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By D Goel

India, the second-largest steel manufacturer globally, achieved crude steel production of around 126 million tonnes (Mt) in the last financial year of April 2022 to March 2023 (FY23), against an installed capacity of 162 Mt. In its National Steel Policy, 2017, India has undertaken targets to take the crude steel production capacity to 300 Mt by 2030–2031 and production and demand to around 255 Mtpa, also by this deadline. The blast furnace-basic oxygen furnace (BF-BoF):electric arc furnace-induction furnace (EAF-IF) ratio in 2022 was at 44:56.

Sep 18, 2023

This paper discusses the requirements for a successful simulation modelling study, and the steps involved in the modelling process. Advantages and disadvantages of simulation are described, and a case study highlights how not to go about it. Two other case studies, for a decline truck haulage and a block caving production operation, are used to illustrate the types of variables whose impact may be investigated. Typical results are presented to indicate the sorts of presentation styles the author has found useful for conveying study results to project sponsors. Standard spreadsheet charting techniques can be very useful in this respect, but the possibilities are limited only by the imagination of the study team.

Jan 1, 2000

Nickel laterite HPAL circuits are known for their complexity and have presented a large number of challenges to process engineers worldwide. An attitude commonly encountered by the author is that the beneficiation of the ore is relatively simple and that the difficult problems are in the realms of hydrometallurgy. On a number of occasions beneficiation has become the 'poor cousin' in the process design phase. Another common theme is that significant difficulties are encountered when beneficiation circuits are started up, invariably slowing the ramp-up of the remainder of the circuit. In some cases the problems impact on throughput for a long period and can require major rectification capital. The HPAL Ni laterite projects encountered each have their own set of beneficiation problems that need to be understood before an appropriate circuit can be designed. This paper will discuss a range of design issues including geometallurgy, ore characterisation through laboratory testing, the application of appropriate sizing and analytical procedures, the selection of appropriate unit operations, materials handling of plant feed and products and setting meaningful plant design requirements.

Jan 1, 2008

By W P. Breytenbach

"The phased application of statistical process control (SPC) infers that processes are classifiable as pre-SPC (or phase zero), phase I and phase II processes, with different objectives being pursued in the different phases. Phase zero processes, defined as processes affected by assignable causes of variation, are characterised as follows: out-of-control with unknown autocorrelation structure having an unknown statistical distribution not performing consistently on target with minimum variability potentially incapable of conforming to the product specifications. The objectives of phase I SPC is to obtain estimates of the mean (µ), variance (s2), probability density function (f(X)) and the autocorrelation structure, as well as transforming the process into a phase II process (defined as a process conforming to specifications and performing on target with minimum variability). As in any other type of research or pragmatic improvement intervention, sampling is required is to achieve these objectives. The challenge of deciding a phase I sampling plan is multifarious since it has to cope with the aforementioned effects of assignable causes and provide for rigour estimates of the unknown parameters. Furthermore, deciding sampling plans in phase I invariably presents a classical catch-22 situation: appropriate sampling is required to determine the autocorrelation structure of a variable, but knowledge of the autocorrelation structure is required to formulate an appropriate sampling plan. This paper suggests, for random variables, guidelines to formulate sampling plans, and presents a methodology to estimate the inherent process parameters of process variables and an approach to identify assignable causes in phase I. CITATION:Breytenbach, W P, 2014. Rational sampling and standard deviations for random variables in phase i application of statistical process control, in Proceedings Sampling 2014, pp 141–154 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Jul 29, 2014

By M Mohammad Khani

An economic block cave is dependent to the characteristics of the rock mass at stages of caving. These are cave initiation, propagation and ore flow. In this research, the rock engineering system (RES), first established by Hudson (1992) to solve complex rock engineering problems, is introduced and verified against the well-established caving parameters established by Laubscher. There are two types of factors influencing caving and these are natural (cannot be controlled) and induced (operator controlled). A RES based interaction matrix is developed by determining the rating parameters required to reproduce the caving database using Laubscher’s caving parameters. This provides the relative importance of the parameters in the interaction matrix. After discussing the rock mass caving process and identifying all the effective parameters, an interaction matrix is introduced to study the cave initiation of rock masses. The expert-semi-quantitative (ESQ) coding method is utilised to assign the numerical value to each parameter’s interaction. Thereafter, the interaction intensity and dominance of each factor in the system is determined to classify these factors. Finally, all the parameters affecting caving operation and their weights on the RES system are identified. This new application of RES in block caving is very efficient and useful for any stage of caving studies and helps experts to make decisions more accurately.CITATION:Mohammad Khani, M, 2016. The application of rock engineering systems to block caving to identify the effective parameters, in Proceedings Seventh International Conference and Exhibition on Mass Mining (MassMin 2016), pp 853–860 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2016

Government established and financed the NZ Steel Investigating Co in 1960. Its investigations showed that a steel industry was feasible and desirable based uponNorth Island titanomagnetite ironsands, and charted a route for its establishment. The initial processing used post-1945 preheating and prereduction developments, but later innovative improvements created what was essentially a new New Zealand technology. Of the North Island titanomagnetite deposits: the small ones at Waipipi were best made available for export; those at Kawhia and Taharoa were too remote for the economic siting of a mill; that at Raglan proved too small; while at Waikato North Head three times the requirement of 50 million tons of concentrate were located in two sand areas averaging 18 per cent titanomagnetite. Economic studies showed that a South Auckland site would be ideal, close to New Zealand's biggest market. The mill site, on a basalt flow at Glenbrook, was located by a half-day's fieldwork - near both the Waikato North Head deposit, and a railhead for bringing in Waikato coal, etc, and taking out steel products.   This development was one of several since World War II which altered significantly the lives and homes of New Zealanders (others were natural gas, oil, geothermal power, epithermal gold, aluminium, opencastable lignite, etc). All had the essential ingredients of the highest government backing, direct or indirect government finance, and first-class New Zealand scientific and engineering skills (eg to create new technologies). Not one such project failed.

Jan 1, 1993

By S A. Campbell

There has been a reduction of coal production in the United States due to environmental pressure and the increased use of natural gas. This reduction will require coal producers and consumers to make decisions on whether to sample more to verify contract quality or sample less in an effort to cut costs.CITATION:Campbell, S A, 2014. The shrinking coal market in the US – sample more or sample less?, in Proceedings Sampling 2014 , pp 3–6 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 29, 2014

By I F. Wood

Planning for flooding and assessment of flood impacts are important requirements for mining projects, as they are also for other types of development. With more intense development and concern from the community, supported by government regulatory requirements, assessment of flood concerns and impacts has become of increasing importance. To ensure that flooding issues are fully understood and results presented in an appropriate format, advanced hydraulic analysis procedures have been developed and are beginning to be applied. These procedures must be rigorous in an engineering context but the results must also be readily understood by the community and government agencies. Advanced two-dimensional hydraulic modelling is becoming accepted as an important means of assessing flooding issues for mining projects. With presentation of results from hydraulic models with Geographic Information Systems (GIS), flood impacts can be analysed rigorously and presented clearly. This paper discusses the application of advanced hydraulic modelling in the planning and impact assessment of a major mining project located on a floodplain where there is extensive inundation. The analysis provides for both input to the planning of the project and for detailed assessment of potential impacts. This case study illustrates some important aspects of the application of hydraulic modelling using a two-dimensional modelling to a critical flood design.

Jan 1, 2003

By G Nicholas, S Coward, J Vann, R Wolff, S Jackson, S Moayer, A Bye

"A new approach to mineral project evaluation is described called Scenario-Based Project Evaluation (SBPE). SBPE incorporates well established æscenario planningÆ and æscenario thinkingÆ approaches, which are used extensively in other industries,?most notably the?petroleum industry. While most scenario planning is qualitative and non-probabilistic, the approach described here includes both quantitative and qualitative aspects. SBPE is complementary to optimisation approaches and allows mining firms to build and operate projects that are more robust in the face of adverse changes as well as proactively respond and exploit the upside offered by a realistic assessment of variability. The approach has potential to improve project performance and decrease operational risk. It also has important applications for currently operating mines.Conventional evaluation of metalliferous mineral deposits uses estimates of metal grades and deleterious attributes in singular æorebody modelsÆ, usually 3D block models, which fail to capture two critical aspects that underpin the realised value of mining projects: the inherent uncertainty of the estimated attributes the spatial variability of attributes, at the scale of mining selection, which impact on downstream processing steps and fundamentally drive realised value. While singular models are appropriate for estimating block averages, conditional simulation (CS) models of the relevant attributes are needed to represent uncertainty and capture spatial variability. Any attributes that can be either built into CS models and/or modelled in the envisaged mining/processing steps, can be evaluated fully through to highly ægranularÆ (ie detailed and un-smoothed) cash flows. A complete view of SBPE relies on selected strategies being tested against plausible æscenariosÆ of factors external to the project and thus outside management control. æExternalitiesÆ captured in such scenarios include market prices, costs and taxes. Via SBPE, project managers may demonstrate that there is material value in preserving or purchasing options that provide future flexibility to respond to the changing externalities or changes in orebody performance. Such flexibility generally comes at a cost but is very difficult to value. It is argued that full value chain evaluation using SBPE can help to value these options for a mining company. A case study for a gold mine is presented.CITATION:Vann, J, Jackson, S, Bye, A, Coward, S, Moayer, S, Nicholas, G and Wolff, R, 2012. Scenario thinking - A powerful tool for strategic planning and evaluation of mining projects and operations, in Proceedings Project Evaluation 2012, pp 5-14 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

May 24, 2012

By D Kentwell

IGO Ltd’s (IGO) Nova Operation (Nova) is 160 km east-north-east of the town of Norseman in Western Australia (WA). Discovered by Sirius Resources NL (Sirius) in 2012 and acquired by IGO in 2015, the Nova-Bollinger Deposit (Nova-Bollinger) occurs within the Fraser Zone of the AlbanyFraser Orogen. Nova-Bollinger is a complex nickel-copper-cobalt (Ni-Cu-Co) magmatic intrusive sulfide deposit, which is characterised by high-grade folded and undulating breccia lodes that host the bulk of the payable metals. Significant sulfide mineralisation is also found in several magmatic intrusive styles including net-textured, disseminated and blebby styles. A smaller but material volume of sulfides has also been remobilised into the deposit’s footwall rocks as ‘stringer’ bands in metasediments, or as discrete massive sulfide lenses. When interpolating Mineral Resource estimate (MRE) block grades in the presence of locally varying grade connectivity trends, such as folds or undulations, the sample search neighbourhood, which is used to identify the composites subset that is used for each block estimate, should be oriented to match the local trends. In theory, the most robust method of estimation where locally varying angles (LVAs) are applied to search neighbourhoods, are techniques where the composites and the blocks to be estimated are transformed to an unfolded coordinate system (UCS). However, UCS methods can be tedious to implement and require subjective decisions to be made that cannot always be fully defended. An alternative LVA method commonly used in the industry is dynamic anisotropy (DA), which is much simpler to implement and is often assumed (but not that often demonstrated) to result in similar results to UCS-style estimation. In 2018, Nova’s Mine Geology team (MGT) estimated the grades and density of the Nova-Bollinger MRE using the UCS approach. For the 2020 MRE update, Nova’s MGT tested and compared the USC grade interpolation method with the DA approach. As applied to the Nova-Bollinger’s 2020 MRE, the comparison, advantages and disadvantages of the two estimation methods are the subject of this paper

Mar 22, 2022

By R Valenta, A Littleboy

Geological heterogeneity is one dimension of complexity in mining. Significant effort is put into developing an understanding of this complexity so it can be used in resource estimation, mine planning and economic modelling. However, over the decadal lifespan of a mining venture, many other dimensions add to the complexity of a mining operation. These include: technological evolution, market fluctuations; investor confidence; social norms; local expectations; and ecosystem functionality. As with geology, these factors are all heterogeneous, uncertain, time varying and represented through sparse and incomplete datasets. Recent work (Valenta et al) is beginning to show us how these risks correlate in different global settings. By analysing data relating to known, but as yet undeveloped copper deposits, this work (the complex ore body database) is demonstrating that it is the combination of issues (both price sensitive and non price-sensitive) that determine the viability of a deposit for extraction in the 21st century.CITATION: Littleboy, A, Plint, N and Valenta, R, 2018. Mining as a complex system: do we need a new model?, in Proceedings Complex Orebodies Conference 2018, pp 41–43 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 21, 2018

The optimisation and validation of shearer cutting methods is a time consuming engineering task. Many different parameters, of which not all can be controlled, can vary. The easiest solution, to increase the installed power and the longwall length, is not always the best. A different cutting method can increase the capacity without the need of new machines. The Department for Mining and Metallurgy Machinery at RWTH Aachen University therefore developed ProSL, the simulation tool for shearer and longwall operations. ProSL enables the engineer to create his own cutting methods and compare it with other methods. Machine-data can easily be varied to see the impact on the method. The research shows that sophisticated longwall methods increase the productivity of the system. The paper presents the results of the calculation with ProSL and shows how higher efficiency and lower costs can be achieved.

Dec 6, 2010

By E J. Sellers, A Cocker

Movement of the fragmented rock mass is an inevitable consequence of open cut blasting. Uncontrolled, unaccounted movement from blasting commonly causes ore loss and dilution from waste mixing. Therefore, the prediction of the post-blast location of both ore and waste is vital in grade control and of direct interest to mining geologists. Direct measurement techniques have matured significantly over the past decade, but their use remains expensive and labour intensive. Access and safety issues are further disincentives to regular movement monitoring. What is needed is a combination of direct measurement to establish baselines and reliable predictive modelling.The W H Bryan Mining and Geology Centre of the University of Queensland has pioneered 3D blast movement modelling using ‘physics engines’ to handle in-flight collisions and predict the final resting place of blasted material. Open cut metalliferous mines are a demanding environment for this style of modelling as they can involve complex geometries and variable buffering, which leads to inconsistent confinement. A version of the model designed to deal with these complexities is under development. A well-controlled field trial was needed to validate this new version.A validation trial was completed at a gold mine in South-East Asia. The aim was to increase throughput by increasing the blast powder factor without losing grade through dilution and mixing with waste. Four blocks were blasted to identify the effect of bench height and face confinement on ore movement, fragmentation and process throughput. The powder factor and blast timing were kept constant. Movement of the broken rock was measured by placing blast movement monitors at known positions in the block and then locating them after the blast. The majority of sensors were recovered, providing a unique insight into blast movement dynamics and generating a substantial data set for model validation.The model (called ‘MetaMove ‘) was calibrated for one blast and applied to investigate the extent of grade loss and possible mitigation strategies. Conventional mining techniques that involved firing across the strike of the orebody, and no post-blast boundary adjustment of the ore/waste boundaries prior to digging, were found to cause up to 44 per cent loss of high-grade ore, depending on the grade distributions. Post-blast adjustment of the ore/waste boundaries can negate this loss. The model indicates that altering timing and ensuring that the block boundaries are well confined can further constrain the movement of ore/waste boundaries. Thus, the model can be successfully applied to minimise grade dilution and limit misclassification of ore as waste whilst using higher powder factors to increase mill throughput. Application of a calibrated model to move ore/waste boundaries prior to digging will enable the production geology team to add significant value to the mining operation.CITATION:Cocker, A and Sellers, E J, 2014. Modelling blast movement for grade control at an open cut gold mine, in Proceedings Ninth International Mining Geology Conference 2014 , pp 377–386 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By M Ireland

Extensive use of diesel-powered mobile equipment in modern mines for materials handling, such as load-haul-dump machines, constitute a significant source of heat, exhaust gases and diesel particulate matter. Provision of sufficient quantities of fresh, cool air are required to remove such atmospheric contaminants from the environment for miners, particularly at depths where ventilation constraints and associated operating costs have an increasingly adverse impact. An alternative solution to diesel equipment to combat economic, environmental, social and health challenges, are battery electric vehicles (BEV), with the potential to expand production and substantially reduce ventilation and cooling demand, subsequently reducing operating costs. In this context, this paper focuses on the introduction of a battery electric loader to a diesel fleet at one of the deepest underground mines in Australia, the CSA Mine, a high-grade copper operation in Cobar, New South Wales. Analysis of a trial battery electric loader compared to existing diesel machines is performed with regards to infrastructure, technical and operational issues. Key benefits of battery electric vehicles over conventional diesel-powered vehicles are discussed, including lower energy consumption and greater efficiency, reduction of emissions and heat, reduced need for ventilation and lower operating costs. Challenges of introducing BEVs into an operation, along with the results from the comparative study are addressed under impacts to energy consumption, equipment selection, effects on ventilation and cooling, mine design and economic viability for future fleet implementation scenarios whilst meeting production targets.

Mar 29, 2023

By A K. B Opitz, M Becker, J L. Broadhurst

"One of the key drivers of geometallurgy is to define the ore characteristics and their variability to build a geometallurgical model. The inclusion of waste rock properties and their variability is just as important, given that the generation of acid rock drainage (ARD) poses one of the most significant environmental challenges facing the mining industry. Formed through the oxidation of sulfide minerals in the presence of oxygen and water, ARD generation is exacerbated through the regeneration of lixiviates by naturally occurring iron- and sulfur-oxidising micro-organisms. In order to manage the potential risk of ARD pollution, timely, accurate, reliable and robust characterisation and prediction of the ARD potential of waste material is critical from an early stage in the mining process.This study demonstrates the use of the biokinetic-accelerated weathering test developed at the University of Cape Town to characterise the ARD potentials of gold waste rock samples under microbial conditions. These tests are performed in conjunction with standard characterisation tests to provide an indication of the potential for ARD generation under both chemical and biological conditions. Results provided information regarding the relative rates of acid neutralisation and acid generation, with the contribution of specific minerals to the observed behaviour considered through use of a detailed mineralogical assessment. Overall, the addition of the biokinetic test to the current geometallurgical characterisation and prediction toolbox will allow for relatively rapid assessment of the bulk kinetics of ARD generation.CITATION:Opitz, A K B, Becker, M, Broadhurst, J L, Bradshaw, D J and Harrison, S T L, 2016. The Biokinetic Test as a Geometallurgical Indicator for Acid Rock Drainage Potentials, in Proceedings The Third AusIMM International Geometallurgy Conference (GeoMet) 2016, pp 183–192 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Jun 15, 2016

Mineral processing is at the hub of the exploration-mining-metals production system. Because of the large volumes of material processed, incremental technology investments can pay off better than for other parts of the system. However, much of mineral processing remains a 'black art', because we are behind in investing in modem technologies. Consequently, we have one of the best opportunities to improve efficiency and competitiveness through the application and transfer of technologies that have already been developed for other industries. The reluctance of minerals companies to place priority in our area is not because we lack new ideas; our senior management has not been convinced, based on our previous results, that such investments will pay off as well as other investment opportunities competing for the same resources. The key is the proper establishment of technology strategy and more effective transfer of technology. The presentation will identify the failure mechanisms of technology transfer and will present a model for improving the success rate, a prerequisite for raising the priority of mineral processing investment. Topics emphasised include strategy formulation, human resources planning, and total quality management principles applied to improving technology transfer.

Jan 1, 1993

By D Matthews

With the increasing demand for quality-specific ores, coupled to the reality of even more complex minable iron ore reserves, there is a growing need for real-time online material analysis of plant feed and product. For a full system mass balance, the combination of conveyor weight scales, flow and density transmitters are required. This alone does not guarantee product grade. For optimal process control and material blending, real-time online elemental scans in combination with the mass weighting is becoming more than a ‘nice to have’. These elemental scans located at key positions, enable the mining and plant operators to make informed decisions timeously, therefore ensuring product outcomes and optimising operations where material grade and the control thereof are important. Typically, these units follow the mining and primary crushing circuit as well as on the product conveyors, low-grade conveyors and tailings lines. Deployed after the primary crushing circuit, an analyser acts twofold:1. guaranteeing mining production, and2. processing facility feed blends.The analysers on the product conveyors guarantee saleable product. The analysers on the low-grade conveyor and tailings line complete the elemental balance and identify the potential of the low-grade and tailings for future processing. The system losses (accumulation) are calculated to determine the amount of material ‘lost’ during the processing stage which does not report to any of the aforementioned and can be used as a measure of the efficiency of the plant. A further advantage of the real-time online analysis of material is that immediate intervention can be taken in the event that the product is not of saleable product grade requirements. In the Khumani Iron Ore mine, Northern Cape, South Africa, run-of-mine (ROM), product and control analysers were included. Run-of-mine and product stockpiles are certifi ed, low-grade material is not currently directly measured, but calculated from the internal control loops. Iron units are reconciled between product and feed material.

Jul 11, 2011

In the UK during the 1990s the energy companies had developed a policy of æDash for GasÆ, building large natural gas power stations to produce more than 30 per cent of the UKÆs electricity demand. The price of imported thermal coal was dropping and the electricity generators were putting pressure on the UK coal producers to produce coal at a reduced cost. Imported coal from Columbia, South Africa, America and Australasia had increased their market share in thermal coal sales to over 50 per cent of a 55 Mtpa market. The pressure on the UK coal industry to reduce costs and improve productivity levels from an ever decreasing resource was high. Companies were benchmarking their operations on the imported coal producers and had to realign their organisations, productivity levels and costs to world best practice, not just technically, but in world class organisational management techniques.

Jan 1, 2005

By D Lucato, B Haase, R Saha, S Limberger-Forte, J Lishman

Cadia East Mining operations have employed geometallurgical techniques to advance the understanding of the in situ rock hardness variability across existing Panel Caves (PC). Geometallurgy advances the understanding of variability across an orebody through the integration of geology, mineralogy and processing response and therefore enhances spatial mapping of comminution or separation properties. Spatially extensive geometallurgical measurements are necessary so that continuous rock properties can be generated and used for the development of comminution and processing domains using geostatistical modelling. Standard testing protocol across geological and mineralogical domains is vital to understand the variability in deposit wide comminution and separation properties. The high cost and large sample requirements associated with metallurgical test work typically results in insufficient data density and distribution, making it difficult to model and map deposit scale variability. Quantitative hardness proxy tools are useful to measure in situ rock hardness, however this data is typically either sparse or missing within advanced mining operations. In recent years, mineralogy and multi-element assay data has often been collected as part of the standard geological data set and is generally coincident with metallurgical test work. In this paper relationships between mineralogy and comminution parameters have been applied to multi-element assay data with coincident measured Bond Work Index (BWi) data to generate a predicted BWi using linear regression. The predicted BWi is intended to supplement existing measured BWi data to enable better extrapolation across the deposit. Geostatistical Conditional Simulation methods have then used the predicted and measured BWi data to produce a BWi variable as a new input to the resource model. The simulated BWi can be used as an input for specific energy models to predict required grinding energy consumption across a deposit.

Mar 22, 2022

By J Tibbett, A Colebourn, B Hebblewhite, F Suorineni

The concept of Big Data refers to data sets that are so large, variable and/or complex that traditional data processing applications struggle to integrate the data for effective investigation, analysis and value generation. With advances in sensor technology and smarter equipment, the mining industry is experiencing Big Data, and in a different way to how the intelligence and marketing communities experience Big Data. Future mining will bring larger, more complicated and diverse data sets increasing the strain on traditional data integration and investigation techniques. Block caving is an important mining method for the extraction of massive, low-grade ore deposits due to its low operating cost and high production potential, given the right orebody geometry and ground conditions. This paper focuses on block caving due to its increasing popularity and importance in the future economic extraction of multiple commodities. The block cave mining system (BCMS) is a complex interrelation of factors, and due to the reliance on natural processes within the system, it is one of the least understood mining methods. Obtaining information on the factors within the BCMS generates large, complex data sets on various time scales. Each sensor network within the BCMS combines spatial and temporal information with tens to hundreds of recorded parameters. Data sets are quickly moving from multidimensional to n-dimensional. Optimisation of the BCMS is only possible through a holistic analysis approach, thus involving the integration of multiple, diverse, n-dimensional data sets (Big Data). This paper presents a current example BCMS Big Data situation involving 12 sources of information with differences in volume, data format and frequency of data generation. This suitability of virtual reality scientific visualisation (VRSV) as a solution to BCMS Big Data interpretation difficulties is then discussed. These 12 data sets can be effectively integrated using VRSV for intuitive and accelerated investigation of the BCMS. Potential future Big Data within the BCMS is presented involving 20 sources of information resulting from our increased need for monitoring and advancements in technology. Current methods of defining queries may not be suitable within these future complex, multidimensional data sets, and the potential of artificial intelligence algorithms within this system is discussed. These advancements in technology and machine learning lead to the requirement of live data acquisition and analysis. VRSV is identified as a suitable technology to satisfy the needs of real-time insight into the performance of these future caves for optimised management and reduced risk.CITATION:Tibbett, J, Suorineni, F, Hebblewhite, B and Colebourn, A, 2015. Virtual reality scientific visualisation – a solution for big data analysis of the block cave mining system, in Proceedings Third International Future Mining Conference, pp 109–116 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 4, 2015