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By J Seccatore, T Marin, M Cardu, G De Tomi, F Galvão, A Rezende, E Melo

Small-scale mining operations are characterised by a large variety of equipment availability and a high level of operational flexibility. Mine planning is usually scarce or absent in small quarries in Brazil, and mine management generally focuses on daily operations. As a result, analysis of the effects of unit operations, such as blasting, over the whole mining process is often neglected. The goal of the following project was to study the effect of production blasting on loading and hauling times, secondary breaking times and primary crushing times at the Experimental Mine of the Research Center for Responsible Mining of the University of São Paulo, Brazil. The operations analysed included blasts that performed:under the average operational standard, defined in this paper as Case 1according to quarry standards, defined in this paper as Case 2.In order to establish the effects of blasting on the downstream process, three key performance indictors were used:The time taken to load the truck, when there is the need for material selection. Due to the fact that we do not have an operational baseline, the increase in time cannot be established, meaning that we must content ourselves with comparing the mean time in each scenario.The average time used for secondary breaking machinery.The time required for the primary crusher to fully process the load of a single truck. The results obtained indicate correlations between the coarseness of the blasted material and these operational times. Solutions are suggested and evaluated for the improvement of the small-scale mining process.CITATION:Marin, T, Melo, E, Seccatore, J, Cardu, M, Galvão, F, Rezende, A, Bettencourt, J and De Tomi, G, 2015. The effect of drilling and blasting performance on fragmentation in a quarry and time for loading, secondary breakage and crushing, in Proceedings 11th International Symposium on Rock Fragmentation by Blasting, pp 355–362 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 24, 2015

By S Gulati, N Sarkar, T Vink, S Battersby, L Okada

This paper examines a successful project implemented by BHP Mitsubishi Alliance (BMA) and the Polymathian team at Deswik, aimed at enhancing short-term scheduling processes to reduce vessel turn times in the BMA Central Queensland coal value chain. The project’s objective was to digitalise the planning process to enable planners to make data-driven insights to improve the profitability of the value chain. The strategy involved developing a digital mining system that incorporates data storage, cloud computing, and the ability to meet the integration needs of both internal and external business systems. This was complemented by a sophisticated, optimisation-based, decision-support tool to enhance the planning teams’ ability to make timely and effective decisions.

Sep 1, 2024

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 G Pattenden, R Hargreaves, P Pettit

"Even with the cyclic nature of mining, when it comes down to it, the bottom line is that whatever direction the commodity market is going there is always a desire to improve the economics of an operation in order to deliver a greater return to investors. Adapting to market pressures by introduction of an operational process change can often have a downstream impact. What may be less obvious is that reconciliation can play an important part in measuring the effectiveness of many operational changes. Through the adoption of best practice reconciliation and related comparisons, it is possible to measure the impact of changes across the mine value chain and identify variability that may have been introduced. Using analytical business improvement tools, examining and monitoring planned changes can be crucial in understanding whether the introduced changes have been effective and whether they have provided the expected result. Using several case studies, the authors will highlight the benefits provided by modern business intelligence tools, which can provide data validation and accurately report data trends related to both planned and unplanned change events.Citation:Hargreaves, R, Pattenden, G and Pettit, P, 2016. Measuring the Effectiveness of Change through Best Practice Reconciliation, in Proceedings Ninth AusIMM Open Pit Operators' Conference 2016, pp 71–83 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Nov 15, 2016

By A Fyans, B Ghahreman-Nejad

This paper discusses the method and results of an options study into selection of the optimal form for a 130 m high tailings/water retaining dam, located in a region of high seismicity in central Iran. The proposed dam is part of a planned expansion project for Sarcheshmeh Copper Mine (SCM), which after construction will provide 550 million tonnes of additional tailings storage over the next 27 years. Geotechnical investigation at the proposed site indicated that adequate suitable low permeability materials (i.e. clay) were not available in the immediate vicinity of the dam site and would need to be imported from a distance of well over 10 km (direct). Given the magnitude of the estimated quantity of material and construction cost it was considered prudent to compare the cost of alternative dam design options for the proposed storage. A total of five dam design options are considered including a conventional rockfill embankment dam with an upstream sloping earth core (ECRD), a geomembrane face rockfill embankment dam (GFRD), a sloping asphalt core rockfill embankment dam (ACRD), a roller compacted concrete dam (RCCD), and a filter rockfill embankment dam for tailings storage together with a separate smaller earthfill core rockfill dam (ECRD) located downstream for storage of decant water. The risks, costing and design of all options are discussed in detail and the outcome of the study is presented.CITATION:Ghahreman-Nejad, B and Fyans, A, 2018. Optimum embankment design for a tailings dam, in Proceedings Mine Waste and Tailings Stewardship Conference 2018, pp 427–438 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 23, 2018

By S Khosrowshahi, A Weeks, W J. Shaw

"To provide an indication of expected performance of the mine and mill, feasibility studies should include an assessment of the expected day-to-day variability in process plant feed. Attempts to do this based on conventional resource models will be flawed as such studies fail to consider and account for the in-built smoothing (averaging) of input data.This can lead to one of two situations: an expensive, over-engineered process plant that can cope with every possible situation, or operational strategies that fail to manage the natural variability within the orebody and the impact of day-to-day operational decision-making.In both cases the value of the project diminishes through excessive capital costs or reduced throughput or recovery during operations.Unlike conventional estimation techniques, the geostatistical method of conditional simulation can reproduce the inherent variability of the deposit. Once a valid model has been developed, it is possible to analyse the model using a transfer function that simulates the proposed mining processes and provides a representation of the likely variation of mill feed characteristics at any time scale.The case study demonstrates how the proposed mining strategy would result in mill feed being considerably more variable than expected, resulting in poor recovery, low throughput and potential breaches of environmental conditions. Mitigation measures included budgeting for additional mining equipment to enable greater flexibility during mining and revised stockpiling and crusher feed strategies.Awareness of the benefits of modelling the variability of geometallurgical parameters will increase the use of this approach in producing more realistic financial models of expected mine performance at the design stage.CITATION:Shaw, W J, Khosrowshahi, S and Weeks, A, 2013. Modelling geometallurgical variability - a case study in managing risk, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013, pp 247-252 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Sep 29, 2013

By T Tan, C P. Holmes, C E. Hartford

Transportation of iron ore from the mine to the plant is critical to business success. Ore from the mine may have to be transported across states, countries and even continents to get to the processing plant or export facilities, and ultimately to the client. Numerous transportation steps may result in potential logistical difficulties. Companies are continually seeking ways to increase production rates, decrease delivery times and reduce operating costs. Transportation cost is a major component of the total cost of mining iron ore and therefore requires effective use of transport systems.Bottlenecks in iron ore transport systems, due to material handling issues, can result in loss in profit in the order of millions of dollars per hour. Bottlenecks can be seen anywhere in the transport system where the desired flow rate cannot be achieved. These bottlenecks occur for various reasons such as increasing throughput in a transport system originally designed for a lower throughput resulting in plugged transfer chutes, changing material characteristics (eg finer material, increased moisture content), changing to a new type of material or blend that again alters handleability, or changes in operational philosophy due to equipment availability or process utilisation.Stockpiles may have limited live capacity such that an adequate amount of ore may not be readily reclaimed when required (eg to fill a complete train’s railcars). In bins and hoppers, material may discharge through a central flow channel resulting in the formation of a stable rathole, which can then collapse causing material to flood the downstream system and cause significant downtime for clean-up (eg railcars beneath train load outs). In transfer chutes, bottlenecks can be caused by pluggages or downtime required for the change-out of liners due to excessive wear. In ship loading, long settling or de-aeration time, or material exceeding its transportable moisture limit (TML) may result in further bottlenecks. These bottlenecks all have associated costs because of the need to address their causes and because of the lost opportunities for throughput.This paper will discuss how bulk material technology and proper understanding of material flow characteristics can be applied to mitigate bottlenecks. It will discuss how to predict potential bottleneck locations through a scientific method of analysis and evaluation to determine if an increase in throughput of an existing transport system is possible, as well as whether or not a new material will flow reliably through an existing system.CITATION:Hartford, C E, Holmes, C P and Tan, T, 2015. De-bottlenecking iron ore transportation from mine to plant, in Proceedings Iron Ore 2015, pp 393–398 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By C Lower

An unprecedented, quantitative, deposit-scale understanding of major clay mineral distribution throughout the Yeelirrie uranium deposit has been achieved by adapting the existing HyLogger™/HyChips™ analytical technique to measure resource assay pulps. Spectral analysis via HyLogger™ and HyChips™ systems has previously been used as a small-scale geometallurgical research tool, but never before has it been quantitatively applied to an entire resource sample population for the purpose of developing stand alone block models for major clay minerals. Economic uranium mineralisation within the thin but extensive Yeelirrie?palaeochannel?primarily exists within the transition zone between a groundwater-derived calcrete and the underlying clay-quartz regolith. Early geometallurgical investigations identified that certain clay minerals could be deleterious to the efficiency of the uranium recovery process. Accurate calculation of clay mineralogy from resource assays proved too difficult due to chemical similarities between co-existing kaolinite, smectite and magnesium carbonate minerals. A relatively low-cost, efficient and accurate method of quantitative clay mineral analysis was required to measure over 70 000 resource assay pulps. After initial testing and comparison with QXRD, the HyChips™ 3-1 spectral logging system was implemented as a primary method of clay mineral analysis for the Yeelirrie uranium deposit. The resultant spatial data set allowed the interpretation and geostatistical analysis of geometallurgical domains across the deposit. Clay block models were generated and used in geometallurgical resource calculations to benefit the mine planning process.

Sep 5, 2011

By K Koskinen, S Ronkainen

The flow field induced in an Outokumpu TankCell and by an OK rotor-stator mixing device in a laboratory and a process size flotation cell was modelled numerically using computational fluid dynamics (CFD). The primary target was to discover and reproduce the various interactions between the flow field and the flotation cell by numerical means. As power consumption depends sensitively on flow field, it can be regarded as a top-level derived quantity (or measure/metric) indicating the validity of the numerically obtained flow field. Having properly validated numerical means to produce the flow field the influence of various design parameters can be captured with certain accuracy. In addition, separate gas and solid phase models for bubbles and solids, respectively, were implemented. The comparisons between velocities and turbulence quantities measured using the laser doppler velocimetry (LDV) technique and CFD modelling were performed. The grid generation was performed with the commercial Gambit 1.3 and the subsequent integration and solving of the resulting algebraic equations with the commercial CFD-code Fluent 6.22. The computationally economic multiple reference frame method was included to model the moving rotor blades. Gas and solid phase models were modified mixture models.

Jan 1, 2005

By A Horeth, E Duggan, B Versiani, A Gooch

Iron ore screening plant productivity is strongly affected by the performance of the shuttle operation, with the control system robustness and associated strategies having a direct impact on utilisation and throughput rates. A number of aspects intrinsic to the methods and technologies traditionally applied on the motion control of shuttles are often observed to decrease the efficiency of the ore distribution process across multiple screening modules, which ultimately impacts the plant’s production. Those include the number of operational scenarios that are unmanaged by conventional discrete control logics which may intermittently lead to undesired events, such as ‘high level alarms’ and ‘low level interlocks’ in the screening bins. This outcome usually demands excessive manual intervention by Control Room Operators. A Reinforcement Learning (RL) Artificial Intelligence (AI) solution was deployed to control the motion operation of the scalping and products screening shuttles in an iron ore handling plant. The RL algorithm was trained in advance to handle multiple operational scenarios and generate optimised outputs. In nominal operation, the shuttles are moved in a modulating and highly predictive fashion over the whole range of safely reachable bins. When the need occurs, the AI control agent deviates from that modulation behaviour, limiting its travel range or moving to other groups or clusters of available bins by employing ‘bin jumping’ or ‘ore break’ strategies. The RL platform capabilities include the ability to learn in real time to account for and auto-adapt to new operational patterns and process changes whilst applying improved strategies for shuttle dwelling times, target setting and speed control. The deployed Reinforcement Learning AI solution has better managed the existing challenges associated with the shuttle operation and control, and resulted in a more efficient ore delivery process, superior operations stability and increased production rates.

Nov 8, 2021

By N Burgio

Block cave mines are often thought of as rock factories where high volumes of production are mined from a fixed area suggesting little requirement for geological input and control. Yet caving operations have peculiar and specific technical requirements from prefeasibility through to post-mining reconciliation. Whilst essential elements such as resource definition, geological interpretation and sampling strategies are common to all mining methods, planning for a block cave requires a different emphasis and philosophical approach in how we deal with these issues. We will examine why a geoscientist’s input is critical towards the successful planning, design and monitoring of a caving operation.

Aug 22, 2011

By S Dykes, R J. McCarthy, B Klein

There is growing interest in the mining industry on the application of ore sorting. While many are familiar with particle sorting, including the limitations that technology presents (e.g. throughput), bulk sorting, with its higher throughput potential, is less understood. Despite the potential to sort at higher throughputs, few operations have adopted bulk sorting processes, certainly not at large scale. It is suggested that the inability to reliably predict outcomes from bulk sorting may be limiting its adoption in mining projects. Consequently, an evaluation approach for bulk ore sorting has been developed such that mass pulls and grade upgrades can be predicted in the context of a mining study. The approach allows for evaluation of drill core assays and application of the consequently derived heterogeneity relationships to the block model for estimation of sorting outcomes. These processes were applied to conveyor-based bulk sorting for the CuMo project in Idaho, USA and are described in this paper.

Nov 10, 2020

By D Jeffery, R Whittering, G Lane

Most aspects of process design are best addressed via bench scale or pilot plant scale test work. However, as experience is gained, fundamental or indicative data can provide more than adequate information to manage the risk associated with some process aspects of concentrator design.Historical precedence exists where minimal design test work has resulted in successful projects. On many occasions benchmarking, sometimes supported by fundamental data such as mineralogy, has been used to successfully develop effective process plant outcomes. Of course, this style of approach is most common with æfast trackÆ projects and often comes with the usual surprises that result from inadequate geometallurgy to define the project cash flow.This paper explores the risks and opportunities associated with the various facets of process development and design for a base metals concentrator. The paper is intended to provide guidance to project managers rather than address the technical aspects of process engineering.CITATION:Lane, G, Whittering, R and Jeffery, D, 2012. Benchmarking versus test work - How should you manage process risk?, in Proceedings Project Evaluation 2012 , pp 49-52 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

By M P. Murphy, C M. D Barton

When developing a new underground mine, the geological interpretation that guides the mineral resource is crucial to the preparation of a reliable ore reserve. In preparing a robust geological model to underpin a resource estimate, practitioners must weigh the comparative risk of accepting a relatively wide-spaced drill hole pattern, versus a more close-spaced pattern that ensures a high local geological confidence for mine planning but may have an exponentially increased time and monetary cost. This paper details the authors’ investigations into the geological uncertainty of IGO’s Odysseus Deposit, which is approximately 645 km north-east of Perth, Western Australia. At Odysseus, the komatiitic nickel sulfide mineralisation is irregularly cross-cut by nickel-barren pegmatites that have intruded and offset its thick ultramafic orebodies. These pegmatites generate significant uncertainty in the precision of Odysseus’ resource volume and tonnage estimates, as well as the subsequent quantification of pegmatite mining dilution in its ore reserve. To quantify the geological uncertainty in the pegmatite interpretations, IGO’s mineral resource practitioners prepared several geological risk studies over the Odysseus North lode, which is the lode most affected by the pegmatites. These studies included categorical conditional simulation of the pegmatites, preparing implicit geological models with alternative algorithms, trialling a machine learning application to prepare a maximum likelihood geological model, and finally assessing the early results of the pre-production close-spaced drilling to these different models. To assess the precision of the different single-outcome models, the authors’ compared the estimated pegmatite content of each model to the range of possibilities modelled by categorical conditional simulation within the planned stopes at Odysseus North. An estimation confidence score for each modelling method was then prepared for each alternative single-outcome modelling method. From these studies IGO concluded that a close-spaced drill pattern is essential at Odysseus, supporting the view of the Competent Person in 2017 who proposed a 25 m drill spacing in areas affected by pegmatite which had been partially classified as Inferred.

May 24, 2023

By P Cesare, S Munro, D Wandel, R A. Bearman

Consideration of the processing plant operational envelope is a key factor in production scheduling,and therefore mine planning, for any mining operation. In many cases hard-wired or regressionbased tonnage-grade-recovery relationships are used as mine planning constraints and as a means of valuing the system output. In extensions of this type of approach, various regressions can be used to describe throughput limits, based on a number of global metallurgical parameters.The ultimate position for the optimisation of a mine plan and production schedule is to have a full process plant model running as an integrated part of the mine planning exercise. A plant model suitable for this needs to have all the required sensitivities to input parameters such asfragmentation, grade, mineralogy, strength and hardness. The model then needs to convert these to performance measures for the plant, which include recovery, throughput, product size distributions, energy consumption, water use and operating cost.In this paper an approach is outlined that takes this view and then goes beyond it to provide a full, time-based bottleneck identifi cation and valuation tool.Using such an approach it becomes possible to run mine plans and production schedules in windows of days, weeks, months and over the life-of-mine with a time-enabled process model acting as the active constraint. In this way virtual bottlenecks can be identifi ed for various mine plans and schedules well ahead of time. The value of de-bottlenecking can be defi ned, not just at a plant scale, but in terms of the overall mining operation, and the data can be used as the basis for capital investment decisions.CITATION:Bearman, R A, Cesare, P, Munro, S and Wandel, D, 2014. Incorporation of a full process plant model as an active constraint for mine planning and production scheduling, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 121–128 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By T Honeyands

At present we are witnessing large investments in the iron ore industry, fuelled by demand from Asia. At the same time, there is a changing landscape in pricing of iron ores, with the recent demise of the benchmark system and the evolution of market based index pricing systems. From a customer perspective, it is the behaviour of iron ores in downstream processing that gives them their value; their impact on the sintering or pelletising process and subsequently blast furnace ironmaking. It is therefore important to consider this value when developing projects, making mine planning/cut-off grade decisions, and in setting quality price differentials.This paper describes the use of the Marx value in use (VIU) model to quantify the downstream value of iron ores. The Marx model consists of heat and mass balance modules for sintering, pelletising and a rigorous two-stage heat and mass balance model of blast furnace ironmaking. Mass balance and cost models are applied for steelmaking, casting and rolling. The use of a heat and mass balance allows accurate comparison of the impact of raw material properties on blast furnace operation. The impact of minor elements, such as alumina, silica and phosphorus, and metallurgical properties on ironmaking is described, and examples given for the relative value of haematite, Marra Mamba, and channel iron deposit (CID) ores.

Jul 11, 2011

By D Reid

Run-out analyses of tailings storage facilities are typically undertaken using methods based on rheological theory. These are reasonable techniques to model the behaviour of tailings that, through significant run-out and possibly mixing with supernatant water, are generally acting in a fluidised manner. Such modelling often follows on from two-dimensional continuum analysis models where, if failure is predicted, grid failure often occurs when deformations begin to increase. This results in a disconnect between the prediction of failure and the modelling of the potential extent of the failure.Recently, rezoning methods have been incorporated into commercially available two-dimensional soil mechanics deformation codes. Rezoning techniques enable large deformations to be modelled within a two-dimensional continuum analysis framework; however, while promising, the use of such tools is not yet widespread, and a consensus is yet to develop on how they should be applied to tailings dam run-out modelling.This paper uses FLAC rezoning techniques to model the flow behaviour of two historic tailings dam failures. The purpose of these analyses is to critically assess the performance of rezoning against some available historic failures. The required data to undertake such an analysis is outlined, along with the inherent limitations and assumptions required. Parametric analyses are outlined to address some of these issues. In general, the analyses undertaken underestimated the flow distance observed in the historic failures by varying degrees; however, in some instances, the analysis reasonably reproduced the qualitative shape of the initial failure zone. A variety of potential reasons for the discrepancy between historical observations and the models undertaken are provided.CITATION:Reid, D, 2015. The use of rezoning techniques to model historic tailings failures, in Proceedings Tailings and Mine Waste Management for the 21st Century , pp 201–206 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 27, 2015

By M A. González, J A. Romero, D L. Fuentes, C J. Poblete, O Abdrashitova

"Robustness can be defined as the ability of a system to resist change without adapting its initial stable configuration. Robust design methodology, which is widely accepted in the manufacturing industry, allows the establishment of robustness and reliability metrics in scenario analysis.In the mining industry, a mine can be considered as a system with design parameters such as processing plant and mining capacities. Traditionally, a limited number of scenario iterations are performed in an attempt to determine optimal capacity values. An important strategic decision such as process plant capacity in particular is made during the very early stages of a mining study, often based on a low level of information. Lack of time and tools to run and analyse a larger number of possible scenarios for different design parameter combinations are usually the main reasons for not performing a full analysis. In addition, the uncertainty of other mining study input parameters creates more risk in decision-making.With advances in technology, it is now possible to automate the process of generating several thousands of scenarios in an affordable and timely manner. This allows performing the results analysis and assessing robustness and reliability criteria within a reasonable time frame. It is possible to generate a surface of results based on the net present value (NPV) for each scenario. This surface will reflect the efficiency level of the capture of the economic rent for each production scale. In addition, each scenario can be tested under diverse conditions of volatility of other external variables such as prices, costs or recoveries for example.This paper aims to establish a methodology that applies robustness criteria to determine the best scenario on several surfaces of value, which is then assessed with real data from a mining project. Obtained results demonstrate the advantages of using the proposed methodology in dealing with the above-mentioned multidimensional problems. It allows better decision-making on key design parameters and better control of the risks of a strategic mine plan.Citation:Poblete, C J, González, M A, Romero, J A, Fuentes, D L and Abdrashitova, O, 2016. Use of Robust Design Methodology for Production Scale Definition in Open Pit Mining, in Proceedings Ninth AusIMM Open Pit Operators' Conference 2016, pp 284–291 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Nov 15, 2016

By F Flitti, M Haest, O Dominguez, D Mittrup, G Hird

The automated geology interpretation (AGI) tool has been developed in BHP Billiton to automate stratigraphy logging of drill holes, using any available quantitative data sets. At present, AGI is set-up to utilise geochemistry and mineralogy from infrared spectroscopic data to predict stratigraphy. Once the AGI tool is calibrated, results show that the tool is capable of automatically defining stratigraphy across all of the deposit types, encountered by BHP Billiton Iron Ore in the north-west of Western Australia. Accuracy of AGI at predicting stratigraphy is on average better than 75 per cent, with average accuracies exceeding 85 per cent for some deposit types. The AGI tool can deliver fast, accurate, consistent and objective geological interpretations.AGI is currently being implemented in BHP Billiton Iron Ore Exploration to streamline the drill hole logging process and allow geologists to spend less time defining stratigraphy at the drill hole level and more time investigating stratigraphy in 3D. This will deliver improved geology models, with significant downstream benefits in terms of better resource models, more accurate mine plans, higher plant efficiencies and more consistent ore products, driving productivity in BHP Billiton Iron Ore over the next decade.CITATION:Mittrup, D, Flitti, F, Hird, G, Haest, M and Dominguez, O, 2015. Semi-automated geological interpretation using assay and infrared spectroscopic sensing parameters towards improvements in geological modelling, in Proceedings Iron Ore 2015, pp 313–318 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 13, 2015

By A Huebner, A Noack

Companies all over the world are very sensitive concerning their IT and network security. In most network connected technical installations and machines however, network security is not taken into account to a significant extent: insecure protocols are run, unencrypted information is exchanged freely and even broadcasted wirelessly and networked machines are accessible via insecure file transfer protocol (FTP).What happens in case of malfunctions of such technical installations? Who is responsible? Who can be held liable in case of accidents? The first computer worm for automation systems (æSTUXNETÆ) (Symantec, 2010) was discovered during 2010.The paper is intended to create sensitivity among decision makers for potential security and resulting safety leaks and points out the current status quo in technical network security. It outlines best practices for secure networking and procedures for remote access and remote software updates on stationary equipment and mobile mining machinery. It describes how to ensure authentic and genuine configurations and software targets and how to ensure secure communication for autonomous and remote controlled equipment. For such equipment in particular, the following statement should apply: æThere is no safety without network securityÆ.

Sep 26, 2011