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By B Ellis

Brunswick Mine is one of the largest underground zinc/lead mines in Canada, producing 3.4 million tones of ore annually. As mining activities advance to deeper levels, ground pressure also becomes greater. To cope with the highly stressed ground, the mine has taken some strategic measures to ensure the targeted production level. Such measures include the implementation of a pastefill system and transferring the mining method from primary/secondary stoping to pillarless pyramid stoping. With the pillarless mining method, stope sizes become smaller and the number of active stopes is also less than before. In addition, mining sequence and cycle time have to be strictly followed according to production schedule. The blasting project described in this paper tackles one of the steps in the mining cycle aimed at shortening the blasting cycle time in a stope. Furthermore, this project was conducted and managed with the Six Sigma initiative in Noranda which was implemented in the fall of 1999. Like a typical process review, the blasting operation was examined by breaking it down into many steps that can be quantified and measured. Each activity was then correlated with different factors associated with blast design as well as blast operations underground. It was found that the utilisation of voids plays a key role in the blasting cycle time. With improved void utilisation ratio, blasting cycle time has been reduced from an average of 12 shifts to ten shifts per stope. This improvement translates into approximately 180 000 tonnes of ore being blasted without any increase in manpower. This paper presents the technical aspects of the study, as well as some operational issues and improvements made during the project.

Jan 1, 2001

By C Claassen, R Balusu

Computational fluid dynamics (CFD) models have been developed based upon field data collected from a longwall mine in New South Wales, Australia to study the behaviour of goaf gas flow in both active and sealed goaf areas. A base CFD model was built to represent the goaf situations when the active longwall retreats near the finish-off line. Results from the base model were calibrated and compared against field goaf gas monitoring data. The base model was then used to carry out parametric studies to investigate a number of operational scenarios and their impact on goaf gas behaviour. CFD modelling results indicate that the overall goaf gas flow pattern changes as the operating longwall retreats towards finish-off line. In all cases, oxygen penetration into the active goaf remains high, reaching 15 per cent or higher, even at some 800 m behind the longwall face.The modelling results also indicated that it would be difficult for early detection of an active goaf heating (on the maingate side) based upon CO readings in the return airflow, as the main stream of the gaseous product will be flowing into the sealed deep goafs in adjacent longwall (LW) panels. Monitoring points (such as tube bundles and bag sampling points) should be selected at deep seated seals along the active goaf so that abnormal CO or C2H6 readings can be picked up for early detection and location of potential heating spots; goaf inertisation can be better achieved by injecting inert gas such as nitrogen at deeper points (>200 m) behind the operating longwall; the injection of in-seam drainage methane into the goaf areas will only have a limited impact on goaf inertisation as much of the injected methane will migrate towards deep and higher parts of the goaf due to its buoyancy effect.

Sep 26, 2011

By K T. Broekman, R L. Koenig

"The Braemar Iron Formation is atypical ore when compared to the current magnetite ores being processed. In attempting to process and economically recover the vast quantities of iron ore stored within the Braemar Iron Formation, æshifting the paradigmÆ is required. The formation has a low Davis tube recovery (DTR) grade of 15 - 20 per cent, which is much lower than magnetite ores processed in Australia. Despite this, by thoroughly testing and understanding the ore characteristics, it is found that the Braemar ores have significant advantages to processing than the harder banded iron formation (BIF) and taconite resources.The Hawsons magnetite iron ore resource has been known from the early 1960s when CRA explored the area. The grade was low and the Pilbara region discovery lead to the development of high-grade direct shipping hematite ores. Carpentaria Exploration (CAP) rediscovered the magnetite whilst undertaking multi-commodity exploration in the Broken Hill district during 2009. Shifting the paradigm away from grade the advantages of processing this ore are achieved by having an extremely low waste to ore ratio, lower Bond work index, lower abrasion levels and high-grade magnetite concentrates with little impurities other than silica. While developing the Hawsons Iron Project (HIP) it became more apparent that a positive business case is achievable when the following factors are exploited: very large resource - the resource is contained within one pit the rock fractures easily along grain boundaries - ideal for cheap impact crushing of the ore the ore is extremely soft, with a Bond work index of 6.3 - 8.0 kWh/t all major infrastructure required is readily available - rail, power, access and port the mine is in close proximity to Broken Hill - rich mining history and skill set available the resource contains many billions of tonnes of magnetite mineralisation.Shifting the paradigm by selecting equipment suitable for processing soft ores and not hard BIF or taconite ores and taking locality and available infrastructure into account may change the way people approach new low-grade resources in future.CITATION:Koenig, R L and Broekman, K T, 2013. Understanding ore characteristics and equipment selection, in Proceedings Iron Ore 2013, pp 403-410 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Aug 12, 2013

By P Minkkinen, J Lohilahti, T Korpela, B McPherson

Concentrator plants intake the ore from the mine and produce concentrates by extracting valuable minerals in a succession of process steps. Controlling the extraction process and detecting changes in the process requires updated information on a minute basis. Moreover, due to economical reasons, one must also collect metallurgical samples on a daily basis for monthly reporting.In this paper, we present how slurry samplers were installed in a Cu-Ni flotation plant to accomplish the aforementioned tasks. An on-stream elemental analyser at the plant is used for flotation process control by taking samples from selected process streams. Two process streams, the flotation feed and tail, are also equipped with metallurgical samplers. The metallurgical samplers were designed to have low head loss, be robust and easy to maintain and to collect slurry samples in a reliable way for the metallurgical accounting.Samples were collected by different sampler types and we discuss the uncertainty arising from sampling in the assays. Variographic analysis was carried out on the process data in order to find periodic components in the process, and estimate the correct number of shift sample increments and measurement error components. The metallurgical samplers were proven to be reliable devices with zero downtime and no sanding issues in the main process flows. In addition, we show that the tail measurement is the most important one for the plant recovery calculation, which emphasises the importance of the sampling accuracy in the tail stream.CITATION:Lohilahti, J, Korpela, T, Minkkinen, P and McPherson, B, 2014. Analysis of slurry sampling arrangements at a froth flotation plant, in Proceedings Sampling 2014 , pp 91–98 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By Stevenson C. H, Lynch A. J

The reasons for choosing autogenous grinding for the new Warrego concentrator of Peko Mines N.L. are discussed and the ores to be treated in the concentrator are described. The mill was designed on the basis of pilot tests carried out at Cobar and the performance of the mill has been most satisfactory both in its metallurgical and mechanical aspects. An empirical technique has been developed to predict mill performance for change in feed rate or feed size and a mathematical model of the mill is being developed for simulation and control work. The weight and size distribution of the mill load was determined at one set of operating conditions for use in the mill model.

Jan 1, 1974

By G W. Swana

Elastoplastic parameter is a parameter that describe how much materials behave elastically up to certain stress states and plastically thereafter (Hudson and Harrison, 1997). In the continuum analysis, two main parameters of the elastoplastic parameter are modulus elasticity and Poisson’s ratio. In the slope, elastoplastic parameter holds the main role for stability related to deformation in ductile type of rock. There’s a limitation to determine elastic or plastic deformation at the field for ductile rock type. Field manifestation commonly showed that there was no accumulation zone during and after the sliding failure mechanism, in other hand, at the research area, manifestation of deformation at the toe of slope only indicated by bulging shape. This paper will focus at the sliding failure occurred at Coal mining Pit Y owned by Arutmin Indonesia, which according to failure investigation report similar with the condition described above. This paper also will be based on two hypotheses, first hypothesis is claystone rock mass has not been reached plastic deformation yet and the second hypothesis is there is a chance that elastoplastic parameter of the rock mass has been changed during the deformation/sliding failure process. Research method of this paper are back analysis using probabilistic analysis in Finite Element Method (FEM), which conducted before and after failure. Then, the result of the displacement or deformation of the analysis will be checked with the actual deformation shape. Meanwhile, the change of the elastoplastic parameter will be analysed and interpreted. This paper hopefully able to be developed to study about elastoplastic behaviour of rock mass in actual condition and the influence of another uncertainty factor which determine the slope stability.

Nov 29, 2022

By Baxter D. A

This paper, one of two written about the Queensland Railways Brunswick Street tunnels presented at the VIII Australian Tunnelling Conference, 1993, describes the design and monitoring aspects of the railway tunnels built between Central Station and Brunswick Street Station.The design was mainly influenced by the need to minimise settlement of buildings above the route. The performance of the design details and the monitoring of the tunnels are briefly described.Appendices include extensions to the work of Curtis in the analysis of circular tunnels in a viscoelastic ground.Reference: Asche, H R and Baxter, D A, 1993. Design and ground support monitoring of the Brunwick Street rail tunnels, Brisbane, VIII Australian Tunnelling Conference.

Jan 1, 1993

By V S. Vutukuri, K Shariar

This paper present a modification of selected strength criteria for coal and rocks containing weakness planes. The three strength criteria, namely, Murrell (1965), Bieniawski (1974a, 1983) and Hoek and Brown (1980) have been assessed for coal (containing weakness planes) by using triaxial strength tests. Triaxial test results indicated that the strength of coal specimens depends on the weakness plane inclination with respect to the principal stress direction. However it is shown that with increasing confining pressure, the effect of weakness planes inclination on the strength of coal specimens is reduced. The constant parameters in the three failure criteria for coal are determined for each weakness plane inclination by using the Datafit computer program (nonlinear regression analysis) and the results are compared with other rock types.

Jan 1, 1999

By S Farrokhpay, C Akop

Copper-gold-pyrite ore types with an elevated pyrite head grade utilise a sequential flotation circuit to recover initially a copper-gold concentrate with a pyrite-gold concentrate being produced from the tailing of the initial circuit.A simpler flotation circuit with lower operating and capital costs for treatment of such copper-gold-pyrite ores with an elevated pyrite head assay was sought in the described work. After characterising the ore, the objective was to apply bulk rougher flotation of both the copper minerals and pyrite for the copper-gold-pyrite ore at natural pH. Hence, no lime or other pyrite depressants were required in bulk roughing. The bulk rougher concentrate was upgraded in a cleaner circuit to reject non-sulfide gangue and then the resulting sulfide concentrate was separated by depressing the pyrite to produce two products (copper and pyrite concentrates, both having significant gold assays). A standard test with a sequential circuit was applied to the same ore for comparison.The chalcopyrite and pyrite losses in the tailing from the rougher circuit were the same for both bulk and sequential roughing (less than six per cent). In cleaning (bulk circuit), the effective pH for pyrite depression was 11.8–11.9; copper recovery was 70–75 per cent (grade of 15–20 per cent copper) and the sulfur recovery (pyrite product) was 80–85 per cent (grade of 34–36 per cent sulfur).These results approached those for the sequential circuit where copper recovery was 80–85 per cent (grade of 15–20 per cent copper) and the sulfur recovery (pyrite product) was 83 per cent (grade of 38 per cent sulfur).The observed effects of feed sizing on the liberation of minerals in the rougher feed are discussed. Options for improving the bulk circuit results are also considered. Importantly, the implications of various aspects of these findings for the bulk circuit are discussed with an industrial focus.CITATION:Akop, C, Farrokhpay, S and Johnson, N W, 2014. An alternative circuit for chalcopyrite-pyrite ores with elevated pyrite content in Cu-Au ore treatment, in Proceedings 12th AusIMM Mill Operators’ Conference 2014 , pp 407–416 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 1, 2014

By H Ishikawa, H Zhou, M Spagnolo, R Halomoan, S Palaniandy

The Karara Mine concentrator commenced operation in November 2012 to produce high-grade magnetite concentrate. The circuit consists of three stages of comminution plus magnetic separation at each stage for early gangue rejection. High-Pressure Grinding Rolls (HPGRs) are used for fine crushing, followed by ball mills and TowerMills in secondary and fine grinding duties respectively. In recent times, the plant throughput rate has had to exceed design by 18% to maintain the targeted concentrate productivity. Meanwhile, the ore hardness has increased by 25% to 15 kWh/t, leading to changes in the circuit operation and design. These changes led to coarser and harder feed to the TowerMill circuit that affects the subsequent separation processes. Nippon Eirich (the TowerMill manufacturer) has partnered with Karara Mining Limited (Karara) to optimise the TowerMill circuit operation to achieve a circuit product with an 80% passing (P80) of 35 µm. Several activities, including a TowerMill circuit audit and performance evaluation, multi-component analysis, modelling and simulation, were carried out as part of the optimisation exercise. The circuit audit results revealed that the TowerMill circuit feed size F80 had increased and ranged from 67–75 µm. The circuit product P80 ranged between 42–55 µm. The average circuit specific energy was 3.4 kWh/t. Moreover, the differences in density between magnetite and gangue minerals had affected the hydrocyclone performance where the efficiency curve exhibits coarse end deflection indicating that low-density coarse material was bypassing to the overflow stream. A multi-component analysis was carried out to further investigate the coarse end deflection of the hydrocyclone efficiency curve. The analysis showed that the magnetite and gangue minerals had different cut sizes of 32 and 64 µm respectively. Furthermore, 33% of the magnetite (below 35 µm) was being recycled back to the mill due to the density effect. Based on these findings, several recommendations for process improvement were identified and implemented including:• converting to a bottom feeding configuration to improve the grinding efficiency in the mill• additional grinding power in the fine grinding duty to compensate for the increase in plant throughput and ore hardness• improved classification efficiency by converting to smaller size hydrocyclones. Simulation studies carried out to evaluate the impact of these implementations had indicated that a P80 close to 35 µm with a steeper size distribution could be achieved by using the bottom feed configuration with additional grinding power. The TowerMill circuit was converted to bottom feed configuration and the performance was evaluated. The operating work index, size specific energy and circulating load were 30% lower than the top feed configuration, indicating that the bottom feed configuration had a higher grinding efficiency. This paper discusses the outcome of the circuit audit, multicomponent analysis, circuit simulations, improvement strategies and quantification of the improvements. CITATION:Palaniandy, S, Spagnolo, M, Halomoan, R, Zhou, H and Ishikawa, H, 2017. Fine grinding circuit process improvement at the Karara mine concentrator, in Proceedings MetPlant 2017, pp 101–120 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 11, 2017

In practice a sampling solution is a compromise of many requirements: the sample should be representative; the sampling system should also be reliable, less than 95 per cent availability restricts the use of the assayed sample for process control purposes; no sample is the worst sample, and investment costs and installation space/layout are frequently a restriction. For instance, online X-ray analysers for process control introduce a delimitation error by the nature of X-ray physics. Thus only in special cases a relative accuracy better than three per cent relative, as one standard deviation, is achieved. A sampling system for process control needs not to be, as representative, for so many sample properties, as one for composite laboratory analysis samples. Sampling system maintenance is also an important issue. There are many sampling systems in the industry which have been difficult to maintain and are in disuse for lack of resources or incentives to keep them running. Pierre Gy developed the most generally accepted sampling theory. One of the main principles is that all particles in a one-dimensional process stream should have equal chances of being included into the sample. A correctly designed and operated transversing cutter comes close to this goal but has limitations in temporal representativity. For slurries an acceptable solution in many cases is to use a fixed vertical cutter(s) in a position where the slurry is well-mixed by turbulence and other means. For online analysis, reliability problems are mostly related to faulty design or installation of the piping system to the analyser. Properties of material processed, process flow sheet and piping details before and after the sampler have to be taken into account when deciding on which sampling arrangement is appropriate. Guidelines and some solutions to these issues are presented in this paper.

Mar 1, 2010

By JOHN G. RAYNER

An examination was made of the filtration characteristics of a haematite slurry using a range of polyacrylamide based flocculants in solutions containing up to 3 per cent sodium chloride. The polymers used were "high" and "Iow" molecular weight and had from 0 to 40 per cent charged groups.Increasing charge density tends to reduce the dose required to achieve optimum performance measured by filtration rate and by cake moisture. In general increased salt addition tends to increase the dosage required to achieve these optima. Both these observations result from the change in polymer extension and accord well with the bridging theory of flocculation.The dose required for optimal cake moisture is up to three times greater than that required for optimal filtration rate. This effect is reasonably consistent for all polymers studied and appears to be non-linearly dependent on salt concentration, with the difference being small at 0 and 3 per cent but quite significant at 1 per cent.

Jan 1, 1987

By A Garvie, D Kentwell, J Chapman

"Most new mining projects require an initial assessment of the locations and volumes of potential acid forming (PAF) waste that is likely to be moved and dumped in surface waste stockpiles. This requires sampling of the waste rock zones and submitting the samples for a series of tests. Key to the outcome of the waste characterisation process is obtaining sufficient samples that are representative of the various rock types both in number and spatial distribution.Various regulatory bodies throughout Australia and the rest of the world are currently struggling with how to define minimum amounts of sampling to achieve realistic estimates without imposing excessive costs and time constraints on a project.This paper addresses two aspects of the process: what constitutes a æsufficientÆ number of samples how to use those samples in determining volumes of likely PAF material.Geostatistical methods of characterising orebodies with large numbers of samples are routinely used in the mining industry by geologists and geostatisticians to estimate and classify Mineral Resources. In theory exactly the same methods can be used to estimate PAF waste locations and volumes.In practice the number and spatial distribution of dedicated PAF waste samples at feasibility stage is typically so small that it is almost impossible to estimate the spatial distribution of PAF material with any degree of confidence at all. Consequently, the common approach is to characterise a few samples from a lithological unit and then assume that they represent the unit as a whole. This approach, however, can be fraught with risk.This paper describes some of the findings of SRKÆs evaluation of several coal projects with respect to PAF waste evaluation and highlights some common misconceptions held by people working in this area that do not have a knowledge of statistics or geostatistics.CITATION:Kentwell, D, Garvie, A and Chapman, J, 2012. Adequacy of sampling and volume estimation for premining potential acid forming waste evaluation using statistical and geostatistical methods, in Proceedings Life-of-Mine 2012, pp 79-88 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Jul 10, 2012

By B Laidens, D Souza, W Bielefeldt

The CaO-MgO-SiO2-Al2O3 system, characterised by its intricate phases and thermodynamic properties, plays a pivotal role in steel secondary refining processes, encompassing desulfurisation, non-metallic inclusion capture, and refractory protection. Accurate predictions for diverse industrial applications, including metallurgy, ceramics, and materials science, are imperative. To address this challenge, a combination of machine learning techniques will be specifically applied to model the liquid fraction of the slag and the solid fraction of MgO. The development of an artificial intelligence (AI) system, leveraging various machine learning techniques, has gained momentum in this project. The focus of this work is on constructing an AI model, based on machine learning techniques, within the CaO-MgO-SiO2-Al2O3 system, utilising simulation results from FactSage™, version 8.1 (by GTT Technologies). The primary objective is to train the AI model using these simulation outputs to predict the percentage of liquid fraction and MgO saturation based on chemical composition parameters. The AI model will undergo training with a comprehensive data set of simulations within the CaOMgO- SiO2-Al2O3 system, covering a diverse range of compositional at 1873 K. These simulations, conducted through FactSage™ 8.1 software, provide a robust foundation for AI model training, ensuring generalisability and precise predictions for the liquid fraction of the slag and the solid fraction of MgO, the solid fraction of MgO in this case is determined by the difference between the total MgO and the MgO in the liquid fraction, so it is not the objective of this study to determine which phase of MgO is in the solid state.. The predictive capabilities of this AI model hold significant implications for process optimisation, quality control, and decision-making in CaO-MgO-SiO2-Al2O3- dependent industries. Precise estimations of the liquid fraction and MgO saturation empower researchers and engineers to enhance operational efficiency and quality. This paper explores the methodologies employed for AI model creation and training, achieved results in terms of prediction accuracy, and potential applications in the field. The development of this AI system signifies a notable advancement in utilising machine learning for better comprehension and control of complex chemical systems. Furthermore, to align the study with real-world steel production, we introduce FeO and MnO at concentrations of 2 per cent and 1 per cent at 1873 K, respectively, following the validation of model results using the CaO-MgO-SiO2-Al2O3 system. This adjustment aims to bring the study closer to the observed reality in steel mills globally.

Jun 19, 2024

By J Savage, A Crawford, M Doyle, N McNaughton, T G. Blenkinsop

Area selection criteria for gold exploration have historically highlighted the low prospectivity of high-metamorphic grade terranes relative to regions with lower metamorphic grades. The Tropicana gold project, Western Australia, is a rare example of a major greenfields gold discovery in Archean mid-amphibolite to granulite-facies gneissic rocks that have experienced widespread recrystallisation and partial melting.The project, located on the tectonically reworked eastern margin of the Yilgarn Craton, is part of the Tropicana Joint Venture, which is 70 per cent owned by AngloGold Ashanti Australia (manager) and 30 per cent by Independence Group NL. Construction of the mine commenced in the June quarter of 2011 and first gold pour from open pit mining is anticipated in the December quarter of 2013. The approved project will have a ten-year mine life and in the first three years of operation, gold production will be between 470 000 - 490 000 oz/a at a cash cost of A$590 - A$630/oz.Reserves as at 31 December 2011 total 56.4 Mt grading 2.16 g/t for 3.91 Moz of gold. The mineral resource, as of 30 December 2012, has grown to 7.89 Moz of contained gold, including Inferred Resources of 11.9 Mt at 2.83 g/t for 1.08 Moz.Economic gold mineralisation post-dates peak metamorphism and is interpreted as younger in age (ca. 2500 Ma) than other gold deposits in the Yilgarn Craton on the basis of structural and geochronological constraints. Mineralisation is genetically related to an imbricate thrust stack that records a prolonged history of reactivation during the Proterozoic era. Gold mineralisation formed from higher temperature (>350¦C) silica-undersaturated fluids that preferentially migrated though a favourable intensely potassium metasomatised zone. Permeability created during brittle fragmentation was accompanied by replacement of mafic metamorphic minerals, and synchronous partitioning of strain into pervasively biotite-sericite-pyrite-altered stylolites and shear planes that bound more competent lithons.CITATION:Doyle, M, Savage, J, Blenkinsop, T G, Crawford, A and McNaughton, N, 2013. Tropicana - unravelling the complexity of a +6 million ounce gold deposit hosted in granulite facies metamorphic rocks, in Proceedings World Gold 2013 , pp 87-94 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 26, 2013

By J E. Everett

Maximising ore tonnage at a selected target grade requires that appropriate ore identification criteria be established. Iron ore mining block models may consist of many millions of estimated blocks, each block corresponding to the selective mining unit (SMU), with grade interpolated from drill hole data. Each block can be considered as a potential ore candidate. Analysis of such a huge database can require large computational resources, especially for sensitivity analysis requiring multiple computations. However, an alternative streamlined approach is possible, where the data are compressed to an appropriately smaller and representative subset. The consequent data reduction not only makes it feasible to consider the simultaneous analysis of multiple pits but also considerably speeds up computation, enabling sensitivity analysis of the potential ore tonnage as a function of the required grade. Ore identification criteria can be successfully established using appropriately chosen reduced data comprising less than one per cent of the blocks. The ore identified is virtually indistinguishable in tonnage and grade from the ore that would be selected using the entire block model.Two methods of data reduction are tested: sampling (using a proportion of unaltered blocks) and binning (consolidating groups of blocks to a single average grade). The source blocks are first sorted (such as by location, analyte grade, principal component score, random order or value) before sampling or binning. In this study, the sorting options considered were by location and Fe grade. The effectiveness of each method was evaluated using the block model subsets to select the maximum tonnage of ore at a specified target grade. Block model data from an anonymous Pilbara iron ore project with about one million blocks averaging 1.132 kt were used. The blocks are from multiple resource models, to be blended to a single product. Sampling is shown to be superior to binning because sampling preserves the full variability while binning, although matching the mean block grades reduces their variability.It was found that the appropriately sampled data sets (sorted by location) gave results virtually identical to the results for the full data set, even when the samples comprised less than one per cent of the original blocks. The reduction in computer time to identify maximum tonnage at a specified grade was approximately proportional to the sample percentage. The increase in computation speed greatly facilitated sensitivity analysis. A sampled data set of one-eighth the total block model was used to investigate the effects of changing each of the component grades around the original grade specification. The results of this sensitivity analysis are discussed, and illustrate the potential benefit of carrying out sensitivity analysis in determining feasible and marketable product grades.CITATION:Everett, J E, 2015. Block model data reduction and sensitivity analysis, in Proceedings Iron Ore 2015, pp 263–270 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By B Nielsen, H Lehto, B Musuku

"The demand for fine and ultra-fine grinding associated with the processing of more challenging, finer grained orebodies and the global driver of minimising energy consumption has been an increased focus in our industry. Outotec’s stirred milling technology, the high intensity grinding mill (HIGmill™), was launched in 2012 in response to this industry need. First Quantum Minerals Ltd selected HIGmill™ technology for its Kevitsa mine in Northern Finland. The 700 kW mill is grinding copper rougher concentrate to improve copper/nickel separation and copper recovery. Selection of the HIGmill™ followed mineralogy analysis and laboratory and pilot testing for HIG milling in parallel with flotation tests to determine optimum grind size and energy input.The paper discusses the challenges and successes of the test work, manufacture, installation, commissioning and subsequent operation of the mill. Grinding performance is presented and a comparison between predicted and operating energy efficiency is made. In addition, the various steps to optimise wear rate and minimise maintenance and downtime are made, with particular reference to internal geometry of the mill.Citation:Nielsen, B, Lehto, H and Musuku, B, 2016. Design, Installation, Commissioning and Operation of Fine Grinding Technology at the Kevitsa Mine, in Proceedings 13th AusIMM Mill Operators’ Conference 2016, pp 59–66 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Oct 10, 2016

By J Zhang, R Dimitrakopoulos

A two-stage stochastic mixed integer non-linear program is formulated for a mining complex to optimise strategic and tactical plans. The objective is to find the near optimal decisions for a mineral supply chain in the context with uncertainties in both ore supply and the commodity market (price and demand). The endogenous spot price in the commodity market and long-term sales contracts are considered in the formulation of the mining complex’s optimisation model and an ad hoc heuristic is developed to deal with the throughput – and head-grade-dependent recovery rate in processing plants. Numerical results indicate that the proposed heuristic is effective and efficient in numerical tests. Based on the proposed model and heuristic, a long-term contract design strategy is proposed for making decisions on the contract price and strategic investments. A shadow price based method is also proposed to evaluate the existing mining schedule.CITATION:Zhang, J and Dimitrakopoulos, R, 2014. Optimising a mineral supply chain under uncertainty with long-term sales contracts, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 25–32 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By J M. F Clout

In the iron ore industry significant emphasis is placed throughout the mining process on meeting chemical composition specifications for the export of fine ores, however, little has been published on the implications of ore chemical composition for iron ore sinter and pellet product quality. The ore bulk composition, together with the nature of the minerals in the fine ore both play a critical role in determining the type of high temperature bonding phases that form during sintering and pelletising. This paper uses the experimental determination of phase relations in model sinter and pellet systems such as Fe2O3-CaO-SiO2 (FCS) and Fe2O3-Al2O3-CaO-SiO2 (FACS) to examine the links between iron ore chemical composition and the temperatures used during sintering and pellet firing. The phase relations help to establish the critical thermal and compositional parameters that control the bonding phase chemistry which in turn influences the physical characteristics of the sinter or pellet matrix. Results show that lower Fe-grade (

Jan 1, 2002

By N Gupta, R Trivedi, S Bhandari

Managing blasting operations in four mines surrounded by villages is a challenging task. This study aims to compare the blast-induced flyrock as observed in opencast mines by predicting flyrock distance using a soft computing approach known as an adaptive neuro-fuzzy inference system (ANFIS) and Flyrock Predictor software based on empirical studies. Blast design and geotechnical variables such as linear charge concentration, burden, stemming length, specific charge, unconfined compressive strength and rock quality designation were selected as independent variables, while flyrock distance was used as a dependent variable. Out of 120 blasts, data from 100 blasts was used to train and test the ANFIS model. Flyrock distance for the remaining 20 blasts was used to evaluate the model. Flyrock distance has also been predicted using Flyrock Predictor software based on an empirical approach using the same data sets as those used for ANFIS. Performance indices like root mean square error (RMSE), mean absolute error and coefficient of determination (R2) were evaluated to compare the reliability of ANFIS and Flyrock Predictor quantitatively. ANFIS was found to be a better predictive tool, with 1.75 m RMSE and 0.966 R2 compared to Flyrock Predictor, which returned RMSE and R2 values of 2.48 m and 0.932 respectively.CITATION:Trivedi, R, Singh, T N, Gupta, N and Bhandari, S, 2015. Soft computing approach to predict blast-induced flyrock, in Proceedings 11th International Symposium on Rock Fragmentation by Blasting, pp 455–462 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 24, 2015