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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 Jodie Robertson, Isabel Barton, Cristian Caro

Prior to mining, all rocks contained in a mineral deposit must be placed in one of several categories known as ore types. Each ore type describes a different way that the rock will behave in processing. The ore type determines which process stream a particular mined unit will be sent to, sets expectations for process engineers and metallurgists, and forms the basis for recovery predictions and production estimates. At first, ore types are assigned mainly by geologists based on visible geological criteria (dominant ore mineralogy, estimated grade, rock type, alteration type). As metallurgical tests are carried out and process data accumulate, the resulting criteria may be factored into the ore typing process, typically as assays and recoverable metal using the relevant process(es). Other variables may also be incorporated into ore typing at operations if they are particularly important, such as grindability, preg-robbing, gangue reagent consumption, and the presence of especially deleterious minerals such as talc or smectite. The mine operation department may also redefine ore types and/or process destinations based on economic criteria. A “best” ore type is designated that (in theory) best describes how the rock will behave in processing. Codes representing this ore type are entered into the drill hole database, then interpreted on cross sections and level plans, and finally added to the block model. Ore types are iteratively reexamined and adjusted over the life of a project. Major difficulties in effective ore typing are (1) lack of communication between geologists and metallurgists, (2) the imprecision inherent in imposing clean categories on messy natural systems without discrete divisions, (3) the need for ore types to provide useful information for a wide range of processes, (4) difficulties in scaling up laboratory test results to mine production, and (5) conflict among geological, metallurgical, and economic criteria for ore typing.

Nov 8, 2023

By V. A. Leão, V. S. Coimbra, V. A. A. Oliveira, R. F. M. de Souza, G. M. de Lima

A willemite concentrate consisting mainly of willemite (55.3%) and dolomite (15.6%) was reduced in a tube furnace with charcoal as reductant. The effects of temperature and varying reductant additions on zinc extraction were studied. A zinc recovery of 86% was achieved with 20% reductant in the charge at 1100°C. During reduction, the calcium oxide generated through calcination of the dolomite promoted decomposition of the willemite, thus lowering the temperature at which reduction took place. The presence of CaO improved the zinc recovery at all temperatures studied. The best zinc recovery (93%) was obtained in the presence of 5% CaO, 20% charcoal reductant, and at a temperature of 1100°C. The results show that the willemite concentrate studied has great potential to be used as a raw material for the Waelz process.

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 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 Ronald C. W. Webber‑Youngman, Philani Larrance Ngwenyama

Entrapments are a huge risk in underground mines. This happens when miners (or any other persons who have entered underground) survive the initial event of an accident, become trapped or lost in unknown and life-threatening locations after evacuation, and remain unaccounted for. At this point, every second counts, and emergency response is highly desired for any chances of saving survivors. The survival chances of the missing persons depend on how quickly they can be located. Rescue teams are often deployed to search for the missing persons underground. However, the rescue teams are forced to search in random and presumed areas of the mine. This is due to the unavailability of information pertaining to the whereabouts of the missing persons. Not only the provision of accurate locations, but various other types of information such as post-accident two-way communication can enhance the survival chances of the missing persons. This information can be provided by a fit-for-purpose missing person locator system. A wide variety of missing person locator systems are already commercially available, some are in testing phases and others in prototype and development phases. This includes tracking, tracing, location detectors and post-accident two-way communication systems. These systems have unique functionalities, capabilities and limitations; making it difficult for mines to select the most effective, applicable and suitable system specific to their mine. In this study, the user requirements for a fit-for-purpose missing person locator system were developed. The purpose of the user requirements was to provide a guideline to facilitate the system selection process. The user requirements can also be used as a tool to measure and evaluate the performance of the selected missing person locator system. The user requirements were also used to predict the success of the selected system under different missing person incident scenarios. The development of the user requirements showed a potential for many other benefits for missing person locator systems.

Nov 2, 2023

By Mustafa Fener, Masoud Rostami, Sair Kahraman, Behnaz Dibavar

The paper introduces a new rock mass cuttability classification (RMCC) system for roadheaders used in coal mines. It includes performance prediction models for both axial and transverse roadheaders, based on six parameters: uniaxial compressive strength, Cerchar abrasivity index, volumetric joint count, strike and dip of joints, joint aperture, and groundwater condition. The study validates the RMCC system through field and laboratory measurements, showing high correlation coefficients between net cutting rates and RMCC indices.

Nov 1, 2023

By A. Dell’Era, E. Ciro, C. Lupi

The paper explores the recovery of indium via electrowinning from sulfate baths, focusing on the impact of different cathodic supports (AISI 316L and nickel) on process parameters such as electrolyte composition, current density, and temperature. The study compares productivity, morphology, and structure of indium deposits on both cathodes, finding that nickel cathodes generally yield better results.

Nov 1, 2023

By Turan Uysal, Ramazan Aydogmus, MURAT ERDEMOGLU

The paper investigates the effects of calcination for thermal activation and intensive milling for mechanical activation on aluminum recovery by acid leaching of pyrophyllite ore enriched via attrition scrubbing and froth flotation. The study compares these methods in terms of energy consumption and aluminum recovery, concluding that mechanical activation is more economical and environmentally friendly.

Nov 1, 2023

By Anne Lemnitzer

Experimental data are the cornerstone of scientific research, providing empirical evidence to validate hypotheses, test theories, inform decision-making and help develop innovative design and analysis methods. However, beyond traditional empirical validations, experimental data have also become the most crucial component of AI algorithms, measuring the algorithms' effectiveness, and allowing engineers to ensure their reliability and applicability. The DFI "Rock Socket Project," awarded in the spring of 2018 allowed for the indispensable, experimental data-based validation of structural shear magnitudes, which have been hypothesized and discussed for years within the deep foundations community and cautiously approached by many design engineers. The fundamental project idea, i.e., the investi- gation of pile shear magnitudes through experimental research, was sparked during a heated discussion in the October 2016 Drilled Shaft Committee meeting in New York. Should we design for amplified shear at the rock socket of a drilled shaft or is this merely an artifact of the p-y design approach? Data were needed to provide consensus.

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 Deniz Akbay

The strength of rocks and soil is a crucial design parameter in engineering projects, and it can be determined through various test methods such as uniaxial compressive strength, tensile strength, and shear strength. The point load index test is a popular indirect test method for predicting the uniaxial compressive strength of rocks. However, the reliability of the point load index’s estimation of uniaxial compressive strength of rocks is questioned due to the wide range of coefficients that are used to predict uniaxial compressive strength of rocks using point load index values. Factors such as the shape and type of rock specimen, practitioner, and test apparatus used can affect the accuracy of the point load index test. This study investigated the effect of four different specimen shapes used in point load index test (diametral, axial, block, and irregular lump tests) in predicting the uniaxial compressive strength. The rock samples were tested using four test procedures which are called diametral, axial, block, and irregular lump tests. The results showed that the irregular lump test was the most accurate in predicting uniaxial compressive strength, with the highest correlation coefficients and lowest mean absolute percentage errors. The point load index test can be used as a reliable predictor of uniaxial compressive strength of rocks when the irregular lump test is preferred.

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 Kasimcan Koruk, Julian M. Ortiz

Building a geological model is important in resource estimation, as it defines the extent of domains for estimation. Geological models are built by assigning a domain to the samples, based on logging of different features related to lithology, alteration, and mineralization. Then, the extent of these domains is determined using geometric or geostatistical tools. However, these models should account for uncertainty, since the actual extent of these domains is not known and must be extrapolated from the labelled samples. With the availability of geochemical datasets and machine learning techniques, employing multiple variables to build resource models should be considered. This article proposes a two-step machine learning approach with an ensemble implementation to define geological domains and their uncertainties. First, an unsupervised binary clustering method labels the geochemical samples into two domains. These labelled samples are used to inform a geological domain model built by support vector classification. This application is repeated with subsets of variables and subsets of samples, leading to an ensemble learning method. Weak models are produced with each subset of samples and variables, and combined to devise a stronger learner. The final model accounts for uncertainties thanks to the ensemble implementation. The proposed workflow is demonstrated on a dataset from a porphyry copper deposit, applied hierarchically to define four domains. Performance is comparable with traditional methods, but provides the advantage of allowing domain knowledge in the selection of the variables, and generates domain boundaries that can be controlled in terms of their continuity and smoothness.

Oct 11, 2023

By D. Stone, M. Le Roux, Q. P. Campbell, M. Fofana

Float-and-sink analysis is widely used in the coal industry to obtain washability data, yielding important information about beneficiation potential and performance. This method is associated with health and environmental problems, and research into alternative densimetric methods is important. The RhoVol is a new technology developed by De Beers Group Technology South Africa (DebTech) for the image-based generation of densimetric data from ores. The analysis is done on a per-particle basis, within a size range of +3 mm –8 mm. In this paper we compare the established methods used for the float-and-sink analysis of coal with a new method using RhoVol. The aim of the study was to determine the validity of the information obtained from the RhoVol analyser by performing comparative densimetric analysis on three different coal samples. The results showed that the RhoVol method was more rapid, safe, and precise, but tended to consistently underestimate the density of the coal sample, probably due to varying coal porosity.

Oct 3, 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