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By C Jenkins, M Mativenga, C Stanton, J Gerber

In 2014, Arrium completed an optimisation program on its magnetite concentrator, enabling a reduction in the overall cost base of producing concentrate through an increased ability to treat a wider range of ore types, previously considered waste. The development was the culmination of four years of work, conducted in house by Arrium’s mining development group. The overall intent of the plant design focused on improving the concentrator’s ability to treat a wider range of magnetite ore types. Metallurgical analysis of these feed ore groups outlined a need for more grinding power if production quality was to be maintained and throughput increased. As such, a tertiary grinding circuit was designed which, alongside the rectification of key operational bottlenecks, would allow the plant to continue to produce concentrate at the required specification and rate. The technology chosen for the tertiary grinding application was the XT IsaMillTM, which is known for efficient fine grinding when compared to conventional ball milling. The transfer sizes between the existing comminution circuits were coarsened, allowed for the treatment of different ores at the required rates. The optimisation project was successfully completed in February 2014 after a three month commissioning phase. The initial metallurgical testing and engineering of new equipment proved highly successful with all equipment meeting or exceeding design parameters.CITATION:Stanton, C, Mativenga, M, Gerber, J and Jenkins, C, 2015. Unlocking plant capability through targeted debottlenecking of Arrium’s magnetite concentrator, in Proceedings Iron Ore 2015, pp 185–190 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By T Nassis, P Louw, M R. Fry, T du Toit

Business intelligence (BI) and business analytics (BA) are established IT technologies that are used extensively in the business environment. This paper discusses the use of these technologies in production environments and beneficiation plants.Assmang’s Khumani mine is an iron ore operation located in the Northern Cape, South Africa. Assmang Limited is jointly owned by African Rainbow Minerals Limited and Assore Limited. This paper presents a case study of a BI solution applied to this plant, which is used by metallurgists, supervisors and all levels of operations and management to extract and analyse data to control and optimise the operation of the plant.The main advantage of adopting an established BI solution is the ease with which production personnel can extract and analyse data. The data is easily presented in familiar spreadsheets and no IT staff or specific training is required to achieve this.The solution adopted at Khumani mine uses a data mart with a multidimensional model (called an online analytical processing (OLAP) cube) acting as the main repository and source of data. The OLAP cube simplifies the access and analysis of plant data.The OLAP cube stores data in a specifically-designed way, which allows extraction and analysis to be performed quickly. It is designed to hold large amounts of data on a long-term basis, which could be for the life of the plant. It also performs automatic aggregations over many dimensions on a background process.A major benefit in adopting such a BI solution is that it allows common BA methods to be applied. This is due to both the efficient long-term storage of data and the availability of standard BA tools. BA tools are now able to perform data mining, predictive analytics, forecasting and other machine-learning algorithms. This paper presents the possible use of such advanced data analysis methods in a beneficiation plant.CITATION:Fry, M R, Nassis, T, Louw, P and du Toit, T, 2015. The use of common business intelligence and analytics tools in the operation and optimisation of iron ore process plants, in Proceedings Iron Ore 2015, pp 129–138 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By P J. Howard, P Darvall, J H. Mainwaring

In less than a year, Atlas Iron’s Corunna Downs Project has moved from a new discovery to a substantial resource of high quality in an underexplored greenstone belt. Located approximately 170 km south-east of Port Hedland and 40 km south-west of Marble Bar, in the Pilbara Region of Western Australia, Atlas Iron Ltd (Atlas) has conducted extensive exploration work at Split Rock, Razorback, Runway and Shark Gully, consisting of geophysical surveying, field mapping, 464 reverse circulation and 16 diamond drill holes resulting in a current resource of 51 Mt at 57.3 per cent Fe (Atlas, 2014b).The Corunna Downs Project is interpreted to be hosted within the Cleaverville Formation of the Archaean Gorge Creek Group. Within the project area these rocks outcrop as subvertically dipping banded iron-formations (BIFs) and jaspilites, cherts, minor shales and meta-sediments forming a north–south trending plateau.Primary hematite-martite iron mineralisation is overprinted in the near surface environment by supergene goethite, and frequently capped with a thin laterite cover. The strongest enrichment areas have been discovered within topographic lows, proximal to fault zones, which coincide with a geophysical anolmaly. These characteristics were targeted, and the subsequent areas mapped in greater detail, allowing for efficient resource definition.Although first explored for iron in the late 1960s, it wasn’t until Atlas’ acquisition of the project in October 2012, that major strides were made to defining an economic resource. At present, Corunna Downs is Atlas’ best greenfields exploration discovery, both in terms of the potential scale of the resource and its blending capacity.The Corunna Downs prospect is emerging as a major new iron ore province in the Pilbara and includes 80 km of potential host stratigraphy. Corunna Downs sits strategically between Atlas’ Mt Webber and McPhee Creek tenements, and can play an important part in Atlas’ growth strategy as iron ore market conditions become more volatile and challenging.CITATION:Mainwaring, J H, Howard, P J and Darvall, P, 2015. Discovery of the Corunna Downs deposits, in Proceedings Iron Ore 2015, pp 305–312 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By M T. Grigoleit, M S. Schneider

The iron ore industry in Australia has, in recent years, experienced an unprecedented growth phase. But now that major expansions are moving into the operation phase, new challenges have emerged. Whereas initial planning may involve a few modelling studies, ongoing performance monitoring and improvement requires a different, more intense approach. This is especially important in the face of changing factors such as commodity prices, exchange rates and labour markets. Response time is key. As a mining operation proceeds from initial planning to daily operations, the time window for analysis shortens, going from months to weeks to days as the business matures.Simulation models and analysis tools are typically built and run by specialists in the planning phase, but then what? The investment has been made, but realised only once. What if further analysis could be carried out in-house, re-using existing models using up-to-the-minute data? Can we create virtual mines that run in parallel to live operations that allow computers to identify areas of a value creation or operational improvement? These questions can be answered by the innovative application of big data, simulation and predictive analytics. The future will be having this all integrated into one platform that offers, for the first time, an opportunity for non-experts to apply existing modelling and analysis assets – combined with live data – to deliver support for continuous improvement, and the ability to respond quickly to external changes in the best possible way, before they become big problems. These techniques will represent a step change in the ability for operations to maximise efficiency and will underpin the intelligent operations of the future. These issues are addressed in this paper.CITATION:Schneider, M S and Grigoleit, M T, 2015. Maximising productivity through big data, simulation and predictive analytics, in Proceedings Iron Ore 2015, pp 475–480 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By X L. Liu, W Huang, J M. Zhu, S L. Wu

The shape, position and thickness of the cohesive zone have a great influence on the operational performance of the blast furnace. Many researchers have found that the high temperature properties of iron ores determine the formation of the cohesive zone. The results of this work show that sinter of high basicity interacts with lump ores and acid pellets due to the difference in chemical compositions. The softening and melting properties and the primary slag formation behaviours in the cohesive zone are improved by the high temperature interactions. The high temperature interaction is mainly influenced by the chemical compositions, porosity, interfaces and so on. Although the softening and melting properties and primary slag formation behaviours of lump ore A (a typical limonite lump ore from Australia) is the poorest of the iron ores studied, the high temperature properties of integrated burden A (consisting of sinter and lump ore A) is no worse than the other integrated burdens due to the high interaction between the sinter and lump ore A. It is useful to apply the results in the optimisation of blast furnace burden.CITATION:Liu, X L, Wu, S L, Huang, W and Zhu, J M, 2015. High temperature interactivity of iron ores in the cohesive zone of the blast furnace, in Proceedings Iron Ore 2015, pp 363–366 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By L Köresaar, J Moilanen

With lower and increasingly variable Fe grades in iron ore resources, the monitoring of Si, Al, Mg and other light elements to meet quality requirements is gaining importance in the iron ore beneficiation industry. The high cost per manual assay and associated manpower requirements often limit the frequency of shift composite samples and laboratory assays. Furthermore, the shift composite assays represent past performance of a plant but are not useful for immediate reactions to feed variations, detection of equipment malfunctions or process control. Automated online analysis of light elements radically reduces the cost per assay and provides repeatable, timely data for process analysis, control and optimisation.A light element online slurry analyser, based on laser-induced breakdown spectroscopy (LIBS) optical emission technique, will be presented. This paper discusses the analyser design for the iron ore industry and also reviews the performance of the analyser against the manual laboratory. Additionally operator safety, user friendliness and maintenance requirements are discussed.A case study will also be discussed in this paper. The sophisticated measurement technique has been implemented in an industrial automated analyser and sampling system to allow for slurry measurement for up to 12 sampling points. However, careful selection of the sampling points and implementation of the sampling system is required for smooth operation.CITATION:Köresaar, L, Timperi, J and Moilanen, J, 2015. Optimised process control in iron ore via online analysis of light elements, in Proceedings Iron Ore 2015, pp 511–518 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By D Connelly

Magnetite orebodies generally means mining lower grade iron ores, crushing and grinding with significant energy costs in processing and the capital costs being significantly higher than for direct shipping ores (DSO). Overseas, the mining and processing of magnetite ores has a long history of production due to the lack of DSO deposits. This raises the question as to why the new magnetite projects have been so problematic and also whether there is a future for the long list of potential magnetite projects in Australia.The quality of the magnetite concentrate product is superior to most DSO products and the magnetite contains energy benefits when converted to hematite in sintering or pelletising. The industry’s hopes for new projects have been dashed and questions are being raised as to the financial viability of such projects.A comparison of Grange Resources Savage River, Arrium’s Project Magnet, the Sino Iron Project and Gindalbie’s Karara Iron Project is used to understand the differences between the projects and why some are more successful than others.CITATION:Connelly, D, 2015. What is the future for magnetite projects in Australia and why have some of the new projects been so problematic?, in Proceedings Iron Ore 2015, pp 107–114 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By J Foo, T Kleinschmidt, B Reynolds, K Kennewell

The consideration of complex supply chains often highlights multiple system bottlenecks that are localised and dynamic – they shift depending on what variability last influenced the system. Using the understanding of a dynamic system model, synergies between items that tackle localised bottlenecks can be understood to generate a suite of solutions. These can be simple solutions, such as a couple of new conveyors placed in series, or more complex ones, including buffer dynamics (capacity, location, behaviour, etc).Each solution in the suite will have an associated uplift in system performance and an associated cost of implementation. Dynamic simulations can address each situation in turn and estimate the projected improvement it would offer. However, these solutions will have different benefits when implemented together, and each solution will give different uplift depending on what other solutions have already been assumed. If the number of solutions is numerous, traditional dynamic simulation analysis becomes the bottleneck, limiting options analysis to the processing power available.This paper will illustrate the use of a new technique applied as part of a capital growth optimisation project with a major iron ore producer. Metamodelling is the creation of a model of a model; in this case study, the focus is on developing a response surface representing the suite of solutions. This can be achieved through a combination of dynamic modelling and an appropriate mathematical process called design of experiments. The result is an approximation surface of the outcomes of the dynamic model, encapsulating interactions between key elements of the value chain.This modelling approach provides a number of advantages compared to traditional dynamic modelling approaches, including but not limited to:early and rapid evaluation of a large range of potential solutionsaccommodation of multiple initial states of the value chainoptimisation of the overall suite of upgrades (down to route-level upgrades) based on business objectiveseasy re-evaluation of outcomes when key inputs such as costs change.CITATION:Kleinschmidt, T, Foo, J, Reynolds, B and Kennewell, K, 2015. Case study of iron ore value chain optimisation, in Proceedings Iron Ore 2015, pp 605–612 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By N Steenkamp, L Furstenberg, W Cele, M Richter

Managing productivity and improving efficiency for a healthy return on capital employed have become key mining industry strategies under prevailing tough global market conditions. However, achieving this in a multisystem environment such as a mining operation can be daunting. The field of discrete event simulation offers some relief, giving engineering teams insight into multivariable systems and stochastic processes. It allows for integrated system thinking and domain expertise to be woven into project thinking fibre. Directed system optimisation and therefore improved efficiency becomes possible. Furthermore, capital discipline accrues from optimal upgrade investments. This paper illustrates the practical application of this approach by reviewing a typical case study for a direct shipping iron ore operation. Dynamic simulation was used to establish maximum processing plant capacity under varying material characteristics and identify capital-efficient upgrades for increasing production.The study started with descriptive statistical analysis of existing data. Discrete equipment and system capacities were defined, followed by static plant mass balance calculations to establish bottlenecks and overall static capacity. Equipment ‘uptime’ and ‘downtime’ analyses established system and overall plant availability and utilisation. From this information, a dynamic simulation model could then be developed and initially calibrated against actual plant performance to verify its robustness. Once confirmed to accurately represent existing plant dynamics, system capacity response to variable changes could be tested to ultimately determine maximum plant capacity. Additionally, plant optimisation was incorporated to arrive at optimal upgrade points. Maximum capacity and necessary upgrades were established as a function primarily of feed size distribution. Additionally, the interfacing effects of rehandling feed material to the final product grade and potentially to life-of-mine were established as important outcomes. The results of the study illustrate the value of using dynamic simulation models to realistically and cost-effectively increase throughput.CITATION:Cele, W, Furstenberg, L, Richter, M and Steenkamp, N, 2015. Capacity evaluation of iron ore processing facilities utilising dynamic simulations, in Proceedings Iron Ore 2015, pp 597–604 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By D Andrew, G Stanway, P Mahoney, C Griebel

The iron ore mining industry is currently going through an adjustment from high to more moderate growth as China’s economy transitions from capital-intensive investment to a more services-oriented economy. We are now witnessing a renewed focus on productivity improvements and cost savings as planned expansions are completed. Despite the scale and importance that the mining industry plays in the global economy, innovation literature is generally more targeted at faster-moving industries with shorter innovation timeframes and lower capital requirements. To fill this gap, VCI set out to understand the state of innovation in the mining industry in 2014. This State of Play report aims to give an objective appraisal of the strengths and weaknesses of innovation in mining. The report has three sections covering both the structure and delivery of innovation in mining:Ecosystem – focused on understanding how the iron ore mining innovation ecosystem system works, including the roles of large and small miners, service companies, researchers and governments. Our recommendations focus on what is required for the system to work well and improve the level and quality of innovation in the industry.Strategy – how do companies define their innovation strategy in relation to their corporate strategy? How are these related to prevailing global and industry trends? How do they communicate this with their business? How successful are they? These are among the questions that this section attempts to answer. Our recommendations are pitched at the executive leadership of iron ore mining and service companies.Delivery – focused on how companies develop and deliver innovation, looking at the success of different structural options, leadership and culture, partnerships and the best approaches to change. Recommendations are aimed at improving outcomes within the iron ore mining value chain, including the role that suppliers play.CITATION:Stanway, G, Mahoney, P, Andrew, D and Griebel, C, 2015. Understanding the state of innovation in the iron ore industry, in Proceedings Iron Ore 2015, pp 631–646 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By D Kepert

It is the role of the exploration geologist to create wealth through the discovery, delineation and characterisation of economic mineralisation. This requires a critical depth of geological understanding.Unfortunately, the resource industry is well known for its cyclic nature. Many of the current generation of workers have only ever experienced the boom of the ‘super-cycle’ and are only just discovering the negative side to the business. For the case of the geologist and especially the exploration geologist, the magnitude of peaks and troughs are usually amplified and may become destructive to all parties. During the uptime a healthy stream of exploration good news becomes the staple diet of company releases, in particular those of junior companies attempting to bolster the share price. The geological knowledge and experience gained thus forms a significant and integral part of the value and therefore, future of a company. On the downturn it is often viewed that geologists are a luxury, an optional extra and a burden on the bottom line with companies entering a period of memory loss and myopia.Retention of geological knowledge however remains critical as projects, companies and cycles mature. Beyond exploration per se, this knowledge becomes both fundamental in de-risking and commercialising an asset (through development or divestment) and in positioning the company for cyclic or counter-cyclic opportunities.The growth and retention of this knowledge base is difficult to quantify in terms of direct value but becomes one of a successful resource companies greatest assets. At worst, its loss can lead to millions of investors’ funds wasted on missed opportunities, drilling, or poorly designed plant and mine.But the rocks are around for the longer haul and pay little notice to the vagaries of the scurrying of Man.This paper reflects on some of the authors own observations through 25 years of iron ore exploration, in why it is critical to always rigorously question the prevailing geological (mis)understanding and the technical and commercial benefits which that may bring, and looks forward to the future.CITATION:Kepert, D, 2015. Geology – the affirmative case, in Proceedings Iron Ore 2015, pp 285–298 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By R. G. Jones

Many novel projects suffer delays, cost overruns or failure because of inadequately qualified technologies. A new qualification to measure the quality of innovation is discussed.

Jul 1, 2015

By M. Schwartz

Mining in Argentina is diverse in terms of the number of minerals extracted from the country, but also in terms of the varied approaches and attitudes of mining investors and their trust in the country's individual provinces. Laws are discussed, investment attractiveness and taxation.

Jun 1, 2015

By R. G. Jones

At its peak in the 1970s, South Africa was responsible for around 80% of global gold production and, according to the US Geological Survey, it still has the largest share of gold reserves - as well as 90% of the world's platinum. But, in January 2015, gold production reached a new monthly low, generating 87% less than it did in January 1980, and South Africa is now the world's sixth ranked gold producer. What next for African gold?

Jun 1, 2015

By Fernando Enrique Toledo Garay

El presente artículo busca simular a través del diseño de un prototipo de dos niveles, los fenómenos físico-químicos ocurridos en las minas Lourdes y Excelsior en Cerro de Pasco a fin de simplificar la explotación de minas, -en tanto elimina los pasos de concentración y fundición,

Jun 1, 2015

By Fernando Enrique Toledo Garay

"El presente texto describe las últimas tendencias de la ISO 55000 y así conocer el objetivo de las normas como de los estándares asociados a la gestión de activos físicos. Por ello, se realiza un recorrido a través de todo el IAM Framework (marco de referencia del Institute of Asset Management para lograr la sustentabilidad de la gestión optimizada de activos físicos) e ISO. dencias en las organizaciones de apoyo. En este análisis participan representantes de todas las áreas del negocio de gestión integral de activos físicos (operaciones, mantenimiento, materiales, ingeniería, finanzas, recursos humanos, confiabilidad, seguridad industrial y medioambiente). "

Jun 1, 2015

By R. G. Jones

Chris Hinde talks us through his career from BSc in Mining Engineering to roles with Golder Associates, Schroder Securities, Mining Journal and SNL. He discusses the issues facing the mining industry.

May 1, 2015

By G. Richards

Mines are facing fresh challenges over how they deal with the huge quantities of water consumed. industry analyst Frost and Sullivan, demand for treatment equipment and services alone is expected to be worth US$3.6bn by 2016, while a report by consultancy Bluefield Research estimates that the total mine water market - which includes water infrastructure such as reservoirs, pipelines and dewatering systems as well as the equipment and services - will be worth US$17bn by the end of 2019. Methods of water decontamination are described.

May 1, 2015

By Paola Icaza Palma

El presente texto describe la importancia de las relaciones entre las empresas mineras y las comunidades. En ese sentido, se busca que el relacionista comunitario se convierta en modelo del ámbito de desarrollo y participación como consecuencia de sus labores.

Apr 1, 2015

By S J. Tear, L D. Queen

"An EXTENDED ABSTRACT is available for download. A full-length paper was not prepared for this presentation. The Frieda River Project is located in the north-west of Papua New Guinea. The target commodities for a bulk mining operation are copper and gold associated with a large felsic porphyry system. The project comprises a series of deposits, with the Horse-Ivaal-Trukai (HIT) being the largest. It also includes the adjacent smaller Koki and Ekwai deposits.Previous resource estimates for the HIT were made using 14 separate mineralised domains based on structure, copper grades, lithology and alteration. H&S Consultants (H&SC) has revisited the deposit and concluded that a simpler methodology could be used for resource estimation without using wireframes as hard domain boundaries. This conclusion is based on reviewing all the available geological data combined with geological and resource experience of porphyry deposits.It is generally acknowledged that porphyry deposits form by diffusion of mineralising fluids through the host lithologies, meaning that sharp boundaries are unlikely unless these fluids encounter specific physical or chemical boundaries. It is important to prepare a comprehensive geological model prior to attempting resource estimation as it forms the framework for the estimates; however, not all geological features may be relevant to the distribution of mineralisation and there can be a tendency to overcomplicate the estimation process by using too many domains. Unless a hard boundary can be identified consistently and unequivocally, it is generally better not to use a boundary in that location.H&SC completed unconstrained models with no top-cutting using both a simple flat search ellipse and a steep search ellipse to generate global resource estimates reported within a predetermined pit shell at a 0.2 per cent copper cut-off. Both outcomes are within 10 per cent for the tonnes, contained copper tonnes and gold ounces compared to the constrained resource estimate. The slight differences are most likely due to the different search strategies, but also indicate the robustness of the unconstrained modelling approach.CITATION:Queen, L D and Tear, S J, 2015. The Frieda kiss – keeping it simple , in Proceedings PACRIM 2015 Congress, pp 361–368 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Mar 18, 2015