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By H Khoshrou, A Siamaki

Blast designs can have productive and non-productive impacts on downstream stages, mine productivity and operating costs. On the other hand, ground vibration, fragmentation, and back break caused by blasting impose damage and financial penalties and which must be controlled by blast design. One of the significant variables in blast design is the burden. In this study, the potentials of artificial neural network are investigated in prediction of burden in the Sungun copper open-pit mine. Input data were assembled through 18 blasting blocks according to different levels and experimental geomechanical investigation. To construct the model blastability index, uniaxial compression strength, hole diameter, specific weight of rock, rock quality designation and cohesion strength are taken as input parameters, whereas, burden is considered as an output parameter. Mean square error was used as the performance function and back propagation algorithm as the training function, containing four hidden layers and 14 data sets. Four sets of data were used to make sure that correct training had been carried out. This produced the coefficient correlation of 0.662.

Sep 26, 2011

By I Treloar, T Elenbaas, E Isaaks

Critical reviews of grade control generally focus on blasthole sampling and the estimation of ore control block model (OCM) grades, with little or no attention given to dig-line design. For example, the estimation of block grades is deemed important as estimation errors lead to the misclassification of ore types and subsequent dollar loss. Recognition of the problem that the underestimation of block grades may be more or less costly than overestimation led to the application of loss functions to the classification of individual OCM blocks by ore type. The method is known as maximum profit selection (MPS). However, each OCM block may be misclassified a second time by dig-line design. Although each block may initially be assigned an optimum ore type by MPS, OCM blocks are seldom individually mineable by ore type. As a result, a common solution to this problem is the design of mineable polygons or dig lines loosely constrained by a minimum mining width. All material within a properly designed dig-line polygon can be mined and sent to a single destination such as the mill, stockpile or waste dump. These dig lines are often designed manually or by simple variations of computer-generated contour lines. They are generally suboptimal and result in additional misclassifications of ore types. This paper provides an algorithm for constrained optimum dig-line design where dig-line misclassifications are also evaluated through loss functions or MPS. Constrained optimum dig-line designs minimise the dollars lost by dig line misclassifications for a given minimum mining width constraint. A case study is provided illustrating constrained optimum dig-line design and subsequent benefits.CITATION:Isaaks, E, Treloar, I and Elenbaas, T, 2014. Optimum dig lines for open pit grade control, in Proceedings Ninth International Mining Geology Conference 2014 , pp 425–432 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

In considering the organization of research, it is necessary to know just what research is, what objects are in mind when setting out to conduct research, and what are the functional units which are required to enable a coordinated effort in research to proceed.The dictionary defines research in the following terms: Laborious and patient search, as for truth, diligent inquiry or examination in seeking facts or principles; inquiry, scrutiny; to search or examine with continued care; to seek diligently; to search again; to examine anew.This is, of course, simply a formal definition, but the reference to "labour", "patience" and "diligence" should be noted.The following quotation from an answer to the question "What is Research?", published recently in a technical journal, puts some life into the formal definition:- Essentially, it (Research) is nothing but a state of mind a friendly, welcoming attitude toward change. Going out to look for a change instead of waiting for it to come. Research, for practical men, is an effort to do things better... The research state of mind can apply to anything: personal affairs or any kind of business, big or little. It is the problem-solving mind as contrasted with the let-well-enough-alone mind . . . It is the "to-morrow" mind instead of the "yesterday" mind. Note the statements that: Essentially, it (Research) is nothing but a state of mind, and the research state of mind can apply to anything.

Jan 1, 1950

A very wide range of technologies are utilised in the mining and processing of ores and a great deal of effort is expended in the development of ænew technologiesÆ to improve mining performance and economics. Traditionally, technology and people have been treated as separate aspects of an operation, when in fact they are inextricably linked. The successful implementation of new technologies is entirely dependent upon the actions, enthusiasm and skills of people, both as individuals and working in groups. This paper discusses the role of technology in mining and how new technologies are implemented by the industry. The paper argues that existing technologies have not been fully or adequately utilised and that effort should be re-focussed on the implementation of technologies that have been taken for granted for many years. The need for greater emphasis to be placed on the management of the human-technology interface is discussed.

Jan 1, 1998

The region we call the West Coast is acknowledged as one of the richest and most diverse mineral provinces in the world. It's the most rugged part of Tasmania and our island is one of the most rugged parts of Australia, so that speaks for itself. A hostile land of razorback mountains, deep ravines, dangerous rivers, almost impenetrable rainforests and a climate that can change from mild to freezing in a matter of hours.

Jan 1, 1993

By J D. Pease, J M. I Tuppurainen, P D. Munro

This paper examines how legislation and regulation can be external drivers of technical change in mineral processing and extractive metallurgy and how the industry can respond. Two examples are considered; the production of copper metal from concentrates and the cyanide process for gold production.The Clean Air Act (1970) in the USA initiated a wave of attempted innovations in the extractive metallurgy of processing copper sulfide concentrates to meet forthcoming standards on sulfur dioxide emissions. Interestingly, a satisfactory technical solution existed (flash smelting and gas capture) but had not been widely adopted.Nearly fifty years later the primary copper industry finds itself with new challenges. One major challenge is how to deal with the increasing level of arsenic in copper concentrates. Most countries impose an upper limit on arsenic in imported concentrate; typically, 0.5% As or less. Higher arsenic concentrates can be blended with cleaner ones to meet the limit, but this tactic cannot be used indefinitely as the average arsenic level of global concentrates rises inexorably. Further, smelters (often in urban locations) cannot be expected to deal with both ever-increasing arsenic in the feed and stricter restrictions on emissions and disposal. A rising “inventory” of primary copper deposits are already constrained from development by high arsenic concentrate. These deposits will need to be developed if future copper demand is to be met. An economic and technical solution to arsenic is needed. The gold industry may also face challenges in the use of cyanide, by far the dominant lixiviant used in gold and silver production. Public perception has driven restrictions on the use or transport of cyanide in some jurisdictions. History suggests that such pressure is only likely to increase. While there are several alternative lixiviants, none can yet match the utility and economics of cyanide.Such important issues will not be resolved by incremental change or new equipment items. They require development of new process technology - a tectonic event rather than an incremental change. It requires sustained effort (and expenditure) over decades and is very unlikely to result from “business as usual” for producers, suppliers or academics. Past major process developments were driven by a dire need for economic survival or by legislative change. What will drive the future changes?CITATION:Munro, P D, Pease, J D and Tuppurainen, J M I, 2017. Technology change by regulation – a cresting wave?, in Proceedings MetPlant 2017, pp 45–58 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 11, 2017

Coal mining legislation makes frequent reference to æSafety Management SystemsÆ but there is a chronic shortage of useful guidance material as to how these might be applied to hazardous exposures. Several studies have indicated that for each death that is reported as a result of an industrial æaccidentÆ, there are five deaths that caused by occupational exposures. Because the deaths from occupational exposures do not occur on site and often well after employment has ceased, they are generally unreported. Improved access to mortality data from coroners, the Australian Institute of Health and Welfare and superannuation service providers (early claims from death and total permanent disability), has given rise to some analysis of death and disability data that provides evidence that there are emerging opportunities to develop and improve safety management systems for hazardous occupational exposures. Issues explored include how safety management systems might be developed in relation to dusts and chemicals and other hazardous exposures to ensure the risk of disorders with long latency periods are reliably assessed and the exposures effectively managed. The current standards and guidelines which refer to safety management systems in general or to management of exposure related hazards are examined. Many standards are based on dose-response studies that provide for an acceptable percentage of workers to suffer adverse health outcomes. An alternative management system might be to apply dose-response relations to health surveillance to identify æat riskÆ individuals and effectively manage health and related safety risk at an early stage.

Jan 1, 2005

By B Klein

This paper stems from research and development in sensor and sorting technologies towards future sustainable mining undertaken by the UBC Mine-Mill Integration group in collaboration with MineSense Ltd. Sensors and sensor-based technologies such as ore telemetry and sorting are envisioned to be a significant component in achieving such ‘invisible’ future sustainable mining. Such technologies offer high flexibility and power in use: delivering valuable information from the very preliminary stages of mining exploration through to final upgrading of the ore preceding the fine comminution stages. This paper reviews sensors and sorting as enabling technologies towards a future smart mining operation and introduces a model in which sensor-based exploration (down-the-hole sensing), ore exploitation (smart-shovels), transportation (smart-conveyors) and preconcentration (sensor-based sorters) are effectively integrated to increase the present value of operations. It is anticipated on the basis of several case studies that an effective use of sensor technologies through tomorrow’s ‘smart mine model’ should lead to several positive impacts ranging from increased mining production, to reductions in transport costs, overall energy use and waste generation. In this way sensors can be used to maximise the profitability and present value of the mining operation from the exploration stage through to mine closure.

Nov 22, 2011

Mr GEPP said: "He proposed at the outset to draw attention to figures dealing with the population of the countries adjacent to Australia for the purpose of comparison with the population of the Commonwealth. He would deal more particularly with the areas of land surrounding the Pacific and Indian Oceans. Korea and Japan had a population of 18,000,000 ; China, 437,000,000 ; Persia, 9,000,000 ; Arabia, 5,000,000; South Africa, 129,000,000; Madagascar, 3,500,000 ; India, 251,000,000; Siam, Indo-China, and so forth, 16,225,000; Federated Malay States, 3,225,000; and, very significantly, Java, only four and three quarter days from Fremantle, over 50,000,000. From the map displayed an idea of the comparative areas of the countries mentioned and Australia could be gained. It was rather amazing that Australia, with its great potentialities, had only about 5,150,000 people. New Guinea had over 750,000 people; Hawaii, a mere speck, 250,000; New Zealand, 1,300,000; North America, 130,000,000; Central America, over 15,500,000; and South America, over 65,000,000. Colombo was only six days from Fremantle, and it was only nine days from Capetown to Albany, and eight days from Albany to Hobart. Proceeding, Mr. Gepp said "It was in 1911 and 1912 that I had the good fortune to spend nearly twelve months in Europe, and during the course of my work in England and Germany to have the oppprtunity of studying both the economical and political systems in some detail... I was in Berlin at the time of the visit of Lord Haldane, when an effort was made by the British Government to arrive at some under...

Jan 1, 1923

By I Sucholutsky, D M. First, D Mogilny, F Yusufali

Machine learning is creating value in all facets of the mining industry, from exploration to production. The authors provide an accessible, high-level introduction to artificial intelligence (AI), machine learning (ML), and deep learning (DL); the latter being widely recognised as one of the most powerful forms of ML. In particular, the authors will introduce deep learning models known as convolutional neural networks (CNNs), how they are applied, and the economic considerations necessary for determining when DL may be the right solution to de-risking complex block modelling problems. The authors present preliminary results from the mineral resource modelling study of the Jundee orogenic gold deposit, Yandal belt/gold province, Western Australia. The primary goal was to identify the direction and location of the narrow gold veins more accurately and demonstrate how non-linearly correlated elements are used as direct inputs to the resource model to assist with the target element’s grade prediction. This demonstrates that: (1) existing techniques for finding correlations between assayed elements do not adequately reflect the complex geology of the asset, (2) nonlinear correlations that are difficult to model as simple mathematical functions are representative of geological patterns in a deposit, and (3) non-linearly correlated assayed data, fed as inputs, increase the performance of the resource model as reconciled through blind tests. To conclude, the authors hypothesise that the patterns represented by the DL block models may be revealing the results of overprinting geological processes that generated mineral deposits. For example, the primary hydrothermal processes that deposited metals created depositional patterns that become particularly complex as a result of being overprinted, in part or in whole, by secondary physicochemical processes. This may explain why non-linear geochemical relationships have the capacity to generate more accurate block models of mineral deposits.

May 24, 2023

By G I. Lumley

‘Every mine is a pilot’ is an attitude which encourages the mining paradox of optimistic mine plans and equipment under performance; propped up by an environment lacking accountability. The premise that ‘every mine is a pilot’, appears to underlie the development and operating approach to most mines. It is the hypothesis of this paper that many mining companies, development teams and their managers largely ignore what is done elsewhere. Anecdotally, most planners don’t know whether the selected rates are high or low (rates based on theoretical models tend to be high – certainly higher than what most companies can achieve). Mines then consistently operate the equipment at rates well below targets; often more than 20 per cent below. Further to this paradox, mine performance data demonstrates the average mine is currently operating their equipment at levels of output not much more than half the output of those in the top ten per cent. On the whole mines don’t know the potential of their equipment and therefore don’t put appropriate plans in place to do better. After all, when ‘every mine is a pilot’ there is little reason to look to one’s peers for an indication of potential. This paper will outline why every mine is not a pilot and how mines do value some knowledge, but not as much as they should. This paper proposes a two-pronged approach to address this issue in the area of equipment performance. This approach is to:1. engage in better forecasting of equipment rates and better subsequent performance through benchmarking against industry standards2. provide conditions for more accountability.These parameters are linked and proper implementation of them will address the losses which many shareholders and financiers have incurred when investing in companies with unrealistic mining plans.CITATION:Lumley, G I, 2016. Is every mine a pilot? In Proceedings International Mine Management Conference, pp 75-88 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jun 22, 2016

By M Scoble, C Hughes, M Roberts

At 14 per cent, the representation of women working in the mining industry is the lowest among primary industry categories in Canada. Despite an increase in research and industry commitment to advance and retain women in the mining industry, the gender gap in mining organisations persists.This paper is based upon a recent Canadian survey of 163 highly qualified women (HQW) working in the mining sector. For the purpose of this research, HQW were defined as women with a BachelorÆs degree or higher. This research sought to identify career progression and retention patterns of women who in theory have the educational qualifications to advance into positions of leadership in mining operations. We considered why womenÆs advancement in mining organisations has stalled; examined the career development pathways of HQW; and investigated the interactions of mining workplace culture on HQWÆs career development and retention within the Canadian mining industry. Results?indicated two distinct career pathway trends for HQW. æThe specialistÆ; a career characterised by multiple professional scientific and technical positions, and æthe corporateÆ; a career characterised by professional administrative roles and roles in mid-level management. It was found that neither æcorporatesÆ nor æspecialistsÆ systematically progressed into senior management and executive roles. These findings suggest that HQWÆs careers in mining are stalled, despite a strong indication by respondents of interest in their professional career advancement. With regards to?workplace?culture, respondents indicated that blatant forms of gender discrim-ination have been reduced in mining workplaces; however, exclusion from informal networks, implicit bias and subtler forms of workplace discrimination persist. Consistent with previous mining sector research, improving work-life balance, work flexibility and mentorship were found as key drivers for HQW to advance and remain in the industry.CITATION:Hughes, C, Scoble, M and Roberts, M, 2012. Where are the women? Highly qualified women in the mining industry, in Proceedings International Mine Management 2012, pp 23-34 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 20, 2012

By P Guj, J A. Bell

The valuation of early-stage exploration projects requires a valuer to take into account a large number of uncertain value drivers, the interplay among which may be non-linear. This paper examines some of the key value drivers including geology, target metrics, project area and maturity, the market and the psychology behind the decision-making process. The commonly accepted valuation methods and their underlying logic are outlined, including a view on why they evolved, what value drivers they attempt to address and their potential shortcomings. These methods include the multiple of exploration expenditure, geoscience rating, expected values and market based methods. The potential future valuation methods of replacement values and neural networks are also introduced along with how to minimise heuristic bias and error within the market-based approach.CITATION:Bell, J A and Guj, P, 2012. Exploration value drivers and methodologies, in Proceedings Project Evaluation 2012 , pp 17-28 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 24, 2012

As the title indicates the central themes discussed in this contribution are sustainable development, information systems, and extractive industry. More specifically, the objective is to present a prototype for the systematic generation of extractive industry (henceforth: EI) û specific sustainability information. The paper begins with the authorÆs viewpoints on the core notions of sustainability, and development, as well as their relationship to information. These set the stage for the introduction of the information system (IS), as well as the follow-up sustainability information system (SIS) extractive industry sustainability information system (EISIS) concepts and related discussions. The paper continues with a second part, in which, efforts to research and develop an EISIS prototype are described. First, the team is presented. Second, the systemÆs aim and target groups are briefly discussed. After, an articulated overarching EISIS conceptual model emphasising capital accumulation, and service flow concepts û is presented. This is followed by a detailed description of the assembled prototype with a focus on data and information generation. The formulation of data generation, storage and transmission processes, as well as its use in sustainability interpretation rules and their embedment in the conceptual model is made with respect to monetised stock and flow parameters, measured in the appropriate dimensions. In the third part, the author presents and discusses the results of a first round of prototype experimental development in three major EI firms. First, the system observation, and data analysis protocols are described. Second, a review of protocol implementation, and respective results, is made. Finally, the overall performance of the proposed prototype, and development process issues are discussed, before suggesting areas for improvement and future research. The paper ends with a conclusion in which the author provides a retrospective balance of the æknowledge creation projectÆ, as well as a prospective outlook for research in this field; before acknowledgements are made and references provided.

Jan 1, 2009

By M J. Nimmo

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

May 24, 2023

In-pit crushing and conveying (IPCC) is being increasingly considered as an alternative to traditional truck-shovel mining methods. The move towards IPCC is driven by a number of factors including the potential to reduce greenhouse gas emissions, the availability of skilled labour and the need to increase extraction rates to levels that present significant challenges to traditional methods.When considering the relative performance of IPCC and truck-shovel methods, the outcome can be inadvertently impacted by either the use of different simulation approaches, or techniques that do not adequately model the processes in sufficient detail.A simulation approach is proposed that models both IPCC and truck-shovel using the same software platform and is capable of functioning at a wide range of resolutions from life-of-mine scale through to second-by-second asset tracking level. The simulation framework also holds models of processing equipment and hence the mining simulations can be extended to gauge the impact on downstream plant.The approach, known as mine-process operational simulation (MPOS), can be tailored to the level of information available and hence the type of study required, ie order of magnitude, prefeasibility, feasibility, or detailed design.Using information from block models and a range of detailed equipment and process models, MPOS can span major system discontinuities, typified by the mine-plant interface, to allow the estimation of final mine and plant product specifications.

Dec 6, 2010

By Zajber A, Kulchen R, Letzel D, Weyer A, Schwellenbach J

The search for modem casting plant concepts today focuses more and more on the harmonisation and optimisation of overall concept lines to obtain a continuous quality control and reduce the cost of production (Figure 1). Fin I As far as continuous casting plant concepts are concerned, this specifically requires an optimal adaptation and flexible operation when converting liquid steel into a directly processable product without any in-between treatment. Continuous casters need to fully satisfy the requirements of both the upstream steelmaking facilities as well as the downstream rolling facilities.

Jan 1, 1999