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By D. Scott Scovira, Thomas Gustavsson

Exiting WW2, the potential of nitrates and hydrogen peroxide for application as industrial explosives both became known. The technology stream advanced the development and uptake of nitrate-based explosives to the point that they are the current global standard for blasting. Recently environmental issues are influencing the strategic agenda of extractive industries. The mid-2010s saw renewed interest in hydrogen peroxide explosives to eliminate NOx fume. Carbon reduction initiatives in the 2020s provided additional impetus to investigate hydrogen peroxide-based explosives. Hypex Bio is at the forefront of developing and delivering bulk gas sensitized Hydrogen Peroxide Emulsion (HPE) for blasting. HPE consists of hydrogen peroxide along with smaller amounts of fuel and emulsifier. The consistency of HPE is similar to industry- standard nitrate-based emulsions. It is compatible with existing priming and initiation systems. HPE does not contain nitrates and thereby does not produce post blast nitrous oxide fumes nor discharge of nitrates or ammonia to mine water. Importantly, HPE contributes to reduction in total carbon emissions as compared to nitrate-based explosives.

Feb 1, 2025

By V. Claremboux

The transformation of raw iron ore into high quality steel can take place via several processes. A general consistent theme involves the upgrading of the iron ores via methods such as flotation and magnetic separation, the preparation of an agglomerate such as via pelletization or sintering, the smelting of the agglomerate into a high grade iron product, and the further refining of iron into specific steel alloys. Each of these steps admit potential for optimizations and alternatives, and the process overall is critical to meeting the world’s continuing iron demands.

Feb 1, 2025

By Antonio Nieto, Jesus Castillo

Research and Development (R&D) departments in the mining sector are essential for creating new solutions on productivity, safety, and sustainability. Nevertheless, the selection of R&D projects is complex, often influenced by subjective judgments and uncertainties. This paper explores the application of the Multicriteria Decision Analysis (MCDA) as a structured approach to evaluate and prioritize innovation projects based on various criteria such as safety, cost, environmental impact, and social acceptability. By assigning weights and quantifying criteria, MCDA enhances decision-making transparency and objectivity. This study aims to show a method that facilitates strategic thinking, resource optimization, and stakeholder engagement, ensuring that selected innovations align with the company’s long-term objectives and commitment to responsible mining practices.

Feb 1, 2025

By Cayo Soto

Mining activity is important for the development of humanity. This development must be understood from the Academy where it allows showing alternatives for the industry performance. Likewise, these mining companies need to improve their results. Historically, a few years ago the application of the ESG (Environmental, Social and Governance) criterion was verified, which is positioned as a factor/regulator in the design of the performance of industries in general. ESG as an integral part of the concept of sustainability serves as a tool to conceive mining without conflicts and with a reputation based on trust in the interrelation of the university, industry and society. Therefore, the academy must strive for new knowledge in a way that allows it to continue in the virtuous circle of constantly feeding it. In this context, the best mining practices are implemented in constant questioning of their activities. The scientific essence of the industry supported by the academy developed in an operational dynamic is addressed. Finally, the objective of this research work is to interrelate 3 variables: ESG, Academia, and the Mining Industry, where the transition of knowledge and the role of each variable in relation to each one can be understood. This allows for an additional understanding of mining in the future with new mental attention.

Feb 1, 2025

By L. Alagha, L. Sanchez-Calderon, M. Silwamba, W. Kirk

Selenium-rich metallurgical waste, also known commercially as “crude selenium,” is a byproduct of the copper (Cu) refining process. This by-product, contains ~ 90% selenium (Se), precious metals, platinum group metals (PGMs), and other critical elements. This study investigated the leaching efficiency of Se from the sludge under alkaline conditions using different oxidizing agents to enrich PGMs and precious metals in the leach solid residue. The effectiveness of each oxidizing agent during leaching was assessed and compared. Additionally, Eh-pH diagram for Se was established under specific experimental conditions and utilized to inform process optimization. Key variables, including leaching time, temperature, and oxidant concentration, were evaluated for their impact on the efficiency and the selectivity of the oxidative alkaline leaching process.

Feb 1, 2025

By Y. Zhang, C. Zhou, M. Girman

Wireless technologies are increasingly being implemented in underground mines for various purposes such as communications, tracking, remote control, remote sensing, and environmental monitoring. However, the adoption comes with risks as common wireless systems, such as WiFi, Bluetooth, IWT (Innovative Wireless Technologies) wireless system, often operate in the unlicensed ISM (industrial, scientific, and medical) band. The shared nature of the ISM band can lead to interference among devices and consequently cause performance degradation and reliability issues. In this study, we developed two wireless communication evaluation boards as a tool to evaluate the performance and reliability of a wireless system with the presence of electromagnetic interferences (EMI) from other wireless systems in underground environments. We adjusted various parameters including signal power from adjacent frequency channels, noise power within the same channel, the movement of personnel, and communication packet size. Our findings indicate that, while the power of the EMI source plays a key role, the motion of personnel in the tunnel also has a strong impact on performance, and this impact increases as the power of EMI sources increases. In noisy environments, smaller packet sizes are preferable as they enhance the likelihood of successful transmission. High levels of interference or noise can lead to increased packet loss or error rates, potentially causing communication links to fail completely or become ineffective. The evaluation boards utilized in this study are based on a practical wireless transmission system deployed in a remote controller for a heavy mining machinery used in underground coal mines. The results and findings presented in this paper can aid in the design of wireless systems that are resilient to EMI in underground mining environments.

Feb 1, 2025

By Justin Jensen, Luis Moya, Jose Carlos Durazo, William Szolga, Tyler McCallum, Tim Doubleday

Sulfuric acid mist is an undesired by-product of the copper electrowinning process, caused by oxygen evolution at the anode which entrains droplets of the acidic copper electrolyte solution. As the oxygen moves to the surface of the cell, these droplets become aerosolized resulting in acid mist. The addition of chemical anti-misting agents to the copper electrolyte is a common mitigation technique. This paper details Syensqo’s laboratory development of a new environmentally friendly acid mist suppressant, ACORGA® EW98. The product exhibits excellent acid mist suppression and it is fully compatible with the adjacent solvent extraction process. Lab and pilot test results are reviewed ahead of future planned industrial trial testing.

Feb 1, 2025

By Marcos de Paiva Bueno, Leonardo Ribeiro Lara, Rajiv Chandramohan, Thiago de Almeida, Greg Lane

This paper explores the impact of the significant difference between the number of geochemical assays conducted for grade estimation and the number of comminution tests performed for throughput and performance forecasting. Both grade and throughput are key factors in determining the project. We analysed 154 feasibility study reports to assess the impact of sample frequency for comminution test work on project revenue. This disparity in size between assay and comminution data arises because geological and resource-grade risks cannot be managed without extensive geochemical testing, whereas comminution risks are traditionally mitigated through design methods and the use of contingencies. This approach is partly due to the relatively high cost and large sample requirements associated with traditional comminution tests. Our analysis demonstrates that insufficient comminution sampling and testing leads to uncertainties in throughput forecasts, creating significant financial risks. Data from the feasibility studies show that a 1% change in mill throughput can result in up to a 5% variation in Net Present Value (NPV), underscoring the sensitivity of project economics to operational performance. Building on previous work, we reference studies that reveal how low frequency of comminution testing can increase uncertainty in mill throughput forecasts and increase financial risks. We propose an approach that optimises the number of comminution samples tested to enhance forecast accuracy and reduce NPV variance. By adopting this approach, mining projects can improve financial reliability and mitigate risks associated with underperformance in SAG and AG mill-based operations.

Feb 1, 2025

By John J. Simmons

There is considerable interest in the iron and steel industry in the development of technologies that can reduce carbon dioxide emissions, as the iron and steel industry is the third largest producer of carbon emissions in the world, after automobiles and the power generation industry. The E-Iron Iron Nugget Making Process, invented by Dr. Komar Kawatra and Dr. Tim Eisele, provided a major breakthrough in the iron making process as the process uses biomass in the form of hard wood or soft wood as the reductant in the place of coal. Dr. Kawatra recognized that biomass is rich in both carbon monoxide and hydrogen, two important reducing agents. This resulted in initial experiments conducted by Dr. Kawatra and Dr. Eisele in the laboratories of the Chemical Engineering Department of Michigan Technological University (Michigan Tech) that prepared self-reducing pellets with wheat flour as the reductant and limestone/dolomite as the flux. Initial results were encouraging so they extended their work to include hardwood, which is in huge supply in the forests of Michigan and Minnesota, as the reductant. Dr. Kawatra has also applied the E-Iron Technology to other iron bearing minerals to produce pig iron grade iron nuggets. He used the E-Iron Process to convert red mud, a high iron waste product of the aluminum industry, into pig iron nuggets with the rare earth elements reporting to the slag. This work resulted in a patent with Dr. Kawatra and Dr. Michael Archambeau named as the inventors. Dr. Kawatra then extracted the rare earth elements as a separate high value bi-product using oxalic acid, which he produced from carbon dioxide. Dr. Kawatra also conducted a test program that produced pig iron nuggets from New Zealand beach sands. The vanadium in the beach sands was retained in the iron nuggets, recoverable as a valuable bi- product in a separate process. The titanium dioxide in the beach sands reported to the slag. This demonstrates the potential use of the E-Iron Process to convert the large ilmenite reserves in Northern Minnesota into pig iron and titanium dioxide. Another use of the E-Iron Process discovered by Dr. Kawatra was its ability to produce iron nuggets from manganiferous ores. Dr. Kawatra was able to direct the manganese into either the metal or slag by adjusting process temperature. The above discoveries are included in several patents that were assigned to Carbontec Energy. This presentation will only address the use of the E-Iron Process to produce pig iron nuggets from steel mill waste and un-pelletized, mid-grade iron ore. Carbontec Energy Corporation agreed to sponsor additional research directed at improving this new technology that would later be trade named, The E-Iron Process. Carbontec Energy conducted further work that proved that the E-Iron technology could also convert steel mill waste into metallurgically acceptable iron nuggets. Carbontec also collaborated with the Lawrence Livermore National Laboratory and Purdue University Northwest to conduct a Department of Energy (DOE) sponsored program that would use their high performance computer capability to both verify and model the E-Iron Process. Purdue University Northwest reported that the E-Iron Process can produce pig iron nuggets with 85% less carbon emissions than a blast furnace. The E-Iron Process is similar to the ITmK3 process, developed by Kobe Steel, that also produces iron nuggets but uses coal as the reductant.

Feb 1, 2025

By Devin Burns, Saima Ghazal, Michael Owusu-Tweneboah, Kwame Awuah-Offei

Trust in AI systems and the nature and amount of information about the system can influence decision-making. It is, therefore, crucial to understand how AI-powered monitoring systems (e.g., gas monitoring systems) influence miners’ trust and decision-making in emergency evacuation. This work focused on measuring the differences between how participants respond to a simulated underground mine emergency evacuation situation when warnings are represented as coming from a human or AI-based monitoring system. We also manipulated the amount of information participants received about the system, yielding a 2×2 between-participants survey design. The participants received an alert message about rising gas levels in a mine and provided a response on how they would react and reported their perceived safety. We also asked questions to assess their trust in, preference for AI over human-based gas monitoring systems, and whether they are willing to delegate the duties of underground gas monitoring to AI systems. The experiment results show the amount of information had a significant influence on miners’ trust and decision-making. The safety perception of participants based on age, number of children and ethnicity was significantly different from one category to another. This work provides valuable insights as the mining industry deploys AI systems to aid mine safety.

Feb 1, 2025

By Monica Campos, Jose Mujica, Maria Campos

The extraction and processing of metals and other minerals have played an important role in economic, political, and social development worldwide, from the early stages of prehistory to the present day (Gosner, 2020). In other words, mining has been a fundamental part of human civilization, providing the raw materials necessary for technological, infrastructure, and industrial advances. As society progresses, the importance of mining continues to grow, supporting the development of everything from the smallest electronic devices to the tallest skyscrapers (The Importance Of Mining In Modern Society, 2024). The mining industry is closely linked to a country’s economy and activities related to natural resources. The economy of a nation is connected to its extractive industries (Moreira & McMahon, 2014), which have seen dramatic growth in recent years (Pietrobelli et al., 2018). In a context of increasing demand for natural resources, driven by the development of emerging technologies, the expansion of infrastructure, and the foundation of engineering achievements for the coming decades (Importance Of Mining - Minerals Education Coalition, 2024), mining should focus efforts on global development, requiring a comprehensive approach to sustainability that addresses the planet’s needs and protects the well-being, primarily, of the communities and environments where mining operations take place (Figari, 2024). In these areas, diversity and inclusion should be promoted, thus fostering equitable and sustainable development. Speaking of sustainable development, diversity, and inclusion brings us to an interesting topic: the Sustainable Development Goals (SDGs), also known as the Global Goals, which could serve as a key framework for fostering a strong social management culture in mining. The SDGs were adopted by the United Nations in 2015 as a universal call to end poverty, protect the planet, and ensure that all people enjoy peace and prosperity by 2030 (Sustainable Development Goals, n.d.). Companies have compelling reasons to align their actions with the SDGs, as their long-term success depends on healthy communities. This is a major challenge and requires collaborative efforts (Singh & Rahman, 2021). As Fraser (2021) mentions, achieving more sustainable outcomes may involve mining companies and communities working together collaboratively. This research proposes an innovative approach: Inclusive Mining for Sustainable Development, which aims not only to maximize economic profitability but also to promote social and environmental well-being by integrating the United Nations’ Sustainable Development Goals (SDGs), primarily focused on diversity and inclusion. This can be achieved through the implementation of a key value-added initiative for mining companies: the Creation and operation of a corporate volunteering program aimed at developing and executing inclusive practices to promote gender equality, the inclusion of local communities and indigenous peoples, and accessibility for people with disabilities. This proposal will educate employees and stakeholders about sustainability and promote concrete actions through corporate volunteering to strengthen the mining company’s commitment to community development, improve social relations, and advance toward achieving the United Nations’ Sustainable Development Goals, establishing the company as a global change agent.

Feb 1, 2025

By Duah Philip, Awuah-Offei Kwame

Regulatory pressure to mitigate the cement industry’s environmental impact has intensified recently, spurring innovation in low-carbon cement technologies. In the United States, cement production, consumption, and carbon emissions are accelerating. Despite this trend, the adoption of environmentally friendly dry clinker production technology with combined preheater-precalciner systems has surged from 53.3% in 2002 to 88.5% in 2019. Concurrently, reliance on wet technologies, known for their higher environmental impact, has dropped from 16.5% to 0.6% within the same period. This paper presents the results of our comprehensive study, utilizing over 100 years of industry data, to analyze these technological shifts and their environmental implications.

Feb 1, 2025

By Liming Yuan, Wei Tang, RICHARD THOMAS, DAVOOD BAHRAMI

The location and orientation of fire suppression nozzles is critical in suppressing mobile mine equipment fires. To effectively suppress such fires, optimization needs to be considered for the suppression nozzle locations and discharge angle. Detailed experiments were conducted to study the effectiveness of fire suppression agents with different nozzle configurations. A variety of fire suppression systems including dry chemical, wet chemical, dual agent (dry and wet chemical), carbon dioxide, and water mist were used. Six types of nozzle locations were studied, and their fire suppression effectiveness were compared. Results from this work highlight potential considerations when determining effective fire suppression designs.

Feb 1, 2025

By Sean Hunter

Artificial Intelligence has a long history but is currently coming strongly into focus with new advancements. This leads to questions many people are asking: what exactly is AI, how can it be used effectively in mining operations, and what foundation is required to make AI implementations successful? In mining, many AI applications exist, from drill pattern optimization to predictive maintenance. However, many implementations struggle due to data integration challenges. Mining operations generate large amounts of data from many sources, such as fleet management systems, drill sensors, process control systems, and laboratory results. Unfortunately, this data often exists in silos where it’s difficult to get it out, making AI applications unable to leverage it. Worse still, tools that use AI don’t always provide their data back to the system, creating even further data silos. All these problems make it hard to take advantage of the data at the mine, slowing down and reducing the effectiveness of AI. This paper presents a comprehensive approach to organizing mining data using an AI-ready knowledge graph system. We will first explore the evolution of AI in mining, from early expert systems to modern machine learning applications. Then, we will detail how a knowledge graph can integrate business context, operational data, and AI models into a cohesive system that enables more effective AI implementations across mining operations. The proposed method has been developed considering both the unique data challenges faced by the mining industry, while also considering best practices learned from the AI field at large. By following this approach, it’s possible to better utilize existing data, getting higher quality and more complete results faster, and in a way that’s reusable and composable.

Feb 1, 2025

By Hilal Soydan, H. Sebnem Düzgün, Jurgen Brune

In this study, with the primary goal of capturing ongoing digital transformation and automation impacts on the mining industry and its workforce, we conduct several interviews with mining industry experts in the United States and analyze our survey reports qualitatively and quantitatively through exploratory analysis. After the interpretation of the insights of industry experts, we proceed to generate a personalized and customized data analysis through a novel metric based on skills, knowledge, competencies and occupational requirements, which quantifies the job similarities for occupations in the mining industry based on the publicly available database of the U.S. Department of Labor. We use text analytics to tokenize and classify the interviews to capture a better understanding of major response categories. The temporal analysis shows that the critical competency needs in the data science and autonomy category increases from 28 percent in current demands to 43 percent. In defining our metric, we also calculate Kullback–Leibler (KL) divergence for each job profile that enables determining whether and to what extent that job is transitionary in our test set based on the mean, standard deviation and kurtosis of each job of interest. Our analysis reveals that the in-group job transitions are significantly easier than the between-group transitions, proving our initial assumptions and common sense. The generated heat maps provide the opportunity to present the gap between the current job and desired job profiles that provide feasible career change options, among others, offering individualized career paths for job seekers and promoting potential job transitions. Through the collection of industry-specific individual employee data, the AI system is envisaged to continue to learn as end users engage with the system, thus creating a central data hub specifically for the future workforce in the mining industry. Although the study has limitations on generalizability for qualitative assessments, it presents itself as a valuable application of how qualitative and quantitative approaches could be of value for future worker training in the mining sector.

Feb 1, 2025

By Amy McBrayer, Vladislav Kecojevic, Juan David Valencia Quiceno, Dragan Bogunovic

The mining industry’s commitment to innovation reflects a history of adopting technological advancements to enhance workplace safety, environmental sustainability and vocational training. The objective of this research was to develop an augmented- reality (AR) system for heavy-equipment operators (HEOs) in surface mining. The developed system has the potential to enhance mine safety, training and data-driven decision- making, which presents a significant step toward a more sustainable, effective and technologically driven mining training, contributing to the industry’s evolution and growth. The AR training system leverages Microsoft’s Power Platform and HoloLens 2 capacities to provide operators with detailed and immersive training guides for three mining equipment, including bulldozers, motor graders and haul trucks. AR guides combine speech controls, 3D objects, informative images and explicative videos in the real working conditions to enhance the operator’s learning process. The system has the potential to modify the training structure based on user performance and provides an efficient approach to data collection during training. This project was developed and applied through a case study in a surface mine in the Southern United States.

Feb 1, 2025

By Jeffrey W. Lin, Larry B. Weston, Jonathan D. Abbott, Jordan L. Arthur

Hydrocarbon fuel oils are one of the main components of ammonium nitrate-based explosives, including ANFO (Ammonium Nitrate-Fuel Oil) and emulsions. While a wide variety of fuels can, and have, been used in the manufacture of ANFO and emulsion products, No. 2 diesel, particularly dyed, off-road diesel, is widely used due to its ready availability and use in fueling mining equipment. However, a number of alternatives to standard diesel have been introduced over recent years, namely, biofuels, ‘high-performance’ diesels, and renewable diesels. The pressure to adopt these alternative fuels come from a variety of sources, such as initiatives to reduce carbon footprints, increased lifetime of equipment, and cost-advantages from tax credits. While these factors may provide a very real benefit to the mine site, a consideration that is often missed is how the use of these fuels can impact the formulation and characteristics of the ammonium nitrate-based explosives. Herein will be presented a discussion of these alternative fuels from a chemical perspective as well as the results of several studies focused on how the inclusion of various alternative diesels influences the production and performance of ammonium nitrate explosives. ANFO and emulsion were manufactured using representative fuel sources and studying in terms of the manufacturing parameters, shelf-life, interaction with other chemicals using in mining explosives. Detonation data was then collected for these products and compared to the behavior of products made with standard diesel fuels.

Jan 21, 2025

By Sam Taoum, Omar Riahi

Few tools allow for accurately tracking ore dilution after blasting. Existing methods often rely on data analysis or linear interpolation of velocity, which can be imprecise and less effective in varied geological settings. A promising alternative is the use of numerical simulations, which involve complex mathematical calculations incorporating real physical data about explosives and geological characteristics. These simulations can model blast-induced fragmentation and subsequent ore dilution with greater accuracy, providing detailed insights into blast dynamics by considering factors such as explosive type, blast pattern, and rock properties. Numerical simulations integrate data from sources like seismic sensors, blast monitoring equipment, and geological surveys, offering a holistic view that single-method approaches cannot match. By simulating different scenarios, mines can predict the outcomes of various blasting strategies, optimize blast designs to minimize ore dilution, and maximize recovery. Advanced numerical simulations enhance the prediction of fragmentation distribution and size post-blast, crucial for effective dilution control and maximizing ore recovery rates.

Jan 21, 2025

By Stephen Mansfield, Saran Sankar

The Sentinel open pit copper mine, operated by First Quantum Minerals Ltd, is located in the North West province of Zambia. The Sentinel orebody is a sediment-hosted, structurally modified deposit in which mineralisation is contained in the phyllite formation, which occurs as a series of layered, continuous sheets having a northerly 20 to 30⁰ dip. The persistent nature of the geological structure can lead to the generation of large slabs when joints are relatively close together or very large blocks when joints are more widely spaced. With standard blasting methodologies, the challenging fragmentation most commonly occurs in the stemming zone and blast interfaces, reducing excavation rates and increasing the risk of crusher bridging events and reduced throughput. A generalised approach to increase powder factor would increase in drill and blast costs and would not be sufficient to target the specific cause of the challenging fragmentation. Implementing differential blast energy based on post blast requirements for different material type, such as ore and waste, and rock mass characteristics is not new in the mining industry. High-energy blasts for ore aim to produce finer materials, enhancing downstream processes such as crushing and grinding, while reducing power consumption and increasing throughput. Conversely, waste rock often requires less energy in order to deliver optimised fragmentation for loading and hauling efficiency. Identifying and applying optimum blast energy to specific material type and geological domains will not only ensure smoother and efficient operations throughout downstream processes, but will have a direct impact on overall profitability of the entire operation. This paper will describe the methods used to model and implement differential blasting across a range of material types in order to deliver the required blast outcomes for ore and waste and the impact on downstream processes and drill and blast unit cost.

Jan 21, 2025

By Park Yun-Seok, Jung Seung-Won, Hwang Nam-Sun, Song Jin-hyuk, Kim Young-ho

This study proposes a new blasting vibration estimation formula that reflects the vibration reduction characteristics of electronic detonators, which are not considered in the current MOLIT blasting vibration estimation formula. Test blasts were conducted across six types of Korean open-pit blasting designs. The results of the test blasts showed that the K value for electronic detonators decreased by approximately 30% compared to electric detonators. Predicted Peak Particle Velocity (PPV) analysis indicated a reduction effect ranging from 30% to 31% across various types. By incorporating this reduction in the K value into the MOLIT blasting vibration estimation formula (K=200), a new electronic detonator blasting vibration estimation formula (K=140) was proposed. Using this new formula, the blasting damage range (R) was calculated under various vibration limits to evaluate constructability improvement. On average, the R value for electronic detonators decreased by about 17%, with significant reductions of around 41% observed for TYPE I under certain vibration limits. In conclusion, the adoption of electronic detonators in open-pit blasting operations improves blasting efficiency, reduces economic costs, and significantly enhances constructability. Electronic detonators have demonstrated superior performance in minimizing damage to safety facilities compared to traditional electric detonators, thereby proving their practicality and effectiveness in blasting operations.

Jan 21, 2025