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By L Q. Amorim

The mining district of the Quadrilátero Ferrífero (QF) in southeastern Brazil contributes to 70 per cent of the Brazilian iron ore production, which reached 370 Mt in 2010. Traditionally, four iron ore types were mined in the QF region:1. soft haematite,2. hard haematite,3. friable ‘itabirite’ (the Brazilian name for metamorphosed banded iron formation), and4. canga (an indurated iron-rich crust).With the exception of the hard haematite, these categories derive from supergene enrichment of the Paleoproterozoic Cauê Itabirite. High current iron ore demand means that the QF high grade supergene ores will be depleted in a few decades. Consequently, several mining projects are being developed to exploit unenriched, fresh itabirite. Among them, the Mineração Usiminas Serra Azul project in northwestern QF is one of the most advanced. Four major itabirite types occur in the QF region:1. siliceous (or standard),2. dolomitic,3. amphibolitic, and4. magnetitic.The dominant type in Serra Azul region is a fresh siliceous itabirite, composed essentially of haematite, martite and quartz that averages 36 per cent Fe (51.5 per cent Fe2O3) and 47 per cent SiO2. The second type, the magnetitic itabirite, consisting of magnetite, martite, gruneritecummingtonite, quartz, dolomite, stilpnomelane, and subordinate haematite, is typically a strongly magnetic greenish banded iron formation with the iron grade varying between 25 and 35 per cent. Chemically, it differs from the siliceous itabirite due to the relatively high CaO, MgO and, consequently, high LOI contents. Together with supergene ores, fresh itabirites have been included in the ore reserves of the Serra Azul project. We anticipate that all the four types of fresh itabirite will be incorporated as ore in the QF region, causing a huge increase on the iron ore resources of the district, and representing enormous environmental and technological challenges for the local iron ore industry.

Jul 11, 2011

By R N. Humphries, R J. K Thompson

Large-scale coal mining in South Wales dates back to the late 18th and early 19th centuries with the birth of ironmaking on an industrial scale. This rapidly gave rise to new and large communities with immigration from far and wide across the United Kingdom (UK). These new communities were largely dependent on coal mining and served as the main form of employment and social cohesion until the industry’s demise in the 1990s. With wholesale mine closure and the concomitant loss of employment, the extensive environmental degradation and chronic mine-related illness left a deep scar on the psyche on many still living in the South Wales mining communities. This coupled with memories of strife in the 1980s has resulted in ongoing hostility toward the surface coal mining of the remaining accessible coal reserves in the proximity of these communities.The purpose of this paper is to set out the historical basis of the concerns of these legacy mining communities in South Wales and explain how they are being positively addressed by both the recently evolved planning and regulation system and by today’s surface mining industry. Reference is made to experience gained from two recent applications for surface coal mining adjacent to former mining communities. Ways are suggested in the approval process that surface mining can work in more harmony with the local communities through working partnerships between the mining company, the authorities and regulators and the affected communities. It is concluded that partnership is key to creating a more responsive mine-operating culture and a means to securing approval for future surface coal-mining prospects in South Wales, and probably elsewhere too.CITATION:Humphries, R N and Thompson, R J K, 2014. Surface mining and legacy mining communities in South Wales, UK, in Proceedings Life-of-Mine 2014 , pp 399–412 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 16, 2014

By H Y. Niu

The coal left in the goaf is easily submerged by groundwater damage. During the mining process of the underlying coal seam, it is necessary to drain the water in the overlying goaf. The coal sample is prone to spontaneous combustion after being soaked in water and air-dried. To explore the effect of micro-functional group transformation of water-immersed coal samples on the spontaneous combustion characteristics of coal samples during the low-temperature oxidation process. Using the experimental method of infrared spectroscopy, the migration law of special functional groups under different oxygen concentrations of water-soaked coal samples was analysed. By means of thermal analysis, the endothermic and exothermic properties of the functional groups in the water-soaked coal samples were studied. The results show that: the higher the oxygen concentration, the more oxygen-containing functional groups in the water-soaked coal sample, compared with the 18 per cent oxygen concentration, the 14 per cent oxygen concentration has a small increase, and the chain length is shortened. The temperature increase together with the oxygen concentration content determines the functional group content, the pyrolysis process produces some functional groups. The lower the oxygen concentration, endothermic rate decreases and endothermic temperature increases, the higher the ignition temperature of coal oxy-combustion, the lower the total heat release, the higher the burnout temperature, and the faster the oxygen-absorbing weight gain and the conversion of functional groups. Below 14 per cent oxygen concentration, the oxidative combustion process will be greatly reduced. The results provide a theoretical basis for preventing long-term water-soaked coal body oxidative spontaneous combustion in shallow buried coal seams.

Oct 12, 2022

By I Arburthnot, N Lawler, C Loan

The function of a thickener is to optimise and accelerate the process of gravity sedimentation. The desired end product (be that maximised concentrated solids or clarified liquid) determines how the thickener is designed and operated.Significant internal research, together with extensive on-site piloting, by Outotec has resulted in the determination that the application of the appropriate amount and type of shear to hindered settling aggregates can result in a substantial change to the sedimentation process. A new patented technology, called shear enhanced thickening (SET), has been developed. SET results in considerable design implications for full-scale thickeners, including a substantial reduction in required footprint and/or significant increases in underflow density.The development of SET, combined with laboratory and pilot scale verification, will be discussed along with the introduction of this technology to a number of full-scale thickeners. The associated implications and benefits for industrial thickeners are outlined.CITATION:Loan, C, Lawler, N and Arburthnot, I, 2012. Industrial scale results from shear enhanced thickening technology, in Proceedings 11th AusIMM Mill OperatorsÆ Conference, pp 341-346 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Oct 29, 2012

By J Ta’ala, M Handyside

Mechanical sampling from conveyors has historically been a staple in the iron ore industry when information related to chemistry, sizing and moisture is required. In order to comply with ISO 3082:2009, samples can be taken either on a mass or time basis provided no bias is introduced by periodical variation in quality or quantity. With the introduction of mechanical sample carousels, you also have the opportunity to collect samples on a mass or time basis. In order to optimise automatic sample stations in a changing production environment, BHP Billiton Iron Ore (BHPBIO) has developed a simulation model that enables the various combinations of mass–mass, mass–time, time–time and time–mass to be investigated.The sample station model can utilise actual (variable) feed rates to achieve high resolution and enables the simulation of sample size variation. Cutter speeds and other settings can then be adjusted to better optimise the performance of the sample station with regards to optimal sample size as well as ensuring the sample station is in compliance with ISO 3082. The model can also assist process engineers in adjusting settings to better optimise the sample station and reduce unwanted events such as blockages. The model can be easily modified to conform to various sample station designs. This paper demonstrates the use of the model and the benefits that can be achieved.CITATION:Handyside, M and Ta’ala, J, 2014. Simulating time versus mass basis?sampling, in Proceedings Sampling 2014 , pp 155–164 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

Alluvial mining even of shallow deposits is often economically a marginal proposition and causes significant disruption of the land surface through the need for large scale excavation. In-situ leaching using chlorine-based solutions eliminates the need for excavation, the disruption of surface activities, and may greatly reduce processing costs and improve recovery especially of fine gold. A spreadsheet model has been developed to design and analyse the economics of in-situ leaching of alluvial deposits. In-situ leaching of shallow deposits may be achieved in a number of ways including solution infiltration via perimeter ditches or the use of injection and production wells. In most instances deeper alluvials may only be processed using well systems. Two deposits are analysed in this paper. The first consists of one metre of payable wash beneath one metre of overburden. Some thirty fields per year are treated processing 450 000 BCM per year at a cut-off grade of around $4/tonne ($8/rn3 or the gold value equivalent of 0.26 gh or 0.52 g/m3). The principal costs are well drilling and labour. Sensitivity analysis indicates that doubling the throughput halves the cost. The economics of the project are relatively insensitive to reagent costs and consumptions, and halving the recovery doubles the cut-off grade. Shallow deposits treated using the infiltration ditch system may be marginally cheaper and more conveniently managed although this depends on the relative cost of digging the perimeter ditches. In a second example, deep leads with one metre of wash beneath 30 metres of overburden necessitate significant drilling and feature reduced throughputs as a consequence. In the example chosen 30 fields a year are processed for an annual throughput of 65 000 tonnes costed at around $20/tonne (1.4 g/t Au equivalent, $40 /m3). Sensitivity analysis indicates that throughput, and drilling cost per metre are not important but there is a high sensitivity to recovery and to the depth to payable wash.

Jan 1, 1992

Although the mining of metals was well established by the time of the Roman Empire mining skills did not really advance greatly for many centuries. Miners did not have the scientific knowledge to distinguish minerals, to process them, and to obtain the best recovery. Each mine essentially developed its own methods in isolation, most of them dangerous. However, with the beginning of the industrial revolution in the early 18th century there was a rapid increase in mining activity in Central and Western Europe and an accompanying need to educate professionals in the developing fields of science and technology. There was also a need for specialised schools (for example, Schools of Mines) to accomplish this since the universities of the time, formed as early as the first half of the 12th century, were cloistered institutions, focused on the study of classics, theology and law. The earliest attempts at organised technical education were made in 1702 with the establishment of a School of Mines in Frieberg, Germany (Table 1) to service rich copper mines, and in 1747 with the establishment of a School of Mines in Paris. By this time, the industrial revolution was well under way and other Schools rapidly followed, at Clausthal in the Ruhr region of Germany in 1775; in 1777 at Almanden to service the mercury mines of Spain (later transferred to Madrid); in 1780 at St Petersburg, Russia and at Falun, Sweden in 1819. The academic staff for these new institutions were often trained in the original School at Frieberg.

Jan 1, 2002

Alternatively are they a necessary evil'? Exploration geologists are a much higher profile group but then again the higher they are the bigger they Bill. At a mine site they are reluctantly being accepted as equals by mining engineers given the requirements of the `Code' in the reporting of Ore Reserves. How best can mining geologists service their customers? Are more revealing questions to be answered in who are their customers? In the past mining geologists lived isolated existences pouring over plans and sections, now with user-friendly software packages available and the use of LAN, mining geologists and mining engineers talk electronically - God forhid what the future might hying - they might even talk to accountants and metallurgists!

Jan 1, 1997

By B Liu, W J. Zhang, S Saydam, B Li

Rock bolts are commonly used to reinforce ground in underground mining and civil tunnel environments. Rock bolts serve two main functions: i) they suspend large, loose blocks of ground, and ii) provide a protective pressure arch to restrain the deformation in an excavated void. Automated and precise tracking of rock bolt positions can assist with the operational success of ground support by reducing the amount of labour required in current manual practices. A point cloud is a large list of x, y and z coordinates in three-dimensional space, that when visualised, show a precise 3D representation of a physical environment. Point cloud data can be collected using accurate LiDAR scanners. These scanners can be mounted on a stationary tripod or on a moving vehicle. A key way point cloud data is used is in the bolt detection project being completed in conjunction with UNSW Sydney, which aims to provide an automated location of underground rock bolts from LiDAR scans. The immediate challenge with identifying rock bolts is that they constitute a very small portion of the data set amounting to approximately 0.01 per cent of some of the collected civil tunnel data. The process of detecting rock bolts from point clouds therefore requires a quick elimination of large background data while still preserving the bolt data. A further challenge is that the geometry of underground environments can often be very complex and non-uniform. To overcome these challenges, a two-step coarse to fine deep learning approach is taken. The first step is a coarse background elimination step aimed at removing as much of the background data as possible. The second step is a finer classification method, which uses deep learning to further segment the bolts from the remaining background. Additionally, a computer vision module is being implemented, which is expected to increase the detection rate by adding another dimension to the training data set.

Nov 29, 2022

WMC Limited, owner/operator of Olympic Dam, the worldÆs largest underground uranium mine and the fourth largest underground copper mine has now completed an expansion that has been classed as a benchmark in the mining industry. To achieve a production increase from 3.4 to 9.25 Mtpa from an underground mining operation in two years was a major challenge, it was essential to review the overall materials handling system from æthe face to the stockpileÆ. The challenge was two-fold:How to deliver 30 000 tonne of ore per day to the processing plant, from a single underground mine? To provide the processing plant with a consistent metallurgical feed. This paper traces the transformation from the old to the new materials handling system at Olympic Dam.

Jan 1, 2000

By Pattinaja MA

Mathematical modelling was carried out to determine the probable convergence and vertical stress patterns around a retreating longwall panel in an underground coal mine in New South Wales. An 'Electrical Resistance Analogue' and a program called 'THREED' based on the displacement discontinuity method were used for the modelling. Parts of the obtained results are presented here and compared with some measurements of convergence at the site. The modelled and measured data agree better qualitatively, than quantitatively.

Jan 1, 1986

By S Watson, L Martinez

Mine projects are complex opportunities that demand a constant assessment of uncertainty, ie risk and upside potential. This is because the value of a mine project is typically influenced by many underlying economic and physical uncertainties, such as metal/mineral prices, metal/mineral grades, costs, schedules, quantities, and environmental issues, amongst others, which are not known with much certainty at the beginning of the project. But, is uncertainty an enemy or an ally of the mine planner/analyst? To answer this question, this paper first assesses and elaborates upon the general concept of uncertainty. It then looks at the different sources of uncertainty in a mining project, such as the orebody, costs and product price uncertainties, and their effect on the final project value. Next, a general?review?of current mine evaluation techniques highlighting their limitations when dealing with uncertainty is made. Finally, an extended evaluation and risk management framework that addresses the existing uncertainty in the (greenfield/brownfield) mine evaluation process is proposed. One important characteristic of this framework is that it uses and manages uncertainty in order to generate additional value to the project; this is done through operational and managerial flexibility, which allow mine planners to minimise/maximise project risk/upside-potential giving a more realistic estimate of the projectÆs market value - this is shown in practical and simple examples occurring at different stages of a mine project, such as exploration and operation. Final conclusions are provided at the end.CITATION:Martinez, L and Watson, S, 2012. Uncertainty - An important source of (additional) value for mine projects, in Proceedings Project Evaluation 2012 , pp 131-140 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By M I. Roberts

Corporate and workplace culture, as many owners, directors, executives and managers know, is by far the most powerful determinant of productivity. It’s much more significant than buildings and equipment. Yet although no one today would build a building or machine without a plan, few leaders have a plan for building and sustaining a safer and more productive culture.Using practical ways, culture can be planned and shaped as desired. Success requires implementing a project plan for changing the systems that drive behaviours that in turn shape attitudes. The combination of behaviour and attitude together with leadership largely shape culture.To improve performance, leaders need to:1. improve the organisational systems that drive behaviour2. action a project plan for improving specific performance metrics 3. demonstrate leadership that is conscious, disciplined, committed and passionate for purposeful use of human energy.This paper explains all three factors in practical ways with operational and corporate examples. It details understanding and applying the power of fundamental statistical analysis tools to recalibrate, focus and drive proactive leadership that takes responsibility for process improvement, supporting people and ensuring accountability.Experience and practical understanding of human and organisational behaviour confirm that the Measurement ? Analysis ? Reporting system combined with conscious leadership is by far the most powerful driver of behaviour. This wisdom produces profound changes in leadership style and behaviour. It develops outstanding leadership to create and sustain a safe and highly productive culture reliably producing consistently high quality products. It is the key to developing accountability, employee retention and a sustained competitive advantage.CITATION:Roberts, M I, 2016. Building safe, productive cultures and leadership, in Proceedings International Mine Management Conference, pp 163-178 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jun 22, 2016

By P Standish

Qualitative risk assessment methods are not well suited to considering complex systems and potential interactions of new technology. As part of supporting tier one mining organisations and international industry groups, the author and colleagues have innovated processes to help provide better solutions to sites/companies considering a move to implementing proximity detection and collision avoidance systems. The process identifies required operating states for the system. By applying a combination of research and team-based analyses, a rigorous identification of credible failure modes which could cause these states to be lost, is identified. Finally, required business inputs, expressed in practical terms are distilled from regulator, industry, organisation and site in a way which clearly addresses the failure modes and so retain the required operating states. These business inputs identify improvements for site arrangements (EMESRT levels 1 to 7) before identifying functional requirements for technological collision avoidance solutions (levels 8 for advisory and 9 for autonomous). The paper presents a case study synthesised from multiple sites analyses and will provide guidance on where to find additional resources to assist in making the best possible transition to better equipment and road network solutions.

Jun 22, 2022

By M J. Nimmo

extremely powerful tools for building predictive and generative models. ML can be used for building highly accurate regression and classification models. But without careful data science and statistical analysis, a regression or classification model could be highly biased and completely wrong – and we may not even realise. An example rock density estimation task will be used to illustrate the potential gains and possible pitfalls in using ML and AI in Mineral Resource estimation. What could possibly go wrong? Nothing! For most simple regression or classification problems, very little. For density estimation, using the global mean may be all that is possible, but the resource classification would need to reflect the uncertainty in global estimation of tonnage. Everything! From data collection and measurement, from selecting ML and AI techniques and designing the analysis workflow to our own cognitive bias. The things that could go wrong are vast and may include but not limited to asking the wrong question, not asking questions, data bias, measurement errors, insufficient data coverage, not collecting the right variables, not collecting enough observations, collecting clustered samples, unbalanced data, filtering out data without reason (outliers), clipping data (outliers), relying on automatic feature selection, including irrelevant variables, excluding relevant variables, geological interpretation, changing context, blindly following best practice, splitting small data sets, subsetting large data sets, using the wrong tool for the task, insufficient budget to complete the analysis, not allowing enough time for testing and experimentation (the science), focusing too much on building the model (the engineering), not learning from the data, our assumptions, our preconceptions, and our skill. This paper will explore the question of how training regression models to predict rock density are affected by gaps in the data (missing observations and missing variables). What could possibly go wrong?

May 24, 2023

By Azizan A

The paper presents the results of chlorination of beneficiated rutile and struverite (a tantalum-niobium bearing, rutile type mineral in alluvial tin deposits) by carbon tetrachloride in the range 623¦K to 773¦K. The chlorination of rutile could reach near completion at 773¦K in about an hour. The process was found to follow a modified pore-blocking law, with the basic reaction constant K varying inversely with the particle size, so that the basic process may be a reaction under interface control (chemical control) as modified by the pore blocking effect. The pore blocking factors for the various experimental conditions were evaluated and the predicted curves showed good agreement with the experimental data. In the case of Struverite, a similar kinetic behaviour was observed but the chlorination process was relatively slower than that in rutile. It was also observed that in struverite, niobium got chlorinated faster, followed by tantalum and titanium, indicating a good possibility of separation by chlorination using carbon tetrachloride.

Jan 1, 1996

By G Malherbe, J Gonzalez, D C. Franklin, J Bassan, C T. Farrelly

To respond to ever-increasing challenges, mining companies have been experimenting with new business models and technologies in order to speed mine development, production, processing and transport. The various experiments involve mobile access to data, intelligent sensors, advanced analytics, virtual collaboration, virtual reality, automated equipment, remote operations centres and strategic partnerships. A synthesis of all these components creates a ænetwork effectÆ that can dramatically improve the overall effectiveness the entire operation. The concept of the Network Centric Mine borrows from a variety of industries, including defence, aerospace, aviation, petroleum, utilities and manufacturing. Central to the concept are improvements to the way we connect people, process, information and technology, resulting in a more highly collaborative business model, with roles and processes designed to take advantage of new technology. The components of the mining operation act as a connected network aimed at a common goal, regardless of the boundaries of organisation and location.The design of this new organisational ecosystem needs to take into account the recent advances that enable the æplug and playÆ integrated collaborative environment, including cloud computing, mobile devices and social networking, as well as advances in augmented reality, robotics, geo-location, digital labelling, simulation and analytics. However, the most consistent lesson from other industries is the need to properly enable the behaviour and process changes necessary for success.Benefits from adopting a network centric approach include the more effective use of scarce expertise, improved data and information analysis, reduced process variance, and more informed and faster decision-making. The future of mining will see more technology savvy workers who will drive the adoption of new processes. The operations will shift from a relatively static and disparate set of functions, to a digitally aware, dynamic, automated, integrated and interactive environment, with increased agility, lower operating costs, higher productivity and improved safety.CITATION:Farrelly, C T, Malherbe, G, Gonzalez, J, Bassan, J and Franklin, D C, 2012. The network centric mine, in Proceedings International Mine Management 2012, pp 143-160 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 20, 2012

By McAuley T. J

Computer software is an integral part of mining operations today with many sites using six or more software packages on a daily basis. However, the use of these different programs generates the need for substantial staff training. The current trend toward large integrated packages to solve this problem is counter-productive because the relatively small companies producing specialised mining software do not have the resources to develop quality software with all the required features. Software standards are being proposed by various parties but recent history indicates these will be unsuccessful. An alternative approach is suggested using the various standards which have been developed for the Windows operating system.

Jan 1, 1995

By H Dehghan Jan Abadi, K Shahriar

The iron ore district of Gol-e-Gohar (GEG) is located 60 km south-west of the city of Sirjan, in the Kerman Province of the Islamic Republic of Iran. Six exploration targets have been identified and iron ore has been mined from one area with dry and wet concentrate products sold. Prior to mining commencing in 1999, the proven reserves were estimated at 265 million tonnes (Mt) in 2004 and 40 Mt of 100 Mt overburden has since been mined. Of the six exploration targets, the largest anomaly in the GEG district is Deposit No 3. This paper discusses economic considerations focusing on mine extraction and construction of a concentration and pelletising plant to process ore from Deposit No 3 of GEG. Planned capacity of 10 Mt product (concentrate and pellet) per year is targeted to commence in 2011, and nominal capacity by 2014. The economical evaluation and analysis is one of the most important stages in the feasibility study of mine development. Financial calculations including the provision of financial resources, operation period revenue, loss and profit statement, cash flow, net cash flow, internal rate of return and net present value have been undertaken as part of the feasibility study. The feasibility study operating plan assumes a large open pit mine containing proven reserves of approximately 250 Mt. The feasibility study assumed an economic return of $80 per tonne iron pellet. The economic study determined that Deposit No 3 of GEG can be economically developed by open pit mining followed by magnetite separation and flotation to generate iron concentrate and pellets.

Jan 1, 2007

By R K. A Taylor

The growth in production of beneficiated ilmenite products has been one of the most significant trends in the titanium feedstock industry over the past 30 years. In this period, the production of titanium slag and synthetic rutile has grown five-fold to the point where these products represented 56 per cent of total feedstock production in 2000. Additional production capacity is being proposed as the core component of new feedstock supply projects presently under consideration. A high proportion of these products is based on technologies for which the inherent quality of the is an essential factor. Location specific factors also play a large part in determining the cost of production. As the demand for such products grows, and the availability of favourably located sources of ilmenite of suitable quality declines, it can be expected that existing beneficiation technologies will become increasingly constrained. Existing beneficiation technologies, and those which have been developed, but are not yet commercially applied, are reviewed. Future issues which are likely to impact on the cost effectiveness of these technologies, or the quality of final products, are identified. These factors suggest directions for development of ilmenite beneficiation technologies to achieve economic production of the quality of feedstocks which will be demanded by the TiO2 pigment industry in the future.

Jan 1, 2001