Search Documents

By R A. Lynch

The state-of-the-art in cave seismic monitoring is reviewed, with the latest developments in active seismic monitoring included. Seismic monitoring systems are routinely used by most of the world’s block and panel caving mines to track the cave initiation and progression. The current best practice is to use the cloud of seismic event locations as a proxy for cave growth somewhere below. Problems with event location reliability due to seismic ray bending around the (unknown) cave are side-stepped by using sensors installed above the cave. However, the aseismic gap – the (unknown) distance between actual cave back and seismic event cloud – currently hinders reliable estimation of cave geometry.Velocity inversions using the passive seismic data are inexpensive and should be undertaken more routinely. The straight-ray methods should be used with caution, as the underlying assumptions are invalid in caving environments. The double-difference method is more correct for the caving situation, and there have been some promising results published. Constrained geometric inversions make a lot of sense, but have yet to be demonstrated successfully.Two active seismic source have recently been developed for use in the caving environment: a piezoelectric source for ranges up to a few hundred metres and a pneumatically-powered source for ranges up to a kilometre. These sources produce signals on standard mine seismic sensors that can be used to measure seismic velocity variations down to 0.01 per cent resolution. This allows the cave progression to be monitored by measuring tiny changes to seismic velocities as the rock above the cave is fractured and destressed.CITATION:Lynch, R A, 2016. Active and passive seismic monitoring of cave front evolution, in Proceedings Seventh International Conference and Exhibition on Mass Mining (MassMin 2016), pp 217–224 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2016

By P Paredes, T Leaño, D Gajardo, C Tramón, S Peñaloza

The definition of an ore handling system and its consequent layout design is of crucial importance in cave mining projects. It not only represents the main driver in the production capacity and reliability of the mining system, it is also a fundamental variable in the footprint’s development time and cost.In recent decades, load-haul-dump (LHD) tramming distance optimisation through the allocation of several orepasses inside the footprint has been the most common practice in ore handling system layout definition at Codelco’s operations. Today, the improvement of existing technology, such as higher-capacity LHDs and jaw-gyratory crushers, and intensive preconditioning techniques to improve fragmentation allow the conceptualisation of simple and highly productive ore handling system layouts for wide caving areas that avoid the complexity and high cost of developing numerous orepasses inside the footprint.The initial macroblocks of the Chuquicamata underground mine project (PMCHS) consider an ore handling system layout in which LHDs dump into orepasses located inside the footprint area. The ore is then transferred into crusher chambers located below the production level, where it is crushed by jaw crushers and then conveyed to surface. In an effort to reduce development time and costs, a new ore handling system layout for the PMCHS experimental macroblocks was engineered using improved technologies and techniques in a simpler mining system. This paper compares the new ore handling system layout for the project’s experimental macroblocks with the traditional LHD-orepass layout in terms of production capacity, reliability, development time and cost.CITATION:Paredes, P, Gajardo, D, Leaño, T, Peñaloza, S and Tramón, C, 2016. Simplifying the ore handling system through the use of current technology at Chuquicamata underground mine project, in Proceedings Seventh International Conference and Exhibition on Mass Mining (MassMin 2016), pp 571–584 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2016

By M I. Pownceby, J Manuel, S Suthers, A Poliakov, E Donskoi, N Ware

"The mining industry is constantly seeking methods for optimising the exploitation of mineral resources, such as iron ore, in a sustainable and eco-efficient manner for economic and social benefit. When faced with resources that have mineralogical or textural complexity, poorer grades or geological variability, it is particularly important to apply a comprehensive geometallurgical approach to the development of the mining operation, from resource definition through to processed product. Integral to this approach is the quantitative characterisation of representative samples across the whole orebody.A key factor that associates the geological characteristics of iron ores to their processing response is ore texture. While the classification of samples on the basis of chemical or physical properties alone is often not sufficient to predict their processing behaviour, classification and quantification of texture types can be effectively correlated to metallurgical performance in processes such as blending, beneficiation, pellet making, sintering and ironmaking. This paper describes some of the research conducted by CSIRO pertaining to the design and rationale of a texture-based classification system for Australian iron ores; some of the tools developed and used to apply such classification; and the application of the generated data to quantifying, modelling and predicting sintering behaviour and performance in the blast furnace.CITATION:Suthers, S, Pownceby, M I, Manuel, J, Ware, N, Donskoi, E and Poliakov, A, 2016. Geometallurgical Characterisation of Australian Iron Ores – from Ore to Processed Product, in Proceedings The Third AusIMM International Geometallurgy Conference (GeoMet) 2016, pp 351–360 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Jun 15, 2016

By M Grigorescu, J H. Hodgkinson, H Alehossein

A new framework that collates and interprets pre-existing data to assess vulnerability and ultimately plan to avoid or minimise flood-related risk to infrastructure, people, downtime, environment and revenue has been developed. The æClimate Related Adaptation from Terrain Evaluation ResultsÆ (CRATER) method tested at a coal mine in Queensland, provides semi-quantitative information to assist decision makers when designating investment for minimising vulnerability of mining operations to climate. Here we present the processes involved in this three-step approach that uses pre-existing spatial data of the mine site and local knowledge to build a set of visual tools to assist decision-making. The first step of the process is performing multi-criteria evaluation (MCE) within a geographic information system (GIS) on ranked natural conditions at the mine, such as elevation, slope, drainage, soil and vegetation, which is performed to identify critical flood areas. Secondly, a fault-tree analysis identifies how impact can occur and what options there are for impact reduction. Finally, a resource assessment of the mineÆs capacity to adapt reduces the adaptation options to those most suited to the mine. The results are confidential, but for the purpose of introducing the methodology, we present simplified results, particularly of steps 2 and 3. CRATER can also be used for future æwhat-ifÆ flooding scenarios to identify the most suitable locations for roads, buildings or other critical infrastructure. The methodology is transferable to any mine, series of mines or locations along the mining value chain that have sufficient data, providing a practical decision-making tool to identify æno-regretsÆ actions that not only could reduce downtime after or during an event, but in some cases may enhance production between extreme events. We now plan to test this method at a broader scale, to encompass more than one mine in the analysis.CITATION:Hodgkinson, J H, Grigorescu, M and Alehossein, H, 2013. Climate Related Adaptation from Terrain Evaluation Results (CRATER) - interpretation of pre-existing data for mine site flood vulnerability and management, in Proceedings Water in Mining 2013 , pp 259-266 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 26, 2013

By J Joy, A Bye, G V. Kizil

This paper presents an application of the newly developed risk-cost-benefit (RCB) framework to support risk management decisions for the selection of wall monitoring technologies at an open cut mine site. The RCB framework quantitatively assessed the risk of unstable slope-induced wall failure and its impact on both loss of life and coal recovery. The RCB framework was utilised in the selection of an optimum group of risk-controls to effectively manage the risk of wall failure to ensure safety and optimal production occurred. The RCB framework incorporates mathematical modules that integrated RCB calculations and risk-control effectiveness assessments to determine the risk reduction and financial impact of the examined safety initiatives.This paper provides an overview of the five-staged RCB framework, incorporating the RCB decision support tools, RCBGEN (Risk-Cost-Benefit Generator) and RCEMETHOD (Risk-Control Effectiveness Method), and demonstrates its application to slope stability risk management at the case study site. The RCB charts are designed to display a balance between risk, cost and benefit for easy interpretation by decision makers to support the objective selection of an optimum suite of risk-controls. The RCB analysis revealed that a combination of ævisual inspections, automatic extensometers and radarÆ for fast- and slow-wall failures with structure were sufficient to reduce the probability of loss of life (PLoL) to the æModerateÆ zone as defined by the Australian Geomechanics Society (AGS, 2007) for the case study site. The new framework presented in this paper provides a method to effectively determine the suitability of risk-controls and supports industry efforts to reduce risk to as low as reasonably practicable (ALARP).CITATION:Kizil, G V, Bye, A and Joy, J, 2012. Risk-cost-benefit analysis of early warning technologies impact for wall failure risk management in surface mines, in Proceedings Eighth Open Pit OperatorsÆ Conference , pp 55-64 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 18, 2012

By F K. R Klose

Malmberget is a sublevel caving mine owned and operated by Luossavaara-Kiirunavaara Aktiebolag (LKAB), a Swedish state-owned iron ore mining company, in northern Sweden. The mine has an annual iron ore production of approximately 15 Mtpa. The current strategy foresees an expansion which will increase the mine’s depth considerably. Ventilation and air conditioning modelling for the planned expansion is ongoing. One of the most influential parameters for ventilation planning anddesign for a deep mine is geothermal gradient, which is crucial for the design of the refrigeration system. It is determined through virgin rock temperature (VRT) measurements carried out at various depth below the surface. This paper details these measurements and the determination of geothermal gradient for Malmberget Mine for the expansion study, which were necessitated by thelack of information for the focus depth and area.

Oct 12, 2022

By T N. Little

The aim of any rock breaking activity is to achieve success by developing designs that are blasting objective-specific and geology-specific, and then implementing such designs. This paper targets mining geologists with the aim of extending their knowledge of the rock fragmentation processes and providing insights to the significant relationships between geology and blasting. There are two main relationships, and if mining geologists appreciate both these relationships, then they can play a key role in optimising production. The business risk continuum is introduced to support this understanding. The first relationship is between geology and potential blasting hazards, and the operational complexity required to manage those risks. The risks associated with eight different ground types are discussed in terms of ground conditions, hazards and controls. These types are: reactive ground, hot ground, geothermal ground, fibrous ground, cavernous ground, combustible ground, pyritic ground and conductive ground.The second relationship is between the bench geology and blasting results. The blasting results discussed include: muckpile characteristics, remaining rock faces and blasting emissions. In this regard, some detailed insights and graphical examples are given for the influence of geology on blasting emissions, in particular, vibration, airblast and flyrock.A detailed description of the geological materials themselves can convey much useful information for blasting operators provided they are able to utilise this knowledge. Geologists are ideally suited to provide this description more effectively if they are familiar with the blasting process and the rock mass properties that influence blasting hazards and blasting results. It is also important to have clear statements of blasting objectives and associated operational targets, and this will maximise the likelihood of achieving the desired outcomes. The main aim of the paper is to highlight that geology is currently not fully utilised in the blasting process. In this regard, geologists are often not entirely aware of the blasting process and how they can contribute. The two significant relationships discussed above are integral parts of this process, and thus they are discussed as separate issues in the main body of this investigation.

Aug 22, 2011

Reliable and discriminating small, laboratory scale methods of study have been developed and used successfully in the critical evaluation and interpretation of the carbonization characteristics of a wide range of raw and prepared materials, the variable factors in the coking process, and' the mechanical properties of the carbonized products. The simple and highly economic technologies have been successfully and effectively integrated with detailed surface and subsurface geological exploration programmes (particularly in the coalfields of the .Central Bowen Basin of Queensland) as well as with quality and utilization studies of a nUII!ber of representative Australian and Japanese coals. Previously, only the results of comparatively large, laboratory scale studies have provided information reasonably indicative of those to be anticipated hi industrial practice, but these suffer serious disadvantages in terms of economy of material, time and resources; they have been difficult or even impossible to use as an essential part of any normal or comprehensive exploration programme. On the other hand, although previously developed smaller scale laboratory methods derive considerable advantage from their flexibility, amenity to critical control and inherent potential for speed and economy, they have hitherto permitted no effective or direct comparison with the results of industrial practice or full scale assessment. Comprehensive study results achieved through technologies developed recently at the University 'of Sydney demonstrate that carefully controlled small laboratory scale methods of evaluation quite suitable for use in exploration and, other programmes may be used to predict with considerable accuracy and reliability (in some cases exceedingthat of pilot scale study) the principal strength index of one of the established and internationally recognized full sc:ale tests-the Japanese Industrial-Standard Drum Test. It is probable that further study may establish satisfactory correlations with the results of other standard industrial procedures.

Jan 1, 1969

By M Castello, P Bouchard, M Sabsabi, A Blouin, B Nguegang Kamwa, M Constantin, K Fytas, M Laflamme, K Rifai, F Vidal

Canada’s Quebec province operates 26 metal mines, 19 of which are producing gold and generating over C$1.8 billion (US$1.3 billion) annually. In all those mines, numerous samples of rock are collected and analysed daily in laboratories in order to determine their gold content. However, laboratory results are generally available within 48 hours of sampling (depending on the number of samples received by the laboratory and the priority of the results), thus potentially slowing down mining activities. In an attempt to find a solution for delayed laboratory results, Laval University, in partnership with the National Research Council Canada (NRC), the National Institute for Scientific Research (INRS) and four mining companies (Agnico Eagle, Canadian Malartic, Hecla Québec and Iamgold) have launched the Laser-Induced Breakdown Spectroscopy (LIBS) project for in situ real-time mining sample analysis. This work aims to minimise the amount of LIBS point sampling necessary to be representative of a full scan of the analysed area. Eight sampling patterns are investigated. A statistical analysis of the data was performed by varying the pattern steps. Results show that two of the patterns, 1 and 5 (single diagonal crossing the stratification of the samples with opposite slopes) minimise the amount of point sampling while remaining representative. The most successful results are obtained from steps which are greater than 6. In terms of the type of material, pattern 5 and steps 9 are better for core sampling, while pattern 1 and steps 8 are better for rock sampling. The geological explanation for these results is the heterogeneous distribution of gold in the sample which seems to be more homogeneous in the rocks than in the core sample due to the small rock size. In terms of the mineralisation, pattern 5 is better for mixed sulfides and quartz veins, and steps 8 and 9 are better for quartz veins.CITATION:Nguegang Kamwa, B, Rifai, K, Laflamme, M, Constantin, M, Castello, M, Vidal, F, Bouchard, P, Fytas, K, Blouin, A and Sabsabi, M, 2017. Sampling strategy by statistical analyses of LIBS data in the context of a portable gold analyser, in Proceedings Tenth International Mining Geology Conference 2017, pp 221–232 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 20, 2017

By E Widzyk-Capehart, P Vallejos, R Asenjo, J Ruiz-del-Solar

Throughout the minerals industry, it is evident that a new wave of technological innovation is needed as the mining sector looks for ways to achieve higher security and safety as well as higher production rates with less investment. Innovation has always been one of the key factors in achieving success within the mining industry. However, its importance will be especially relevant in the coming years if negative trends in commodity prices and new challenges facing the industry (lower grades, deeper mines and economy of scales) are to be overcome and the future sustainability and profitability of the sector ensured.The drive towards fully autonomous operations has begun, with the implementation of automated systems in both surface and underground operations. However, these automated systems are currently planned and realised with well-defined automated tasks within structured environments and isolated spaces. Currently, there is no interaction between automated systems, manned systems or humans, which creates physically isolated environments.For fully autonomous and continuous operations, the automated systems need to operate in environments that enable flexible interactions between automated machines, tele- and manually operated machines and humans.In this paper, we address the automation paradigm considering the synergistic collaboration between humans and automated systems. In this paradigm, humans and machines would interact in a flexible, collaborative and synergistic way without the need for isolation. The implementation of this concept within mining operations will have to be underpinned by science and technological developments and will require adaptation from many fields, including robotics, automation, distributed systems, communication, human factors, pattern recognition and mine design.The paper also presents the research and development work being undertaken at the University of Chile’s Advanced Mining Technology Center, in collaboration with the Chilean mining industry. This will provide the basis for flexible interactions between humans and technology-based systems towards a future of autonomous and continuous mining systems.CITATION:Ruiz-del-Solar, J, Widzyk-Capehart, E, Vallejos, P and Asenjo, R, 2015. Synergistic collaboration of humans and automated systems – innovative steps towards fully autonomous and continuous mining systems, in Proceedings Third International Future Mining Conference, pp 83–94 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 4, 2015

By G J. Harbort, K Lam, C Sola

The relationship between the geology of porphyry copper deposits and their processing performance is an area of interest. Being able to predict comminution properties of the ore from physical characteristics and geological descriptions would allow an increase in the precision of capital cost estimates, operating cost estimates and throughput rates. This geometallurgical approach would reduce the requirements for expensive comminution tests.As the comminution circuit is the highest capital cost item in the plant and a possible throughput bottleneck, understanding the variability in hardness within the orebody is critical. A geometallurgical model allows calculation of ore hardness values in mining blocks from ore characterisation data. This model subsequently uses a combination of simulation and power-based approaches to relate ore hardness and flotation feed size to grinding circuit throughput.This paper reviews the geometallurgical models developed for seven porphyry copper deposits and discusses the strengths and shortfalls of the methodology and similarities and differences between the different deposits.CITATION:Harbort, G J, Lam, K and Sola, C, 2013. The use of geometallurgy to estimate comminution parameters within porphyry copper deposits, in Proceedings The Second AusIMM International Geometallurgy Conference (GeoMet) 2013 , pp 217-230 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 29, 2013

By J Geronimo, P Kumar, Z Yussupova, M Yahyaei, M Powell

This work goes beyond the general perception of how the well-known mine to mill process can be applied, by applying deeper knowledge along the mining chain. Grade deportment and dilution are considered at the mining stage, and modelled with the new SMI blast movement simulator, linking with the block model data. Assessing the shift to a considerably more competent section of the orebody is quantified via substantial milling trials at standard and higher-intensity blasts. These were stockpiled for batch processing through the mill to ensure feed integrity. The trial work included operating the mill at widely different fillings to develop Grindcurve milling responses. Additionally, model informed process control is initiated via a mill prediction tool.It has been found that accounting for blast movement for the higher intensity blasts could generate additional value of around $1.5M per blast. With the high-intensity blast and changing mill control, the plant was easily able to exceed projected mill throughputs with the far more competent Pipeline ore. Strategies to shift the workload and debottleneck the milling circuit were proposed and proven during the milling trials, demonstrating an increase in throughput of 7 per cent despite running at a lower SAG mill speed, and potential of 16 per cent for increasing the SAG mill to standard operating speed. A number of process improvement opportunities have been identified to enhance current productivity and ensure long term capability to process the considerably more competent future ores. All of this is being linked in with the major digitisation program at the Barrick Cortez site, with an objective of linking all the data into a mine-wide process optimisation system, that can embed the processes by providing process-wide data access and production support via the future dynamic models linking ore body knowledge to productivity along the full process chain.CITATION:Powell, M, Yahyaei, M, Geronimo, J, Yussupova, Z and Kumar, P, 2018. The designed approach to mill liner optimisation – experience at Pustynnoye mine, Kazakhstan, in Proceedings 14th AusIMM Mill Operators' Conference 2018, pp 595–612 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 29, 2018

By V Srinivasan, P Knights, C T. Farrelly

By 2025, with the widespread industry adoption of remote operation centres and advanced analytics, mining companies will find themselves making better, more informed decisions across the value chain. Process automation will drive significant business integration and reorganisation. Better collaboration between functions will make cross value chain optimisation a reality. Wherever possible decisions will be automated, based on analytical models and embedded in an enterprise decision management (EDM) architecture. This will take care of many of the minor day-to-day or the minute-to-minute decisions that consume operators and managers today. More flexible information technologies and architectures derived from the extensions to Web 2.0 and service oriented architecture (SOA) will solve many of the integration issues of today. The ongoing business imperatives for doing more with less people will make true collaboration with partners such as mining contractors, equipment vendors, transport providers, suppliers and maintenance contractors commonplace throughout the industry. All these organisations will be linked in and share common goals and objectives in real-time while providing visibility of internal constraints and available capability, allowing optimised decisions to be made across the extended enterprise. Humans will increasingly move to a more supervisory role and will use advanced collaboration to quickly solve complex abnormal issues that span the value chain out to the extended enterprise. The open collaboration and communication models instilled in the workforce through the widespread use of social networking technologies will drive thought leadership far beyond current æbest practiceÆ thinking. This will encourage the mining industry to extract the business value from rapidly converging fields of study such as environmental sciences, neuroscience, psychology, engineering, information technology and business finance. The future of mining will see a more uniform distribution of data savvy workers between the ages of 20 - 40, forcing a change in current operations. This group will drive the adoption of ubiquitous computing, augmented reality, presence and digital labelling. The enterprise will shift from a relatively static disparate set of functions to a digitally aware, integrated and interactive environment with information available, in context and just in time, to those who need it. The networked virtual enterprise will therefore be a reality.

Jan 1, 2008

By S G. Li

Mine intelligent ventilation is an important guarantee to realise intelligent mining. It is the integration of the Internet of Things, big data, artificial intelligence, internet, cloud computing with ventilation technology, forming a complete ventilation system with intelligent perception, intelligent decisionmaking, intelligent emergency response and airflow control. In order to fully grasp the progress and trends of mine intelligent ventilation research in western China. The paper based on literature analysis and field application research, comprehensively expounds the main research and practical results of mine intelligent ventilation in western China, mainly analyses the development status of key technologies such as accurate and rapid determination of mine ventilation parameters, intelligent analysis and decision-making of ventilation and intelligent regulation of ventilation equipment, and introduces the field test or application of mine intelligent ventilation technology in western China. It lays the foundation reference for related research and improving the intelligent level of mine ventilation.

Oct 12, 2022

By R Ballantyne, M Adams

Time Usage Models, used as a basis for calculating performance indicators for mobile mining equipment, have developed from very simple to very sophisticated models. This development has paralleled the increased collection and analysis of production data that itself has been enabled by the evolution of underground voice and data communications along with the relevant information systems. A Time Usage Model divides the hours that equipment is (or is not) used into standard components, by a hierarchical breakdown, so that measures of productivity can be used to compare performance of both people and equipment. The calculation of equipment availability, and thus the underlying Time Usage Model, has always been an extremely emotive topic as different groups use time usage information for different purposes. The direct link between measuring performance Key Performance Indicators (KPI) calculated from these models and employee rewards impacts upon the workforce. This paper discusses the conflict in use by various stakeholders and proposes ways to address some of the more contentious issues each supported by case studies. The simple status code functionality used by early systems has proven inadequate, leading to the evolution of “work-arounds”. These workarounds have become the norm and unfortunately have become embedded in the next generation of models and the information systems that incorporate them. This paper contends that the industry should stop building Time Usage Models to accommodate shortcomings in proprietary systems, but rather collaborate with suppliers to develop innovative methods to deal with the fundamental requirements. There are many points of differentiation that are not clear-cut. Pitfalls are discussed as well as threats to success. A framework of rules is developed as guidelines for how a Time Usage Model should be developed and applied. This will hopefully stimulate the on-going discussion as to how Equipment Availability and other components of the model should be calculated.

Mar 15, 2021

By E Kabwe, M Karakus

Deep hard rock underground mines tend to experience high stress as such drives exhibit dynamic responses attributed to a rock burst variant (strainburst). This dynamic behaviour is difficult to predict, and every effort is made to devise the appropriate dynamic support system for its associated failure restraint. This paper outlines the back analysis and the support scheme design for an underground decline that exhibited damage from a dynamic strainburst occurrence. It employs a decline section that experienced a dynamically loaded strainburst that initiated rock fragment ejections. The procedure involves a preliminary structural analysis, a seismic intensity measure, and a rock mass simulation to determine the static stress concentration and ground support system response. The numerical simulation is conducted in FLAC3D which employs the advanced strain-softening IMASS constitutive model governed by two Hoek–Brown (HB) bounding yield surfaces. To account for the post-peak brittleness response associated with strainburst the plastic strain multiplier () is adjusted to 0.0 < < 1.0. The back-analysis shows that the occurrence was initiated by a low-intensity seismic wave that superimposed an extra stress component to the initial static stress which triggered rock fragment ejections. Additionally, the appropriate support scheme comprised of Weldmesh, Fibrecrete, static (split set) and yieldable (Kinloc) reinforcements is recommended and implemented. Thereafter, the bolt’s efficiency is evaluated based on the axial force and elongation capacities and then compared with the published bolt performance data. The evaluation results show that the maximum bolt axial force (0.1 per cent) and elongation (0.006 per cent) are below the designed capacity and rupture strain.

Nov 29, 2022

By S H. Begg

There is strong evidence that many major oil and gas (O&amp;G) projects are plagued by large cost and schedule overruns, or significant underperformance in productivity. Similar evidence exists for large mining projects. This paper claims that uncertainty is the underlying reason why projects fail to deliver the metrics used to justify their investment, or to deliver the economic value possible if alternative decisions had been made.Most technical and economic analyses are performed to reduce uncertainty to help make decisions. Decision-making is about ranking alternatives and choosing the best; rarely are precise predictions required, if this is even possible. Better uncertainty assessment is one of the keys to better decisions, thus better business outcomes. To get better decisions it is suggested that the focus or reward/penalty incentives be shifted away from the quality of outcomes to the quality of decisions. High-quality decisions are those that are generated from the skilled use of the tools, methodologies and processes from the discipline of decision analysis.Uncertainty is quantified by probability, which is a degree of belief in the truth/falsity of some proposition about a quantity relevant to a decision, such as volume of in-place resource, future price or action of a competitor. The probability a person ascribes to a proposition depends upon their information set; hence probability is subjective – it is not an inherent attribute of the quantity of interest or the physical system.The above simple observations have profound implications for modelling approaches, how they deal with uncertainty, the use of data to help assess uncertainty and the reliability of information provided by subject-matter experts. The limited circumstances under which frequency data (from spatial or temporal variables) can be used to assign probabilities is also reviewed.People, in general, are subject to a range of biases and cognitive errors. Research with O&amp;G subject-matter experts shows that their expertise offers little or no protection from making errors in probability assessments and other judgements.CITATION:Begg, S H, 2016. Decisions, decisions – uncertainty, variability, modelling and psychology, in Proceedings Seventh International Conference and Exhibition on Mass Mining (MassMin 2016), pp 9–18 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2016

The reliable estimation of ore reserves in mineral sand deposits depends on drilling methods and assay techniques that have been specially developed within the industry. Improvement of these techniques is a continuing process, as variations within and between deposits are highlighted during the actual mining operation. Constant monitoring of metallurgical losses along with mineral production allows comparison of mineral tonnages accounted for by mining, with original calculated reserves. A review of ore reserves in the Jerusalem Creek field from scout drilling in the sixties, through mining in the seventies, shows the progression from understatement prior to mining, to the present when more than two thirds of the reserves have been depleted.

Jan 1, 1979

By Lumley G. I, Hayes H

Non-intrusive methods for the reliable determination of dragline bucket and rigging performance have been achieved using physical modelling. Modelling offers a logical first step towards developing mathematical simulation models. The process of physical modelling has been applied successfully to predict dragline bucket performance and capacity as well as to demonstrate the effect of varying dump rope length on performance. ACIRL&apos;s Surface Miming Group has used physical modelling to carry out dragline bucket sizing for a new high productivity bucket and compared performance with Throng Coal&apos;s existing dragline bucket. The predicted bucket performance has since been confirmed in the field using dragline monitoring techniques.

Jan 1, 1992

By Waters CA, Happ JV

The debismuthising plant, commissioned in 1980, is based on the Kroll-Betterton process for preliminary bismuth removal with subsequent antimony treatment for fine debismuthising. Bullion flowrate is continuous and the plant was designed to achieve low bismuth lead product at rates of up to 20 tonne/h.Development of the first stage of the operation has enabled reliable operations at 25 tonne/h to be achieved. Thesedevelopments also introduced the opportunity to treat higher bismuth bullion at up to 35 tonne/h when operating the first stage only to produce product lead of 0.029 per cent Bi, meeting the ASTM B29-55 Corroding Lead Standard.

Jan 1, 1985