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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

By J Rutter, D Francois-Bongarcon, M Federov, N Odiar, M Scott

There are two fundamental methods for metalliferous sensing of primary crushed ore available for deployment at operations. These methods can be classed as surface measurement techniques (including XRF, LIBS, NIR, SWIR) or penetrative/semi-penetrative measurement techniques (including PGNAA, PFTNA, GAA, MR). While the individual sensing technologies exploit different physical phenomena to measure metal content, penetrative sensor measurements of grade are often regarded to be superior to surface measurement techniques due to the much larger sampling volume penetrative techniques provide. Surface sensing techniques often utilise simpler, established technologies that have considerable benefits in the speed of analysis, capital costs, ease of deployment, social license to operate and operational safety. This paper investigates whether surface sensing techniques achieve adequate sampling representativity of primary crushed rock mass to provide economic benefit over penetrative sensing technologies for bulk ore sorting applications. The paper details the methodology used to assess whether surface XRF measurements change throughout various stages of comminution, and increased surface exposure, from primary crushed ore (top size of -175mm) to finely crushed product for assay (top size -2mm). The methodology was applied to 2 ore mineralisation styles, across variable metals and grades, to identify any associated opportunities and limitations to surface sensing techniques. The results assist in developing a method to determine if surface sensing and measuring via XRF is an adequate representation of the rock mass for bulk ore sorting applications and identify any associated limitations in particle size distribution, mineralisation or natural deportment strength to guide suitable application of surface sensing techniques.

Nov 10, 2020

By M Nehring, M Kizil, P Knights, A Mousavi, F Sotoudeh

A cut-off grade is used to distinguish an economically viable block of ore from non-economical ones in mining operations. In order to obtain a high Net Present Value (NPV), a strategic and precise determination of cut-off grades (mill feed/marginal, marginal/waste) is required. In recent years, the significant depletion of feed grades and increasing mining operating costs have affected the viability of new and existing mining operations. Hence, the introduction of a pre-concentration system to process ore before sending it the main processing plant has gained increasing attention for its potential improvements in resource exploitation processes, mineral processing, energy consumption and environmental impacts. The primary potential advantage of implementing a pre-concentration system is the improvement of resource utilisation and increased reserves as a result of a reduction in cut-off grade. The objective of this paper is to present a new cut-off grade method, which can be used in the presence of a pre-concentration system for underground metalliferous mining operations. The results of this study illustrate the potential economic benefits of using a pre-concertation system prior to a mineral processing operation as a result of the reduced cut-off grade and increased NPV.

Nov 10, 2020

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

Grade Engineering® (GE) involves a range of integrated technologies and operating protocols for improving effective feed grade through early rejection of low value material prior to costly processing activities and has the potential to transform the economics of large, low grade, mining operations. Extensive GE test work by AngloGold Ashanti (AGA) and the Cooperative Resource Centre for Optimising Resource Extraction (CRCORE) determined that the Gramalote gold deposit in Colombia is highly amenable to implementation of grade-by-size screening to upgrade the ore at a production scale. To understand the relationships between geology and the upgrade response drill core and bulk samples were analysed at the Centre for Ore Deposit and Earth Sciences (CODES) as part of a larger CRCORE project to understand geological controls on grade-by-size deportment, i.e., the tendency for specific mineral phases to preferentially fractionate during breakage into different size fractions. This work is focussed on understanding the role of mineralogy and texture in influencing rock breakage and natural fractionation at a range of scales. Detailed logging of Gramalote drill core and mineralogical analyses including hyperspectral logging, portable and bench-scale X-ray fluorescence (XRF), plus low resolution Laser Ablation of intact drill core pieces, combined with data from site (drill logs, geochemistry, petrophysics) were used to evaluate the ore and alteration mineralogy, vein paragenesis and textural variability. This provided information on gold deportment and allowed the identification of favourable host veins. Bulk sample material from different ore grade zones was also analysed. A comparison with the results of GE testing shows that positive upgrade results are produced by rocks with abundant veins, particularly those associated with potassic and/or white mica alteration. This work indicates upgrade response can be predicted from drill core using data collected by a combination of automated systems including hyperspectral data, XRF, and detailed drill core logging.

Nov 10, 2020

By I Auranen, J Raatikainen

IMA Engineering (IMA) and Mine On-Line Service (MOLS) companies have used on-line sensors for analysing ore and waste rock in mining for more than 25 years. Today IMA on-line sensors are used in various stages of the mining process including on-line analysis of drill cores, drill chips, ore and waste in loader bucket, ROM ore analysis on belt conveyor belt and in bulk ore sorting and in slurry analysis in concentrators. During years of extensive field experience and testing we have found that the waste rock dilution and ore losses create much larger economic and environmental losses than has been previously recognized. According to our studies the main reason is limited number of analysis already in exploration when drill cores or drill cuttings are used in block modelling. The same happens in production because too few and biased samples from benches are used to estimate the ore grade. Much more than today estimated amount of waste enters the mill and considerable volumes of ore losses happen at the same time. The ore grade on the benches and in muck piles is averaged and “homogenized” with averaged and biased samples. These are the main root causes of waste rock dilution and ore losses. Sensor based preconcentration can be the remedy to waste rock dilution and ore losses. This presentation will show examples of the use of on-line sensors in preconcentration when analysing ore and waste rock in drill cores, drill cuttings, on conveyor belt and in bulk ore sorting. Waste rock removal in preconcentration has direct effect on energy consumption in crushing and grinding and chemicals in concentrator. In concentrator waste is separated and goes to tailings pond, however, preconcentration directly reduces the volume of the tailings. In our presentation we will cover cases in base metals and in gold mines.

Nov 10, 2020

By M Pyle, R Ch, T Vizcarra, ramohan, G Lane, G Ballantyne

Preconcentration, through gravity separation (Wallace et al, 2015), magnetic separation and particle size (Clout, 2013), has been used in many historical projects to convert low grade material into ore. More recently, pre-concentration technologies such as bulk sorting (Kurth, 2017), screening (Bearman, 2014) and coarse particle flotation (Vollert et al, 2019) have also demonstrated their ability to progressively reject waste through the value chain. These technologies can not only deliver stepchange improvements to the economics of mining operations, but can transform the environmental and social aspects by minimising water and energy consumption and significantly reduce the quantity of fine tailings produced. However, implementing progressive waste rejection requires technologies and approaches to be combined and applied in the right way to capture the value. From a technical perspective, progressive waste rejection introduces challenges related to the orebody, equipment performance, engineering and understanding the value chain from the resource through to final product. From a management perspective, the key issues are related to people and processes, in particular; motivating the business, challenging the paradigms, and introducing new ways of operating within the constraint of existing management structures to manage risks and minimise lost opportunity costs. This combination of technical and management issues means that progressive waste rejection is a complex undertaking for mining companies, yet the reward for the business and other stakeholders is potentially high and should not be ignored. This paper presents how progressive waste rejection can offer step-change improvements to the business case for high and low grade greenfield and brownfield projects based on case studies completed by Ausenco. The paper then outlines different implementation approaches from concept studies to execution to address the various technical and management challenges outlined above.

Nov 10, 2020

By J Rutter, D La Rosa, P Walters, M Scott, L Keeney

Bulk ore sorting technologies, whether surfaced based or penetrative, have seen an increased uptake by the mining industry for preconcentration application. As with all technologies, going through the technology validation process is key to de-risking the operationalisation of the technologies and to demonstrate and confirm predicted value propositions. The ability to laboratory calibrate cross-belt bulk sensors is standard practise for sensor vendors, however transitioning the technology from laboratory to real-world application is a non-trivial process. The industry has taken two main approaches to trialling and validating bulk sensing technologies in operational environments, namely:  Construct an off-line pilot facility at scale, or  Install bulk sensing systems on production conveyors Each of these two approaches have significant advantages and disadvantages and require different experimental design programs and analysis methodologies. Consideration of material movement, heterogeneity degradation, logistical requirements, and financial investment all factor into which approach is most suitable for an evaluation scenario. CRC ORE in partnership with mining companies, have conducted several bulk sensor pilot trials utilising different sensor technologies employing each of the two main approaches outlined above. This paper describes the challenges faced, learnings obtained and outlines a position on how to transition bulk sensing technologies from the laboratory into the operating environment. The case studies presented cover a range of commodity types in both open pit and underground operations.

Nov 10, 2020

By J Rutter, S Dunham

Technological advances in sensor and material handling technology has enabled a step change in mine operations performance. Sensors capable of monitoring the grade of broken rock mass can be mounted on shovels, truck loading units or conveyors allowing highly precise ore/waste decisions to be made on small parcels of rock, increasing selectivity. This increased selectivity has the potential to remove sub-economic material from the product stream prior to incurring ore treatment costs. Bulk ore sorting is capable of intervening at <10t “pods” on Run Of Mine conveyors, or alternatively at per bucket loading (5-100t) or truck scale (30-350t) parcels of ore. This Grade Engineering technique being developed by CRCORE (Rutter, 2017) can improve mill feed grade, remove deleterious materials and ensure that the high capital intensity ore treatment facility is presented with the best ore feed strategy. While this technology can improve mine economics, estimating the performance of a bulk ore sorting system is challenging. Traditional resource estimation practices such as Ordinary Kriging and Inverse distance weighting (IDW) are based on weighted averages, a process that smooths the grade profile, reducing modelled variance and dispersion. Its purpose is to generate a globally unbiased result but is less suited to generating a model of adequate granularity to enable confidence in local grade heterogeneity. This is an essential component for bulk ore sorting success. Estimating ore sorting performance requires knowledge of the grade-tonnage curve at the scale of the sensor diversion unit (SDU). Evaluation based on an estimator that smooths the SDU distribution will not correctly predict ore/waste separation or economic performance. Alternatives to traditional linear geostatistics have been tested on a variety of mineralisation styles. Additionally, a number of heterogeneity metrics have been developed to assist with evaluation and assessment. The difference between estimation for grade (metal) and modelling for traditional mining block models, versus methods used for predicting heterogeneity and variability are explored.

Nov 10, 2020

By R Yong, A McEwan, D G. Miljak, D Milinkovic, A Curtain, P J. Coghill, R Stefulj, B Lovric, G Roberts

The CSIRO has pioneered the development and use of certain classes of magnetic resonance (MR) for mining applications. The MR technique is a radio frequency-based spectroscopy that provides highly quantitative measurement of selected ore minerals. MR has many inherent advantages for bulk sensing in mining applications, including deep sensing penetration into most bulk ores with the use of non-contact sensors that are robust and tolerant of demanding mine conditions. The highly discriminating nature of the technique also provides the very desirable attribute of robust and simple calibration, that can often be performed prior to sensor installation. Rapid sensing (within seconds) at very low grade (few hundred ppm Cu) has been demonstrated, as well as sensing at high tonnage rate. Besides sorting applications, MR may also be applied to preconcentration applications involving very large volume sensing including: (i) haul truck sensing using portal arrangements, where truck destination assignment may be dynamically determined based on the truck grade, (ii) in-pit gantries used for loading trucks that may similarly be equipped with sensors for truck assignment and (iii) deep mine bench sensing, recently progressed through a CRC ORE project, where local bench grade is determined at the few-metre lateral scale and at depth prior to blasting, to aid selective blasting and ore extraction. MR sensor prototypes have been developed for each of these applications and have been tested in laboratory or limited field conditions. To inform the value proposition for truck or bench sensing, initial analysis of truck assignment improvement based on an analysis of in-situ mine bench grade has been performed for a porphyry style deposit. The prototype sensors, preliminary results and future technology development and objectives will be described.

Nov 10, 2020

By E Amini, N Beaton

Application of ore pre-treatment technologies such as Grade Engineering and in-pit ore treatment require comprehensive analysis to show proven value is being generated by switching away from the current practices. Considering most mining operations last several decades; the pre-treatment technologies must be investigated over life of mine (LOM) to truly show value was generated or lost. Therefore, a value chain flowsheet model has been usually developed to run those analysis/simulations over LOM using a set of defined ore characteristics and the operating equipment capacities. The Integrated Extraction Simulator (IES) has been used for this type of LOM simulations as it has the necessary flexibility to accommodate the whole mining value chain flowsheet in one platform and provide essential computation power to run mass simulations for the given scenarios using the resource block model. This allows to forecast the value chain response over the LOM for all given scenarios in a feasible amount of time. The traditionally developed flowsheets for the analysis/simulations are usually limited to the mineral processing plant and were developed based on a single audit conducted on the plant in a very short time, e.g. several hours. The process plant is being operated with a certain ore at a certain condition during the short audits which would not reveal the true capacity of the operation equipment when ore characteristics changes. Therefore, it would be impossible to define the true capacity of the equipment and identify the constraints along the value chain. In this study, a methodology was developed to identify the constraints along the value chain and implement those in the IES flowsheet using process information. Also, the equipment models were fine-tuned to represent the true capacity of the equipment in the flowsheet using the same data set. The methodology was tested over five process plant in two operations and showed the performance forecast was significantly improved over the traditional methods being used so far. Then those high-fidelity flowsheets were used to evaluate the ore pre-treatment technologies proposed by the relevant resource company experts.

Nov 10, 2020

By A Kobzev, C Robben

Sensor-based particle sorting of gold ores is the masterclass of preconcentration. The technical challenges of a grade in ppm scale makes a direct detection with currently available technology in milliseconds impossible. Consequently, the detection and classification of particles into ore and waste classes relies on detectable proxies which are the foundation for the classification. These must be reliable and repeatable across the ore bodies processed in future. A sensor-based particle ore sorting equipment must therefore be calibrated systematically by understanding the gold deportation in different lithological groups. Also, it must be in best operational state to minimise possible misplacement. The technical challenges are met by a stringent financial regime governing the business case. Many gold ore sorting projects require a stable grade of gold in the rejected waste significantly below 1gr/t. Two examples are introduced in this paper:  The pilot results and operational experience of X-ray transmission (XRT)-based particle ore sorting for pebble sorting of sulphide associated ore;  Laser-based particle ore sorting for pebble circuit of an orogenic, quartz associated gold ore. Usually, sensor-based particle sorters are installed in the crushing section of a plant. However, for large capacity plants, the number of equipment required, and the associated material handling costs result in significant capital and operating expenses for plants with 1200tph run-of-mine capacity. As a conclusion, it was decided to investigate sensor-based particle ore sorting applied to the pebble stream of two existing semi autogenous mills.

Nov 10, 2020

By P Revell, A Jenkin

This paper presents an analysis of significant Australian-based R&D programs focussed on the minerals industry, which was commissioned by CRC ORE. The landscape analysis may assist organisations with R&D management issues including program creation, program/partner selection, portfolio management, and public policy settings. The dataset was collated early in 2020, and contains programs being conducted by or with Australian-based ‘Research Service Providers’ (RSPs), most notably Universities and CSIRO. It does not include R&D being conducted in-house by mining and METS companies, or by them with other organisations that are not RSP’s. The dataset contains 65 R&D programs, with total annual cash funding of $229m (70% from industry and 30% from government). The total funding compares unfavourably with the combined R&D expenditure of Australian universities and CSIRO of over $12b, and minerals industry export revenues of over $200b. The R&D landscape is analysed by program numbers and funding, technical domain, geography, and funding source. Areas of relative strength are noted in ‘mineral processing’, CSIRO Minerals, and the CRC program. Areas of relative weakness are noted in ‘bulk materials handling and logistics’, ‘tailings and waste management’, and ‘social and community’. The field of preconcentration is noted as a current area of R&D strength, but it is under significant threat with the impending completion of CRC ORE. The overall R&D landscape is characterised by a majority of small-scale programs, low levels of industry coordination, a low focus on step-change innovation, and total funding lower than should be expected for such a large critical industry. It is hoped that key stakeholders in the Australian minerals industry, particularly governments, and mining and METS companies, reflect on the analysis and act to address holistic weaknesses.

Nov 10, 2020

By P Esteves, J L. Bechir, R Galery, C Senna, V Souto

The current moment experienced by the mineral industry is marked by a series of economic, social and environmental challenges. Among the main challenges, it is important to highlight the decreasing in ore grades with the gradual depletion of the existing deposits, the high volatility in international commodity prices and the operational inefficiencies in the mine, beneficiation, and metallurgical plants. In this context, mining companies are continuously looking for alternatives that minimize production costs and maximize overall production. In addition, recent tragedies involving tailings dam collapses in Brazil, reinforced the need for a more responsible, sustainable, and conscious mining, such as aiming the preservation and rehabilitation of the land environment. In this scenario, the Sensor-Based Sorting (SBS) technology is currently getting more space into the mining market. This separation technology aims the removal of gangue material in coarse particle size fractions, prior to comminution and concentration stages. As a consequence, the technology allows a smaller consumption of energy, water, chemical reagents and other inputs. Moreover, the sensor-based sorting is a dry processing technology and favors the reduction of fine material to be sent to the tailings. The aim of this paper is to provide information regarding the technical and economical evaluation of SBS technology applicability to a zinc silicate mining in Brazil. The project evaluation was performed in two stages: laboratory test work and the execution of a pilot plant. The execution of a pilot plant allowed the technology optimization, quantification of downstream process effects, such as a proper economic evaluation about the technology benefits. Keywords: Sensor-Based Sorting; Particle Sorting; Ore Sorting; Preconcentration; capital expenditure (CAPEX); operating expenditure (OPEX); zinc; comminution; dry processing.

Nov 10, 2020

By R Kroukamp, G Rech

CRONIMET Australia in cooperation with Speciality Metals International, the mining lease holder of the Mt Carbine Tungsten mine, have demonstrated the preconcentration and processing of large (>12 million tonnes) tailings and mine waste dumps on site in far north Queensland. The first stage of this project has proven the economic viability of preconcentration using sensor-based particle sorting whilst ensuring high recovery of industry critical tungsten minerals – wolframite and scheelite. Sensor-based sorting technology have enabled the production of a sorter product to feed the existing wet gravity plant ensuring higher recoveries and increasing concentrate production. Processing of 1,000 tonne low grade samples using the TOMRA x-ray transmission (XRT) ore sorter installed on site, has reduced the volume of material entering the downstream wet processing plant by up to 60%. The sorted 10-25mm size range produced the highest upgrade ratio (product/feed) of 24:1 and achieved sorter concentrate grade of 1.52% WO3, sorter waste grades below 0.014% WO3 and metal recoveries of up to 93.4%. The appropriately sized, barren sorter waste material is also sold as aggregate and other quarrying products and thus adding to the overall economic benefit of the project. The utilisation of the sorting technology on site has produced an economically viable project, significantly reduced capital cost, and reduced the time to market of the final tungsten concentrate. The next phase of the project includes design and installation of a larger two sorter plant capable of over 150t/h feedrate.

Nov 10, 2020

By T BoBo, D La Rosa, P Cameron

Efficient pre-concentration using natural and induced deportment starts with effective blast design. Leveraging these characteristics using Size-Based Grade Engineering® techniques requires detailed understanding and measurement of the particle size distribution (PSD) of the Run of Mine (ROM) ore. In turn, blasts must be designed to optimise fragmentation for the pre-concentration method. To be successful, fragmentation outcomes must be predicted and measured as part of the blast design process to account for the response ranking of the rock mass. The upgrade achieved using Size-Based Grade Engineering® methodologies will rely on the proportion of feed that reports to the screen undersize, so particle size distribution of the feed stock is of paramount importance if the potential benefits are to be achieved and maintained. Measuring actual fragmentation in the ROM ore and comparing with predictions allows the modification of subsequent blast designs to optimise fragmentation for pre-concentration scenarios. Automating this process can deliver significant increases in productivity and mine site profits. This paper discusses the importance fragmentation plays in Size-Based Grade Engineering® and explores technologies and methodologies used to measure it, consistently ensuring the best outcomes.

Nov 10, 2020

By E Amini, M Scott

Grade Engineering® involves the planning, integration and operation of coarse preconcentration techniques to reject uneconomic material as early as possible in the mining value chain to improve the quality of ore delivered to mineral processing activities. These preconcentration techniques include screening for natural and induced deportment of grade to finer size fractions during blasting and coarse breakage, sensor-based measurements of grade and mechanised sorting at particle or bulk scales and coarse gravity separation. Over the last decade, the Cooperative Research Centre for Optimising Resource Extraction (CRC ORE), with the support of its participants, has developed a framework for the holistic evaluation of economic and production impacts attributable to these preconcentration techniques. The framework combines the characterisation of preconcentration responses, geostatistical modelling, process modelling and simulation of downstream and upstream production impacts and the optimisation of strategic mine plans to quantify changes in net present value due to different preconcentration strategies. This framework has been applied to evaluate preconcentration techniques at numerous metalliferous operations and can also be used to quantify changes in the environmental metrics for energy, water and steel consumption and emission, tailings and waste rock production. This paper collates the results of these Grade Engineering® studies to show the range and magnitude of economic and environmental impacts attributable to preconcentration. The studies have shown that rejection of uneconomic material prior to mineral processing activities can have a pronounced improvement in energy, water and comminution steel productivity, emission intensity and the profitability of metalliferous mining.

Nov 10, 2020

By Y V. Haarlem, P Coghill, N G. Cutmore, M Millen, I Carter

Due to the low concentration of gold, ore sorting for gold has always required measuring indirect properties, such as density or colour, to allow separation on a rock by rock basis. This only works on an ad hoc, by deposit basis and is likely to be least reliable where it is most required in low grade ores. One candidate technique, Gamma Activation Analysis (GAA) has been demonstrated to directly measure gold extremely accurately in powder samples of around 500gm and is used in the Chrysos PhotonAssay assay system. This method uses a linear accelerator (linac) to generate the X-ray radiation that activates the ore at low levels to emit a characteristic gold gamma ray that is then measured by a radiation detector. CSIRO is adapting this measurement technique to application on a belt at up to 800tph to measure pods of ore. The principal differences between measuring samples and an on-line measurement of pods are the requirement to measure coarse ore (<50mm), to measure a larger volume of ore as uniformly as possible, and to have an open-ended geometry with adequate shielding of the linac radiation source. These issues have all been addressed with measurements of coarse ore reported down to around 1ppm in sub-optimal test conditions. They have been demonstrated for <75mm particles with detectors capable of measuring a large volume geometry continuously. These are projected to allow measurements down to 0.3ppm in more optimum conditions for a 10 second measurement time period where the U/Th content of the ore is less than ~10ppm. Extensive Monte Carlo modelling has demonstrated that adequate shielding can be provided in relatively simple geometries with only 1 right angle transfer in the material handling. Steady progress is being made to reach the technical position required to trial an ore sorting system.

Nov 10, 2020

By H Rossiter, A Maddever, J Market, P Jeanneau, A Virani

It is generally acknowledged that the head grade of the world’s copper resources is declining. Accordingly, there is an increase in the volume of resource material being mined and processed to maintain copper production. This has led to increases in cost base accompanied by reductions in Life of Mine (LOM) Net Present Value (NPV). The higher tonnages of material mined are driven by increased quantities of lower grade material required to satisfy the short term mine model. In turn, this has brought an increased focus on sampling and assay methods, since any error associated with estimating the grade of each block and determining its correct destination serves to magnify the losses that will occur. Presently most open-pit copper mining operations use blasthole sample assays to feed their shortterm model. The problematic nature of blasthole sampling is well documented (Engström, 2017), particularly the poor timeliness of the data and the significant errors that are inherent to the technique. Methods to improve grade control, such as drilling a separate grade control grid, have been proposed but come with their own cost, logistical, and accuracy shortcomings. A recent development in grade estimation is the Pulsed Fast and Thermal Neutron Activation (PFTNA) downhole logging probe. Deployed on an efficient semi-autonomous platform, PFTNA is being aggressively adopted in the Australian iron ore industry. The technology provides in-situ elemental analysis of the geological formation, delivering high accuracy, high efficiency, near realtime data from a sizeable measurement volume. In this paper we consider the application of the technology to copper. Whilst there are several operational components to such a value proposition, we focus on the benefits of improved gradeestimation. A simulated copper mine is used to model the quantum of improvement expected from a reduced grade-estimation error, which reduces the likelihood of misallocating material to the wrong destination, which in turn increases NPV.

Nov 10, 2020

By T Soares, P Esteves, C Senna, V Souto, E Dias

Steinert provides a wide portfolio of Sensor Based Sorting (SBS) technologies, including the possibility to combine different sensor data in the development of the separation applications. This multi sensor approach provides a larger applicability and extensive flexibility for the technology. This effect is emphasized for mining applications, once every ore body presents its own features that can also comprise a large material variability. In this sense, every sorting application is customized and comprises a personalized solution. This means each project development includes a test work stage that approaches from the project discussion, test definition, up to test outcomes and processing development. In relation to very complex and large projects, a sorting pilot scale plant has become a crescent tendency. By having a pilot plant stage can represent a chance to test larger amounts of material from different mining areas, different mining projects, such as to consider different processing targets and application approaches. Based on that, a better understanding about the technology application can guide a more assertive development of large and complex ore sorting projects. The aim of this paper is to provide information about the applicability of the Steinert multi sensor technology at different pilot plants in South America. It consists in a compilation of laboratory test results, plant design and operational results. For that, a chromite, an IOCG deposit and a sulphide gold ore projects are presented. Additionally, the paper discusses the application of different sensor technologies combinations such as various processing targets, thus providing a wider understanding about sorting applications and flexibility.

Nov 10, 2020