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By R. H. Lambeth

Disposal of mine tailings in "waters of the United States" is presently prohibited even though case studies indicate that the practice may be environmentally viable. To simulate disposal in the natural environment, nine containers of tailings and sediment were instrumented and placed on the ocean floor near Juneau, AK as were ninety-six biosample containers. Pore water concentrations of five metals were determined, and biota populations were characterized for both materials. After 500 days of exposure there were no statistical macro scale differences between tailings and sediment biota populations or Cu, Pb, and Zn pore water concentrations. Tailings released slightly more Fe than sediment, but sediment released significantly more Mn than tailings. Disposal of mine tailings in marine waters may be environmentally safe.

Jan 1, 1998

By D. G. Hulbert, D. J. Oosthuizen, D. de V. van der Spuy

Expert Online, as a software system, is aimed at providing plant operators in the minerals industry with effective training and on-the-job assistance. It incorporates a number of features to achieve this goal, of which the most important is its ability to explain the dynamics of the plant and control system in simple language, mimicking an informed plant expert who has online access to the inner workings of the plant and control system. This is made possible by a novel form of Artificial Intelligence, called the Interpreting Expert System. Previous implementations of the IES were only capable of explaining controller actions. Expert Online will extend this capability to also perform the more difficult task of explaining process behaviour. Expert Online will implement three main processes, namely the accumulation of data from the controllers and plant models, the interpretation, processing and filtering of that data and lastly communicating the relevant information to the user, both as written messages and in other audio-visual forms. Although Expert Online is aimed at the operator, other plant personnel, like supervisors and plant managers, will also benefit from it. This paper focuses on the structural and functional design of Expert Online for implementation on the latest version of Mintek’s open control platform, PlantStar, highlighting advances and additions since the previous implementations of the Interpreting Expert System and concluding with an example illustrating some of the principles.

Jan 1, 2003

By David G. Hulbert, Daniël J. Oosthuizen, Bernard Muller, Daniël de V. van der Spuy

"OVERVIEWExpert Online is a software system that aims to mimic an informed expert on a minerals processing plant. The primary objective of Expert Online is to provide operators with effective training and on-the-job assistance. Training will mostly be done off-line (e.g. using simulators of the plant), while on-the-job assistance will help the operator during normal operation to run the plant in an effective manner. Although Expert Online focuses on the operator, it is expected to also be of value to other plant personnel, including supervisors and plant managers.Expert Online will make use of novel artificial intelligence technology (developed by MINTEK) known as the Interpreting Expert System (IES). Previously the IES was only able to explain the actions taken by the controller. Expert Online will extend this functionality to also take the process dynamics into account.Expert Online is being developed by a South African consortium comprising MINTEK (focusing on the research and development of the system as a whole), Lonmin (globally one of the biggest platinum producers, with plants suitable to test Expert Online on) and the University of Natal (academic partner, providing consultation and focusing on complex process modelling). The initial application of Expert Online will be on milling- and flotation plants.This paper discusses the structural design of Expert Online for implementation on the latest version of MINTEK’s open control platform, PlantStar, as well as several advances and additions since the previous implementations of the Interpreting Expert System."

Jan 1, 2003

By David G. Hulbert, Daniël J. Oosthuizen, Bernard Muller, Daniël de V. van der Spuy

"Expert Online is a software system that makes use of novel artificial intelligence technology, known as the Interpreting Expert System (IES), to mimic an informed expert on a minerals processing plant. Previous implementations of the IES were only capable of explaining the controller actions. Expert Online will also take on the more difficult task of explaining the complex process behaviour to the operator in simple language.The primary functions of Expert Online are to serve as a training tool and an online assistant to operators. However, it is also expected to be of value to supervisors and plant managers.A number of additional features are envisaged, including different operating modes, fault detection, speech synthesis and advanced message filtering. Expert Online will increase the operator’s knowledge of the process and his/her understanding and acceptance of the complex control systems. Users would be supplied with relevant and timeous information required to make informed decisions to ensure smooth plant operation.This paper discusses the structural design of Expert Online for implementation on the latest version of MINTEK’s open control platform, PlantStar, as well as several advances and additions since the previous implementations of the Interpreting Expert System."

Jan 1, 2003

By N. B. Prenn, R. H. Robinson

"The model described is a design and economic planning tool for analyzing surface mineral deposits. Mineralization, topography, costs and significant geologic features are input to the model. The results are:(i) final pit limits yielding the maximum total profit,(ii) annual cut-off grades and plant sizing yielding the maximum present value, and(iii) annual maps of the pit and annual production statistics for the mine, concentrator and smelter.Additionally, summaries are printed of the block mining sequence and cash flow. A special feature is an option to include dump-leaching operations. Stockpiling of material can also be simulated by the model. The model is built around theories of dynamic cut-off grades and a pit design algorithm. The dynamic cut-off grades maximize present value by examination of all economic and physical constraints for the optimum combination. The pit design algorithm is a set of rules formulated to find the maximum value from a special graph. The graph is different from graphs of analytical geometry, being made up of points and arrows connecting some of the points. These graph elements describe the relationship between any point in the deposit and the material which must be mined to get at that point. The model was designed to bring together the interdependent theories of economics, pit design and production scheduling."

Jan 1, 2014

By M. Weir, J. R. Cutland, L A. J. Pronk van Hoogeveen

"A computer system for the design of open pits to mine stratiform orebodies has been developed for use at Nchanga Consolidated Copper Mines, Ltd. The particular requirements of such a system, for example, the accuracy of representation of geological detail and the ability to follow footwalls, arc described in this paper, together with the methods that have been adopted to satisfy them.A modified version of the Open Pit Design Program of Rio Tinto Zinc Consultants, Ltd. is incorporated in the system and the geological data are converted into a form usable by the computer by means of a pencil follower. Some of the uses which have been made of the system are described, with reference to the long- and medium-term planning of the Nchanga Open Pit, the major producing pit at Chingola Division."

Jan 1, 2014

By S Q. Liu, E Kozan

This paper proposes a new multiresource multistage scheduling problem for optimising the open pit drilling, blasting and excavating operations under equipment capacity constraints. The flow process is analysed based on the real-life data from an Australian iron ore mine site. The objective of the model is to maximise the throughput and minimise the total idle times of equipment at each stage. The following comprehensive mining attributes and constraints have been considered: types of equipment; operating capacities of equipment; ready times of equipment; speeds of equipment; block-sequence-dependent movement times of equipment; equipment-assignment-dependent operation times of blocks; distances between each pair of blocks; due windows of blocks; material properties of blocks; swell factors of blocks; and slope requirements of blocks. It is formulated by mixed integer programming and solved by ILOG-CPLEX optimiser. The proposed model is validated with extensive computational experiments to improve mine production efficiency at the operational level. The model also provides an intelligent decision support tool to account for the availability and usage of equipment units for drilling, blasting and excavating stages.CITATION:Kozan, E and Liu, S Q, 2014. An Open pit multistage mine production scheduling model for drilling, blasting and excavating operations, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014 , pp 329–334 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 24, 2014

By Lorrie Fava

Two needs in the mining industry, to enable overall process improvements, are open systems and network connectivity in underground mines. The Pando project, a collaboration between Symboticware, Vale and Xstrata Nickel, and supported by CEMI, addresses these issues, and leverages the solution platform to deliver intelligent applications. An open system is one that uses publicly available standards for its key interfaces. Vendor-neutrality and ease of information flow are two main benefits that result from the use of open systems. By facilitating the interoperability of systems, open systems allow information to be available when and where it is needed for decision support. Network connectivity in underground mines is typically limited, with hotspots in strategically chosen areas that are relatively static. Mobile equipment moving through a mining work cycle experiences intermittent connectivity; in this situation, seamless remote equipment monitoring is impossible. The Pando project establishes an open technology platform, adhering to the IREDES and OPC UA standards. It enables the collection and integration of information generated by mobile equipment? seamlessly while there is a network connection, and as a store-and-forward gateway to manage intermittent connectivity. The platform capabilities are leveraged to support embedded intelligent applications. This open platform, the SymBot, is a rugged hardware and software device. The platform complies with open standards for industrial automation and systems interoperability. The SymBot platform is capable of providing advanced real-time decision support at the device level, and is designed to be remotely configurable. Applications being developed through the Pando project include engine monitoring, a dynamic load weighing system, machine location monitoring and automated activity monitoring including production and maintenance reporting.

Oct 1, 2010

By M. Frenzel, K. Bachmann, M. Rudolph, R. Tolosana-Delgado, E. Schach, M. Buchmann, L. Pereiraa, K. G. van den Boogaart, N. Kupka

Geometallurgy - the science of predicting the behaviour of ores along the value chain based on their geological and mineralogical characteristics - has barely moved beyond process minerology studies. These studies typically link process behaviour to the mineralogical and microstructural characteristics of pristine or processed ores in a qualitative or semi-quantitative manner. Eventually, a trial-and-error optimisation of the operation is achieved. However, to deliver on its promise, geometallurgy should progress beyond this current approach to a fully quantitative understanding of process behaviour, including the various uncertainties involved, namely predictive geometallurgy. One of the barriers currently hindering this development is the neglect of most ore characterisation data obtained in geometallurgical studies. This is mostly due to the large extent of this information exceeding the capacity of conventional software. To address this challenge, we developed a data mining platform consisting of an SQL database, an R front-end in-house package, and back-ends to interpret data from several analytical instruments. This platform enables the use of the statistical and data mining power of the R open-source environment for any geometallurgical study. Potential applications range from ore characterisation to process understanding and forecasting, and from geostatistical prediction to operational control and optimisation. The scripting abilities of R allow for the: 1) processing of many streams in loops, thus freeing the user from repeating tedious click-and-drop tasks; 2) computation of virtually any derivate or aggregate quantity from the data; 3) distribution of the work among several processor clusters; and 4) keeping of a log file for the calculations done. This contribution presents the building blocks of this platform, and illustrates with several examples its potential to enable predictive geometallurgy. Keywords: Data mining, entropy, kernel methods, LASSO regression, predictive geometallurgy

Jan 1, 2020

By M. E. Gershon

An approach for scheduling the mining of ore and waste blocks in a surface mine is presented. While mathematical programming approaches have been developed to solve this problem optimally, they are difficult to implement and understand. The more simplistic approach presented here achieves practical mining schedules, taking into account both long- and short-term considerations. The key to the approach is use of the concept of ranked positional grade. The program can determine a complete schedule for a specified time period, or it can be used interactively as a guiding tool for the engineer.

Jan 1, 1988

By Hubert E. Sherer

The mining industry is presently one of the most heavily capitalized industries in the U.S. (U.S. - Statistical Abstracts, 1979). U.S. sales of new mining equipment (not including environmental, preparation, or long distance transportation equipment) are projected to reach approximately $5 billion/year in 1980 (Frost and Sullivan, 1979). Of these new equipment sales approximately 30 to 40 percent of this equipment will be used to replace old equipment. Therefore, an increase of efficiency in the use of equipment replacement capital could have substantially positive effects for the U.S. mining industry. This is very critical in these times of restricted capital availability, double digit inflation, burdensome governmental regulation, and rising foreign competition in the mining industry. This paper examines the numerous factors that constitute the typical mine equipment replacement problem. A computerized, mathematical model is formulated to utilize historic cost and production information to predict equipment cost versus age for the existing and potential replacement machines. Another part of this computerized model determines the best equipment replacement strategy that accomplishes estimated production goals at a minimum discounted cost. This computerized model is an easily used, consistent method of determining the optimum replacement age for any equipment unit or fleet of equipment at a mining operation.

Jan 1, 1982

By L. J. Surges, C. Bazin, D. Hodouin

"A kinetic model was developed for the conditioning and flotation processes of an industrial lead concentrate dezincing circuit. The models were incorporated into a flowsheet simulator. Simulation results demonstrate the advantages of split conditioning of coarse and fine particles and the potential of this approach for the production of the heuristics required for the development of intelligent control strategies.The conditioning model relates the proportions of activated and hydrophobic surfaces and residual reagent concentrations to activator and collector reagent flowrates. The model accounts for the solids and water flowrates, and for the solids grade and size distribution. The flotation model uses the predicted proportion of hydrophobic mineral surface, the aeration rate and the froth depth to estimate cell, bank and circuit performances. IntroductionFlotation has been the object of modelling and simulation studies for more than two decades. The process is usually modelled as a kinetic one in which the particle flotation rate constants are key parameters. Rate constants are related to the operating variables (pH, reagent flowrates, aeration rate, etc), however these relationships are seldom established in the literature.In spite of the large amount of literature on flotation modelling and simulation, few papers deal with the interaction between flotation rate constants and operating variables. This important gap, which was identified in the early seventies by Woodburn (l970), still exists. One of the first attempts to include operating conditions in a flotation simulator was made by King (l973), who explicitly introduced the aeration rate into an air bubble loading model. Lynch et al. (1981) used an empirical model to relate the proportion of slow floating particles to the ratio of collector per ton of ore. Such empirical relationships are difficult to calibrate and cumbersome to use when an activator and a collector are added to slurries in which particle size distribution and surface characteristics are changing. Eascur and Herbst (l982) relate in a fundamental way the mineral flotation rate constants to the aeration rate, froth depth, agitation and frother concentration, however the model does not account for reagent flowrates. Niemi et al. (1982) have proposed a model for the conditioning of minerals and included it into a conventional flotation simulator."

Jan 1, 1988

By Arthur W. Ruff

One of the major challenges to management in the mining industry today is the establishment and maintenance of positive and dynamic programs for cost control and cost reduction. To meet the challenge, management must have a good cost system. There are various types of cost accounting systems in use today: some companies check their, performance by comparing the costs incurred during one period with the costs incurred during previous periods, while others compare the current costs with estimated costs which the company considers desirable. A third type of system is a standard cost system which provides predetermined allowances for the various cost elements and operating activities. Such a system, based on sound standards, can be established to fix responsibility for cost performance in each segment of the operation; recognize the impact of volume or rate of activity by establishing a standard volume and evaluating departures: take into consideration fixed and variable costs and their dissimilar behaviour at varying levels of operations: and provide consistent and equitable yardsticks for measuring performance.

Jan 11, 1962

The recent boom in the mining industry has lead to some unique challenges in successfully operating processing plants. With high turn-over rates of both operators and technical staff, and many experienced personnel leaving regional sites for city based jobs there is often an onsite knowledge vacuum and this in turn puts pressure on both site training departments and senior metallurgists to provide the relevant skills to the continuous stream of new staff. Frequently both operators and new metallurgists are instructed on a æhow-toÆ basis rather than giving them the understanding as to why tasks are performed and decisions are made. This paper has been written with the plant operator and metallurgist in mind and aims to provide suitable material to be incorporated into a site training manual. Topics have been broadly divided into the following categories: factors that operational staff can control; including pulp density, air addition rate, froth depth, particle size and reagent type and use; factors that operational staff cannot control; providing general information on bubble size, froth stability, pulp chemistry and the mechanical effects of the rotor/stator system; and process improvements. Each topic is discussed with a view to clarifying the key process variables that need to be understood and optimised in an industrial operating plant.

Jan 1, 2009

By H Waterer, L Zheng, T Kalinowski

The Hunter Valley Coal Chain (HVCC) consists of mining companies, rail operators, rail track owners and terminal operators, together forming the worldÆs largest coal exporting facility. In 2008, the throughput of HVCC was about 92 million tonnes, or more than ten per cent of the worldÆs total trade in coal for that year. The coal export operation generates around $15 billion in annual export income for Australia. As demand has increased significantly in recent years, and is expected to increase further in the future, efficient supply chain management is crucial. The Hunter Valley Coal Chain Coordinator Limited (HVCCC) was founded to enable integrated planning and coordination of the interests of all parties, thus improving the efficiency of the system as a whole. One of the many planning challenges faced by the HVCCC is that of annual maintenance planning. Different supply chain elements, such as trains, railway track, terminal equipment and load points, must undergo regular preventive and corrective maintenance, leading to significant reductions in system capacity (up to 15 per cent). However good alignment of the maintenance tasks can reduce their impact, and the HVCCC undertakes an annual process to ensure the impact of maintenance on the supply chain capacity is as small as possible. This is achieved in an iterative negotiation process between HVCCC and individual service providers. In the past, maintenance schedule optimisation was largely manual, which for the more than 1000 tasks involved is quite labour-intensive.In this paper the authors describe an approach developed at the University of Newcastle in partnership with the HVCCC to automate this schedule optimisation process. We will discuss our experience in applying exact (mixed integer programming) and heuristic techniques from mathematics and computer science to address the problem. This work is anticipated to lead to new decision-support tools for the HVCCCÆs capacity planning team.

Sep 26, 2011

By Y. J. Wang

Optimal sizing of a ventilation shaft is a classical subject in mine ventilation economics.. The shaft size is optimized by minimizing the sum of shaft-construction and ventilation-power costs, or owning and operating costs. The length and air quantity of the shaft are held constant, and the location of the shaft, affecting its depth, and construction and ventilation power costs, is not considered (Hartman, 1961; Lambrechts, 1974; Wang et al., 1978). This paper proposes an approach by which the location and size for a new pair of shafts (intake and return shafts) are optimized for a coal-mine ventilation network. Specifically, the problem is to determine the location and size for a new pair of shafts, and the distribution of air between the new and old shafts so that the combined cost of shaft construction and ventilation power is minimized. The shaft length or depth corresponds to the height of overburden at any shaft location. To simplify the problem, the shaft locations will be limited to the line along the main or submain entries, and the connection entries at the shaft bottom neglected. In order to calculate the ventilation-power cost, the air power of the system should be determined. This in turn requires the calculations of the air quantity and pressure of each fan in the network, satisfying Kirchhoff's laws and Atkinson equation. After obtaining the air power, the cost calculation is straightforward. In the following, we shall assume that the resistances of all airways, and the quantity for each mining section, which is controlled by adjusting the air regulator, are all known. The resistances for the shafts are determined from the estimated friction factors, and shaft dimensions and lengths. Furthermore, it will be assumed that the fans can be selected to meet the duties called for by any network solutions.

Jan 1, 1982

By D. deV. van der Spuy

A procedure for optimizing the secondary cooling zone of continuous casters is proposed and illustrated by a billet caster example. The procedure consists of quantifying deviations from the required conditions of the secondary cooling zone?as far as temperatures, metallurgical length and reheating are concerned?by means of a ?cost function?. The optimal spray settings are then found by minimizing the total ?cost?. The billet caster examples serve to emphasize the importance of specifying the required conditions in a consistent manner. Some envisaged practical limitations of this approach are discussed.

Jan 1, 1999

By G. Favini

A Bayesian decision model of minimun risk, based on the probability and costs of mine discoveries and non-economic projects, is presented for massive sulphide exploration in the Canadian Shield. The sample used for the model is composed of data relating to forty mines, sixty non-economic sulphide occurrences, and sixty occurrences of graphitic and pyritic material. These economic and barren samples consist of drill-tested occurrences which were, in varying degree, characterized by conductivity anomalies. Given the large size, the reliability and the homogeneity of the data base available for massive sulphide exploration, it is shown that certain statistical models can and should be utilized as a tool for decision-making by explorationists. Given this data base, information theory tells us that only those signals that are independent of one another will transmit information with minimum error. An ensemble of six significant multilevel signals, markedly independent of one another and consisting of numeric and geometric form descriptions derived from Bouguer anomaly, aeromagnetic and physiographic maps, were identified and evaluated by case studies. The use of these signals as input in a simple statistical procedure, or in a carefully planned and experienced visual appreciation scheme, can be of significant aid in decisions concerning the choice of favourable areas or sectors to explore in detail. The method of discriminant analysis is theoretically and practically suited for the statistical modelling involved. By way of a simulation on our statistical model, the efficiency of the model and of the underlying criteria is determined for historic cases and, by inference, for its validity in future exploration. An approximate optimized solution is derived from the model which suggests that over 90% of the known ore could be found by screening, according to a model such as that herein described, and drilling only 30% of the targets (mostly barren) normally identified and tested in current and past exploration.

Jan 1, 1979

"This paper describes an alternative method of vehicle control which uses a micro-processor to control the field current and armature voltage concurrently. The field tests carried out and the conclusions drawn from the basis of the paper.IntroductionIt is generally accepted that the main obstacle to a greater use of electric vehicles is the relatively poor range and performance when compared to alternatives such as diesel and petrol-engine vehicles. Much effort has been applied to the problem of increasing the energy storage density of batteries and considerable improvements are now being reported.Improvements in the efficient use of the stored energy, although unlikely to achieve the necessary increase in range and performance for a widespread acceptance of electric vehicles, can nevertheless make a useful contribution. Because the improvement in efficiency is achieved by a reduction in losses, it follows that the temperature rise in drive-train components is reduced. These advantages, coupled with the increasing cost of energy, make improvements in the efficient use of the stored energy desirable, if not absolutely necessary. To achieve this with the large and rapidly varying loads encountered during the operational use of a vehicle will require a more flexible system of control than that provided by the current limit. This paper describes an alternative method of control which uses a micro-processor to control the field current and armature voltage concurrently.The value of these parameters is selected to supply the power demand at the motor shaft, with the minimum losses in electrical transmission, thus increasing the efficiency with which the stored energy is used."

Jan 1, 1982

By I. M. Macleod

An adaptive steady-state on-line optimizing regulator is proposed as an integrated approach to the control of autogenous run-of-mine milling circuits. This optimizing regulator continuously estimates an internal model of the controlled process, and, based on this, determines mill fresh solids feed rate, mill water flow rate and sump water addition flow rate such that a circuit performance objective is optimized. The dual -requirement of controlling both the mill pulp load and the load of particles of grinding media size is thus directly and simultaneously addressed. The concept and theory underlying the operation of the adaptive optimizing regulator are discussed.

Jan 1, 1987