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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 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 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 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 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 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 Michael MacMillan

AI is already changing how mining companies are seen, judged, and trusted. This paper discusses “reputation engineering,” a structured way to build trust in a world where AI systems summarize and evaluate everything a company says publicly. Using mining examples, emerging AI search trends, and real communication work, the paper explains why the next 12–18 months are a crucial window for action. It also provides a practical framework to help mining companies improve their visibility, accuracy, and consistency across both human and machine channels.

Feb 22, 2026

By C. H. Stephenson, Z. White

This paper presents the design approach case study for incorporating a Technogrid® conveyance End-of-wind arresting system within the new South32 Hermosa headframe. Focus is placed on energy absorption requirements, structural integration, and mounting details tailored to the geometry and operational constraints of the headframe. Key considerations include arresting forces, load path continuity, and connection design to ensure reliability and maintainability. The paper also discusses coordination with other headframe systems and the iterative design process used to meet safety standards and client objectives.

Feb 22, 2026

By Germán Toledo

The closure of TSF represents a critical milestone in the life cycle of mining operations, requiring the integration of technical, environmental, and social dimensions to ensure long-term safety and sustainability. The GISTM introduces the concept of “safe closure” as a demonstrable technical condition in which there are no ongoing material risks to people or the environment. This status must be validated by an independent technical reviewer and formally approved by the Accountable Executive. This article presents a risk-based methodology to support the achievement of safe closure, aligned with the principles and requirements of the GISTM. The proposed approach emphasizes the need to identify, assess, and manage closure and post-closure risks progressively throughout all phases of the TSF life cycle: from site selection and design, through construction and operation, to closure implementation and long-term monitoring. The methodology integrates key elements of effective risk management, including comprehensive knowledge bases, consideration of climate change, credible failure modes, continuous monitoring, stakeholder engagement, and governance. The ALARP principle is applied to demonstrate that residual risks have been reduced to tolerable levels. By incorporating closure planning from the earliest stages and adopting a risk-based view throughout the entire life cycle, this methodology aims to support mining organizations in achieving a verifiable and responsible closure of tailings facilities, in line with international best practices such as those of ANCOLD and ICOLD. The proposed framework offers a practical contribution to strengthening the credibility, effectiveness, and sustainability of tailings closure processes.

Feb 22, 2026

By Omar. M. Arafat, Edgar Pérez, Kyle. M. Bartholomew, Robert. E. McIvor

The “circulating load” confounds understanding of ball milling circuits. Conflicting opinions exist as to its role. Should it be high, or low? Why does it even exist? It is commonly accepted in the plant as a given, the outcome of largely unknown factors. As such, it may often go unmeasured or even ignored. This paper describes the importance of the circulating load in wet ball milling circuits. It is characterized not only in terms of solids mass flow (or ratio of mass flows), but also by its other key physical characteristic, its size distribution. Its effect on grinding circuit performance is explained. The equipment application design steps to achieve a desired circulating load, in terms of both its mass flow and size distribution, are described. Finally, its pivotal role in grind control is specified. Our goal is for the reader to come away with a fresh understanding of the role of the circulating load in wet ball milling circuits, including how and why it should be measured and managed.

Feb 22, 2026

By William Gleason

Since 2004, Dave Kanagy has served as the executive director and chief executive officer of SME. In that role, he has worked with 22 SME Presidents, traveling the world to represent the Society. His prestigious one-million-mile status with United Airlines is a testament to these efforts. He has been to six of seven continents while leading the Society on a journey from a struggling association in 2004 to the largest and arguably the most influential professional mining society in the world. In the following pages, some of those past SME Presidents reflect on their time with Kanagy and paint the picture of a visionary leader who was willing to make the hard decisions for the betterment of the Society while remaining open to new ideas and opportunities. One of his first accomplishments as the executive director was to streamline the SME Boad of Directors from 29 members to nine, making it much more effective. With a keen financial sense, he was able to add value while cutting excess to expand the Society in every measure. As the leader of SME, Kanagy helped facilitate much of the Society’s growth and innovation as the world’s largest mining related organization. He has a B.S. degree in industrial education from the University of Maryland, an M.S. degree in technology education from Eastern Illinois University and is a certified association executive by the American Society of Association Executives. Under his leadership, several unique programs were created or advanced, including OneMine.org, the world’s foremost online mining research library. He enhanced legacy programs and increased collaboration with international organizations. Kanagy is the recipient of prestigious awards, including the Colorado Society of Association Executives’ Professional of the Year award and the Mining and Metallurgical Society of America’s Gold Medal award.

Feb 1, 2026

By William Gleason

At 6,898 ft below surface, the historic No. 9 shaft at Resolution Copper near Superior, AZ is now the second deepest single lift mine shaft in the United States and connects to the deepest single lift mine shaft in the U.S., Resolution Copper’s No. 10 Shaft (6,989 feet). The shafts serve as ventilation and access for future underground development of what could one day become one of the most significant copper mines in the United States. It is from the base of No. 9 and No. 10 shafts that hundreds of employees of Resolution Copper, a joint venture of Rio Tinto and BHP, hope will soon be given the go ahead to begin driving lateral tunnels to reach a copper deposit that is estimated to contain 28 Mt or 40 billion pounds of copper. Copper was recently added to the U.S. Geological Survey’s (UGGS) critical minerals list, in large part because of increasing demand. A study by S&P Global Energy & Market Intelligence “Copper in the age of AI: Challenges of electrification” released on Jan. 8, 2025, “identifies a transformative trajectory for copper demand, projecting a surge from 28 Mt (31 million st) in 2025 to 42 Mt (46.3 million st) by 2040 – a 50 percent increase that underscores the metal's pivotal role in multiple technological and economic domains.” The surge in demand is driven in large part by the global energy transition, electrification of vehicles, growth of artificial intelligence and data centers, and most recently robotics. Meanwhile, geopolitical tensions have increased the focus on the need for the United States to secure more of its own mineral supply chain. S&P Global’s report is one of many warnings that while copper demand has accelerated rapidly, future supply is being held back. Resolution Copper stands out as one example of a known mineral deposit remaining locked in the United States’ complex and lengthy permitting slog.

Feb 1, 2026

By A. K. Raji, E. F. Orumwense, M. O. Ojumu

The Fourth Industrial Revolution has driven significant advancements in autonomous robotic systems, particularly in subsea exploration and offshore mineral dredging. This review examines the latest developments in electrically powered quadrotor-track subsea robotic crawlers, highlighting their potential to enhance efficiency, mobility, and adaptability in challenging underwater environments. The integration of advanced automation, artificial intelligence, and real-time control systems has paved the way for more effective robotic solutions in offshore mining. This study explores the dynamic performance of hydraulic crawlers to quadrotortrack robotic dredgers, focusing on their propulsion, navigation, and stability under high hydrodynamic conditions. By leveraging state-of-the-art technologies such as lithium-ion battery power systems, intelligent microprocessors, and sensor-based control mechanisms, these robotic crawlers offer a promising alternative to conventional subsea excavation methods. Furthermore, the review analyses recent experimental and simulation-based studies that assess the feasibility and performance of these systems in real-world applications. The findings of this review provide valuable insights into the role of 4IR in transforming subsea robotics for offshore mineral dredging. By addressing existing limitations and identifying key technological advancements, this study contributes to the ongoing development of nextgeneration robotic systems capable of operating efficiently in extreme underwater conditions

Jan 30, 2026

By J. Hadjigeorgiou, J. Wesseloo

Mining companies employ a multitude of risk management tools. The effectiveness of these tools for decision-making and communicating risk has not been addressed. This paper investigates the use of verbal probabilistic expressions in communicating geomechanical risk. Analysing survey data obtained from a group of mining geomechanics professionals, it identifies limitations of common probabilistic expressions. The paper concludes by making specific recommendations to avoid the use of certain expressions that may result in increased uncertainty, thus compromising the use of risk management tools.

Jan 30, 2026

By T. Szendrei, S. Tose

The Gurney approach to explosive/inert material interaction was adapted to analyse the face velocity in bench blasting. The model is based on the blasthole diameter, rock and explosive density, burden, spacing, linear charge density, and the Gurney energy constant. It is validated by comparing its predictions with a set of 20 field measurements of face velocities reported by Chiappetta et al. (1983) in an iron ore mine. The Gurney model links the observed large scatter of measured face velocities to the variation of the Gurney energy constant. This in turn is linked to the variability of the gas pressure acting on the burden. These variable pressures are generated when detonation product gases migrate into the extensive and complex fracture network around and between in-row blastholes. The energy efficiency of burden movement can be derived from the model. It is shown that ~7% of the explosive’s chemical energy is available for gas expansion work on the burden; of this quantity, 36% is actually converted to burden kinetic energy. That is, less than 3% of chemical energy is ultimately expended in burden displacement and throw. The model further indicatesnthat the projection of high-velocity (say, 100 m/s) flyrock is possible only when the path of leastnresistance through the burden has an effective density far less than the host rock. An equationnis derived that identifies the combinations of burden and path density that may yield flyrock. These values are specific to a particular baseline blast design.

Jan 30, 2026