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By B Haase, R Saha

Conditional simulation (CS) has been extensively used in metal industry to assess uncertainty of geo metallurgical variables to build robust distributions around grade tonnages across different time horizons. Coal’s entry to nonlinear stochastic modelling is relatively new and this paper summarises the work done at BHP to enable its practical usage from production time frames to Life of Asset planning. CS in coal using Sequential Gaussian Simulation (SGS) is used to understand resource confidence around specific variables within pre-defined boundaries of spatially continuous domains for each coal seam. The variation between simulations for a given parameter reflects uncertainty. This paper demonstrates the use of CS to profile resource based upon agreed seam/parameter uncertainty thresholds which affect planning, forecasting, extraction and inform identification of key production risks and defining mitigation strategies. The end goal is to de-risk long-term plans by optimising infill data collection and improve stability in short-term planning through increased understanding of confidences locally rather than at global resource definition stages. The paper also briefly discusses the use of automated workflows and systems to minimise the time spent on the process to enable use in decision-making.

Mar 22, 2022

By S Sullivan

A recent review of resource reports lodged to statutory bodies found geological models with oversmoothed or unrealistic lithological boundaries, many of which do not represent geological appearance in the field, pit or underground drive. The underlying data is often too complex or messy to be incorporated into the resource model and is thus a simplification of reality, to the detriment of the mining operation and its shareholders. Volumes can be over- or underestimated and subsequent grade predictions can be misplaced, combining to cause over- or understatement in resource reporting to stakeholders and statutory authorities. Domain models can be improved with new modelling techniques such as machine learning. However, with poor data or improper use of machine learning techniques, the conclusions can be just as misleading as with current techniques. Machine learning rarely offers a single ‘right’ outcome, rather a range of possible outcomes from the data provided. But importantly it can take advantage of the full richness of data for more informed models. Machine learning also provides confidence in its predictions so that uncertainty in the resultant models can be quantified and passed through for risk assessment during mine planning and operation. This paper will discuss the factors accentuating complexity in deposit modelling: data diversity, structural controls, chemistry, data volumes, process workflows and external non-geological constraints. A case study illustrates the risk of reducing or ignoring complexity, which can result in an overly simplified geological model.

Mar 22, 2022

By E J. Hill, F Huang, A Otto

Geochemical data from drill core samples is used in mineral exploration to enable geologists to understand subsurface geology. However, it is challenging to analyse these data sets rigorously and consistently. Manual data interpretation relies on the knowledge and experience of logging geologists. When multiple geologists are involved, it is possible to introduce inconsistencies in logged lithology type and scale of logging (‘splitters’ versus ‘lumpers’). Machine learning (ML) is a powerful tool for analysing high dimensional data (ie data with many variables) and large data sets (ie data with many samples). However, ML methods applied to drill hole samples do not incorporate spatial information and this can result in high misclassification rates and small-scale ‘noisy’ results. We demonstrate the use of multiscale spatial analysis (wavelet tessellation) as a pre-ML step to analyse spatial information. This step helps reduce misclassification and filter out unwanted small-scale variation in the data. In an experiment, we used wavelet tessellation and supervised ML to predict litho-geochemical rock types from geochemistry data. The data set is from the Valhalla uranium deposit near Mount Isa, northern Queensland. First, geochemical knowledge and statistical analysis was used to select appropriate geochemical elements for litho-geochemical classification. Second, the elements were processed using multiscale spatial analysis. Third, we trained a Random Forest model with the data set and found that the model performs worse in predicting rare rock samples than common ones. We applied over-sampling and down-sampling methods in aim to overcome this issue. As a conclusion, the combination of multiscale spatial analysis (to define rock unit boundaries) and Random Forests (to classify rock units) is a good method for rapid and accurate analysis of drill hole geochemistry.

Mar 22, 2022

By M I. Pownceby, S P. Suthers, V Nunna, G J. Sparrow

Global demand for iron and steel has increased substantially over the past 20 years and there has been a greater focus on developing suitable processing options to treat low-grade hematite-goethite ores containing higher levels of silica and alumina impurities. The processing applicable to reduce the impurity levels in these lower-grade iron ores depends on their mineralogy and a thorough understanding of the process dynamics associated with the separation technology. Different separation technologies used to remove silica and alumina from low-grade iron ores were reviewed. The major concentration methods that may be applied to upgrade lower-grade lump iron ores include magnetic separation, wet and dry heavy media separation, and air-pulsed jigging. The technologies applicable to beneficiating iron ore fines include wet and dry gravity and magnetic separation, flotation, and roasting followed by magnetic separation. It is necessary to investigate the application of separation technologies on a case-by-case basis to select economically viable beneficiation strategies suitable for the particular low-grade iron ore. A commercial flow sheet is expected to involve the implementation of several separation technologies.

Nov 8, 2021

By N Madani, S Abulkhair, N Morales

Conventional geostatistical algorithms cannot reproduce bivariate complexities such as inequality constraint, nonlinearity and heteroscedasticity. Poor reproduction of these features may decrease the accuracy and reliability of mine planning results. For example, it is not unusual to have an inequality constraint between primary and disturbing elements in a metalliferous deposit. Implementation of traditional methodologies for such complex data sets can lead to the incorrect reproduction of a bivariate relationship, which will affect the validity of NPV results. In this paper, an iron data set containing iron and silica grades with an inequality constraint between variables is introduced as a case study. This study proposes an algorithm based on a hierarchical sequential Gaussian cosimulation integrated with inverse transform sampling. The proposed methodology considers the linear inequation between two variables in the hierarchical cosimulation process to reproduce an inequality constraint. As a comparison, conventional sequential Gaussian cosimulation is also applied to the same data set to demonstrate the difference in bivariate relationships from both models. Unlike the proposed algorithm, the conventional cosimulation cannot reproduce an inequality constraint and slightly overestimates silica grades. The modelled realisations are then used to assess the uncertainty of a plan and generate a stochastic strategy that adapts the destination of the blocks depending on the scenario. Two-stage stochastic long-term production scheduling takes extraction decisions using average information (ie e-type model) and ore/waste destinations based on geostatistical realisations. As a result, the proposed strategy is closer to the upper bound, highest possible NPV for each realisation, than to the lower bound, deterministic strategy that does not manage the risk of sending extracted material to wrong destinations. Furthermore, Comparing production schedules resulting from proposed and conventional geostatistical methodologies shows the importance of inequality constraint reproduction and more accurate long-term mine planning.

Nov 8, 2021

By M I. Pownceby, S Hapugoda, H Han, E Donskoi, L Lu

Iron ore sinter mineralogy and its associated macro-/micro – structure has a strong impact on sinter quality. At a macroscopic scale, sinter ideally consists of a strong, porous matrix which bonds relict ore nuclei together. Microscopically, the sinter matrix (solidified from the melt part of the initial sinter mix) generally consists of complex calcium ferrites known as SFCA, secondary magnetite and hematite grains (precipitated from the primary sinter melt), glass and silicates. Depending on the conditions under which the sinter structure is formed, two major forms of SFCA with different morphologies are generally recognised, ie fine micro-platy SFCA (usually termed SFCA-I) and coarse columnar/prismatic SFCA. Detailed optical microscope observations of several pot grate and compact sinter samples revealed the presence of a variety of fine, coarse and dense forms of both types of SFCA. The controlled cooling tests revealed that cooling rate has an impact on the form and size of SFCA crystals. In this work, EPMA analysis of SFCA compositions from a variety of pot grate and compact sinter samples are presented. Results show that the SFCA types exhibit a broad range of complex compositions within the system Fe2O3/CaO/SiO2/Al2O3/MgO/TiO2/MnO2. Although SFCA-I and SFCA are known to be crystallographically distinct and with different, well-defined ranges in composition, there was considerable overlap in compositions of the experimental sinter samples. The development of SFCA textures depend on several parameters including the local chemistry and conditions including the maximum temperature attained and the cooling rate, within the sinter bed, thereby suggesting that SFCA identification based on morphology alone may be erroneous.

Nov 8, 2021

By J Loeb, R Ramanathan, H Ingham, P Cameron

Most mining operations, including iron ore, maintain a focus on continuous improvement and asset optimisation in their operations. As all the unit operations in the Mine-to-Mill value chain are interdependent, available technologies that address efficiencies across the value chain are once again in the spotlight as companies are driven to improve productivity and maximise mine site profits to increase return on capital invested. Core to continuous improvement is the need to understand the baseline and impact of changes to the process. In this paper, we discuss some of the critical attributes in the Mine-to-Mill process, including their influence on productivity and cost, the need for direct measurement and areas where they should be applied. Many initiatives can be considered to improve Mine-to-Mill processes. Mining operations are planned and executed based on designs and models to achieve the operation's objectives. However, there are many variables in the different parts of the value chain, such as blasting, material handling, crushing and screening. Therefore, measurement of the key attributes establishes the baseline for Mine-to-Mill (or Pit to Plant) performance, which is necessary to understand the impact of any proposed improvements to the process design and execution and monitor the outcomes on an ongoing basis sustain the improvements that have been implemented. This paper focuses on two types of measurement – blast movement and particle size of materials through the Mine-to-Mill process. Several innovative technologies and control loops are readily available to measure these attributes and assist operations to improve productivity and mine site profits. The size of the tangible benefits, which can flow from measuring and optimising fragmentation and blast movement, provide a remarkable return on the investment. Realising these benefits needs a focus outside conventional operation silos as a successful Mine-to-Mill project requires a multidiscipline approach across all the silos in the value chain. Required technologies are available; adding the necessary ingredients of communication and co-operation by all concerned across the silos will ensure the benefits are realised.

Nov 8, 2021

By G S. Beros

In 2019 the Chinese Ministry of Ecology and Environment issued guidelines promoting the implementation of ultra-low emissions in the iron and steelmaking industry. These guidelines aim to drive improvements in air quality through the reduction of particulate matter (PM), sulfur dioxide (SO2) and nitrogen oxide (NOx). Secondly, it also represents an initial means to commence decarbonisation of the industry. The ultra-low emissions guidelines propose that well over 80 per cent of China’s production capacity will achieve these targets by 2025. In response, many sintering operations have implemented numerous improvements to the process that result in significant efficiency gains. Of note is the adoption of deep bed sintering where, with some modifications to equipment, the sintering bed depth is increased resulting in sizable reductions of SO2 and NOx emissions. This paper will also provide an overview of the requirements to introduce deep-bed sintering into an operation and highlight test work completed which quantifies the resultant reduction in emissions.

Nov 8, 2021

By H Lemos, E Nunes, D Jacobson, R Costa, L Ono, A Alves, H Delboni Jr

Oversize rock breaking and metal tramp removal are key issues for reducing primary crusher downtime, as well as improving the safety associated with its operation. Remote operation of such tasks would thus not only increase productivity, but also reduce the risks related to work in confined spaces, fall risks, and overhead hazards. These issues are particularly relevant in high-capacity operations such as iron ore mining, where large machines are in continuous operation. This article describes the architecture, construction and advanced testing of a novel remotely operated robotic mechanism for assessment and removal of metal tramp from primary crusher chambers. The system essentially includes a robotic-arm equipped with a hydraulic clamp tool for handling oversize material, as well as an oxy-flame module for cutting metal pieces entrapped within the primary crusher cavity. The first industrial unit was delivered to a large iron ore mine in Brazil, where the installation and testing is scheduled within the coming months.

Nov 8, 2021

By T Seifert, P Krolop, K Niiranen, S Gilbricht

The Per Geijer iron oxide apatite deposits (IOA) display significant potential mineral resources for Luossavaara-Kiirunavaara AB (publ), known as LKAB. LKAB continuously mines magnetite/hematite ores in northern Sweden for almost 130 years. The Per Geijer deposits reveal a high phosphorus content and vary from magnetite-dominated to hematite-dominated ores, respectively. Furthermore, they show a large variation in texture, mineral composition, and relation to wall rocks. The high phosphorus concentration of these ores results from highly elevated content of apatite as gangue mineral. Reliable, robust, and qualitative characterisation of the mineralisation is required as these ores inherit complex mineralogical and textural features. For this purpose, comminution tests at laboratory scale in combination with scanning electron microscopy-mineral liberation analysis (SEMMLA) were carried out. Based on this work, significant information on the modal mineralogy and degree of liberation of minerals of economic interest (eg magnetite, hematite, and apatite) were obtained. Results show that there is a difference in the degree of liberation of magnetite and hematite between ore types. This seems to be dependent both on the size fractions and the dominance of each iron oxide in the individual ore type. The amount of gangue minerals seems to have no significant impact on the degree of liberation after comminution. Apatite is generally best liberated in ore types associated with silicates, regardless of magnetite or hematite dominance. Based on the results of this study it can be inferred that a high degree of liberation of the minerals of economic interest can be achieved. However, results need to be verified with further beneficiation steps such magnetic separation, apatite flotation and possibly reverse silicate flotation.

Nov 8, 2021

By E Mare

Recent highly publicised incidences of disastrous containment failures, none more pertinent than the 2019 iron ore tailings dam failure in Brumadinho, have focused the world’s attention squarely on the often-challenging subject of tailings storage. Unwanted ultrafines, that are deemed to be unworthy of further treatment or not to have further saleable value, are therefore a significant issue for mine owners looking to reduce risks and perceptions associated with long-term storage of tailings. In this context, there are strong drivers to identify safer approaches to ultrafine tailings management, especially if it can also lead to increased revenue, together with better water stewardship and environmental outcomes. The better management of tailings needs to be considered from both containment challenge and processing opportunity perspectives. This paper focuses on the latter, reviewing from a technical and economic perspective, the feasibility of more extensive processing and/or reprocessing of specifically iron ore tailings, in a bid to reduce the overall volume for management in long-term storage. Herein the opportunity lies in recovery processing, as much as enhanced thickening and/or mechanical dewatering, and therefore the paper discusses both issues as equally important sides of the same coin. Recent interest in iron ore ultrafines processing and reprocessing studies suggests that the enhanced processing of iron ore tailings offers multiple perceived advantages. Apart from a potential reduction in tailings volume, associated with safer containment, lower environmental impact and improved water management, the prospect of increased revenue from additional Fe recovery presents supplementary motivation for iron ore players to embrace this approach, as further elaborated in this paper.

Nov 8, 2021

By C Simpson, J Market

The process of sampling blasthole cones utilising personnel to manually shovel material into sample bags is a long-standing industry accepted process. However, this method has several drawbacks, including the safety issues around having personnel performing manual sampling in a harsh environment and the variability involved in getting a human to repeatedly get a ‘shovel full of dirt’, and make it always representative. Geophysical blasthole sampling, or utilising a Downhole Assaying Tool (DHAT) has been tested and has now begun implementation at many iron ore sites throughout the Pilbara region, Western Australia. This method uses a geophysical tool to capture data within blastholes, and together with a semi-autonomous logging platform to minimise risks around manual handling, delivers a multielement proxy-assay which can be utilised by the mine geology team to accurately domain the orebodies. Logistically, the combination of a specially designed tool and semi-autonomous truck are the way forward for a safer and more data-robust blasthole sampling practice. The method utilises a neutrongenerating geophysical tool and linked elemental spectroscopy sensor, which measures the response of the material surrounding an open hole. This delivers results at submetre intervals. These results are then utilised, similar to blasthole sample results, to map out areas within the blast pattern that are ‘ore’, ‘waste’, or ‘other suitable grade’. This paper outlines a project that has been in ‘proof of concept’ at selected Fortescue sites over the last few years with testing of these tools carried out on reverse circulation (RC), diamond drill and blastholes. The method is now being implemented at operational hematite mine sites. Fundamentally, the method adds more than enough value to justify its implementation. The aim is that these learnings will enable the greater industry to adapt, implement and improve their mining practices. Ultimately, the outcome will be greater value in mining for the industry by having a larger volume of good quality data to make reliable decisions on material movements, minimising ore-loss and dilution, and maximising the value of our current and future orebodies.

Nov 8, 2021

By D McB Martin, A Piechocka, M Jessell, M Lindsay, E Ramanaidou

The Hamersley Basin of Western Australia, approximately 500 km long by 200 km wide, is recognised globally for its rich endowment of iron ore resources. Two types of bedded iron ore mineralisation are recognised: the Proterozoic hypogene martite-microplaty hematite ores; and the more recent Cenozoic supergene martite-goethite ores. Exploration strategies depend on the style of mineralisation being targeted; however, stratigraphy and structure are fundamental controls on both ore types. Therefore, the ability to visualise the 3D geology of the entire basin is critical for the understanding of iron ore occurrences and their relationship to ore genesis of bedded iron ore mineralisation. However, due to the large size of the basin, generating a 3D geological model of the regional stratigraphy and structure has not been possible, or prioritised, primarily due to software limitations. Recent advances in implicit automated geological modelling presents an ideal opportunity to develop a 3D model of the entire Hamersley Basin. The innovative Loop software was used to model open source geological data (ie geological mapping, outcrop orientation data, and fault data) sourced from the Geological Survey of Western Australia. In addition to generating a 3D geological model, information such as stratigraphic thickness and fault offset information was extracted using the map2loop module and demonstrated its application to exploration targeting. This study demonstrates how a basin-wide 3D geological model was used to conduct a regional structural analysis of the Hamersley Basin. The results of this study provide opportunities for other prospective regions to be rapidly modelled in order to enhance the understanding of the geology and improve exploration targeting.

Nov 8, 2021

By H Rossiter, C Simpson, J Market, P Jeanneau

Downhole Assay tools are a geophysical method to collect an instigated response from the material surrounding a drill hole and deliver a multielement proxy-assay. They were first tested in the Pilbara at the turn of this century, however since 2011 they have seen a more focused testing and implementation regime with multiple companies across multiple Pilbara mine sites. The increase in the volume of data has led to advances in the measurements and significant improvements to the efficiency of the calibration process. Pulsed Fast and Thermal Neutron Activation Analysis (PFTNA) downhole assay tools collect gamma photon spectra which are characteristic of elemental signatures. One of the key components of the technique is calibrating the spectral signatures to lab assays. Each tool is slightly different due to the organic nature of the crystal detector and therefore responds slightly differently. Environment and hole conditions as well as ore characteristics are among other external influencing factors. Thus, a unique calibration is required for each tool. In addition, not all elements are measured directly, but some are actually characterised by proxy, meaning that if the signal-to-noise ratio for an element is small, it may be easier to identify the mineral or geology in which that element is found and thus infer the concentration of the element. These proxies may differ for each site or geology type within a site. There is a large advantage to build a unique calibration per tool at each site rather than a universal one to be used across the whole province. This then delivers the accuracy and precision of measurements that mining companies require for modern operations. Early work with the tool required several thousand metres of calibration data and several weeks of analysis to build each calibration. This process has now been streamlined to significantly reduce the amount of data required and the analysis time to make it much easier to introduce new tools to a site with an existing model or to create new models. This paper details the calibration process, illustrating the increasing accuracy of the models as training data are acquired as well as the methods for transferring a calibration from one tool to another.

Nov 8, 2021

By S Hapugoda, J R. Manuel, X Cao, B D. McDonald, N A. Ware, L Lu

Roy Hill is a large iron ore mining, processing, railing and port operation in the Pilbara region of Western Australia. Since delivering its first shipments to customers in December 2015, Roy Hill has quickly achieved a 60 Mtpa production rate of lump and fines products. The process plant, principally consisting of wet scrubbing, screening and de-sanding unit processes, was expanded from early 2020 to include operation of a Wet High Intensity Magnetic Separation (WHIMS) Plant. The WHIMS Plant treats tailings to recover approximately 4 Mtpa of ultra-fine (nominally -150 μm) high-grade hematitic concentrate which, after dewatering, is blended into the fines product. Unlike typical hematite concentrates, which consist largely of dense particles with smooth surfaces, the WHIMS concentrate is characterised by very finely microporous hematitic/goethitic particles, reflecting the overall characteristics of the Roy Hill deposit. Detailed test work has been conducted in collaboration with CSIRO to characterise the WHIMS concentrate in terms of its physical and mineralogical properties, and to determine its influence on the granulation and sintering performance of Roy Hill fines – from fundamental/lab-scale and sinterpot perspectives. The results demonstrate that blending of the high-grade hematitic Roy Hill WHIMS concentrate into the fines product can maintain overall sinter quality and positively influence granulation and sinter melt formation, as well as Fe grade.

Nov 8, 2021

By A Larsson, K Niiranen

The Palaeoproterozoic Leveäniemi iron oxide apatite (IOA) deposit of the so-called Kiruna type is currently mined by Luossavaara-Kiirunavaara AB (publ.), commonly known as LKAB. The mineralogy of iron oxides, ie magnetite, hematite, maghemite, and goethite is more complicated compared to the neighbouring and more famous IOA deposits of Kiirunavaara and Malmberget. Furthermore, the mineral chemistry of the iron oxides in the Leveäniemi deposit is also slightly different. Especially, the information about the deportment of titanium and vanadium in iron oxides and distribution in the deposit is essential since they can have an impact in the steelmaking process. For this study 50 samples were selected from exploration drill cores and investigated by optical microscopy, FE-SEM-EDS and EPMA at LKAB and the Geological Survey of Finland. Investigations revealed that magnetite is the predominant iron oxide mineral with secondary hematite being the second most abundant mineral. Primary hematite, maghemite, and goethite seem to be less abundant. It should be noted, however, that this investigation focused on magnetite which currently is the only mineral with economic value. Vanadium occurs as a substitution element in the crystal lattice of iron oxide minerals in the Leveäniemi deposit and not as discrete stochiometric vanadium minerals. In the investigated samples vanadium concentration in magnetite ranges from 0.12 to 0.32 wt per cent V2O3 with higher concentration in the southern part of the deposit. Contrary, titanium does not substitute for iron in the crystal lattice of magnetite or secondary hematite (less than 0.018 wt per cent TiO2). It either occurs as tiny inclusions of titanium oxide minerals or as exsolution lamellae of ilmenite in magnetite. The spatial distribution for titanium in the deposit, however, remains unknown. Furthermore, results of this study indicate that alteration of primary magnetite to secondary hematite has had no significant effect on the trace element chemistry of these minerals in the Leveäniemi deposit.

Nov 8, 2021

By J Caron, M Athayde, F Lavoie, R Joyce

Decarbonisation has become a major challenge for the global steelmaking industry, turning towards new technologies aimed at carbon footprint reduction, which on its own accounts for approximately 9 per cent global emissions. The iron and steel industry represents a ‘hard to abate’ sector, where much of efforts are currently being deployed into initiatives aiming to decarbonise the ironmaking through the use of green hydrogen, carbon capture utilisation and storage and state-of-the-art operation of current technologies, while little efforts being deployed to find carbon-efficient solution to iron ore burden preparation, where high-grade iron concentrate will increase in importance to ironmaking regardless of the chosen reduction route. Quebec Iron Ore (QIO), a subsidiary of Champion Iron Limited (Champion), produces high-grade hematite concentrate with one of the lowest carbon global footprints. Still, QIO is partnering with its clients to the development of burden solutions to minimise CO2 emission, in the seek for a decarbonised steel. In a strong technological partnership, Binding Solutions Limited (BSL) has developed a novel, coldbinding technology to provide a cleaner, more cost-effective alternative to induration. The technology allows miners and steel producers to reduce Capex significantly and reduce energy consumption and CO2 emissions by 90 per cent. QIO and BSL have partnered to adapt the disruptive cold binding technology developed by BSL to QIO’s concentrate to produce a high-quality low emissions iron ore agglomerate. This paper describes the efforts taken to further develop BSL’s cold binding technology and its application to QIO’s high-grade iron ore concentrate to produce a hematite cold bonded briquette (hCBB) showing comparable performances with high quality seaborne fired pellets.

Nov 8, 2021

By Y K. Leong

Iron ore tailings typically containing 40 to 50 per cent Fe can be beneficiated to iron ore products containing 54 to 60 per cent Fe. The impurities are comprised of clay, quartz, cristabolite and TiO2. Goethite and hematite are also present. At high concentrations of 55–60 wt% solids, the tailings displayed high yield stress and viscosity and cannot be pumped over long distances. Composite additives comprising of NaOH, phosphate-based additives and sodium metasilicate are found to reduce the viscosity and yield stress very significantly by a few orders of magnitude. The yield stress of 100 Pa can be reduced to almost zero. At this state, dilution of the tailings with its process water to 40 per cent solids causes the coarse and high-density iron ore particles to separate from the colloidal fractions located in the supernatant after a few minutes of sedimentation. Separation by decantation produces a sediment with an Fe content of 54 per cent from tailings with 47 per cent Fe. Another tailings sample with 48 per cent Fe was beneficiated to greater than 57 per cent Fe using NaOH-metasilicate-polyphosphate additives and employing an additional washing step. The use of other composite additives, NaOH and polyphosphates, increased beneficiated product Fe content to greater than 60 per cent from the same tailings. With the current iron ore spot price of more than US$180 per tonne, the cost of this treatment process even including a desalination step, if necessary, is relatively insignificant. This study has given tailings an economic value that should be exploited as soon as possible.

Nov 8, 2021

By E Bouchard March, F Lavoie, B Legare, K Bourassa

Quebec Iron Ore (QIO), a subsidiary of Champion Iron Limited (Champion), completed the restart of the Bloom Lake iron ore mine located in the heart of the Labrador Trough region of Northern Quebec, Canada in February 2018. Prior to its restart, the concentrator flow sheet underwent major upgrades which brought the iron recovery to the highest of all Labrador Trough operations. After two profitable years of production, QIO, supported by Soutex, started to look at technologies to improve its current performance and integrate into its expansion project flow sheet. From the lessons learned while optimising Phase 1, the addition of a scavenger-cleaner processing stage was identified as an improvement opportunity to increase recovery, produce a higher-grade product, and further improve the stability of concentrate quality. In 2019, the NI-43101 feasibility study for the Phase 2 expansion, aiming to double the production of high-grade iron ore concentrate, was published. Based on the metallurgical test work, the hydraulic classifier was selected to perform the scavenger-cleaning duty for its well-established performance and known behaviour at the cleaning step in the Phase 1 plant. To validate laboratory results, a pilot scavenger-cleaning hydraulic classifier was installed in Phase 1. Although the hydraulic classifier was selected for the feasibility study, metallurgical test work performed with the REFLUX® classifier showed interesting potential. It was thus decided to also install a pilot RC300 Reflux classifier at the scavenger-cleaning stage in Phase 1. Despite their apparent great similarities, the metallurgical performance was significantly different, and many dozens of sampling campaigns highlighted the different performance of both pieces of equipment considering the feed material particle size. This article presents the pilot plant results in terms of recovery, selectivity and stability for both the Reflux classifier and the hydraulic classifier operated in a scavenger-cleaner stage at the Bloom Lake iron ore concentrator.

Nov 8, 2021

By C S. Kelsey, J R. Kelly

Australia is presently enjoying the fruits of a booming iron ore market. Expectations are that market strength will be supported in the short to medium term by increasing feedstock demands from steel mills, as world economies rebuild post-Covid-19. However, as cost and environmental pressures increase the longer-term market outlook will be dominated by product quality. The ‘flight to quality’ will place increasing demands on direct shipping ore miners as they compete to maintain their standing in the iron ore marketplace. China will progressively disengage from its dependence on Australian imports, leaving miners under increasing pressure to boost product quality and diversify outlets globally. Australia has vast deposits of low-grade magnetite ores located mainly in remote and arid regions of the continent. This paper proposes a dry grinding and magnetic separation process to produce premium concentrate grades from the low-grade ores, to assist in meeting future product quality demands. The premium grade concentrates could be either blended with lower quality direct shipping ores or marketed separately. The proposed dry concentration process involves the pairing of Vertical Roller Milling (VRM), a mature technology widely used in the cement industry, and Planar Magnetic Separation (PMS), a new methodology, which has been developed to the threshold of commercialisation by the private Australian company Cyclomag P/L. Two laboratory prototype planar magnetic separators with field strengths of 1800 gauss and 6000 gauss have been built and tested on a range of magnetite ore types over the past three years. In each case, following grinding to liberation sizes, a combination of roughing and cleaning operations has produced pellet grade concentrates. Vertical roller milling has competed successfully with conventional media milling in grinding cement clinker, limestone and blast furnace slags. A key advantage of dry VRM/PMS processing is its potential adaptability to stepwise modular development, which can minimise initial capital investment, while generating early revenue streams to cope with unpredictable market volatility.

Nov 8, 2021