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By S Dykes, R J. McCarthy, B Klein

There is growing interest in the mining industry on the application of ore sorting. While many are familiar with particle sorting, including the limitations that technology presents (e.g. throughput), bulk sorting, with its higher throughput potential, is less understood. Despite the potential to sort at higher throughputs, few operations have adopted bulk sorting processes, certainly not at large scale. It is suggested that the inability to reliably predict outcomes from bulk sorting may be limiting its adoption in mining projects. Consequently, an evaluation approach for bulk ore sorting has been developed such that mass pulls and grade upgrades can be predicted in the context of a mining study. The approach allows for evaluation of drill core assays and application of the consequently derived heterogeneity relationships to the block model for estimation of sorting outcomes. These processes were applied to conveyor-based bulk sorting for the CuMo project in Idaho, USA and are described in this paper.

Nov 10, 2020

By P Luo, J E. Danoczi, P Nakutnyy

Sensor-based sorting methods to remove waste or for upgrading ore prior to downstream metallurgical processing is becoming more prevalent for mining operations. X-ray transmission (XRT) sorters are a popular choice for mineral processing plants since they can sort a wide variety of minerals. XRT sorters pass high intensity X-rays through particles to generate images of varying greyscale, based on their effective atomic density. The ore sorter then mechanically separates the particles using algorithms based on the images. A popular test currently used to evaluate the amenability of the ore to XRT sorting is to pass the particles through the sorter and obtain the greyscale images showing mineralogical differences. This test provides information on the mineralogical heterogeneity between ore particles for their separation. However, it does not provide an understanding of the actual mineralogical composition of the ore or information pertaining to which other minerals may respond in a similar manner, nor does it provide liberation information. This paper describes a test that combines high resolution X-ray micro Computer Tomography (CT) combined with QEMScan to obtain information about amenability of ore to XRT sorting and to obtain valuable information that can streamline metallurgical testwork programs. This test also provides information relating to particle thickness and associated X-ray attenuation coefficients, desired mineral presence and mineralogical information relating to associated minerals and clays to assist with developing sorting algorithms. Combining the CT and QEMScan can address many limitations of the current method to determine whether XRT sorting technology is appropriate for particular ores. Mineralogy information from QEMScan can identify incidences of; mineral encapsulation, problematic clays, detrimental minerals as well as calibrate the greyscale values of CT data. Additional 3D CT imaging carried out on cores provides spatial information of the minerals within the ore and mineral grades.

Nov 10, 2020

By J Salaya, J Kwak, L Keeney, S Dehkhoda

In addition to volatile commodity prices influencing decision making, in recent years, social and environmental performance have become important decision drivers within the mining industry. There are increased demands from stakeholders, communities, and governments to ensure that raw materials are mined, processed and refined responsibly. The industry also faces the challenge of better managing its waste, which has led to severe consequences when not done properly. The high commodity prices of the late 90s and early 2000s encouraged larger economies of scale and drove mining companies to extract large volumes of rock for separation and concentration at the downstream processes. Over time, as ore grades dropped, the cost of mining escalated and tailings volumes grew. This arduous process also caused strains on recovery cost and performance. Scarcity of water and energy resources coupled with increased production demands and higher operating costs are putting pressure on companies to find innovative ways to increase mining intensities. Hatch’s value chain optimisation methodologies, specifically Grade Engineering® and early waste rejection of the mine, have been of interest to intensify operational performance and minimise waste generation. Enabling preconcentration of the plant throughput, the methodology has significant potential to improve overall metal production and reduce water and energy intensities, whilst minimising wet tailings. Using representative data from real world mines, this paper reports on a case study that evaluates the impact of preconcentration using sensor-based ore sorting on downstream process improvements as well as energy, water and tailings reduction. Financial and economic viability of this technique is presented for both brownfield and greenfield implementation cases. The results show that business case for preconcentration is best when: the distribution of metal in the run of mine ore is negatively skewed and left tailed; mining costs are low; energy, water and tailings management costs are high; and low cost methods of recovering pay metal from low grade material are available.

Nov 10, 2020

By A F. von Wielligh, M Scott, L Keeney

Operational Grade Engineering (GE) is the early (pre-processing) discard of low-grade mineralised and/or barren rock to improve the ore grade and/or reduce deleterious elements within the run of mine ore to be processed. GE activities generally have an impact on primary and ancillary mining activities, equipment utilization and overall equipment productivity. By discarding material which would have reported as ore (in a non-GE mine plan) means that GE must increases the total ore and total rock mining rate requirements to sustain mill feed targets. One challenge of GE and the planning of GE activities is that there are several indirect parameters which impact operational productivity. Modelling these potential impacts and determining if they can be overcome with alternate mine sequences, equipment application or possibly a different equipment fleet altogether is a key question requiring investigation. Overcoming these potential productivity obstacles associated with a more complex operation by introducing new operational parameters and destinations for ore and possibly sub-grade blocks, requires a GE mine plan that is coupled with detailed equipment productivity metrics and a sound operational plan incorporating all GE infrastructure requirements. Several GE mine plans and equipment productivity models indicate that mining rates generally need to increase by approximately 5% to 15% to sustain mill targets and often negatively impact equipment unit productivity metrices through increased cycle times, additional queuing and destination changes. These changes to productivity metrics are however offset by step change increases in asset value. This paper details a methodology to develop GE mine plans that incorporate equipment modelling, flexible mine sequencing and equipment-based production scheduling. In addition, the paper will outline impacts of GE planning on equipment unit productivities through worked examples and models.

Nov 10, 2020

By N Clarke, J Hunt, A Barros, L Keeney

The Gramalote orebody is a large low-grade gold deposit situated in the San Roque municipality, 124 km north-east of Medellin in Antioquia, Colombia. It is jointly owned by AngloGold Ashanti (AGA) and B2Gold and is currently in Feasibility Study phase. In 2013 AGA requested CRCORE to undertake a preliminary study of the potential application at Gramalote of pre-concentration by screening, part of the Grade Engineering suite. 160 samples of coarse assay rejects (-3 mm) were tested and showed one of the strongest responses seen worldwide to that time, suggesting that about 70% of the gold could be recovered into 40% of the mass. This was seen as potentially markedly improving the Gramalote economics. A large-scale testing program was implemented on site to follow up these results. A total of 18 samples of 17 t each were mined along a pre-existing exploration adit. A complex test flowsheet allowed size fractions to be generated from the as-received material as well as after crushing to 53, 23 and 3 mm, all from the same head sample. The procedures were designed after carrying out a heterogeneity study to measure sampling errors. The coarser size fractions were designed to study the effect of crushing on upgrade response and predict the response on open-pit run-of-mine ore. The finer size fractions were designed to investigate means of predicting the upgrade response across the orebody. The large-scale testing closely confirmed the average upgrade response as predicted from drill core assay rejects but found that only the -53 mm crushed material accurately predicted the upgrade response of individual samples. Ore geochemistry was able to usefully distinguish samples with good and poor response. A small study on drill core suggested that, for Gramalote, fine crushed material distinguishes vein associated and disseminated values but not other factors that control actual outcomes.

Nov 10, 2020

By S Ferguson, G Noble

The mining industry is facing economic pressures to treat more challenging and lower grade ore types, as well as pressure relating to environmental impact and social license to operate. Preconcentration through bulk ore sorting has the potential to benefit all these areas by enabling mining operations to divert material of low economic value prior to processing, thereby achieving higher feed grades and recovery, while reducing the processing plant and tailings dam footprint and capital required throughout the life of mine. The effectiveness of bulk ore sorting depends on the heterogeneity of material at the measurement location, as well as the accuracy and precision of the measurement. An understanding of ore heterogeneity can be assessed using drill core data, which provides metre by metre elemental assays. This paper reviews such data and assesses the grade distributions over different scales, which suggests that sufficient heterogeneity exists at mining scales to allow the potential for bulk ore sorting. Prompt Gamma Neutron Activation Analysis (PGNAA) technology has proven to be a successful measurement technique within many industries, including mining. PGNAA was first developed in the early 1980’s for the measurement of the elemental composition of bulk materials on a conveyor belt. Today, Pulsed Fast Thermal Neutron Activation (PFTNA) technology is also applied in elemental analysis of bulk materials and has some advantages for bulk ore sorting. In order to enable effective bulk ore sorting, however, a PGNAA/PFTNA analyser must be designed to provide a representative bulk ore analysis with the necessary accuracy and precision. Examples are presented to provide an understanding of the factors affecting PGNAA/PFTNA performance in relation to effective bulk ore sorting.

Nov 10, 2020

By J E. Moffatt, N A. Spooner, T J. de Prinse, D J. Ottaway, E Klantsataya, L d. S Teixeira, B W. Smith, T B. Payten, G Tsiminis

Single wavelength fluorescence sensing has been used in the preconcentration of ores for many years in situations where it is typically specific to the mineral of interest. Examples of fluorescence sensing include the sorting of diamonds in diamond mines and the sorting of scheelite in tungsten ores. However, the number of minerals that show useful single wavelength fluorescence properties in the visible spectrum is relatively small, so the application of fluorescence sensing is currently limited to niche application in the minerals industry. Recent developments at the University of Adelaide have focussed upon extending fluorescence signal measurements into the infrared spectrum, as well as investigating multi-wavelength fluorescence known as up-conversion fluorescence. These techniques may not only significantly increase the number of minerals that exhibit fluorescence properties suitable for both identification and sensor-based sorting, but also provide mineral-specific signatures of higher quality than previously attainable. This paper details the research work carried out by the University of Adelaide and funded by CRC ORE to develop a mineral-specific fluorescence sensor. The sensor targets two fluorine bearing minerals, fluorite and fluorapatite, that are common in many base metal ores such as porphyry copper ores and silver/lead/zinc ores. Fluorine is a known penalty element in mineral products derived from these ores, so mining companies need to monitor and control the amount of fluorine in their final product to keep it below commercially agreed specifications. Currently there is no real time sensor capable of monitoring fluorine in the ore feed so monitoring and control is carried out using time-consuming standard sampling and off-line laboratory measurements. The development and application of a real time fluorine sensor will enable the mining companies to monitor and control fluorine levels in the plant, greatly reducing the time and cost associated with producing their mineral concentrates within the prescribed specifications.

Nov 10, 2020

By C Beal, S Singh

Sensor-based bulk ore sorting is a form of preconcentration that autonomously measures and physically separates discrete bulk ‘pods’ of run of mine (‘ROM’) or primary crushed material. This case study examines the results of a full scale bulk ore sorting trial undertaken at Cozamin mine in Zacatecas, Mexico in 2019. The bulk ore sorting plant comprised primarily of a mobile jaw crusher, fixed conveyor, MR analyser, and diverter gate. Results of the trial demonstrate that bulk ore sorting could deliver a net improvement in copper metal fed to the processing plant of 6-8 per cent within an equal gross tonnage of ore. Copper metal increases were the result of improvements in mining recovery, where valuable mineralisation is recovered from marginal or sub-grade material that would otherwise be discarded as waste or stockpiled as low-grade. The increase in mining recovery more than compensates for metal losses suffered in the bulk ore sorting plant.

Nov 10, 2020

By E J. Y Koh, G J. McLachlan, E Amini, N Beaton

Preconcentration greatly reduces the ore mass input to the processing plant while upgrading the grade. One of the commonly used methods of preconcentration is optical sorting. These methods rely on optical sensors which classify the material stream into “accept-reject” streams. Currently, it is common to use near infrared (NIR) or colour cameras to classify streams based on reflectance or colour thresholds set by experts. The imaging is done through line-scan sensors where the material is scanned on a belt or a chute. Then, a separation apparatus like a diverter gate or air jet is controlled to separate the streams according to the classification made by the algorithm. Separation efficiency is dependent on the classification algorithm. Existing classification algorithms rely on low-level feature discrimination like observing individual pixel values for reflectance or colour hues. This limits discrimination between minerals with low contrast in colour. Human experts perform mineral segmentation using texture, colour distribution and shape, but it is difficult to translate these visual rules to mathematical thresholds. Deep learning methods like Convolutional Neural Networks (CNNs) provide high-level feature discrimination similar to a human expert. Instead of relying on pre-defined features, the CNNs learn complex features from the dataset. CNNs can construct a hierarchy of features based on pixel clusters to learn texture, shapes, and colour spectrums of the mineral grain surface to provide better separation. In this study, a state-of-the-art deep learning instance segmentation method is used to outline boundaries and classify grains from the background (mineral segmentation). The algorithm is trained on images collected from a flotation feed of a gold deposit, where the gold is mechanically locked inside pyrite. This method can process on-line video inputs at 5 frames per second to provide a live grade. The proposed method is inexpensive as it only uses a camera and a desktop computer.

Nov 10, 2020

By M Pyle, T Vizcarra, G Ballantyne, B Foggiatto

Bulk Ore Sorting (BOS) has the potential to add significant value to mining operations by manipulating the feed grade and throughput to the processing plant. However, assessing the performance of BOS is complex, as it is influenced by geology, equipment, spatial and time domains. This increases the risk (real and perceived) of the technology. To manage risk, brownfield operations have the option to: (a) first test the variability in feed grade using a detector on the feed conveyor and subsequently construct the diverter and associated materials handling equipment when the value is established; or (b) conduct site trials with standalone sorting plants. The approaches described for brownfield projects are not available for greenfield projects where the in-situ heterogeneity needs to be quantified and translated into an economic evaluation to test the viability of BOS. Ausenco has developed a methodology that allows assessing the in-situ ore heterogeneity and uses an in-house technoeconomic model to determine the value of BOS for greenfield projects and assess the effects of sorting performance on project economics. The in-situ grade heterogeneity can be measured on a length of drill core and fitted to a mathematical model to assign a heterogeneity index. Given the spatial location, this heterogeneity index can be mapped across a deposit in combination with the average grade. Linking this information with relevant mixing models can determine the likely technical performance of BOS at an operation. However, the real value is only realised when this technical understanding is linked with an economic model and used to optimise the mine plan. Three case studies will be presented that show how Ausenco applies this methodology to assess the value of bulk ore sorting for greenfield studies.

Nov 10, 2020

By J Zhou, T D. McGrath, K P. Galvin, C P. Lowes, J J. Eksteen

Pre-concentration of low grade ores can improve the economic and environmental sustainability of an operation significantly, with opportunities for implementation ranging from run-of-mine to mill discharge depending on ore specific characteristics. For a gravity separation, where the performance is fundamentally constrained by mineral liberation, these feeds often represent a very difficult separation given the dominance of the relatively coarse gangue and fine liberation sizes. Thus, building knowledge of the feed through characterisation of the density distribution is critical to assessing amenability before progressing towards lab/pilot-scale test work and full-scale operation. The traditional approach to determining the density distribution typically involved sink/float testing, however, recent developments in hydrodynamic fractionation using inclined channels now offers a more cost-effective alternative with minimal health and environmental risk. A non-hazardous dense liquid, namely an aqueous solution of lithium heteropolytungstates (LST), is supplied as fluidisation to a REFLUXTM Classifier, consisting of a vertical section below a system of inclined channels, operating in semi-batch configuration. Fractionation is achieved by increasing the flow rate incrementally and collecting the particles to form a series of flow fractions. The purpose of this paper is to present this new method in the form of a case study, aimed at assessing the amenability of a low grade gold-bearing sulfide ore to pre-concentration. The robustness in the method is demonstrated through comparison with sink/float data, examining the density distribution and the liberation-limited product grade and recovery achievable. These data are then used as a benchmark to assess water-based continuous gravity separations conducted on the feed using a laboratory-scale REFLUXTM Classifier. This data set is used as the basis for process modelling and empirical validation for the recently established partition surface of the separator.

Nov 10, 2020

By M Wagner, H Assimi, F Neumann, C Garcia, B Koch

Run-of-Mine (ROM) stockpiles are the inventory of valuable materials extracted from the mine. Depending on the customer requests, a selective addition of ore from stockyards should be selected at the required tonnage. In the stockyard, stackers and reclaimers are the machines which load and unload ore, respectively. Currently, humans determine the reclaiming/stacking planning sequence in the stockyard by rules of thumb. However, this is a complex task subject to multiple operational constraints, such as where undesirable mineral properties should not exceed certain limits in a request. Human planning can lead to limited decision support and lower ability to consider the upcoming blends and requests. This kind of decision making can cause perturbations in the assumed profit and unexpected loss in practice. Therefore, an intelligent decision-maker and sequence planner would be highly valuable to automate stacking and reclaiming operations in practice. The benefits are reducing variability in decision-making and operation costs. This paper considers a stockyard with available mineral information in the stockpiles using load and dump locations from GPS data feeds. We present an optimisation problem to find a solution which results in reclaiming more ore in a shorter time. To solve the problem, we develop an automatic search strategy based on the greedy search algorithm independent of the type of machine used in reclaiming. The proposed method plans a sequence for stockyard recovery blend optimisation to meet multiple customer demands in a timeframe. Blend optimisation is subject to various constraints such as the elemental composition of the valuable materials and penalty elements. We present three case studies using EKA’s simulator, to fulfil two to four requests from four stockpiles. We compare the obtained results with a pilgrim step reclaiming heuristic and we show how our proposed search strategy outperforms the current strategy used in practice.

Nov 10, 2020

By J Rutter, E Amini, D La Rosa, N Beaton, M Scott, F Faramarz, L Keeney

Anglo American’s Los Bronces copper mine in Chile has been conducting detailed assessments investigating value adding options for their asset. The mine has conducted several detailed Mine-to- Mill and Grade Engineering studies to investigate increased throughput and head grade and to quantifying the impact of these approaches across the life of mine. CRC ORE has two key technologies namely Grade Engineering and the Integrated Extraction Simulator. These two technology suites have been combined to understand the technological landscape and associated value drivers suitable for application at Los Bronces. Detailed ore characterisation test work was conducted to:  measure and spatially model the propensity of ores to naturally deport and  develop customised blast models for Mine-to-Mill and Grade Engineering evaluation The outputs of this work were utilised to develop a block model populated with a range on new Grade Engineering and blasting parameters suitable for scenario analysis. To facilitate scenario analysis a high-fidelity value chain model of the Los Bronces operation from blasting to concentrate production was built in IES. IES was combined with sophisticated analytical tools such as Neural Networks to develop and reconcile a fully integrated value chain. The value chain model made it possible to simulate in IES all available blocks in the block model to predict throughput and grade changes for different strategic scenarios. The scenario analysis was run across 24 strategic combinations of Mine-to-Mill and Grade Engineering and comprised several million simulations. The scenarios investigated each technology independently and jointly to provide an attributed block model that can feed forward into technoeconomic modelling to determine optimal execution strategies for the mine. This paper presents the first published study combining Grade Engineering and IES to provide mass simulation capability to investigate strategic options for a mining asset.

Nov 10, 2020

By V Chamberlain, M Appeah Owusu, M Aniawu-Asumakah, A Anyimadu, R Peattie

This is an integrated geology and plant improvement study arising from the heterogeneity seen in mineralogy and gold association at the Obuasi goldmine in Ghana. This heterogeneity comes from the two ore types mined, the one being a sulphide ore, mainly composed of gold-bearing arsenopyrites. This gold is refractory and exhibits a strong relationship between gold and As. The other is quartz veins, that are high grade and free milling. The installed circuit consists of comminution – Gravity -Flotation – BIOX – Leaching and Adsorption processes. The opportunity tested involved improved mass pull - related flotation recovery of Au in the Sulphide stream; while balancing the need for a minimum Sulphide grade for the Bio-oxidation process, occasioned by the removal of 25 to 30 % of the (quartz) stream through preconcentration by Ore sorting. The current circuit is then utilized for the sulphide route, while a smaller grind-gravity circuit is utilised for the quartz stream in a relatively inexpensive way, followed by a common leaching and adsorption circuit. Added advantages of the strategy includes faster recovery of gold from the quartz stream, with less consumption of reagents from saving on flotation and BIOX reagents for this stream. Screening and Ore sorting was successfully tested with laser technology, achieving over 98% separation of quarts (containing up to 40% of the gold). The plant schedule of Ore, the suggested circuit design for the Ore sorting, the results obtained from the different flotation regimes, as well as consequent financial modelling have been presented and discussed in this paper. This illustrates the opportunity that arises out of a detailed analysis of material versus installed circuits, even if the gains in pre-concentration do not necessarily involve rejection of gangue material. An added opportunity for future investigation, briefly discussed but not tested in this paper, would be to maintain current mass pulls but with increase in throughput (by the space created by the sorted material). This will of course require the mining ability. It could also add LOM value by altering the cut-off grade.

Nov 10, 2020

By A N. Parry

In May 2018 Kasbah Resources Limited (“Kasbah”) completed an ore sorting test work program which was a precursor to releasing in July 2018 an updated Definitive Feasibility Study (“DFS”) for the Achmmach Tin Project in Morocco, which it is proposing to develop along with its joint venture partners. The testwork program evaluated ore sorting as a pre-concentration option to achieve early elimination of gangue and the low-grade component of ROM feed, thereby potentially:  Significantly upgrading the head grade of tin to the downstream processing plant.  Significantly reducing the required throughput capacity (and projected capital expenditure) of the downstream processing plant.  Reducing total consumables, power and water requirements in downstream processing.  Increasing the recovery of tin in the gravity and flotation circuit due to the higher feed grade achievable with ore sorting.  Reducing tailings tonnage, tailings cost and environmental footprint.  Using sorter rejects for mine backfill or road base applications. Key aspects of the design of the metallurgical testwork program centred around the need to ensure that samples representative of ROM ore feed (including projected mining dilution) were selected for the ore sorting testwork. The design and implementation of the ore sorting bulk testwork program is described, as well as a summary of the test work results and a discussion of the enhancement of the project economics reported by Kasbah, which led the company to adopt ore sorting as part of the proposed processing circuit in the updated 2018 DFS.

Nov 10, 2020

By P Holtham, K Duffy, B, W Valery, E Tabosa, rade

Pre-concentration has potential to significantly improve Mineral Resource efficiency by removing gangue early in the process, before energy intensive and expensive comminution and fine processing. However, there are numerous options for pre-concentration and the performance and benefits of these are very case specific. To determine the best option for a particular deposit and to successfully integrate it into the overall mining and processing operations requires comprehensive evaluation. This needs to consider orebody suitability, technology capability and economic viability. The in-situ variability of a deposit and how it is influenced by mining methods and the liberation size of gangue are key factors which are generally not well understood. Geostatistical methods provide an insight into orebody variability, and the overall selection of any pre-concentration solution must be an integrated approach between geology, mining and processing. Many pre-concentration evaluations investigate the potential of just one option. Technology selection should start wide and may include: selective mining, pre-screening (with or without selective blasting), sorting (bulk and or particle), coarse gravity separation (e.g. jigging, DMS), coarse particle flotation, magnetic separation, etc. The upgrade performance of these processes is very ore specific and should be determined from testing, with detailed multi-component modelling used to determine the overall process performance. Many of these pre-concentration processes require significant ancillary equipment, feed preparation and materials handling. It is important to realistically estimate all costs to understand overall economics and select the best option. Some examples showing evaluation and comparison of pre-concentration options are presented in this paper. These include assessments of in-situ variability using geostatistical tools, process modelling of pre-concentration options and overall performance, preliminary layouts and cost estimates, and economic evaluations.

Nov 10, 2020

By G J. Wilkie, P A. Revell

The R&D landscape for ore pre-concentration technologies within mining is characterised by the development of individual technologies and point solutions. This presents METS and mining companies with the combined challenge of understanding how to apply pre-concentration technologies to create maximum value, and how to sustainably integrate the technologies into their businesses to maintain the value. The paper will consider the requirements of an integrated pre-concentration system and presents a portfolio of R&D projects that have co-developed and integrated a suite of new precencentration technologies and methodologies across the mining value chain. Focus areas include in-situ orebody characterisation, blast design, real time cross belt mineral sensing, and consideration of how much data needs to be acquired in order to make value based decisions between ore pre-concentration options. An ore pre-concentration workflow is presented to demonstrate how additional optimisation opportunities are enabled both by moving decision points further upstream in the value chain, and by integrating the concepts of pre-concentration into the design of mineral processing equipment. Additionally, several research projects examine the non-technical factors that present barriers to uptake of new technologies within mining companies. Organisational culture, risk management and socio-political factors are discussed and a set of management tools are presented that allow organisations to self-assess their readiness for new technology uptake, along with process models to assist management with identifying and navigating the ecosystem of stakeholders that are decision makers in the use of pre-concentration technologies.

Nov 10, 2020

By H Kurth, L Balzan

The potential for bulk diversion was identified and quickly implemented following the development of bulk sensing technologies applied to conveyed flows. In the early 1980s real time analysis of ash in coal was intended to improve the understanding and control of quality variability. By the end of the 1980s approximately 5% of coal analysers installed were being utilised for bulk sorting; diverting flows to create stockpiles to improve blending flexibility and boiler feed consistency, diverting waste material, or bypassing the beneficiation process when the coal met product quality criteria. In the 1990s bulk sensing and sorting utilising natural gamma detection was applied to conveyed waste in gold-uranium mineralisation and allowed ore to be recovered and processed that would otherwise have been discarded. Further applications developed in the iron ore sector where product quality ore could be diverted to bypass beneficiation and save significant unnecessary processing costs and improve recovery by avoiding process inefficiency losses. Plant capacity was freed up to be utilised by material that required processing. Similar benefits became evident in the phosphate industry and in base metals where multi-elemental analysis using Prompt Gamma Neutron Activation Analysis provides ideal opportunities to representatively measure 30 second conveyed increments at high accuracies. This has been successfully adopted in copper, nickel, platinum and lead-zinc to improve waste removal after primary crushing to eliminate unnecessary expense and improve plant efficiency. The benefits include increased output from existing operating capacity, significant reductions in consumable costs and generation of fewer detrimental waste streams. The paper outlines the technologies and discusses case studies covering the above commodities, demonstrating the immense value that representative real time measurement of conveyed flows can create. Measurement data concurrently provides multiple benefits in operational performance besides sorting, through ore reconciliation, ore blending, feedforward control and metal accounting, adding further value.

Nov 10, 2020

By P Revell, G Wilkie, P Walters, L Keeney, F Faramarzi

Grade Engineering® is a value-driven strategy aiming to maximise benefits by exploiting intrinsic grade variability of ore deposits. It utilises a multitude of separation techniques to remove low grade material before being introduced to post-blast size reduction processes, i.e. crushing and grinding. At an operational scale, Grade Engineering® techniques can be implemented at the drill-and-blast stage, to control the degree of fragmentation in accordance with the spatial distribution of valuable minerals across an ore domain through differential blasting. It can also exploit intrinsic textural and breakage characteristics of a given ore type to reject uneconomical barren material at coarse sizes, which is known as Natural Deportment. Grade Engineering® can also be employed in the deliver stage of the mining value chain through sensor-based bulk and particle sorting. Each strategy is therefore highly dependent on the responsiveness of an orebody to available techniques. That is, the extent to which Grade Engineering® drivers would be capable of unlocking potential values of currently un-amenable orebodies depends on how detailed the heterogeneous nature of ore domains can be described. This paper considers exploring possible linkages between deportment characteristics of an ore and its competence when broken in a range of energy inputs at a particlebased level. Accordingly, potential opportunity may lie in exploring whether the intensity of input energy (or degree of fineness) can be used as a lever to improve or ‘unlock’ ore amenability to Grade Engineering® techniques. Implications from such a detailed approach offers new opportunities to enhance Grade Engineering® gains through engineering ore competence variability.

Nov 10, 2020

By D Gagnon, P Bouchard, F Vanier, E Soares de Lima Filho, J El-Haddad, M Sabsabi, G J. Wilkie, A Beauchesne, A Hamel, A Blouin, T Vaillancourt, F Boismenu, A Harhira, A Plugatyr, C Padioleau

Quantitative mineralogy is an established discipline in the geosciences and is aimed at providing mineral grade and texture information for geological and mineral processing applications. The two core technologies underpinning Quantitative Mineralogical Analysis (QMA) are Scanning Electron Microscopy (SEM) in combination with Energy-dispersive X-ray Spectroscopy (EDS). Technologies such as QEMSCAN and MLA are now routinely used to optimise the performance of large-scale mineral processing plants in the base and precious metal sectors. One of the major disadvantages of the QMA methods used today is extensive sample preparation requirements which make application of this technique to real-time mineralogical characterization not feasible. A breakthrough has been achieved by the National Research Council Canada in collaboration with CRC ORE by developing a novel Laser Induced Breakdown Spectroscopy (LIBS) based technology capable of real-time mineralogical characterization of process streams without sample preparation. The potential applications of this technology include, but not limited to, in-pit muck piles, underground draw points, cross-belt analysis as well as slurries. This paper describes the development of the LIBS-based technology from a proof-of-concept (TRL2) to the construction of a prototype sensor and its validation in a simulated environment (TRL5). Future work is being planned to test and further validate the LIBS sensor on a mine-site which will progress the technology to its next readiness level (TRL6).

Nov 10, 2020