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The placer gold industry has experienced a roller-coaster history incorporating four major boom eras. The first, 'hand-methods' boom arose in the mid-19th Century from application of an old idea in new places around the globe. The subsequent hydraulic mining, bucket dredging, and 'hydraulic excavator-portable plant' booms each arose from application of new ideas in old places around the globe, ie in places where gold had been found during earlier booms. The new ideas that heralded the second, third and fourth booms were all significant advances in excavation technology. These enabled the industry to target the known deposits that were too deep, too wet, too small, or too low-grade for recovery by earlier boom methods. Relatively few new deposits or new deposit styles arose from the 'history book' exploration approach, so the number of known deposits to which each of the boom methods were applicable was limited. Consequently, the first three booms were each followed by significant periods of industry decline, and the fourth boom is currently waning inNew Zealand. Further decline is not inevitable and can be avoided by changing to a knowledge-based exploration approach similar to that adopted by the hard rock gold industry in the 1970s. Such an approach could easily herald the next placer gold boom.   Most of the relatively coarse, easily won alluvial gold in proximal and medial reaches of the active placer systems is gone. However, a substantial alluvial gold resource remains in the distal reaches of active systems, and in ancient placers formed onshore and on the continental shelf during previous sedimentary cycles. The resource in these deposits probably exceeds the total New Zealand placer production to date. Successful development of these placers requires application of robust geologic models for the formation and distribution of the placers through time, and advanced exploration technology that has not been used before in New Zealand. Nevertheless, the knowledge and technology required to explore and mine these deposits is available now. Many of these deposits contain a large proportion of problematic gold types that are difficult to recover with the commonly used gravity technology without sustaining significant losses. Despite advances in recovery technology in last few years, too much emphasis is placed on the incorrect assumption that gold size is the primary control on recovery efficiency. Other gold particle parameters, especially particle shape, exert a much greater control on whether gold will be saved or lost to the tails, and must be considered in the design of recovery technology and configuration of recovery circuits.

Jan 1, 2003

By A G. L Pratt

Operational readiness is a commonly used term in mining and many other industry settings. However, translating this term into a coherent scope of work that is practical and meaningful is a challenge faced by many mining projects. This inhibits the allocation of resources to the work and its completion. The problem is with understanding how the terminology applies to establishing a mining operation. Resolving this problem requires clarity around what operational readiness means for a mining project’s transition to operations and who owns the tasks of completing operational readiness. The motivation for resolution of this problem is in appreciating the consequences arising from any lack of clarity in definition of this task, the timing of the work, and ownership for its completion. In broad terms, these consequences amount to an erosion of value at a critical time for both the new mine and the company and shareholders. This situation often arises where operational readiness is not adequately addressed in project’s study phases. As a result, neither time, resources nor money are adequately provided to complete the work required. In other cases, operational readiness is sometimes assimilated with the delivery of the project’s physical assets by the project’s construction team, rather than aligned with the establishment of the operating team to deliver the desired operational outputs. This paper argues that operational readiness starts in a project’s study phases and flows through into the start of operations. The definition of operational readiness is discussed as a task, and a model for its planning and completion is presented. This discussion includes assigning ownership for operational readiness planning and delivery to the General Manager of a new operation and the operations leadership team, who are central to the success of this work. After all, the reputations of this leadership team depend on the performance of the operation in its first few years. The author’s work over the last 20 years, leading operational readiness programs and the preparation of feasibility studies for mining projects, has provided the insights and evolution of ideas that are central to this paper. Operational readiness is fundamentally directed at ensuring a new mining operation gets away to a successful start and builds a solid foundation for the future of the mine/operation/province. It requires clarity of purpose, ownership and coordination by people in the operating team, and their preparation of the requisite process definition and establishment of the significant relationships required for operations. Without its successful completion, it is unlikely the new operation will meet and sustain its start-up targets. This paper discusses a practical approach to operational readiness for mining projects.

Mar 29, 2023

A GREAT deal of attention has lately been given to the discussion as to the education required for engineers, and especially for mining engineers. The Institute of Civil Engineers has had a committee's report on it which has come to some interesting and valuable conclusions.The Institute of Mining and Metallurgy had a few years back a very long discussion on the subject, and the subject appears to be one of perennial interest to similar societies. Two recent addresses by Prof. Kernot, as president of the Victorian Instituteof Civil Engineers, are among the most interesting and practical of the contributions to the discussion. Engineers seem to feel either that the coming generation has not the same capacity to benefit by the training that has made themselves what they are, or that such training has turned out in themselves inefficient men, and that they must consequently struggle to obtain a better one for their successors. For not only is there a desire to extend existing instruction to cover the advances of science, but there seems to be a general desire also to make a completely radical change in the methods.It is not necessary to observe that education does not mean the imparting and acquiring of information, but rather the cultivation of the faculties so that the best use can be made of them and of any information acquired. For instance, a man is not educated who has by heart his lectures and the contents of his text-books, but that man is who remembers little of the actual wording of his text-books, but is able to find anything required in them...

Jan 1, 1909

By M Pyle, R Ch, G Lane, ramhan

Data is the most valuable commodity in the information age. The use of data enables productivity, opportunity, and safety in various sectors and industries. In the late 1950s, Alan Turing coined the term artificial intelligence (AI) to describe the ability of computing machines to think and behave like humans through simplified reasoning and logic (Turing, 1950). This concept of mimicking human behaviour is the building block of machine learning algorithms used in most AI software. The ‘learning’ aspect in machine learning requires data, that is, information on the environment or the objective, to be modelled or predicted using AI. An AI-enabled system aims to predict the unknown faster and intuitively. Intuition in software algorithms can be described as probabilistic, learned through the data that the AI system is trained on; indeed, the AI software cannot predict the future, but it can provide the likelihood of an event/action occurring, thereby enabling decisions or responses to prevent it or take action. Just as various industries have adopted AI as the tool of choice to seek new opportunities (examples: medical research, self-driving cars, financial modelling), the mining industry, too, has been receptive to embracing AI for problem-solving and maximising the value of its business.

Sep 1, 2024

By S McEachern, J Lowe

An important issue currently facing the mining industry in Australia is the management and cost to the industry and other stakeholders of entry into and exit from towns and their communities. These costs can be environmental, social, economic, political or reputational. The ability of companies to engage the trust of stakeholders, including: communities, governments and investors, is critical, and corporate reputation plays a significant role in this. For the industry to secure a long-term and sustainable future, it must have the technical, business and reputation assets to proceed in a cost-effective, environmentally acceptable and socially supportive way. This research assesses reputation as a critical competitive issue for mining companies, as technology and information make mining more predictable; the physical and human assets of mining companies are less likely to be the critical resource in a Resource Based View model of competitive advantage. The proposition is that in mining today, reputation as it facilitates day-to-day operations, regulatory zeal and access to new mine sites will become the rare, inimitable and valuable resource for mining companies. This paper reports on an ongoing research program to evaluate the impact a mining companyÆs reputation(s), with its various stakeholder groups, has on a companyÆs ability to sustain competitive advantage. Integral to this study is to develop an understanding of the relationships between mining companies and their stakeholders, and the importance of corporate citizenship polices to reputation and hence to corporate sustainability. Through the identification of the drivers of reputation for the various stakeholder groups, a model of reputation formation will be developed and also reputation measures for the mining industry in Australia. The preliminary findings of this research, the results of an industry focus group conducted with representatives from regional mining operations, are reported. The industry focus group was designed to enable a better understanding of who are the main stakeholder groups and how they regard mining companies and to inform the second stage of the research project a Delphi Study of the drivers of reputation by stakeholder groups. The aim of this research is to further the understanding of the relationship between corporate citizenship, reputation and performance in the mining industry, thus assisting companies to strategically manage their corporate citizenship investments.

Jan 1, 2006

By Hellsten KJ, Butt CRM

Major Francis Hamilton Buchanan coined the term `laterite' (Latin; brick-rock) in 1807 for the red earths used for building blocks in southern India. Although these earths were actually weathered basalts, the term is now applied to weathering profiles developed upon a wide range of bedrocks. The Ni-laterites are a special class within the broad laterite family.

Jan 1, 1996

By Walker G. S

A study of the crystalline materials on or near the surface of freshly made or "green" superphosphate granules and mature, "set" superphosphate granules was undertaken using X-ray diffraction, X-ray mapping, scanning electron microscopy and electron probe micro analysis techniques. Calcium sulphate (CaSO4), calcium sulphate hemihydrate (CaSO4 1/2H20), and mono calcium phosphate monohydrate (Ca(H2PO4)2H2O), were the only crystalline species present in the "green" superphosphate.In the set superphosphate however, additional compounds were present, namely complex iron and aluminium phosphates Ca(Fe,AI) H(HPO4hF2)2H2O, (Fe)3(H3O)H8 (PO4)6H2O and calcium sulphate dihydrate (CaSO4.2H2O).The complex phosphates tied up the major part of the Fe and Al in the system and were concentrated on or near the surface of the granule. An intimate mixture of CaSO4.2H2O, and CaSO4, along with the above mentioned complex Fe-AI compounds, crystallize close to the surface of the granule and cause the setting of superphosphate that takes place during storage.

Jan 1, 1980

By Lever R. R

The paper discusses assay methods generally used when prospecting for gold, and also the applicability of various chemical methods, it describes a new paper chromatographic technique.for making fairly rapid semi-quantitative assays for very fine gold. Testing of the method in field work shows that this simple method could have applications in geologic work, in prospecting and in certain routine mine sampling work. It is not yet a method that can be used to detect anomalies in traces of gold dispersed around an orebody, as is general practice in geochemical prospecting.INTRODUCTIONAccording to the English economist Harrod (1958), "the acute shortage of gold in the world-because currency value has not been adjusted in line with the fall in the goods value of the various currencies-has been a familiar fact for some time now". Harrod calculates that a rise in the price of gold to double its present value is necessary to rectify this condition, and that, if this rise were to take place, increase in production and reduction in private hoarding might well bring annual accretion to world stocks from the presentaverage of about $464 million to a figure close to the $2,000 million that would probably eiiminate these shortages.Any increase in the price of gold is bound to lead to a great increase in prospecting at working mines, in abandoned areas and possibly in untouched country. Prospecting, techniques for base metal orebodies have improved greatly in the last thirty years; but methods available to detect gold occurring without accessory metals have not received the same attention. With this in mind a paper chromatographic method of assaying for gold has been developed by Lever (1958). In the field this semi-quantitative method has proved...

Jan 1, 1959

By Y Lanwin

The Australian mining sector is undergoing a significant transformation with the adoption of advanced technology to the operational landscape. This has highlighted a critical disconnect between our traditional educational systems and the skill requirements of working with these advanced technologies. This paper aims to provide a behavioural science analysis of how the traditional manufacturing mindset, deeply rooted in our educational frameworks from primary to tertiary education, registered training organisations (RTOs), and in-house learning and development, is misaligned with the needs of today’s technologically advanced mining operations. Originating in the industrial revolution, the manufacturing mindset prioritised efficiency, mass production, and the division of labour. In educational institutions, this translated into an emphasis on rote learning, linear examinations, and a rigid adherence to processes and procedures. Such a system, while effective in producing a workforce suited for repetitive and predictable tasks, falls short in fostering skills like problem-solving, adaptability, flexibility, and coping with change – skills that are increasingly vital in a mining sector dominated by automation, robotics, and AI. The paper discusses how the focus on disciplined adherence to standard work procedures and processes in educational and training programs has inadvertently stifled creativity and autonomy in learners. This issue is compounded in the workplace, where employees, having been conditioned to operate within strict guidelines, now face the challenge of adapting to environments where autonomous decision-making and creative problem solving are crucial. In essence, the traditional approach to education and training has prepared individuals for a world of work that no longer exists. This paper advocates for a whole of pipeline approach, grounded in behavioural science, to revamp mining education and training. It highlights the importance of understanding and influencing the behavioural aspects of learning and recommends for an approach that promotes diversity, critical thinking, and adaptability, preparing the workforce to excel in the rapidly changing landscape of the Australian mining sector.

Sep 1, 2024

The profitability of individual ore blocks can be classed as clearly profitable, clearly not profitable, and those in between which are by nature quite sensitive to their major cost and revenue drivers. It is often the case that the most effort goes into the least profitable ore blocks to ensure that these will in fact not generate a loss. In these cases a cut-off grade policy is often not sufficiently live to separate individual sources given the volatility of financial markets and individual circumstances of some sources particularly in remnant operations such as Mount Isa MinesÆ Lead Mine. Standard sensitivity analysis can determine which factors stope profitability is most sensitive to. However, this does not usually indicate the likelihood of any input change, nor the combined effect of multiple inputs changing. The author attempted to modify the Lead Stream financial model that determines cash margin by inserting probability distribution functions and then using Monte Carlo simulations to determine the probability of any particular ore block making a profit. This effectively demonstrates the combined effect of varying a number of inputs simultaneously to provide a probability of making a profit. The limitations of this analysis lie in the accuracy that individual probability distributions can be specified. Attempts to generate valid functions from first principles have proved difficult for a number of reasons and these are discussed along with some practical alternatives.

Jan 1, 2002

Major Francis Hamilton Buchanan coined the term `laterite' (Latin; brick-rock) in 1807 for the red earths used for building blocks in southern India. Although these earths were actually weathered basalts, the term is now applied to weathering profiles developed upon a wide range of bedrocks. The Ni-laterites are a special class within the broad laterite family.

Jan 1, 1996

By E J. Cowan

Efficiency demands that mine geologists devote the most time to tasks where they can have the biggest effect on production. One of the most time-consuming tasks is geological interpretation of the orebody and turning this into a block model for the planning engineers.The current best practice for mines that require a geologically constrained resource model involves capturing the interpretation of geologists as three-dimensional (3D) wireframes. However, there is significant overhead in the production of valid wireframes from sectional and plan interpretations. This overhead consists of the mundane tasks of digitising polylines, then building 3D wireframes and validating them. While software can simplify this task, the current process is not the best use of a geologist’s time. Under time pressure exerted by planning engineers and the time required for modelling from polylines, geologists are forced to roll-up the presence of other elements or impurities into the interpretation and encode them in the polylines, even though it is often desirable to consider these other factors separately.While it might seem unlikely that mine geologists can produce constrained geological models without the intermediary of wireframes, the technology to accomplish this is getting closer.In this paper, the results of a trial at the Savage River magnetite mine, which is owned and operated by Grange Resources Ltd, are reported. The trial was for a ‘direct-to-block’ implicit geological modelling method. The focus was on creating a geological attributed block model from drill hole geological log data; resource estimates were not determined. The categories modelled were air, waste, low-grade ore, medium-grade ore, and high-grade ore. The block model outputs either resulted in a proportional block model (categories expressed as percentages within equivolumetric blocks) or a sub-blocked model (parent block and one sub-block), which is the preferred block model output at the Savage River mine. When compared to the traditional best practice modelling method, which takes 43 work days, the wireframe-free modelling method took only 26 hours from initial modelling, using both exploration and grade control data. An update using appended drill hole data is achievable within one day. These results represent time savings of more than one order of magnitude compared to the traditional workflow, and, as such, these figures merit serious consideration for the use of the direct-to-block modelling approach at other operations.With these time savings, geological and estimation models can be kept updated constantly; geologists will not need to set aside two months for quarterly or half-yearly modelling of the drill hole data for resource review. Such dramatic time savings will allow for the better use of highly skilled geologists, who are in short supply in the current market, and will also impact directly on downstream mining engineering workflows.

Aug 22, 2011

By Y G. Anoman

This paper discusses the operating model within Endeavour Mining Corporation regarding the options of owner mining against contract mining. It’s based on the concept of ‘are we carrying out the most efficient mining’ regarding cost and performance. This question can only be answered through an extensive contract mining tender process and conducting a comprehensive comparison to evaluate the transition viability. Karma mine, located in Burkina Faso, is the subject of this paper. The Tender model included sales of equipment, parts and tooling associated with the traditional Load and Haul Schedule of Rates (SOR). The methodology focused on the structure of the tender process, which consists in the development of a SOR based on haulage profiles and mining schedule. This is a new Endeavour framework that allowed the bidders to compete on an even level. This was performed using a systemic analysis which encompassed all the elements involved in a transition such as the Human Resources (HR), taxes and customs implications, directs and non-direct costs (Finance and interest on assets, depreciation, insurance), contractor risk profiling. It was assessed against the normalised internal pricing tender-based. This paper gives an insight into how a West African mining operation addressed the sensitivities of the HR functions against the commercial aspects. This was one of the most successful transitions in West Africa and was carried out during the COVID crisis. The outcome of this project has created value by detailing a lesson learned model for both commercial and HR aspects. This discusses the commercial comparisons along with the internal model with the underlying HR functions as a risk factor that could have jeopardised the continuation of the operation. This resulted in a smooth transition with the additional cash flow generated by the sale of the parts and equipment turned Karma into a viable operation.

Jun 22, 2022

By J Lööw, M Nygren, E Segerstedt, L Abrahamsson

The purpose of the paper is to discuss socially sustainable development in the mining industry and the communities surrounding the mines. The discussions are based on results from a prestudy and literature review on mining and sustainable development conducted during 2013–2014 at Luleå University of Technology in Sweden. ‘A social licence to mine’ is important for the mining industry, but the social dimension is a relatively underdeveloped dimension when it comes to sustainable development in general and the mining industry in particular, one reason probably being the lack of effective methods for capturing social impacts. The mining industry and the surrounding communities face many challenges that provide both possibilities and obstacles to socially sustainable development; eg aspects such as gender, work conditions and cultural aspects. For example, a strong mining workplace culture and community identity can create strong cohesion but also lead to excluding certain groups, rejecting new ideas and reinforcing obsolete values. Other challenges include recruitment, as well as health and safety in relation to an increased use of fly-in-fly-out, contractors and automation of mining. Some challenges relate to the effects of fluctuations in the mining market. There is a lack of research that links attitudes, policies and activities within companies to their impact on the wider community, and vice versa. Future research should also include the development of methods and indicators for social sustainability relevant for mining – in other words: how do mining companies get ‘a social licence to mine’?CITATION:Abrahamsson, L, Lööw, J, Nygren, M and Segerstedt, E, 2015. How to get a social licence to mine, in Proceedings Third International Future Mining Conference, pp 125–136 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 4, 2015

By D M. Frantois-Bongarton

Variograms can be powerful tools for the analysis and control of process streams and their sampling. Their uses and proper utilisation have been described somewhat unclearly to date, and their limitations and precautions of use are too rarely mentioned. The general meaning and properties of the variogram tool and its use in geostatistics are therefore reviewed in details to derive a critical view of its proper use for process control: what to expect from it and what it cannot deliver and which uses are illusory or potentially misleading. A summary of GyÆs seminal work accompanies this essay to put the concepts into historical perspective.CITATION:Frantois-Bongarton, D M, 2012. Review of variogram properties and remarks on its use in process control, in Proceedings Sampling 2012 , pp 175-180 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 21, 2012

By J Deraisme, P Epinoux, O Bertoli

"Société le Nickel exploits the Dôme lateritic nickel orebody at its Tiébaghi operations in New Caledonia. The site geology has an obvious bearing on recovery and metallurgical performance, with controls that are extremely complex at all scales, including lithology, oxydo-reduction conditions, mineralogy and multivariate geochemistry. In this context, establishing an adapted recoverable resource estimation method that is efficient and transparent proves an interesting challenge. The method must address the key notions of: support effect – the exploration data set can only warrant the estimation of large panels of 20 × 20 × 3 m3 that are much larger than the selective mining units (SMUs) of 5 × 5 × 3 m3 information effect – the selection at the production stage uses estimates based on information that is much denser than that available for mine planning.The problem is rendered more complex in this type of deposit by the fact that the additive variables used for the estimation (metal accumulation and ore tonnage) are not the ones used to establish the selection at the mining stage (ie the nickel grade of SMUs, which is the ratio of accumulation on tonnage). Eventually, the selection criteria not only involve Ni grades, but also other elements such as Al2O3, Fe2O3, MgO and SiO2.The solution presented in this paper is to construct an SMU multivariate simulation in the saprolitic horizon and construct an efficient post-processing aimed at producing multivariate recoverable resource estimates. The efficiency constraints imposed by the number of blocks to be simulated (1.5 million) lead to resorting to direct block simulations. The underlying multivariate discrete Gaussian model, which had its validity tested beforehand, is put to good use to mimic the selection process that happens at the mining stage by offering the ability to simulate a composite value located at random within each block.The paper also presents the application of a scenario reduction algorithm to pick a representative subset of a few simulations to help appraise the risk attached to the downstream (reserve optimisation and mine sequencing) phases of the project. The original version of the paper (see Deraisme, Bertoli and Epinoux, 2014) used an early version of the scenario reduction plug-in (named S2RM) built in Isatis® software, where measuring the distance between the initial set of scenarios and the reduced set was based on Ni only. The implementation presented here is for the second generation of S2RM, where measuring the distance between the initial and the reduced set of realisations is based on all study variables. The benefits of the measure adapted to the true multivariate nature of the problem are highlighted in this updated version of the paper.CITATION:Bertoli, O, Deraisme, J and Epinoux, P, 2014. Multivariate block simulations of a lateritic-type nickel deposit and post-processing of a representative subset, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 99–108 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Nov 24, 2014

By S Das

Deposit-10/11A is situated in the iron rich Bailadila region of India comprising haematite ore of average grade 65 per cent Fe. The deposit production line was commissioned in the year 2002 having a capacity of 5 Mt/a. The plant has the state of the art mineral processing equipments.The ore is transported from mines to crushing plant by means of dumpers. The ore is comminuted in two stages to get 150 mm top size product and this product is transported through conveyor system and is stored in silos as feed stock for beneficiation plant. In the beneficiation plant this crushed product is wet screened in two stages to produce a product of lump (-150 + 10 mm) and fines (-10 + 3.15 mm). The product of -3.15 mm top size is fed to primary classifier for a size separation at 150 µm. The resultant product (-3.15 mm + 150 µm) is dewatered and transported to fi ne ore product stock yard through conveyor system. The minus 150 µm material from classifier overflow is fed to cyclones (508 mm cyclone battery with an apex of 65 mm) for desliming at 45 µm and to recover ultrafi nes (-150 + 45 µm). The cyclone overfl ow slimes (-45 µm) along with water is treated in lamella thickeners to recover process water. The thickener underflow material is transported to tailing pond (discharge rate is 300 m3/h at a specific gravity of 1.4) by pumping through HDPE (high density poly ethylene) pipeline and the over flow water is being recirculated. The water requirement for beneficiation is approx 1.5 m3 per ton of ore.This paper aims at identifying and quantifying the factors that affect the overall plant performance (grade and recovery) during the different seasonal variations especially in the rainy season (mid-June to end October). The effect of seasonal variations on unit operations such as milling, classification, thickening and filtration are discussed. Specific cases are presented as examples and recommendations are formulated.

Jul 11, 2011

By L Edwards, M Haest, D Mittrup

The focus in the iron ore industry has shifted from increasing production volumes with less regard for cost, to efficient production of quality tonnes. BHP Billiton iron ore geoscience and exploration has embedded infrared spectroscopic sensing of drill hole samples to help meet this challenge.Infrared spectroscopy is delivering mineral predictions that are used for (automated) geology logging and modelling. The spectra are processed together with other available data sets to predict geometallurgical and geotechnical variables that include lump per cent and uniaxial compressive strength.Trials are ongoing to test the benefit of infrared spectroscopy during mining, including the analysis of grade control samples and remote sensing of mine faces. Results show great benefits in the fields of short-term geology modelling, better understanding of material (handling) properties, identification of geotechnical risk areas and high resolution ore-waste delineation.These trials are bringing BHP Billiton iron ore closer to its ultimate goal of having infrared spectroscopic data collected across the mining value chain. Once such data are available everywhere, regression models can be trained at one point (eg iron grade model trained on exploration samples) and be applied elsewhere (eg iron grade predicted on mine faces). Such predictive analytics will enable not only high precision mining, but also provide maximum time to tailor plant design to the ore in the ground, based on learnings from ores processed in other plants. This will improve planning outputs that will eventually increase mining efficiency, processing capability and product quality.CITATION:Haest, M, Mittrup, D and Edwards, L, 2017. Infrared spectroscopy in BHP Billiton iron ore with a focus on in-mine infrared sensing, in Proceedings Iron Ore 2017, pp 549–556 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 24, 2017

In this paper a quantitative deterministic risk modelling approach (Quadrim) is introduced. The mathematical framework and equations for quantifying uncertainty within and aggregating across value chain nodes from error propagation techniques is proposed and discussed. A case study and worked examples, based on a hypothetical mine are then presented. This illustrates how uncertainty from the mining and economic value chains can be handled in a typical net cash flow calculation, and how this can be translated to a risk model. It is then illustrated that current valuation techniques do not just result in an information gap for decision makers. Traditional approaches such as discounted cash flow (DCF) analysis and truck and shovel productivity analysis, which do not take into account uncertainty in input values, can result in potential bias in estimates such as net present value (NPV) or equipment hours

Sep 26, 2011

By A Deakin

It has been almost a decade since the release of the International Council of Mining and Metals (ICMM) Health and Safety Critical Control Management: Good Practice Guide (2015a). During this time the ICMM member companies, along with many others across industry, have been busy designing, deploying and enhancing their own critical control management (CCM) programs. So, what have we learnt? This paper discusses the scope, application and learnings from the implementation of CCM within the mining industry. What’s going well? What are the common challenges? What are the opportunities to strengthen the approach? What are the threats to successful implementation? The paper draws on the author’s experience as one of the key contributors to the development of the CCM Good Practice Guide and an adviser to many mining companies, including six of the ICMM members. The paper focuses on the practical (operational) application of CCM and the cycle of identifying, defining, implementing, verifying and improving critical controls at the frontline. The paper also includes a discussion on the safety performance of the ICMM member companies over the past decade and provides a recommendation for how CCM can be incorporated into a more proactive model to measure safety performance. The paper concludes with practical recommendations that mining companies, regardless of their CCM maturity, can consider as they look ahead. They are supplemented by three additional recommendations for consideration at the industry level.

Apr 16, 2024