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By A Millar, B Wraith

Process plants are characterised by variability of performance over a wide range of time-scales; reflected in fluctuations in metal recovery, concentrate grade, plant throughput and reagent costs. In turn, these fluctuations impact financial metrics such as operating costs and revenue. The primary cause of plant variability is variation in the physical, lithological and mineralogical characteristics of the ore fed to the plant. The variability of the ore is driven by the intrinsic heterogeneity of the geology and mineralogy of the orebody, the mining method and mine production plan, the capacity to stockpile and blend, as well as the plant flow sheet and the level of plant automation. Whilst the impact of ore variability on process plants is universally recognised, it is rarely quantified in financial terms. Consequently, opportunities to reduce its impact are often overlooked due to the lack of a basis for a quantifiable cost-benefit analysis to justify improvement initiatives. This paper will present case studies using production data from the Renison tin concentrator and a zinc concentrator. These case studies demonstrate that as the standard deviation of plant head grade increases (as a proxy for ore variability), plant metal recovery subsequently reduces. The metal recovery is then converted into plant revenue losses, to quantify the economic impact of ore variability. The Renison case study demonstrated that whilst a very rare occurrence, revenue losses were as high as 34 per cent (relative to the baseline) when standard deviation was at its highest. The zinc concentrator case study demonstrated that revenue losses were as high as 6 per cent (relative to the baseline) when standard deviation was at its highest. Options are available for reducing and managing ore variability in the process plant. These options include changing mining practices so that the ore is fed to the plant with less variability, more advanced process plant control systems and the use of predictive geometallurgical models.

Aug 24, 2022

By A J. Morrison, M Yahyaei, J S. Siong, J Wang, K Runge

The flotation cells used to upgrade ultrafine metallurgical coal (-250 µm) are usually poorly controlled leading to unnecessary loss of combustibles from the flotation system. This is mainly because coal flotation cells are typically controlled for process stability rather than optimisation of flotation performance. This is especially true for a flotation device commonly used in coal applications in Australia – the Jameson Cell. This then provides an opportunity to improve the flotation performance by shifting from a stabilising control strategy to a proactive optimising control strategy. For an optimising control strategy, the control system will require a means of relating and then measuring in real-time, the effect of changing operating conditions on the coal flotation performance. Hence, the major aim of this work is to propose a possible model-informed process control strategy that could be used for real-time performance optimisation. In this study, industrial site work was conducted on an industrial-scaled Jameson Cell at a Coal Handling and Preparation Plant (CHPP) in Central Queensland, Australia where superficial gas velocity was controlled to six different levels. At the same time, other process variables such as froth depth and flotation feed properties were measured. The empirical models developed from this study suggested that combustible recovery is a function of superficial gas velocity, froth depth, feed solid content and feed ash content and that a peak in combustible recovery existed as a function of superficial gas velocity. This led to the development of a model-informed control strategy that aimed to maximise the combustible recovery by determining and then operating the cell at the superficial gas velocity at which the peak occurs. This peak superficial gas velocity was found to be only a function of feed solid content. Based on these findings it would seem possible to operate a Jameson cell at peak performance by online measurement of feed solid content, prediction of the optimum superficial gas velocity and stabilising control to maintain operation at that superficial gas velocity set point. The development of this modelinformed control strategy can serve as a basis for the development of a more sophisticated modelpredictive control (MPC) system. However, more work will need to be done to improve the predictivity of the combustible recovery model by measuring and modelling performance over a wider range of operating conditions.

Aug 24, 2022

By A Castillo, K Wiese, L Panduro Robles

For decades, organisations worldwide have been working to overcome challenges associated with new technology adoption while keeping up with rapid growth, development, and globalisation. In minerals processing, the challenges in developing and implementing solutions that contribute to the mining value chain are unique from other markets, as mining operations expect that world-class suppliers provide them solutions to gain a competitive advantage in their operation, production, performance as a financial asset, and as a long-term partner as we move into the future of mining. A simple shift in mindset is proven key to successful technology implementation. Change leaders must no longer think of their expertise in the area of application as their only responsibility; they must make a mental shift and see themselves in dual roles that strive to integrate the perspectives and needs of both developers and users. Successful change leaders must: (1) collaborate, seeking user involvement to ensure fit between product and operational needs, (2) demonstrate commitment to receive new technology, and (3) communicate to achieve an eventual shift of ownership from supplier to users that is seamless. Additionally, this strategy contributes to the mining value chain, as it allows developers and implementers to evaluate how change contributes to the asset’s position both within the company and in the commodities market. This paper will explain the shift in perspective for new technology implementation in detail and provide recommendations that operations can emulate, using examples of real challenges and lessons learned during a commissioning of the CYCLONEtrac™ Particle Size Tracking (PST) system at Cerro Verde’s C2 Concentrator. This concentrator has led technological change for plant optimisation, witnessed improved Net Metal Production (NMP), among other benefits with PST, the only technology in the market capable of providing real-time, online, and direct particle size measurement at the individual hydrocyclone level

Aug 24, 2022

By S Gray

Based on the 2021 Volume 5 State of PlayTM mining survey of key executives and board members in the mining sector, the key responses to ‘Which of the following technologies will have the biggest impact on mining in the next 15 years?’, were ‘Sensing and Data’ followed by ‘AI and Analytics’. From the early 1970s it would have been unlikely to predict the level of sensing and automation introduced to the broad industrial sector. No better example is the automobile industry where the combination of technological advances and external drivers (such as emissions control) have driven an incredible rate of change. The introduction of sensing, data, AI, and automation in the mining industry is just ramping up. Until now our energy efficiency, environmental footprint, labour shortage, skills, and safety have not been challenged by stakeholders in the way we are seeing market forces develop today. In order to address these challenges, we need to look back to the automobile industry and learn their lessons to accelerate our application of digital capability, analysis, AI and automation This is critical, particularly as access to skilled human resources becomes more difficult. An example of how this can be achieved in a gold processing plant utilising the latest real-time sensing technologies is the ‘Carbon Scout’ developed by Curtin University, and OLGA developed by CSIRO, which are both online technologies, coupled together with Gekko’s ‘Neon’ digital platform to achieve a fully automated real-time gold processing system.

Aug 24, 2022

By T Perera, B Fan, S Thang, T Hsia

Minerals are valuable resources and critical elements for a broad range of biological and technological applications, including technological developments to improve energy efficiency and the global movement to promote a low-carbon economy. However, in order to extract these critical metals, large amounts of waste and toxic chemicals are generated, as well as the use of high energy and large amounts of water consumption. Froth flotation is one of the most commonly used processes to separate and collect high-value minerals, but it still has some limitations, including low flotation efficiency performances using existing collectors and other reagents. Therefore, there is an urgent need to design and develop new metal-specific collectors to more efficiently separate and recover valuable minerals and to allow bulk water recovery from flocculated tailings. In this research, we propose to use our newly designed and synthesised novel collectors derived from a type of vitamin E (α-tocopherol), a relatively inexpensive and non-toxic natural molecule. As a potential collector-building block, α-tocopherol has a long hydrophobic carbon chain that facilitates the attachment to air bubbles during the froth flotation process. In addition, the phenol group of this molecule can be easily modified to incorporate various functional groups for targeting different types of minerals. Furthermore, α-tocopherol can be converted into a monomer for polymerisation by the reversible addition-fragmentation chain-transfer (RAFT) process, which can provide us with polymer based-collectors with high precision control of molecular weight and architecture. So far, small-scale qualitative experiments on α-tocopherol-based collectors have been performed with good results, which indicates the feasibility of these compounds as novel collectors for improved froth flotation processes.

Aug 24, 2022

By J J. Hanhiniemi, M S. Powell

A ‘Variable Blend and Rates’ model is developed for SAG mills which extends upon the JKSimMet® Variable Rates Model. Similarly, a ‘Variable Blend Residence Constrained Perfect Mixing’ Ball Mill model is also introduced, also extending upon the existing JKSimMet® model. These models are used in conjunction with JKSimMet® while employing external technical programs. The technical model is then used to inform an economic model described elsewhere in Hanhiniemi and Powell (2022), which calculate operating and unit costs based on operating conditions, design, and ore characterisation. The SAG and ball mill models include constraints beyond those in the JKSimMet® models. The SAG model constraints include Size Specific Energy (SSE) verification, charge weight limit, and assessment of the impact of media to ore composition in the charge using the SAG Charge SSE Model developed in this paper. The ball mill model includes residence time, volumetric capacity, and SSE verification constraints. These models are applied to Cortez Gold Mine in the processing of two very different ore types and their blends; ‘Horse Canyon’ which is softer in coarser sizes and competent is fine sizes, and ‘Wenban’ which is competent at coarser sizes but softer in fine sizes than Horse Canyon. Horse Canyon also has a finer run-of-mine size distribution then Wenban. The application of the model at this site included undertaking five surveys at varying blends. The behaviours of the blends and individual components is then studied in the SABC circuit. A nonlinearity is observed with throughputs increasing with blending. The newly developed modelling approach captures these responses. Controlled blending based on ore competence-by-size and size distribution was implemented by the site, which then realised significant improvements in throughput without any capital cost (Ntiamoah et al, 2020). The modelling developed in this paper is then compared to existing practice, and the new method was found to provide improved fidelity and utility. A three-dimensional surface is then developed using the model describing the SAG mill throughput capacity at varying conditions (speed-filling) versus varying blend. The change in throughput as a function of only the changing charge composition is presented. The result is nonlinear, and explanations are provided to describe this behaviour.

Aug 24, 2022

By K Mayank, A N. Mainza, I Govender, M Narasimha, A Mittal

In mineral processing industries grinding is the most energy-consuming process. A tumbling mill is an essential grinding equipment widely used for particle size reduction. Power consumption, impact forces and trajectory paths are critical parameters for characterising a tumbling mill to determine grinding efficiency. The effect of lifters and mill speed plays a vital role in such parameters. However, most of the studies ignore the impact of the lifter and do not investigate the effect of slurry dynamics on charge motion. The focus of the present work is to prepare a computational model that can accurately predict the complex multi-phase dynamics of charge particles, air and slurry inside the mill using a model that couples computational fluid dynamics (CFD) and the discrete element method (DEM). The details of impact forces with lifter profiles and mill speed variations will be refined even further using the CFD-DEM coupling approach. The slurry-air free surface is modelled using the volume of fluid (VOF) method, and the charge motion is modelled using the DEM. The phases are coupled using the interface momentum exchange between the charge and the fluid slurry. The coupled model is validated against experimental results from the positron-emitting particle tracking (PEPT) data. The validated model compares the effect of slurry content on charge dynamics with the dry DEM model. The presence of slurry is observed to dampen the tangential and shear contact forces.

Aug 24, 2022

By D Teyhan, J Kirsch

Traditionally, most Australian iron ore mining operations have been surface-based. Processing plants were designed to handle dry ores. In recent years mining operations in the Pilbara have progressively moved below the water table exposing wet, sticky ores which have caused lost efficiency in screening operations as particles tend to agglomerate and adhere, blinding screening media. Miners and vibrating screen manufacturers have experimented with a shift from linear motion to elliptical motion screens. Elliptical motion conveys and lifts particles. Effective on flat deck (horizontal and inclined) or sloping decks it can be configured to provide a controlled transport rate, applying pressure in all directions to maximise screening efficiency. In practice, elliptical motion screens have proven to be effective in dislodging sticky particles from screening media, reducing blinding rates and improving screen efficiency. Moisture and clay content change during the life of a mine. These changes are sometimes the effect of seasonal rainfall, in other cases due to increased groundwater and clay content as mining operations go deeper. To compensate for such changes and optimise screen efficiency, changing the ‘shape’ of elliptical screen motion is required. This has traditionally required shutting down processing plants and making mechanical screen adjustments. Plant downtime is costly and machine adjustment has been a ‘trial and error’ practice. This paper will explore the results of a field trial that is currently underway in Brazil of a next generation elliptical motion screen design that allows operators to make changes to exciter rotational direction, speed and screen stroke angle, through electronic drive phase control. The machine’s electronic drive system synchronisation is enhanced for stability with a unique mechanical timing system. Operating at up to 6 g, screen adjustments can be made on the fly without stopping production. Early trial results are showing up to 50 per cent improvement in screen efficiency compared with traditional elliptical motion machines under certain feed conditions.

Aug 24, 2022

By P Ireland, S Mitra, G Evans, A Wang, M M. Hoque

This work presents an experimental study of flow dynamics in a bubble column system (crosssection: 100 mm × 100 mm) using a non-intrusive optical technique with targeted application in a novel REFLUX™ Flotation Cell. The study had two aims – measurement of the bubble size distribution (BSD) and local energy dissipation rate in the system due to bubble motions over a low range of gas flux varied from 0.02 to 0.08 cm/s without impairing the visibility of the system. A central bubble plume was generated by injecting compressed air through a sintered glass distributor in quiescent liquid. Highspeed shadowgraphy imaging was performed to determine the BSD in the presence of surfactant (Sodium Dodecyl Sulfate (SDS) concentration ~ 10 ppm). The BSD exhibited a unimodal shape at different locations of the column for all gas flux cases. A non-intrusive particle image velocimetry (PIV) technique was used to quantify the flow field generated by the bubble motions, which was used to estimate the local energy dissipation rate. The local energy dissipation rate exhibited an increasing power-law dependency on the gas flux.

Aug 24, 2022

By H Park, L Wang

Froth flotation is one of the most widely used beneficiation processes for fine and ultrafine coals and minerals. Maintaining optimal metallurgical performance in industrial flotation operation is still a challenging task owing to the lack of an effective tool to diagnose the flotation performance in realtime. For this purpose, a number of flotation performance monitoring systems with different working principles have been developed to provide instant feedback for process control and optimisation. In this paper, for the first time, five different flotation performance monitoring systems were systematically compared through an on-site trial in a coking coal flotation plant in Queensland, Australia. The monitoring systems were used to measure (i) gas holdup, (ii) overflowing froth velocity, (iii) overflowing froth height, (iv) air recovery and (v) drag force exerted by overflowing froth, in an industrial flotation column and the outputs of these systems were collected simultaneously at a wide range of operating conditions. For each monitoring system, the best regression model describing the correlation between the system output and the flotation performance was selected from various regression models (eg linear, quadratic, power-law and logarithmic) using the Akaike information criterion (AIC). A comparison of the coefficient of determination (R2 ), residual sum of squares (RSS) and measuring accuracy at 95 per cent confidence level of the best regression models of these monitoring systems suggested that the drag sensor outperformed the other systems at a wide range of flotation operating conditions. The superior performance of the drag sensor was attributed to its distinctive design that enabled intimate sensing of variation of the overflowing froth properties. Furthermore, the drag sensor had the ability to monitor feed ash content variation when the other operation variables were set almost constant.

Aug 24, 2022

By G R. Ballantyne, A N. Mainza, M S. Powell, M Evertsson

Quantifying the performance of a comminution circuit relative to the potential that can be achieved is a standard requirement in justifying operating practice (the stick) and seeking operational upside (the carrot). Historic measures tend to focus on performance relative to laboratory design tests that provide a direct measure of specific grinding energy, such as the Bond Work index; or use dropweight breakage tests calibrated to a substantial database of operating sites, such as the SMC methodology. Although of value, such approaches are flawed in significant aspects. The assumption is that the laboratory prediction is correct and the single sample it is based on is representative. The database benchmarking methods are, by definition, locked into current average operating practice. These approaches do not illuminate upside; can ‘punish’ operations that are actually more efficient, such as grinding finer than standard operation; and reward poor operation that may comfortably produce a coarser grind than optimal for recovery or excess slimes that reduce recovery and increase water consumption and tailings volume. The authors present a set of established and easily applied measures, that draw together daily operation, highlight areas of opportunity and inefficiency, use simple samples and data, and can be used to provide the ‘size of the prize’ in pursuing specific areas of process improvement. These tools include size specific energy (SSE), overall operating effectiveness (OEE) which includes product quality, theory of constraints, and links this to the end objective – maximising the efficient production of valuable metals. Feeds into objective function driven by economics – financial return, energy, environment.

Aug 24, 2022

By K Barbosa, G Wilkie, F Reyes, V Jokovic, C Evans

The idea behind Grade Engineering is to exploit the natural heterogeneity of an orebody (spatial, temporal) in order to divert low-value waste out of the mining value chain. Essentially, this involves rejecting material at relatively coarse particle sizes (10 mm to 200 mm). However, lack of knowledge about the inherent particle grade distributions in these coarse particle size ranges limits the opportunities for optimisation. Particle grade distributions are essential for quantifying and modelling gangue liberation and yield curves. These curves can then be used to predict the mass and value flows that will go towards the accept and the reject streams. Particle grade distribution information for particles coarser than 10 mm can be collected based on chemical assays of sufficient number of individual particles. However, for smaller particles (1 mm to 9 mm), a significantly larger number of particles is required for assays. Moreover, in some cases, the mass of individual particles is smaller than the minimum mass required for chemical assaying. Also, other quantification techniques such as automated mineralogy, eg Mineral Liberation Analysis (MLA), require extended measurement times to analyse statistically representative numbers of particles at these size ranges. This work investigates the use of 3D X-ray microtomography to fill this quantification gap at these size ranges (1 mm to 9 mm). In-house image processing algorithms are used to estimate the mineral/metal content in each particle. Particle grade distributions, as well as density distributions, are thus produced without a minimum mass requirement and with each scan providing information about tens to hundreds of particles at a time. Mineralogical data from MLA analysis, of finer size ranges, is used to inform X-ray microtomography, so a simpler 3D mineral map can be obtained using the image intensity. Chemical assay information of the scanned samples is used to validate and correct the mineral phase segmentation.

Aug 24, 2022

By R H. Yoon, M Gupta, A Noble, K Huang

Froth flotation is the most commonly used separation technology in the mineral industries. Given the complexity of the pulp and froth phases as well as the multitude of operational parameters that influence flotation performance, purely fundamental models with strong predictive capacity are limited. As a result, accurately modelling modifications to an existing flotation circuit are challenging, particularly when using empirically-derived models from a different operating configuration. Despite these complexities, a recent publication by the authors (Huang et al, 2022) has shown that flotation rates can be accurately predicted from a first-principles model that incorporates hydrodynamic parameters (eg pulp density, superficial gas velocity, feed flow rates etc), surface chemistry parameters (eg contact angle, zeta potentials and surface tension), and size-by-class liberation data. Circuit simulations using this model were shown to be effective in predicting experimental graderecovery curves from the size-by-class mineral liberation matrix. Since the model is derived from fundamental characteristics of the flotation system, it can be used to simulate alternative circuit configurations with varying degrees of recycle. Conventional flotation circuits are operated in a closed-circuit configuration by routing the cleaner scavenger tails (CST) back to the rougher feed to provide an additional opportunity to recover the slow-floating particles. This widely-used flotation strategy has been under constant debate, and several researchers have provided evidence that open circuit configurations provide higher separation and better circuit control (Konigsman, 1985; Bulatovic et al, 1998; Thompson, 2016). Recently, Finch and Tan (2021), used linear circuit analysis to show that open circuit configurations have a fundamental advantage when stage recoveries are high. Given the limitations of these prior studies, the objective of the current work is to further evaluate the merits of the open circuit configuration through a detailed circuit analysis and simulation study incorporating the first principles model described above.

Aug 24, 2022

By H Park, D J. Holland, L Wang, Y Matviychuk, Y Lee

Reuse of process water in mineral and coal flotation plants is widespread to effectively reduce freshwater consumption. However, the accumulation of the frother in the recycled process water is a growing problem as high remnant frother concentration often leads to undesirable overfrothing issues throughout the plants. Various approaches have been proposed by others to measure frother concentration, but none of them is used in flotation practice owing to the requirement of timeconsuming sample preparation steps and/or specialist training to operate and maintain. There is a pressing need for the development of a simple and fast frother concentration measuring technique to avoid overfrothing issues and to optimise the flotation process. The present paper presents two promising approaches to measuring frother concentration online. The first approach measures the concentration of alcohol type frothers based on the host-guest interactions between frother molecules and a formulated liquid. This method is simple and fast as it only requires mixing the formulated liquid with the water sample for up to one minute. The potential of this approach was demonstrated by determination of the residual MIBC concentrations at different locations across a coal flotation plant. The second approach measures frother concentration using a solid-phase extraction (SPE) process and a cryogen-free benchtop NMR spectrometer. Using this approach, both alcohol type and polyglycol type frother solutions can be analysed for concentration determination within 30 minutes. It has also been demonstrated that the concentration of individual frothers in a frother blend (ie MIBC and PPG425 in water) can be accurately analysed even in the presence of background chemicals. This technique has otential for real-time measurement of frother concentration as the whole process can be fully automated.

Aug 24, 2022

By G P. W Suyantara, Y Tanaka, T Hirajima, Y Aoki, K Sasaki, H Miki

The effect of sodium sulfite (Na2SO3) on the flotation behaviour of bornite and tennantite is reported in this work. Flotation tests were performed using pure minerals of bornite and tennantite under various concentrations of sodium sulfite at pH 9. The flotation results indicated that sodium sulfite exhibited a depressing effect on the floatability of bornite in the presence of 0.1 mM PAX. However, tennantite remained floatable after the addition of sodium sulfite in the presence of 0.1 mM PAX. The flotation tests using mixed bornite and tennantite confirmed the flotation results of single minerals. Surface characterisation using X-ray photoelectron spectroscopy (XPS) was performed to explain the flotation results. A mechanism is proposed based on the XPS analysis results.

Aug 24, 2022

By L O. Filippov, A Piçarra, I V. Filippova, N P. Lima, K Silva

The reverse cationic flotation using the starch as depressor of iron oxides is the most efficient upgrading process when is applied to the simple systems composed by hematite/magnetite and quartz. The fundamental studies performed with iron ore samples from different deposits over the world (Brazil, Russia, Mexico) confirmed the inefficiency of starch when the silica content in the concentrate is controlled by Fe/Mg-bearing minerals. The main approaches for solving these issues focused on using new collector formulations or new depressants. However, the alternative depressants tested inhibited flotation of quartz or were less efficient as iron oxide depressant. In this work, a comparison between new amidoamine collector with conventionally used etheramine and oleate collectors in the flotation of pure minerals and actual iron ore samples was performed. The electrophoretic mobility, contact angle and infrared spectroscopy measurements allowed to deduce the hindrance effect as main mechanism of selective adsorption of the amidoamine on the quartz surface compared to hematite and kaolinite. Molecular modelling studies revealed that this steric hindrance effect can be explained by the combination of the "shield" formed by the coordinating water molecules on the (001)-D2 hematite surface and the large volume of the amidoamine head group. The amidoamine tested as collector without use of a depressant showed excellent flotation selectivity allowing the total flotation of quartz from a mixture with hematite. High collector performance and selectivity were confirmed during reverse flotation of quartz using continuous flotation column (D = 500 mm; H = 4000 mm) and allowed to produce the iron concentrates with more than 60 per cent of iron from the rejected slimes samples of Vargem Grande 2 processing plant (Iron Quadrangle, MG, Brazil). The new collector allowed to develop flexible flotation flow sheets to process the iron ore with a complex gangue mineralogy and unlock the old altered tailings and slimes product as new resources

Aug 24, 2022

By J Kuva, M Parian, B I. Pålsson

One of the main factors affecting the suitability of an ore for autogenous grinding is the ore’s competency, ie providing enough critical stones for the grinding process. Several experimental test routines exist and are used for assessing the viability of the ore for autogenous grinding. However, very little attention is given to the generation of fatigue in large stones experiencing repeated shocks in the mill. To investigate this, large pebbles sampled from an industrial autogenous grinding mill running hard and soft ores were categorised based on the grinding energy. From the pebbles, small drill core samples were prepared and went through a series of fatigue cycle tests. Both hard and soft ores showed similar average resistance to failure in compression tests, but the hard ore had a consistent resistance with lower variations. The cores were scanned by XCT before and in-between fatigue tests at the highest reachable resolution, 1.5 µm voxel size. The outcome showed that a higher number of micro-cracks were visible in the soft ore compared to the hard ore. The frequency of micro-crack development in the soft ore may be the reason for its lower specific grinding energy compared to the hard ore. It is obvious that for realistic conditions in an autogenous grinding mill, stones are pre-weakened by fatigue before they fracture. Therefore, shortcut methods focusing only on running tests on fresh and small samples may operate in unrealistic conditions by ignoring the fatigue phenomenon. This is even more important for ores that are on the borderline to be considered as competent for autogenous milling.

Aug 24, 2022

By M Yahyaei, F Reyes, R Lage, V Jokovic

Equipment wear is strongly related to the performance of grinding circuits. In particular, SAG mills are subjected to the wear of their shell liners and grates. Changes in lifter height and face angle impact mill performance, while classification at the mill discharge is also affected as grates wear out. Moreover, liner mass loss caused by wear affects how operators interpret readings of sensors such as load cells or bearings pressure. Automating and optimising grinding circuits under these constrain becomes challenging due to the nonlinear and dynamic nature of the system. The operation of SAG mill grinding circuits remains largely dependent on human intervention, which frequently results in inconsistencies in performance across shifts, reflecting the operator’s personal preferences, experience, and other human factors. The influence of human factors can be reduced by careful training of operators as well as by automation using advanced supervisory control. The latter approaches could benefit from the development of dynamic process models that consider the effects of wear on the performance of equipment over time. This paper presents detailed industrial data showing the effects of wear on SAG mill performance. Additionally, a dynamic SAG mill model that accounts for these phenomena is proposed and demonstrated in a simulated environment. This model is shown to mimic the effect of wear on the performance of industrial scale mills and the operational constraints they are subject to, thus extending traditional SAG mill models. Incorporating wear into modelling and simulation platforms can improve the understanding of the effects that wear can have on the performance of key assets in comminution circuits and may allow the development of more robust model-based advanced process control strategies.

Aug 24, 2022

By J Moffatt, T Payten, N Spooner, L Teixeira, L A. Balzan, G Wilkie, G Tsiminis

Fluorine is a penalty element due to its reactive nature. In acidic environments many fluorine minerals dissolve to form hydrofluoric acid (HF), changing processing conditions. When smelted HF can be released, causing negative effects to nearby people and the environment, as well as potentially damaging the smelter. Sale of ore with high fluorine levels elicit a financial penalty or are banned outright. Real-time sensors create the opportunity for instantaneous decisions on ore processing due to changing conditions. A fluorine sensor would allow rises in fluorine concentration in a processing stream to be flagged, and decisions on processing conditions or diversion to stockpile before processing could be undertaken. As fluorine is a light element, it is difficult to detect with in-field XRF devices and does not work well with PGNAA. There are currently no existing sensors to quantify the presence of fluorine in real-time, and thus decisions based on fluorine grade cannot be made at minute- or even hour-scales. Sensors designed to measure the presence of minerals that contain fluorine are a possible avenue to enable the real-time detection of this element. Mineral-based sensing may also give an added advantage of additional information about how the fluorine will react under different processing steps. The authors were given a grant under CRC ORE II (project number P1–005) to search for mineralspecific signatures suitable for real-time analysis. The work focused on novel regimes and applications of fluorescence as a means to detect specific minerals. The aim was to exploit fluorescence responses unique to minerals of interest in mining systems in order to produce sensors that address gaps in existing capability. After the successful discovery of signatures specific to two major fluorine minerals an additional grant (P1–014) was funded to develop the research into a prototype on-belt sensor, in partnership with Scantech International Pty Ltd. This paper details the development of a sensor package through multiple Technology Readiness Levels (TRLs) through collaboration with government/industry grant schemes, academics from university, and a sensor-focused Mining Equipment and Technology Services (METS) company. We give a brief description of the new sensor technique and provide a case study of multi-disciplinary collaboration.

Aug 24, 2022

By A Batnasan

The main techniques for removing phosphorus as an impurity element in iron ores are physical separation (eg magnetic separation, flotation) and chemical separation (acid leaching, alkaline leaching and bioleaching) processes. When phosphorus occurs in iron ores as phosphate minerals (eg apatite), physical separation techniques are available to remove the gangue minerals from iron ores. On the other hand, chemical separation techniques are suitable for reducing phosphorus levels when phosphorus is associated with iron oxides and hydroxide minerals (eg hematite and goethite) in iron ores. In this study, the dephosphorisation behaviour of high‐phosphorus iron ore was investigated using a combined alkaline roasting and water washing route. Roasting experiments were conducted in a laboratory electric muffle furnace using various concentrations of sodium hydroxide (0–50 g/kg-ore) at different temperatures (100–800°C), varying prolonged roasting times (0–2 h), and different particle size fractions (-45 – -250 μm) of iron ore. Subsequent water washing experiments were employed at various pulp densities (30–1000 g/L) and different times (30 s – 60 min) at ambient temperature. Hematite and goethite were the main minerals in the high-phosphorus iron ore identified using X-ray diffraction (XRD) analysis. The iron ore assaying 63.40 mass % Fe (total), 0.240 mass % P, 4.53 mass % SiO2, and 4.87 mass % Al2O3 were determined using X-ray fluorescence (XRF) analysis. The results showed that the dephosphorisation rate of the iron ore was reached 40 per cent under roasting with 50 g/kg-ore NaOH at 300°C for 2 hours followed by water washing for 30 s with a pulp density of 300 g/L, reducing phosphorus level from 0.240 mass % to 0.142 mass %. At the same time, the iron grade was reduced from 63.4 per cent to 59.5 per cent, caused by an iron loss. Results suggest that the phase transformation of goethite induces the dephosphorisation of high-phosphorus iron ore under alkaline roasting conditions

Aug 22, 2022