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By CIM Mineral Resource, Mineral Reserve Committee

Industrial minerals are generally considered to include non-metallic minerals, mineral products, or materials that provide raw material inputs for the construction, chemical, and manufacturing industries. They are often relatively low-value and bulky materials that are generally used close to where they are produced; however, some raw materials may be transported hundreds of kilometres to manufacturers and customers (ENDM, 2021). They do not include the metallic minerals, mineral fuels, or gemstones, and are used in industries based on their physical and/or chemical properties (Wikipedia, 2021). In contrast to most metallic minerals, a general distinguishing characteristic of the industrial minerals sector is their general low degree of market elasticity in relation to the market prices and product specifications. The estimation of either a Mineral Resource or a Mineral Reserve (MRMR) for an industrial minerals deposit can be affected to a significant degree by a number of factors that are not typically applicable to metallic mineral deposits. These factors can include such considerations as the particular physical and chemical characteristics of the final product, product quality issues, market size and market access. In some cases, such information may be confidential and proprietary. One of the key challenges of the industrial minerals sector is to define a commonly accepted listing of which types of minerals, materials, or mineral deposits can be considered as industrial minerals (Mining Standards Task Force, 1999). Although definitions for what constitutes an industrial mineral can vary in detail, general descriptions can be found in American Geosciences Institute (2021), Fastmarkets IM (2021), Snowden (2019), SME (2021) and Wikipedia (2021). A brief listing of some of the materials and minerals that are generally considered to be industrial minerals is provided in Table 1. For the purposes of this document, all references to industrial minerals include not only the minerals, materials, and mineral deposits themselves, but also the various commercial products that are derived from these sources.

Nov 19, 2023

By Nilufer Kursunoglu

Despite being crucial for meeting the world’s energy demands, coal mining operations present considerable health risks, especially when it comes to exposure to coal dust. Longwall coal mining, an advanced technique, has considerably enhanced production but made dust control more difficult. Due to its explosive nature, coal dust continues to be a serious and dangerous concern in the industry despite developments in safety technology. This study aims to comprehensively assess the risk of coal dust explosions by integrating fuzzy risk matrix and Pareto analysis methodologies, offering precise risk ratings for various root causes. A fuzzy risk matrix was developed to assign exact risk ratings to identified root causes. Additionally, a Pareto chart was used to identify the main reasons and suggest particular preventive measures. 17 significant causes were determined for underground coal mines based on the study’s methodology, and some preventive measures were suggested. In accordance with fuzzy risk rating values, root causes were divided into six categories. The root hazard with the highest risk rating was identified as ‘accumulation of inflammable gas/gases’. The proposed approach was used to examine incidents caused by coal dust explosions in Turkish coal mines in order to demonstrate the effectiveness of combining the fuzzy risk matrix and Pareto analysis for assessing coal dust explosions. This study gives not only a solid framework for risk assessment but also critical information for classifying the risks associated with coal mine dust explosions. The results highlight the critical necessity for proactive and preventive actions to reduce the hazards of coal dust explosions and protect the safety of mining workers.

Nov 16, 2023

By Fengyu Ren, Kunpeng Yu, Gideon Chitomb, Qiangqiang Gao, Liqiang Ma, Jiangtao Zhai, Ichhuy Ngo

The penetration of rock fragments of overlying strata causes advanced ore dilution during drawing. The results of numerical and physical experiments showed that the proposed numerical simulation was applicable and the microscopic parameters of the model were reliable. The penetration under the variables of particle diameter ratio, density ratio, overlying strata thickness, and particle morphology was clarified. The penetration was quantitatively characterized by the discharge amount and the dilution rate. The experimental results showed that the diameter ratio and density ratio had a significant influence on the penetration. On the irregular shape of particles, the penetration is weakened. The overlying strata thickness had little effect on the penetration. This study could provide a theoretical basis for the full section uniform drawing, avoiding advanced ore dilution and further optimization of recovery rate.

Nov 13, 2023

By Turker Hudaverdi, Yasar Agan

This study tries to predict blast-induced flyrock using intelligent modelling techniques. Flyrock is a site-specific phenomenon. Design variables and rock properties highly influence flyrock throw distance. Site investigations were conducted in a sandstone quarry. Fundamental operational parameters, blast dimensions, bench face condition, and rock mass structure were monitored. Stepwise regression technique was applied for variable selection. Burden–hole diameter ratio, in situ block size, and powder factor were determined as the most significant parameters. Considering output of stepwise regression, artificial neural network, ANFIS, and Gaussian process regression techniques were applied to predict flyrock throw. A comprehensive validation was performed using twelve different performance indices. Pre-determination of input parameters supported development of successful soft computing applications. Rock block size was found to be an appropriate input variable for flyrock modelling. In addition to classical performance indices, standardized and symmetric accuracy metrics were quite useful in model validation process. The intelligent models predict flyrock range with an error less than 6 m. The mean percentage errors are lower than 10%. ANFIS seems to be the best model for flyrock prediction. The calculated mean absolute error is 5.36 for ANFIS model.

Nov 12, 2023

By Arman Hazrathosseini, Ali Moradi Afrapoli

Fleet management systems (FMSs) as the pivotal part of any surface mining operation find it essential to evolve from conventional into intelligent systems because of both Mining 4.0 requirements and some shortcomings inherent in conventional methods. However, this novel transformation needs to be investigated technically and strategically. To this end, the previously published research works on intelligent FMSs are explored to track the latest status of these third generation frameworks within the surface mining context. Following that, their underlying models are compared in terms of five categories of allocation and dispatching features to pinpoint the technical gaps ignored. Having drawn the future lines of research, the present article then leverages the popular SWOT analysis method to outline the strengths, weaknesses, opportunities, and threats associated with the advent of these intelligent FMSs in mines of future. By and large, the analysis indicates that advantages outweigh disadvantages. Solutions are offered to address the existing weaknesses and threats.

Nov 10, 2023

By Dairo E. Chaverra, Carlos Argumedo‑Jimenez, Oscar J. Restrepo‑Baena

This paper presents the results obtained by processing a gold and silver telluride mineral concentrate from a mine in Colombia. An acid wash, also known as acidification, was carried out, followed by oxidation with nitric acid as a pretreatment. Cyanidations of the pretreatment residues were carried out and the results were compared with results from cyanidations of base materials. The removal of carbonates in the acidification, a tellurium extraction close to 90% during the pretreatment, and a 30% improvement in the gold recovery compared to the conventional process were achieved.

Nov 8, 2023

By D. O’Connor, A. Pytlik, D. J. Corbett

The resistance of yielding rockbolts to multiple impact loads was tested by means of a drop hammer. The methodology was based on the ASTM D7401-08 standard as well as the requirements specified for rockbolts by Luossavaara-Kiirunavaara Aktiebolag (LKAB – a Swedish mining company) and the Safety In Mines Research Advisory Committee of South Africa (project number GAP 423). During the tests, the loading force and bolt elongation were measured with a sampling frequency of fs = 19.2 kHz. In order to analyse the phenomena involved, the tests were recorded using two independent high-speed video cameras (600 and 1000 frames per second) and one thermal camera (128 frames per second). The tests demonstrated that all the samples transferred double the gravitational potential energy of Ep = 50.85 kJ from the impact load of mass m = 2825 kg and impact velocity of v = 6.0 m/s without failure. Damage to the bolt-resin contact in the upper anchoring zone of the bolt in the steel tube occurred after subsequent impacts. As a result, the macro-deformed bolt exhibits additional yield, and its operation following the shearing of the resin bond is similar to that of a ‘cone bolt’. Only one test resulted in damage to the threaded bolt rod-nut coupling, during the fourth impact; however, no damage to the bolt-resin contact zone was observed.

Nov 6, 2023

By M. Z. Emad, S. Raza, K. Jalil, M. A. Raza, M. U. Khan, S. A. Saki

Dimension stone mining is Increasing because of growing demand from the building and construction industries. Diamond wire saw cutting is a popular dimension stone mining technique around the world. Estimation of the production cost for this method is critical for these operations. n this research a production cost model was developed for the mining of granite using a diamond wire saw. Cost and production data were collected from a granitic dolerite operation in Pakistan for a 4.5-year period, and analysed to identify the cost components. Fuel (34%), labour (15%), consumables (40%), and maintenance (5%) were found to be the four major cost components in this operation. A regression-based dimension stone production cost model incorporating statistically significant variables was developed. The data presented a strong correlation of production cost with fuel, labour, and consumables costs. Finally, a production cost model based on the consumption cost of diamond wire is presented. The model was verified using actual production cost data, which indicated 95% (R2 = 0.95) variance in the data between the predicted and actual production cost values. The model may help field engineers in computing their dimension stone operational cost during the cutting phase.

Nov 6, 2023

By N. Mashaba, D. Botha

The aims of this study were to investigate the factors that influence women’s engagement in technical positions in the South African mining sector and to determine what could be done to promote their successful participation. A convergent parallel mixed-methods research design was used to ascertain the factors that facilitate, inhibit, and influence engagement. In the quantitative phase of the study, questionnaires were circulated to women employeees; and in the qualitative phase, semistructured interviews were conducted with employer representatives, most of whom were human resource personnel. Confirmatory factor analysis showed that the three-factor structure (vigour, dedication, and absorption) of the Utrecht Work Engagement Scale fit the sample data reasonably well. Although there is room for improvement, respondents demonstrated acceptable levels of engagement in their work. On the other hand, the qualitative findings showed that employee engagement is impacted by unfavourable working conditions, work–life balance, and the mining industry’s male-dominated work culture. The findings showed that employee engagement should be elevated to a core human resource function. To increase the participation of women in mining, human resource professionals are encouraged to collaborate with mine supervisors, managers, and employees to develop programmes that promote employees’ absorption in and dedication to their work.

Nov 6, 2023

By G. M. Wali Ullah, MEHMET KIZIL, ` Micah Nehring, PETER KNIGHTS

In operations that use the sublevel stoping mining method, production scheduling takes into account factors, including ore reserve envelopes, ore grade averages, equipment capacity, feed controls to the mill, and geotechnical restrictions, across the scheduling horizon. Mathematical programming is one of the most effective methods for enhancing the decision-making process in regard to the most viable production schedule in light of a given set of limitations. The majority of research on sublevel stope mining focuses primarily on a single objective of optimisation, which is to maximise the net present value (NPV). Environmental, social, and governance (ESG) considerations are becoming more prevalent in the mining industry. This includes aspects relating to deforestation, land disturbances, gas emissions, community relations, and water usage, among many others. Institutional and other kinds of investors are becoming more interested in the work that resource companies do regarding their ESG obligations. This review article identifies the gap in the existing literature and proposes to simultaneously optimise the production schedule around three objectives. Two of these relate directly to ESG aspects.

Nov 6, 2023

By Andrew Stafford, Kate Willa Brown Requist, Eric Lutz, Simon Lotero Lopez, Moe Momayez, Jeffrey Gordon

This formal literature review identifies strengths and shortcomings of current literature related to mine rescue, self-rescue, and self-escape technology. Key concepts and factors that influence the decision making behind mine rescue and self-escape were identified. Historically, underground mining has been one of the most dangerous occupations due to the harsh nature of working environments. During the latter half of the twentieth century, and into the twenty-first century, mining fatalities have declined, yet large-scale mine emergencies persist. The emergence of new technologies, in combination with evidencebased mine emergency research, is resulting in new training methods, monitoring systems, and self-escape approaches being tried in operating mines. This review identifies areas in which substantial research is being conducted, such as the use of virtual reality and game-based training and areas that warrant further development such as the measurement and information gathering capabilities of unmanned ground and aerial vehicles, as well as emergency management and incident command systems. This paper summarizes the current underground mine rescue and self-escape landscape in the USA, including the breadth and depth of mine rescue and self-escape training and practices as evident in the literature.

Nov 2, 2023

By Ross Cutts

As a public servant geotechnical engineer, I observed how costly and valuable geotechnical field explorations are to the success of every project. Often however, the field exploration is a long and complex process that is made less efficient by the difficulty of retrieving and utilizing nearby internal or external historic geotechnical datasets. As an employee of a public agency, we would often start our investigations for every project from scratch, given the difficulty of locating and utilizing historic geotechnical data. This is an ethical and technical failing of our profession. When we start subsurface explorations from scratch, not only do we often duplicate investigations, we are also likely defaulting to reapplying tradi- tional test methods that yield con- servative geotechnical parameters, resulting in overly conservative and potentially costly construction. To address this issue while working as a public servant, I started a research program with Yunfeng Zhang, Ph.D., of the University of Maryland, to build a tool that could compile internal historic geotechnical data and extract additional value from it, using machine learning. This tool was able to provide, upon request, nearby historic geotechnical data, estimated soil parameters and recommendations for geotechnical test methods best suited for a given project site. This prevented common field ex- ploration problems such as, requesting duplicate data, requesting test methods that were not applicable for the project geology, not realizing presence of karsts, missing permits for wetlands, private property and others. This tool allowed for more efficient field investigations with regards to time and money saved. There was one problem with this tool: it could only be used by internal employees of a single state's depart- ment of transportation (DOT) for which this data was compiled. I realized at that point that it would be of tremendous value to make this concept universally accessible to the geotechnical engi- neering profession. I left public service to devote time to building a platform that would host historic geotechnical data from publicly funded sources throughout the country. The tool I helped build as a public servant was the foundation of Geosetta, a nonprofit company dedicated to serving the geotechnical profession. The nonprofit structure was adopted to prevent acquisition by a for-profit company and to ensure that Geosetta remains an independent steward of our profession's valuable data. Geosetta provides a GIS (geographic information system) platform that enables users to view historic geo- technical data and extract value from it with machine learning-based predictions and visualization tools. This data is provided in an open and interchangeable format called DIGGS, which stands for Data Interchange for Geotechnical and Geoenvironmental Specialists, making it easy for users to integrate it into their workflows. Geosetta is collaborating with the American Society of Civil Engineers' Geo-Institute and other sponsors to extract public data at no cost to the agency and provide the profession with free access to the existing data and access to advanced tools through a subscription to support the nonprofit mission.

Nov 1, 2023

By A. Yadav, B. Behera, G. S. P. Singh

The size of chain pillars in the Indian geo-mining conditions is primarily decided in accordance with the regulatory provisions. These provisions are of little help for deep longwall workings, exceeding the cover depth of 360 m. Furthermore, these provisions are primarily meant to support pillars in bord and pillar workings. They may not be suitable for the chain pillars owing to a significant difference in layouts and functional requirements. Hence, it is imperative to develop a method to evaluate the stability of the chain pillar considering the complex loading and geo-mining conditions. To this end, a machine learning-based model was developed in this study to assess the stability of the chain pillars under high depth of cover considering the field-representative conditions. The data for this work was generated by conducting a parametric study using a field-validated numerical model. The strength and deformability parameters of the caved, fractured, and continuous deformation zones were established by calibrating the numerical model outcomes against the site-specific field observations. The developed ML model was used to evaluate the influence of pillar width, pillar height, cover depth, abutment angle, face length, coal strength, moduli ratio of the roof and floor strata to the coal seam, and the elastic modulus and unit weight of the overburden on the chain pillar stability. An interesting finding of this study showed that the factor of safety of the chain pillar increased with the increasing abutment angle, which may be indicative of the confining effect of the abutment angle on the pillar. Eventually, the ML model was verified by comparing its outcomes with the calibrated numerical model for a typical longwall working from Indian geo-mining conditions.

Oct 18, 2023

By Brendan Donnelly, Lasitha Piyathilaka, Jung‑Hoon Sul, Sanghyun Jeong, Benjamin Probyn

Premature failure of armoured face conveyor (AFC) chains due to corrosion is a significant proportion of the unplanned downtime experienced on longwall equipment. The AFC chains are constantly in contact with water and wet coal. The premature failure issue of AFC chains has become more prominent since the introduction of longwall top-coal caving with its additional AFC. Reverse osmosis (RO) is a popular water treatment method for reducing salinity and dissolved solids, but its impact on the corrosion of the AFC chains is unclear. This study has been commissioned to investigate the direct effects of RO water on the corrosion of AFC chains. An immersion test was carried out using AFC chain steel submerged in two water samples: untreated dam water and treated water from an RO treatment plant. Elemental analysis was conducted for both water samples, and four corrosion indices were measured for both water samples. The RO water more vigorously dissolves calcium carbonate scales leading to increased corrosion of the AFC chains although the dam water has much higher levels of calcium, chloride, sulphate, sodium, and magnesium. Bicarbonate ions are the main alkaline factor of water that provides the buffering capacity to acids. Decreased alkalinity without balancing other ions in water causes high corrosivity and decreased scaling tendencies.

Oct 16, 2023

By M. Frenzel, D. Ebert, K. Bachmann, A. D. Renno, R. Möckel, J. Gutzmer, J. Krause

With the increasing demand for metalliferous and mineral raw materials and the consequent depletion of the global natural resource base, the possible utilization of secondary raw material sources is receiving more and more attention. In the present study, we present results from a detailed vanadium deportment study of three basic oxygen furnace slag (BOS) samples known to containing elevated bulk concentrations of vanadium. Complementary analytical methods that were used to quantify the abundance and composition of V-containing phases include SEM-based automated mineralogy, X-ray fluorescence analysis, and X-ray powder diffraction as well as electron probe microanalysis. The vanadium deportment was quantified using Monte-Carlo simulations of the data obtained from automated mineralogy and electron microprobe analysis. The total V concentrations identified by XRF are between 1.7 and 2.2 wt.% V. The most important hosts of vanadium are larnite-, brownmillerite- and portlandite-solid solutions. In two samples Ca carbonates also significantly contribute to the V deportment, while wuestite, lime, and native iron do not contribute significantly to the vanadium deportment. A thorough consistency check identifies considerable uncertainties in the density of the V-bearing phases as the most likely reason to explain remaining discrepancies between measured and calculated V values.

Oct 14, 2023

By Robert Kimutis, Heather Dougherty, Eric Watkins

Gas wells have often intersected mining resources, but unconventional shale well drilling has more recently challenged mines to balance the risk of interaction due to higher pressures and larger quantities of gas. Full extraction mining, such as the longwall method, induces ground movement that may influence the casings if wells are drilled within the mining area. The possibility of a casing shear would lead to the risk of unplanned gas migration into the mine. This has the potential to quickly overcome the ventilation system and reach the explosive range which, if ignited, can have catastrophic consequences on the health and safety of underground workers. The utilization of network software to model mine ventilation is a common practice in the mining industry as a predictive tool for planning and monitoring and can assist with a well breach scenario over a large mining area. This work focuses on a well breach in between two longwall panels after second panel mining with gas entering primarily through the gobs of the adjacent longwall panels. Applying the network software Ventsim, a gob zone and ventilation network were created to better understand the distribution of gas within the mine and the limitations and effectiveness of a ventilation system. The model shows both a transient flow simulation and steady state concentrations throughout the mine ventilation system. Using a standard Pittsburgh coal seam longwall ventilation scheme, we find that the system can dilute a significant inflow of up to 700 cfm of methane.

Oct 12, 2023

By A. K. Raji, M. O. Ojumu

Robotic subsea dredging crawlers are dynamically and remotely controlled vehicles that are used for deep sea mining and recovery operations. These exploration machines are released from a mother ship and move around on the ocean floor using tracks. Current ocean crawlers such as the MK3 ROST are hydraulically powered. In this paper we develop a scaled-down model for simulating and performing static loading analysis of an electrically powered robotic subsea dredging crawler (EPRSDC). The modeling, simulation, and analysis were carried out using modelling software from Solidworks. The structural frame was assembled using the Tetrix max robotics kit. The kit’s structural components were produced from 1050 aircraft-grade aluminum. The results were used in optimizing and for considering other materials, and the to identify specific areas to be reinforced in future crawler designs.

Oct 3, 2023

By A. F. van der Merwe, R-D. Taylor, M. Jacobs, F. H. Conradie

Total bound moisture (TBM) is a typical quality indicator of industrial-grade gypsum. This gypsum is comprised of three distinct phases, namely anhydrite, dihydrate, and hemihydrate, of which only the latter is of much industrial use. TBM analysis is a lengthy laboratory procedure, and an artificial neural network (ANN) TBM inference measurement is proposed as a fast and online alternative. An ANN inference model for gypsum TBM based on plant data was developed. The inputs to the network were primarily focused on the plant's calciner, and different network topologies, data divisions, and transfer functions were investigated. Furthermore, the applicability of the TBM value as a quality indicator was investigated based on a gypsum phase analysis. A strong correlation between TBM and the gypsum hemihydrate and anhydrite content was found, validating the plant target TBM of 5.8% as a quality indicator. A network topology consisting of one hidden layer with logarithmic-sigmoid (logsig) and pure linear (purelin) transfer functions showed the best performance (R > 90%).

Oct 3, 2023

By Ehab Gomaa, K. A. El‑Nagdy

Backfilling material such as tailing (mine wastes) mixing with cement or gypsum has grown throughout the world’s underground mines. However, despite their growing popularity, the typical hydraulic and mechanical fill types utilized in many mines still exist. Deep underground mining has increased due to the lack of commercial minerals nearby. Mine wastes were considered the main part of backfilling to prevent environmental pollution, ground subsidence after mine abandonment, and mine collapse during deeper extraction phases. The cemented backfill technique is the principal technique used in underground mines, which include cement with fly ash and/or filter dust, cement with tailing material and fly ash, gypsum with fly ash, and synthetic anhydrite with fly ash and have been reviewed. It has concluded that a backfilling material must be selected based on further goals, available material near the mine site, and economic factors. This paper analyzes different backfill material mixtures to create a technique that will increase safety in underground mining conditions and foresees an appropriate formula that gives high uniaxial compressive strength. The multiple linear regression (MLR) on the collected data from the experimental works to construct the relationship between the uniaxial compressive strength (UCS) of the mixture and the components of the backfilling and the prediction formula for expected compressive strength was obtained. The results revealed that the predicted regression equation was robust and reliable to predict the (UCS) for the new components of the filling (cement (CE), filter dust (FD), water content (WC), and time (T)).

Oct 3, 2023

By Manoj Kumar, Anil Kumar Singh, Prabal Patra, Ashish Agrawal, Souvik Ghosh, Subhashis Kundu, Kamma Ramakrishna Rao, Manish Kumar Gupta, Anindya Sarkar

The slag measurement systems in the cast house are very important. In the conventional method, the slag is granulated in a slag granulation system, and the slag flow rate is measured by the associated belt scale. However, in places where a slag granulation system is not available, the alternate approach is to deduce a theoretical calculation and develop the measurement because the commissioning of such slag granulation requires huge capital and has inherent geographical limitation. However, the theoretical approach suffers from several drifts and is far from the reality. In the present paper, we have innovatively engineered a sensor by designing the stellite-coated thermocouple that can measure the temperature of the slurry and placed it in such a way that the abrasive slag granules do not obstruct it, but we could measure the temperature of hot water, and further based on the thermodynamic approach, the slag flow rate is determined that can be compared with the theoretical approach. This approach of slag rate measurement is cost-effective and long-lasting.

Oct 2, 2023