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By D. R. McConnell

The seafloor in the US Pacific OCS and EEZ is enriched to varying degrees in critical and economically important minerals such as nickel, manganese, cobalt, copper, zinc, REY (rare earth elements plus yttrium), titanium, vanadium, antimony, gold, and silver. These mineral deposits take the form of polymetallic nodules on the seabed, cobalt rich ferromanganese crusts on seamounts and ridges swept clean of sediment accumulation, and seafloor massive sulfides formed by hydrothermal systems at geologic plate spreading centers and volcanic margins. Each of these mineral deposits form on or near the deep ocean seafloor where water depths are typically 4000 m to 5500 m and on the seamounts and volcanic arcs that rise from these depths. Commercial interest in deep sea mineral deposits and the potential for collecting or mining them began in earnest in the 1970s but has been heightened in the last 20 years as the international framework for developing these minerals in International Waters has matured that has coincided with forecasted rapid rising demand for minerals to supply energy and manufacturing needs for the green economy. Compilation reports published by academia, government, and private companies are reviewed to assemble data and assess the prospects for deep sea marine minerals in the US Pacific OCS and EEZ. Key compilations were made by the Circum-Pacific Council and USGS in the 1980s and 1990s. These, together with recent (2023) efforts by USGS to compile geochemical data from USGS affiliated marine research sampling cruises from the 1980s and 1990s, historical data maintained by NOAA National Centers for Environmental Information (NCEI), and recent publicly disclosed results from ISA contractors are used to inform the known occurrence and prospectivity for polymetallic nodules, cobalt-rich ferromanganese crusts, and seafloor massive sulfides in the US Pacific OCS and EEZ.

Feb 22, 2026

By Tania Schmid, Marco Portal Valdivia, Sandra Nowosad

Today’s mining industry faces rapid transformation driven by automation, climate responsibility, and ESG demands, requiring more than technical expertise. Future mining engineers must blend engineering excellence with key human skills such as communication, leadership, resilience, empathy, adaptation to change, curiosity and lifelong learning. Based on two recent surveys, one to senior leaders with over ten years of experience in the mining industry and a second, focused on understanding the perceptions of young professionals, this paper explores which skills become core competencies by 2030 for navigating complexity, leading responsibly, and enabling sustainable transformation. Furthermore, it also examines how educational institutions can adopt strategies to foster the development of these critical skills, preparing future mining talent for evolving challenges.

Feb 22, 2026

By J-P Strydom, J P. Z, S. Schafrik, M. Beck, Z. Agioutantis

Developing a method to accurately determine the weight and distribution of the load within a shuttle car bed eliminates the need for manual activation of the flight chain. Accordingly, this experimental study characterized the thermo-mechanical response of two unique load cells in force shunt, implemented as an engineering control to quantify load position and distribution without human intervention. The influence of environmental and installation conditions on the measurement accuracy was quantified and determined to be indirectly dependent on the characteristics of the material load cells that are mounted to.

Feb 22, 2026

By Onur Golbası, Berk Gokce

Investment decisions in the mining industry are complicated by sector-specific uncertainties. This study presents a multi-submodule system dynamics model to capture the dynamic complexities of decision-making across mineral property development stages. The model includes five interconnected subsystems: valuation, production, growth strategy, demand, and finance. Developed through system decomposition, expert input, and literature, the model is tested on a hypothetical copper mine with 850 ktpa capacity and 1% cu grade. Simulated over five years with quarterly steps, it estimates an enterprise value of $78.9 million and a target growth rate of 11.2%. Results highlight the significant effects of operating costs, capital policies, and inflation on free cash flow, and the critical role of mineral reserves in sustaining growth. This model supports strategic investment analysis across different minerals and development phases, offering mining investors a robust tool for optimizing decisions.

Feb 22, 2026

By S. Wegerer, M. Semel

The search for minerals typically starts with a reconnaissance phase. After finding a promising target area, further prospecting work will be conducted. Finally with growing confidence of having encountered an ore deposit with commercially viable concentrations of relevant minerals, an extensive exploration campaign will verify its potential. Best practice and reliable, efficient tools for mineral resource estimation of massive sulfide deposits in the deep sea have to be established yet. Therefore, a new seabed exploration system is in development. Various challenges are caused by the extreme environmental conditions in the deep sea and by the nature of massive sulfide deposits. Information of past and ongoing expeditions were gathered to form the basis of an in-depth requirement analysis. System functions and corresponding process times were derived. The experience from the existing MeBo seabed drill rigs serve as starting point for the concept study and following development. Initial MeBo system was built for maritime research purposes and now has to be converted into a new design, suitable for efficient and economic resource exploration. The new system configuration is modular structured to adapt easily to different application scenarios and challenges. To achieve an extension of the deployment depths, the overall equipment weight has to be limited through light weight construction and material. The drilling module contains a range of geotechnical coring tools to face the varying soil conditions of heterogeneous massive sulfide formations. The major challenge to overcome is the touch down sequence on uneven, 25° inclined, rough terrain in up to 4.000 m water depth. Furthermore, high precision of the final unit positioning is necessary. Landing sub-system proof of concept is validated in laboratory environment with small scale model. A novel seabed exploration system capable to land and operate safely on highly inclined slopes of mineral deposit is described. Obtaining high quality samples by wire-line coring technique is the objective.

Feb 22, 2026

By Max Friedemann, Franziska Günther, Helmut Mischo

Ensuring adequate ventilation is a critical aspect of safety in underground mining operations. In small-scale mines in particular, key ventilation parameters such as temperature, humidity, and air velocity are often measured manually and only at infrequent intervals, typically using analog instruments. As a result, real-time monitoring of environmental changes, timely detection of hazardous situations, and demand-driven ventilation control are not feasible. This presentation discusses the selection and evaluation of modern digital ventilation measurement devices, including handheld instruments with digital data logging capabilities and continuously operating sensors with potential for real-time data transmission. The investigations focus on the challenges posed by underground environments with extremely high humidity levels, which can adversely affect sensor performance and electronic components. The results are based on testing conducted at the Research and Teaching Mine of TU Bergakademie Freiberg—an underground ore mine characterized by humidity levels exceeding 95%. Findings include assessments of measurement accuracy, reliability, and practical applicability under these demanding conditions.

Feb 22, 2026

By Enrique Rubio Esquivel, Matías Fuentes Bustamante

The transition from open pit to underground mining represents a key strategic challenge in modern mine planning. This paper presents a multicriteria and multivariable methodology to plan such a transition, integrating technical, economic, environmental, and social considerations. The proposed framework focuses on risk reduction (de-risking) through the identification of alternative development paths, the use of stochastic simulation to model geological and technical uncertainty, and different mining strategies such as methods, production rates, sequence, etc. for ultimate underground implementation. The study summarizes the limitations of traditional planning methods—which usually treat the open pit and underground mine designs as independent processes—, also often it considers a single mining method and production rate for the underground option. Instead it is proposed an integrated approach that leverages synergies between both mining methods and scalable production rates. Also the proposed methodology incorporates the definition of critical variables (geotechnical, economic, and social, among others), the construction of multiple operational and technological transition paths, and the evaluation of each path under criteria of economic attractiveness and practical do-ability (capacity to be executed). Using simulation tools (SIMPLAN for operational performance and SIMVAL for economic evaluation), probabilistic distributions of the different path are obtained, enabling the quantification of the project’s Value at Risk (VaR). A subsequent multicriteria analysis weights the expected profitability against the feasibility of execution of each alternative, producing a decision matrix that provides a framework for evaluating the different project path. As a result, the proposed approach identifies OP→UG transition strategies that maximize business value by capturing remaining resources while minimizing financial and operational risks. Finally, strategic conclusions and recommendations for the industry are provided, emphasizing the importance of early transition planning even challenging the open pit sequencing of the latest push backs by introducing early underground operations. Future work includes strengthening the methodology—such as integrating real-time analysis and adaptive decision-making—and providing recommendations for its application in various mining operations. In summary, this paper delivers a technical and professional framework to guide mining companies on when and how to carry out a successful transition from open pit to underground mining, balancing resource recovery with financial, operational, and social security.

Feb 22, 2026

By Bahadir Ergener, Angel Maria Tobar Escudero, Sandra Nowosad

Modern mining companies are increasingly turning to integrate digital technologies and circular economy (CE) principles to increase the sustainability of their operations. The so-called “mine of the future” is envisioned as a smart, integrated system where technologies such as automation, artificial intelligence, digital twins, and real-time data analytics work in harmony with human decision-making and environmental responsibility. Already in 2018, McKinsey and Co. identified that the three drivers that would define a technology-enabled change in mining would be technology, including digital, analytics and automation, management systems able to identify the potential and value of the new technologies, and the culture and capabilities of the organisation, leaning to more agile and responsive organisations. From the three drivers, in the last five years most developments have been centred in the first one. Yet despite rapid advances, the adoption of new technologies across the industry today remains uneven and often slower than expected. Furthermore, it has been identified that the problem on the technology uptake often relay on the lack of operational readiness, process incompatibility or misalignment, and resistance to change within the mining operation. At the same time, leading companies like Rio Tinto, BHP, and Anglo American have each launched major digital transformation programs. Rio Tinto, for instance, operates one of the world’s largest autonomous mining fleets and has integrated digital technologies across nearly all its operations (Rio Tinto, 2025). BHP is actively investing in information and communication technology (ICT) development as artificial intelligence, big data analytics and robotics, and has partnered with battery companies to pursue circular economy initiatives. Only in 2024, their ICT spending reached US$ 438.3 million (Global Data, 2024). Anglo American has rolled out its FutureSmart Mining™ framework, explicitly aligning innovation with circularity and sustainability goals (Anglo American, 2025). The accelerating pace of change across leading mining companies along with the uneven adoption in the technology uptake clearly state how digital transformation is no longer just about implementing new tools, instead it requires a fundamental shift in how people, processes, and culture are aligned. Addressing only the technical layer, while neglecting the human and organizational dimensions, leaves transformation efforts fragile and unsustainable. As the industry must act decisively to close this gap, the true test of transformation is today centred in changing behaviours, mindsets, and systems. Even at the listed leading companies, initiatives have encountered cultural and structural resistance that are relatable to the industry in large: siloed departments fail to collaborate, procurement teams focus on upfront costs rather than lifecycle value, and operators are often excluded from early-stage planning, reducing buy-in. In many cases, a lack of communication or failure to link technology to real operational bottlenecks leads to disengagement at the ground level. This friction reveals a broader issue: mining organizations have historically treated technology and culture as separate domains, when in fact they are deeply interdependent. To address this, the authors propose a systems engineering approach focusing on the mining operations as a complex socio-technical system composed of people, processes, and technologies. Systems engineering offers tools and frameworks for mapping interactions, aligning incentives, designing for feedback and adaptation, and integrating change across organizational boundaries. Specifically, besides technical requirements, it demands treating culture not as an afterthought or side-effect, but as a design variable that must be intentionally shaped alongside infrastructure and workflows. This paper explores how this approach can be applied in practice, by analysing a real-world case scenario where resistance to innovation was overcome not by technical capabilities alone, but through alignment of stakeholder incentives, thoughtful communication, and cultural integration. A particular focus is set on the adoption journey of the Powerbit X, a drill bit technology with significant potential for operational and environmental gains.

Feb 22, 2026

By Issac Douglas, Sheila Devasahayam, John S. Thella, Manoj K. Mohanty, Jeremy Prishmont

The flotation performance of Sodium O, O-diisobutyl Di thiophosphate (referred to as reagent A) was compared with Aerophine 3418A (referred to as reagent B) for floating a complex copper ore grab sample (Ore A). Preliminary test results indicated a cumulative copper concentrate grade of 10.19% with a recovery of 86.31%, which was achieved with reagent A from a feed consisting of 5.32% Cu. The grade and recovery achieved using reagent B are 9.11% and 87.85%, respectively. A comparative analysis based on the preliminary test results indicated that reagent A’s performance is better than that of reagent B at lower concentrate grades, specifically below 12% Cu. However, the flotation performance is better for reagent B at higher concentrate grades (>12% Cu). A more detailed study was conducted to optimize the grade-recovery performances achievable from both reagents on a complex low-grade copper ore sample (Ore B) from Western USA. Test results indicated a copper concentrate with a grade of 5.5% Cu and 78.59% recovery was obtained with reagent A compared to 4.31% Cu and 62.04% recovery with reagent B from a feed consisting of around 0.25% Cu.

Feb 22, 2026

By Roberto de Moraes

Lunar construction faces unique challenges arising from the nature of regolith and megaregolith. Unlike terrestrial soils shaped by weathering, lunar regolith is composed of angular, poorly sorted particles produced by impacts, with bulk Density, strength, and trafficability varying sharply with depth and terrain. Boulder fields, floaters, and talus aprons add further complexity, disrupting excavation and mobility. Apollo missions documented these conditions through drive-tube samples, trenching, penetrometer data, trafficability tests, and seismic profiling, but the results remained as datasets rather than a unifying classification. This paper introduces the LRC (Lunar Regolith Classification) Framework and the Overconsolidation Ratio applied for the Moon (OCR*), the first contractor-ready system to organize Apollo-derived trends into excavation demand zones (L1–L5). LRC is explicitly a classification, not a stratigraphy: depth ranges are indicative and require in-situ verification before use. Each zone is defined by bulk density and strength ranges, field proxies (bootprints, trench stability, auger torque, seismic contrasts), and corresponding excavation implications. Worked examples from Apollo 15 (mare), Apollo 16 (highlands), and Apollo 17 (pyroclastics and talus) demonstrate how observed data translate into LRC zones. These cases show that LRC captures both systematic depth trends and sharp local heterogeneity. The framework standardizes excavation planning for landing pads, haul roads, berms, foundations, and tunneling trials, while converting floaters from hazards into resources. LRC thus provides a common language for lunar construction. Rooted in Apollo evidence but designed for Artemis verification, it is proposed as a living standard; a reference framework to guide site preparation, excavation, and risk management in the next phase of lunar development.

Feb 22, 2026

By M. Schlegel, J. A. Villa Mena, R. E. Vivas

ArcelorMittal, headquartered in Luxembourg, is one of the world’s largest steel and mining companies. It supplies steel to industries such as automotive, construction, and energy, with a strong emphasis on sustainability and innovation. The company employs about 125,000 people and, in 2024, produced 42.4 million tons of iron ore and 57.9 million tons of crude steel across 15 countries. Its mining operations span Canada, the United States, Mexico, Brazil, Ukraine, Bosnia and Herzegovina, Kazakhstan, and Liberia, focusing on iron ore and coal extraction to support steel production. This study examines Peña Colorada, one of Mexico’s largest iron ore mines (a joint venture by ArcelorMittal and Ternium). Facing declining ore grades, Peña Colorada adopted Hexagon solutions to uncover and capture project value. A comparison of two Life of Mine (LOM) plans from 2012 and 2016 (before and after implementing Hexagon solutions) shows that between 2019 and 2023, Peña Colorada reduced actual waste by 26% (compared to 2012 LOM) and 19% (compared to 2016 LOM). LOM Plans are generated yearly, and each time, opportunities for reducing mining waste were identified, evaluated and implemented. The key driver was schedule optimization using Hexagon MinePlan Schedule Optimizer (MPSO). This reduction means less waste transported to disposal sites, resulting in fewer hauling equipment operating hours, lower fuel consumption, and reduced carbon emissions.

Feb 22, 2026

By Abdallah Khair, Nathalie Risso, Arie Herrera, Victor Tenorio

This study introduces a machine learning strategy to optimize icy regolith extraction from the Shackleton-de Gerlache Ridge using autonomous mining equipment. The model incorporates key parameters—distance, road gradient, vehicle load, speed, recharge logistics, and regolith water content—into a cost framework for excavation, hauling, and dumping. Regression models estimate energy and time requirements; classification predicts terrain navigability; clustering groups craters for efficiency; and K-Nearest Neighbors (KNN) determines optimal routing and scheduling. The system adapts to a six-month daylight cycle to maximize productivity and minimize costs, enabling intelligent planning for sustained lunar resource extraction under extreme environmental and logistical constraints.

Feb 22, 2026

By Francisco J. Sotillo

Using new ecological-natural-organic depressant for gangue and pyrite with antibacterial properties (control of acid mine drainage) with new improved xanthate collectors using rheology additive not chemical reacting with xanthate resulted in better sulfide flotation. Rougher-scavenger lead flotation tests were conducted increasing the concentrate grade from 7.07% Pb to 13.44% Pb, enhancing selectivity. Lead recovery increased from 64.08% to 79.38% and 80.40% using only the new depressant, and improved xanthate Z-11 and Z-4, respectively. The results demonstrated that the new depressant was selective and efficient, and the new improved xanthates stronger more selective collectors.

Feb 22, 2026

By Giorgio De Tomi, Rondinelli Sousa

Whilst all public mineral reporting codes require classification of mineral resource and reserves according to the level of geological knowledge and confidence of the estimates, companies are not required to disclose how mineral estimates and associated cashflow projections respond probabilistically to the incorporation of different types of risk events. As the level of expectations and scrutiny of investors and stakeholders continue to increase over the years, it will be essential for companies to adopt an integrated framework for sensitivity analysis to increase corporate value through better capital allocation and reduce potential losses associated with poor investment decisions. Failure in fully capturing the impact of unexpected incidents in mineral estimates and financial modeling could be extremely harmful to the business, affecting the company’s reputation, and negatively impacting the relationship with stakeholders.

Feb 22, 2026

By Bright Oppong Afum, Kojo Boakye, Kwaku Boakye

This research developed and simulated a novel multi-indicator Fatigue Detection and Alert System (FDAS) designed to enhance fatigue detection accuracy in mining environments. The system integrates a comprehensive set of inputs: eye blink rate, eye closure duration, yawning frequency, distraction levels, Pre-shift Check-in Scores (Self-report) and Electroencephalography (EEG) Levels. Using MATLAB’s Fuzzy Logic Rule Viewer (FLRV) and Simulink, simulations demonstrated the FDAS’s robust ability to process these diverse physiological and behavioural indicators accurately. It effectively classified operator fatigue into low, moderate, and high fatigue levels, consistently providing appropriate outputs and corresponding intervention recommendations across various mixed-signal scenarios. The system achieved a calculated accuracy of 85.19% across 27 test entries, with a standard deviation of approximately 1.8459, confirming its reliability for real-time fatigue monitoring. These findings highlight the significant potential of this fuzzy logicbased approach to proactively identify early signs of fatigue, substantially enhancing safety and operational efficiency in demanding mining operations.

Feb 22, 2026

By Jim McKinley

With a growing number of mines reaching closure and seeing closure costs materialize, regulators, lenders, and banks are observing projects that fail economically by miscalculating these costs. Mine closure costs are often categorized as a type of liability which is defined as the money owed by the company to offset effects from the project, and the money available to pay for those debts (e.g., bond). Often, decisions made before Day 1 of mining (e.g., co-disposal, dry stack tailings, waste segregation) can significantly change the bond calculation. Once the bond is calculated and funded, operators are encouraged to conduct closure research and use applied science for progressive bond release prior to final closure. However, this author has observed few instances of financially significant progressive bond release, as there are typically no robust procedures for bond return, either before or during closure activities. As a result, many companies decide that entering a state of Care & Maintenance (C&M) is less risky than attempting to fund closure activities with an unknown bond return mechanism. Although perhaps less risky in the short-term, the primary long-term risk with entering C&M is that it increases the chances of the bond not covering the cost of closure and the chances of the government/regulatory agency inheriting the mine closure. Bonds are typically reevaluated on a regular cycle (e.g., five years) so every mining company goes through this financing challenge eventually.

Feb 22, 2026

By Ali Soofastaei

Mining operations are increasingly data-rich yet decisionconstrained. Fragmented systems, variability in geology and operations, and sustainability obligations create multiobjective trade-offs that classic analytics cannot reconcile at operational tempo. This paper proposes an end-to-end framework that fuses digital transformation practices (governed data platform, semantic layer, feature store, and MLOps) with generative AI (retrieval-augmented generation, tool-use, and agentic workflows) and decision intelligence (simulation/digital twins and multi-objective optimization). We formalize sustainability-aware objectives, define a practical stack and governance controls, and demonstrate how an AI “decision copilot” can surface options, quantify trade-offs, and document rationale. Two figures illustrate a production-grade architecture and a Pareto frontier for cost–emissions trade-offs; two tables operationalize decision-domain mapping and a transformation maturity rubric. The approach is product- and company-agnostic.

Feb 22, 2026

By M. E. Rossi

In mineral resources, geologic and mining data are acquired, processed, analysed, interpreted and modelled, eventually serving as basis to generate predictions and production plans. This is a complex process, and the resulting predictions are impacted by uncertainties related to the data itself and the processing methods and techniques used. They are also impacted by the subjective decisions made by the modeler(s) at each step of the way. Knowledge, biases, skills, and prior experience come into play in the long mineral resource evaluation development workflow. It is meaningless to discuss uncertainties without evaluating the associated risks that those uncertainties imply. It is important to quantify and assess uncertainty, and to evaluate and mitigate its consequences. This paper discusses (1) conceptual and practical sources of uncertainty; (2) the utopia of an “objective” uncertainty; and (3) the quantification and public reporting of uncertainty using geostatistical conditional simulations. The objective of this paper is to postulate that the industry is running out of reasons and excuses to ignore uncertainty and risk in project evaluation. This is done in two parts, with this, the first one, presenting a more conceptual discussion. Part 2 will present case studies from different types of mining projects and operations showcasing the impact that risk assessments can have in a mining project.

Feb 22, 2026

By Lina Ospino Ballesta, Oscar J. Restrepo Baena, Juan Diaz Martínez

Artisanal and small-scale underground gold mining in Colombia plays a significant role in the country’s economy, but it faces persistent occupational hazards that threaten worker safety. Despite mining economic contributions, outdated technologies, limited risk management practices, and insufficient regulatory enforcement have led to recurring workplace accidents, many of which have been fatal. This study presents a systematic review of mining-related accidents over the last decade. Through geo-referenced analysis, high-risk municipalities were identified, and the frequency of accidents was correlated with the mining legal status and operational practices of these municipalities. The findings underscore the urgent need for evidencebased interventions that are tailored to the country’s unique mining context. Ultimately, this research contributes to the global discourse on mining safety by highlighting practical pathways to reduce occupational risks and promote safer, healthier workplaces in resource-constrained environments.

Feb 22, 2026

By Corey Vaughan

Unplanned shutdowns from abrasive wear part failure in crushers, chutes, and slurry pipe assets can cost millions in lost production and reactive maintenance. 2Censor patented sensor technology enables real time abrasive wear monitoring of mineral processing equipment, turning passive assets into smart, data driven components. Wireless sensors embedded in liners and pipework transmit wear data live to operators, allowing for predictive maintenance, safer scheduling, and optimized asset life. This paper will present global case studies showing reductions in downtime, increased throughput, and improved maintenance accuracy. The system is ready to retrofit, neutral to original equipment manufacturers, and proven across more than twelve countries in abrasive wear liners and slurry pipe applications.

Feb 22, 2026