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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 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 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 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 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 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 Derek du Preez, Andrew Hall, Timothy M. Pelech

Net Present Value (NPV) derived from Discounted Cash Flow (DCF) analysis remains the dominant metric for evaluating mining projects despite its well-documented inability to capture managerial flexibility under uncertainty. DCF assumes that all risks are perfectly priced by financial markets. This is an unlikely assumption for volatile commodity prices, geological variability, or the array of mining technical and operational risks present on all mine sites. Real Options Analysis (ROA) was developed to remedy this limitation by explicitly valuing the ability of managers to defer, expand, scale, switch, or abandon investments as new information emerges, and to capture upside and mitigate downside risks. While ROA is philosophically correct and routinely shows an uplift in project value compared with DCF, its practical application at industrial scale is severely constrained, ROA faces the reality of a combinatorial explosion in complexity of decision trees, Monte Carlo simulations and other models required when multiple interdependent or sequential options exist across numerous mining zones and time periods. The AMC Hill of Value® (HoV) process adopts the same intellectual foundation as ROA, that flexibility has economic value, but operationalizes it through a far more robust and scalable architecture. It is built on parametric relationships, rapid scheduling, and multi-objective evolutionary optimisation. HoV can evaluate millions of compound, interdependent real options in a single optimisation run, delivering resilient, adaptive strategies that preserve managerial flexibility while simultaneously optimising NPV, mine life, risk exposure, and other corporate objectives. This paper demonstrates that HoV is the practical, industrial-scale embodiment of real options thinking in mining: it discovers, ranks, and translates the most valuable real options into strategic mine plans, overcoming the scalability barriers that have prevented widespread adoption of classical ROA.

Feb 22, 2026

By A. J. Richins, M. G. Nelson, R. Dunne

From the inception of flotation in the late 1800s, coarse particle recovery has been a challenge to practitioners. By the early 1900s, flotation processes included oil flotation, skin flotation, agglomeration flotation, and froth flotation, and for each there was a proliferation of flotation equipment. Ensuring good coarse particle recovery included desliming of the feed and proper conditioning were required. Froth flotation was at first used mainly to treat finer materials from grinding circuits. The maximum size for coarse particles was from 3.18 to 4.78 mm. In froth flotation, large particles with high specific gravity tend not to be recovered. Coal and minerals of low specific gravity and flaky minerals such as graphite, mica, and talc can be floated in larger sizes. In the early 1960s, the phosphate industry began using column cells to recover coarse particle by froth flotation, but early columns suffered from poor bubble generation and sanding at the flat base of the column. Recently, improved coarse particle recovery has been the object of new cell designs—the Eriez HydroFloat™, the Jord NovaCell™, the FLS coarseAir™ cell, and the Cidra P29 integrated system. The paper will follow the development of coarse particle flotation with a focus on the development, laboratory assessment, and operation of the new flotation equipment and technology designed to recover coarse particles.

Feb 22, 2026

By Scott O’Brien, Richard Williams, Camilo I. Mejias, Elias Godoy, Javier Sierra

High-rate thickeners play a critical role in tailings management by enhancing water recovery and increasing solids concentration. However, these units face operational instability due to fluctuations in feed solids, flow rate, and flocculant response typically managed in manual mode with delayed corrective actions. This work presents an adaptive automatic control algorithm designed for dynamic thickening environments. The algorithm integrates real-time measurements of feed density, rake torque, bed level, and turbidity (overflow), optimizing the underflow slurry density while minimizing suspended solids in the overflow. The proposed control strategy is modular, simple, scalable, and applicable to both existing and new thickening systems, offering a robust alternative to manual operation in increasingly demanding metallurgical environments.

Feb 22, 2026

By Patricio Vergara Lara, Jorman Barrera

The selection of the production level elevation is one of the most critical strategic decisions faced by large-scale block or panel caving projects. This elevation largely affects project timelines, capital expenditures, resource recovery, and may even constrain the mine’s maximum production capacity. Over the years, many computational tools have been developed to assist in this decision, most of them based on the same principle of maximizing the project value given its production level elevation. However, for large and inclined deposits, or those extending significantly in the vertical dimension and where extraction cannot be achieved from a single level, traditional selection techniques involving multiple production horizons often lead to suboptimal results. This paper proposes a methodology ensuring that the selection of production level elevations in a multiple horizons (“lifts”) case is globally optimized. Input parameters include economic and cost variables, maximum extractable column height, and deepening costs. The methodology is demonstrated through a real case study to illustrate its potential impact on project value.

Feb 22, 2026

By Oscar Cabello, Luis Mendieta, Maribel Guzman

Mineral flotation processes generate large volumes of tailings, which must be disposed of efficiently and safely. In addition to dry stack disposal, the possibility of reusing these tailings as aggregates in shotcrete is an interesting alternative. Tailings samples from a mining operation in southern Peru were characterized by granulometric analysis, X-ray diffraction and Scanning Electron Microscopy. Concrete samples were obtained with different tailings formulations. The samples were subsequently subjected to geomechanical testing. The results showed that replacing 20% to 30% of the tailings with aggregates in shotcrete production achieved compressive strengths exceeding 30 MPa after 28 days of curing, with an energy absorption capacity of 500 joules. Results show that this shotcrete can be used in the support stage of the mining cycle in underground mining.

Feb 22, 2026

By Alper Kirmaci, Taghi Sherizadeh, Dogukan Guner, Cameron Mitchel

Brow hazards are a significant concern in coal mine ribs and form when weak coal sloughs out of a rib face and exposes an overhanging block of more competent rock or coal. Of 36 rib failure fatalities in the last two decades, 36% resulted from rib brow failures. This highlights the need to better understand the mechanisms driving brow formations and failures to mitigate this hazard and eliminate potential fatalities. The research team at Missouri S&T worked to enhance the current CPRR system and include the potential for these brow hazards. We employed physical modeling methods to build a scaled model from critical brow cases observed in the field. The dimensions and properties of the models were scaled down by 14.4 times from the field cases. The results of the physical modeling efforts were used to assist in calibrating distinct element numerical models vital to understanding brow formation and failure mechanisms. Subsequently, three physical models were created and tested to provide data on an otherwise impossible-to-capture event at the field scale. The results of these tests provided formed brow dimensions that agree well with those observed at the field scale. The brow dimensions were 1.25 inches deep into the rib, equivalent to 1.5 feet when scaled up. Similarly, the numerical modeling efforts provided good agreement by capturing a brow forming 1.55 inches deep into the rib. The physical model results further validate the applicability of physical modeling efforts for capturing otherwise difficult and dangerous phenomena in a controlled lab setting.

Feb 22, 2026

By N. Sloan Dworian, Alyssa Smith, Ian Kellogg

Many studies have utilized magnetic susceptibility data to fingerprint porphyry copper centers; however, usage of magnetic susceptibility data to identify trends in a Climaxtype molybdenum porphyry deposit is limited. To better understand potential petrophysical signatures in a Climaxtype Mo porphyry deposit, magnetic susceptibility data was gathered at regular intervals from core holes across the Climax Mine, targeting major lithologies and styles of alteration. Preliminary analysis suggests that there are quantifiable patterns which may correspond with the mineralizing intrusions. This data can complement current mapping and exploration techniques to identify Climax-type molybdenum porphyry centers and likewise further the exploration potential for this deposit type.

Feb 22, 2026

By Ashish Kumar, Khadija Said, Ulupi Mishra, Sekhar Bhattacharyya

Using battery-powered equipment in underground mining can improve safety, advance automation, and reduce greenhouse emissions. In this context, rechargeable lithium- ion batteries (LIBs) have a competitive edge due to their high Coulombic efficiency, superior energy density, and extended cycling stability. However, several conditions must be met for their safe operation. Their failure can cause thermal runaway (TR), which poses a significant safety risk in underground mines. Despite studies having investigated this phenomenon using physics-based models, limited research has used deep learning to predict its implications. This study aims to bridge this gap by characterizing LIB TR under dynamic airflow through simulations and predicting temperatures using two of the most common recurrent neural networks: long short-term memory (LSTM) and gated recurrent units (GRU).

Feb 22, 2026

By C. H. Stephenson, M. Du Preez

Overland belt conveyors often use vertically guided counterweight take-ups or horizontally tensioned carriages to maintain belt tension. In the event of belt or wire rope failure, these systems can release significant stored energy, creating high-impact forces that risk structural damage and personnel injury. This paper reviews current safety arresting technologies and presents a calculation methodology for estimating impact velocity, energy absorption requirements, and stroke limitations. Worked examples illustrate the selection process for appropriate arrestor types under different design constraints. The study emphasizes early integration of safety devices to minimize structural loads, avoid costly retrofits, and enhance operational reliability. Implementing robust arrestor systems improves safety and reduces downtime in bulk material handling environments.

Feb 22, 2026