing on copper, zinc, and lead. Copper and zinc are crucial for renewable energy systems and low-carbon technologies, while lead supports energy storage applications. A dataset containing mine production and mineral resources from several mine projects, gathered from a specialized global company, was used to create a production rate equation and then compared using an adherence indicator to validate the formulae. The best adherence indicator from earlier studies was 59%. Copper projects did not show good adherence to the new formulae. Zinc and lead projects showed very good results, generating three formulae with good adherence numbers (above 70%), and they can be taken as a reference to calculate the production rate of new open-pit and underground mining projects. These findings offer a reliable strategic approach for estimating production rates in early-stage zinc and lead projects, enhancing the efficiency of the conceptual study phase in mining.

The purpose of this study is to analyze the extant literature on Project Finance (PF) with a comprehensive understanding of the status quo and research trends in the mining industry. Thus, this study utilizes a scientometric review of global trends and structure of PF and mining research from 1977 to 2020 using techniques such as co-author, co-word, co-citation, and cluster analyses. A total of 80 bibliographic records from the Scopus database were analyzed to generate the study’s research through scientometric networks. The findings indicate a steady growth of the research field, which includes Environmental, Social, and Governance criteria. The most significant contributions have originated mainly from the United States, Australia, the United Kingdom, and South Africa. The main research trends identified several issues related to risk, management, and financing concerns. This study provides researchers and practitioners with a comprehensive understanding of the status quo and research trends of ontology research within PF in the mining context and promotes further studies in this domain.

Investment in mineral industries always deals with various economic, political, technical, and environmental risks. Not paying enough attention to such risks increases the possibility of investment failure. Accordingly, in this study, the risk criteria for investing in mineral industries and sub-criteria for risk assessment according to the type of industries, including mineral exploration, exploitation, and processing projects, have been identified and prioritized. In this regard, a methodology is presented based on multi-attribute decision-making methods, including Fuzzy Delphi, DEMATEL, and ANP methods to identify and analyze the risk criteria and evaluate sub-criteria. The results indicate that financial and commercial, technical, HSE, infrastructural considerations, geological, political, security, and legal risks are the main risk measures affecting investment in mining projects with different priorities. From the viewpoint of investment risk assessment in mineral processing and exploration projects, technical, financial and commercial, and geological risk criteria are the most significant, respectively. Generally, all risk criteria must be considered to make a reasonable investment in the mining sector, especially those more important.

The recent changes in mining policy in Ethiopia have led to a significant increase in mining investments in regions rich in minerals. One such region is the Benishangul Gumuz regional (BGR) state, which has attracted both domestic and foreign investors interested in extracting coal, marble, and gold. However, there is a lack of studies on how mining projects in Ethiopia, particularly in the BGR state, affect the livelihoods of households. This study aims to address this gap by examining the impact of mining projects on household livelihoods in the BGR. To achieve this, we employed quasi-experimental and cross-sectional research designs and collected primary data from 333 households. This included 162 households located near the mining projects (treated households) and 171 households in areas without mining projects (control households). For the analysis, we utilized principal component analysis (PCA) and propensity score matching (PSM) techniques. We used the sustainable livelihood framework (SLF) as the conceptual and analytical tool, focusing on the five livelihood assets as the outcome variable of the study. The results of the Average Treatment Effect on the Treated (ATT) revealed that mining has a significantly positive impact on the financial and physical assets of households. However, it also has a notable negative impact on human, natural, and social capitals, which are crucial for the sustainable development of rural households. Therefore, the research recommends that government institutions and policymakers should address these challenges using a comprehensive approach that balances the benefits of mining with the preservation and enhancement of necessary community assets.

It’s challenging to predict the potential impacts of mining extraction on household food security. On the one hand, mining projects can create job opportunities, improve market access, and enhance infrastructure. On the other hand, these projects can have adverse effects on livelihood assets, such as farmland, livestock, and grazing areas, which are crucial for household food security. The purpose of this article is to bridge the gap by studying impacts of mining projects on household food security in Ethiopia, using empirical evidence from the Benishangul-Gumuz Region (BGR). To achieve this goal, we employed a cross-sectional and quasi-experimental research designs. Using systematic random sampling, we collected primary data from a sample of 333 households, comprising 162 from a community located around the mining projects (treated households) and 171 from a community without mining projects in the area (control households). We analyzed the data using descriptive statistics and Propensity Score Matching (PSM) techniques. We measured food availability by assessing food energy intake (FEI). We evaluated food utilization by using the food consumption score (FCS), and we determined food stability through the coping strategy index (CSI). The Average Treatment Effect on the Treated (ATT) results show that treated households, on average, consume 1,407.34 kcal per adult per day and 8.54 more FCS per week compared to control households, respectively. The ATT results also showed that treated households had a 3.24 lower CSI than control households. This is due to the wage employment created by small-scale and the infrastructure built by large-scale mining projects in the study area. Our research indicates that expanding mining investments brings benefits, as long as local sustainable development is taken into account.