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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 Brian Mangogna, Clay McNail, Weishi Mang, Adam Steimel

Together with innovatively applying modern flotation reagents and developing the breakthrough mill enterprise expert control and operating system, Doe Run Buick Mill constructed an advanced large copper rougher scavenger to process its complex Pb\Zn\Cu ore more efficiently. The scavenger circuit, featuring its own motor control center, air blower, multiple reagent loops and FrothSense+™ camera, operates both mechanically and chemically to maximize copper recovery and under expert control. Such scavenger features can be applied to zinc rougher circuits for all Doe Run mills to maximize Cu recovery during Cu special runs when the zinc rougher becomes a copper rougher scavenger.

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 William G. Pariseau

Solvay Chemicals Company mines trona in south-central Wyoming and has done so for many years. The mine is one of several in a mid-continent sedimentary basin that hosts the largest trona resource in the world. Trona is an evaporite, a sesquicarbonate that occurs in several seams of varying thicknesses and depths. Trona is processed into soda ash which has a number of industrial uses in the manufacture of glass, detergent, paper and chemicals. Figure 1 shows the location of the Solvay Mine. A ventilation shaft was recently excavated at Solvay Chemical Company’s mine in the trona patch. In fact, a 22 ft (6.7 m) diameter shaft (inside diameter) was bored upwards from the 1500 ft (457 m) level to the surface. The first bored section was 26 ft (7.9 m) in diameter that allowed for a 2 ft (0.6 m) thick concrete liner. This section began at a depth of approximately 1500 ft (457 m). A second bored section was 24 ft, (7.3 m) in diameter that allowed for a 1 ft (0.3 m) thick concrete liner. This section began at a depth of approximately 750 ft (229 m). This shaft is the #5 Shaft. Figure 2 shows the cutter head used to excavate the shaft.

Feb 1, 2025

By Jed Greenwood, Lyall Workman, Michael Haggerty, Russell Sheets

Draglines often work from a position on the active highwall or spoil side bench to remove undisturbed waste material and spoil in the previously mined pit. To protect the dragline crew members and the machine, it is necessary that the highwall remain stable while the dragline is present on the bench. In the past several years, we have been involved in determining the causes for highwall failures that included the dragline. While there have been no injuries and limited dragline damage with these incidents, the potential certainly exists for a more serious outcome. In all cases, the operation had completed a geotechnical study to support the ground control plan and pit designs. However, all these incidents included aspects that would not likely have been identified in studies to determine highwall and spoil designs to support ground control procedures. In general, these events included aspects that were localized and would have been difficult to identify in initial slope stability studies either observationally or during the soil testing and modelling efforts. Although the authors do not have quantitative evidence of this, it does seem there has been an increased number of events in recent years. This may be due to loss of institutional knowledge, mining in more challenging areas, or simply an increase in localized variation. This paper will describe some of the issues we have seen and what the causes of failure were. It becomes clear that avoiding similar incidents in the future requires on-going observation and inspection of active highwalls and spoil benches to try and identify local variability and impact on mining. The information can proactively be used to update stability modeling of any concerning issues to determine likelihood of problems and to develop solutions.

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 Boyd Eisenbraun, Dennis Murr, Milton Rojas

Approximately since 1925, the phenomena of grinding and classification of minerals with screens have been studied. In the U.S. iron ore mining operations located in the so-called “Mesabi Iron range,” magnetite processing plants have made progress in the application of high-frequency screens that have allowed them to process low-grade Taconite ores and successfully achieve the economic benefit of these minerals. In the particular case of magnetite minerals disseminated in the siliceous matrix, the main objective is to reduce the generation of particles called “middlings” with high silica contents. Commonly the primary challenge of the metallurgical task is to achieve high recoveries and iron concentrates with low impurities. To achieve this, several studies and industrial applications have shown success in this regard and not only in iron ores, but also in other minerals around the world. The study described in this paper attempts to describe some key aspects that helped develop an effective solution and list the benefits associated with this modern process design by using industry-proven technologies for minerals in Chile that have similar characteristics to the minerals of the iron belt in the United States.

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 Claudia Castillo, Katja Freitag, Jan Cilliers, Diana Drinkwater, Robert Seitz

The talent gap in mining is not a new challenge. Mining companies continue to seek innovative ways to attract, develop and retain talent, and younger workers are looking for opportunities to develop their professional careers. Training provides a key value proposition for both employees and employers as it helps build a talent pipeline while offering opportunities for learning and growth and value creation. In 2020, Metcelerate launched its 20-month program for early career mineral processing engineers. The program helps develop critical technical skills in the workplace and is a tool to identify motivated engineers and change culture within teams. Learners cap their skills development by executing a technical investigation. This generates immediate value—a win-win outcome for learner and company.

Feb 1, 2025

By Paul Culvenor, Brad Gyngell

Large language models (LLMs) have generated a lot of hype since ChatGPT was released in early 2023. In essence, they allow people to interact with computer systems through natural language and have the ability to generate highly complex text, images and videos (Patil and Gudivada, 2024). It is clear that this technology has significant potential, however most mining companies have not yet found practical applications for it within their operations. In this paper, we present a range of such applications along with the tactical considerations associated with developing and implementing them. We have identified use cases across a variety of operational and functional areas within the mining industry and evaluated them based on their potential business value and ease of implementation. Firstly, we provide an overview of how LLMs work and a review of how LLMs are being applied in other industries to provide best practice inspiration for mining. Next, we present a list of possible applications in mining and a critical assessment of each use case. This section also includes a technical deep dive into the different methodologies for developing the technologies as well as an analysis of barriers to adoption within mining organizations. Finally, we share a discussion of the potential path forward for LLMs in mining and the impact they could have on the industry. We analyze the potential differences between early adopters and laggards in the artificial intelligence (AI) space. This research draws on interviews and surveys with artificial intelligence experts as well as mining subject matter experts to connect cutting edge thought leadership with the specific problems faced by our industry.

Feb 1, 2025

By Wei Zhang, Jinhong Zhang

An atomic force microscopy (AFM) image analysis has been applied to study in situ the adsorption of hydroxamic acid collector, i.e., octanohydroxamic acid (OHA), on malachite in aqueous solutions. AFM images show that hydroxamic acid collector adsorbs strongly on malachite mainly in the form of insoluble copper hydroxamate complex. Increasing the collectors’ concentration and the adsorption time both increase the adsorption of hydroxamic collectors on malachite. Results from the attenuated total reflectance–Fourier transform infrared spectrometry (ATR-FTIR) also show that the collector adsorbs strongly onto malachite, with strong absorbance spectra being detected, and the ATR-FTIR results confirm those as obtained by AFM. This specific adsorption mechanism explains that a high selectivity with a moderate collectivity will be achieved with a hydroxamic acid collector for the flotation of malachite. The findings of present study also show that AFM image analysis is a powerful tool for the study of the hydroxamic acid collectors’ adsorption on malachite surface and it can help with the development of novel collectors for malachite flotation.

Feb 1, 2025

By Kadri Dagdelen, Steven Hoerger

For gold mines, orebody uncertainty is one of the leading causes of differences between planned and actual production. Geostatistical conditional simulations create multiple equally probable orebody block model realizations which are conditional to the current drilling information and demonstrate the sampled grade distributions and spatial statistics. These simulated block models are key inputs for a stochastic evaluation to show the likely range of grades and cash flows to be delivered by a mine plan. The stochastic evaluation outputs can be used to compare different mine plans in terms of expected values and risks to planned grades, production, costs, Net Present Value (NPV) and other plan metrics. For the McLaughlin gold mine, risk profiles are demonstrated to show how different mine, cut-off and stockpile strategies can reduce risk and improve expected value. The strategies considered were effective in improving expected NPV and reducing or eliminating tonnage uncertainty, but the strategies had little impact on reducing the uncertainty of NPV’s or mill grades. The stochastic evaluation process is also used to compare the risk impact of orebody uncertainty against the risk of not achieving planned mining tonnages or vertical advance rates. Risks for plans created with and without stochastic mine plan optimization are also compared.

Feb 1, 2025