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By M J. Pejovic, I Miljanovic, A Milutinovic4, T Benovic, A Petrovski

The paper presents a model of a multigrade monitoring-management structure for support to decision making and management in real and extended time in mineral processing (MP). The model was created as a result of a long-lasting research, design and development of mining, computer integrated monitoring-management systems. Apart from the general explanations, the authorsÆ state in the introduction that efficiency of a system for support to decision-making and management in mineral processing is more difficult to achieve by conventional approaches, than by the fuzzy logic approach. Starting from the multiphase structure of process flows in MP, the following are process and monitoring-management oriented graphs. The graphs served as a foundation of the multigrade hierarchical fuzzy model for support to decision making and management in MP. Following the example of the monitoring-management system of the æRudnikÆ mine flotation plant, fuzzy logic implementation was shown. The key conclusions of the paper are that fuzzyfication of layers of the decision making and management model has full justification due to the complexity and dynamics of mineral processing processes, complications and often insurmountable difficulties concerning the precise description of real systems by conventional mathematical tools, variability of external influences, and the (general) non-linearity of the MP processes management criteria functions.

Sep 26, 2011

By A Noack

Today underground infrastructures, like tunnels and especially wide spread underground mines, are often equipped with ethernet based communication systems. These networks are used for the unified communication of data, voice and video. As these networks stretch along the major tunnels and in increasing scale also into the production areas, a high degree of coverage can be reached. For wireless coverage, standard IEEE 802.11 WLAN access points are being used. In order to provide a maximum availability and reliability, the active components are equipped with battery backup power supplies and the network infrastructure is set up in a redundant way using ring or meshed topologies. This provides a much higher availability compared to traditional phone systems or dedicated data links using a conventional star topology.Distributed computing intelligence that is installed on active network nodes throughout the whole network, additionally supported by a central server system, creates the basis for new mine safety functions introduced in this paper for both coal and non-coal mining. These new safety functions cover the detection of potential emergencies, using the status of the network as a æsensorÆ, as well as dynamically guiding people to safe exits or rescue shelters in case of an emergency. Furthermore, these functions are of important benefit for improving the efficiency of search and rescue operations following a major incident or accident underground.

Sep 26, 2011

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 J V. Mehrabani, A R. Sayadi

Adequate estimation of equipment costs is a key factor in a feasibility study and in evaluation of design alternatives for mining and mineral processing projects. Inaccurate early cost estimation could lead to the elimination of investment benefits. However, this estimation is complex and time consuming because of data accessibility problems and consequently access to a rapid, up-to-date and accurate tool is desirable for carrying out cost estimations.This paper describes the development of models for estimating capital and operating costs for a jaw crusher, which is used as the primary crusher for a wide variety of mineral beneficiation plants, applying single and multivariate regression analyses, together with the design of experiment approach, based on principal component analysis. Explanatory variables include gape size, length of feed opening and power as numeric (quantitative) variables and toggle type (single or double) and the existence of extra heavy duty construction as categorical (qualitative) variables. The performance of each model has been investigated and comparing the estimated R-squared (R2) of each model, the best was selected and its validity examined. The cost models include the capital and operating costs along with the operating cost components. The results indicate that the suggested best cost model is sufficiently accurate for use in feasibility studies.

Sep 26, 2011

By D Wyborn, P A. Dowd

The characterisation of rock fracture networks is an important component of rock engineering applications involving stability assessment or fluid flow analysis. However, the derivation of a reliable rock fracture model remains a very challenging problem in practice. This paper describes a Bayesian framework, in the form of Markov Chain Monte Carlo (MCMC) simulation, for the construction of such a model. Model conditioning using different data sources is discussed including seismic events recorded during hydraulic fracture stimulation, rock face fracture mapping data and downhole geophysical survey data. The freeware FracSim3D is used for the simulations.

Sep 26, 2011

Real-time data collection and plant historians are becoming common place in mining and processing plants. This vast quantity of data must be turned into easily accessible and actionable information for all levels of the organisation.Queensland Nickel use a combination of Microsoft and SAP business intelligence tools to collect, cleanse, aggregate and present plant information to the appropriate people for supporting decision making in the business. SAP Business Objects, for visualisation, and SAP MII, for integration, allows complex and accurate metrics to be delivered as real-time dashboards. Designing a rigid data management architecture to segregate the data collection, integration and logic and visualisation into distinct logical layers, allows for rapid report development and greatly assists with IT maintenance, while also minimising the complexity of any customised programming. This type of architecture ensures a common data source for all business reports, ensuring one version of the truth. The past few years at Queensland Nickel have seen process and maintenance engineers spending considerably less time collecting and integrating data and spending more time analysing what is happening in the plant. Real-time reports and dashboards have been developed around the business needs rather than around the data. Two years ago Queensland Nickel introduced an employee bonus scheme based upon meeting monthly performance targets; an easy to use dashboard that allows everyone, from operators through to management, to monitor these metrics day-to-day.

Sep 26, 2011

By A Esfahanipour, M Osanloo

Determination of cut-off grade?strategy is one of the most important stages of open pit mine planning and design. It is the parameter directly influencing the financial, technical, economic, legal, environmental, social and political issues in relation to mining operation. Choosing the optimum cut-off grade strategy that maximises the economic outcome has been a major topic of research workers for nearly one century. Many researchers have contributed in devising methods and algorithms, such as dynamic programming, linear programming, optimal control and so on for various aspects of its determination. In this paper, a non-linear mathematical programming for cut-off grade strategy optimisation is presented, considering the three main stages of mining operation introduced by K F Lane. In this model maximisation of net present value of mining operation, under the three constraints of mining stagesÆ capacities, considered as the optimisation criteria. Due to the discrete representation of the mining resource, the proposed non-linear formulation is approximated by a non-linear signomial geometric programming. According to non-convexity and the complexity of the proposed model, an augmented Lagrangian genetic algorithm was used to find the optimum cut-off grade strategy under varying and fixed price circumstances. To validate the proposed non-linear model efficiency, the results were compared with the results obtained by the K F Lane methodology. It was found that the proposed non-linear model works efficiently in the determination of cut-off grade strategy. According to the simplicity of the structure of non-linear programming modelling in comparison with dynamic programming it is hoped that, further development of this model would certainly provide the ability of considering managerial and technical flexibilities as well as incorporating more real mining conditions in the determination of cut-off grade strategy optimisation.

Sep 26, 2011

By M J. Pejovic, S BoÜevski, I Miljanovic, M Hudej, A Milutinovic, A Petrovski

The paper deals with the problem of managing the supplies of consumables (energy resources, lubricants, explosives, explosive supplies, tires, spare parts, etc) in mines. After the introductory remarks and comments, a general stochastic model of supply, relating in general to the dynamic programming method is presented. A selection of stochastic supply model for experiments and research by the authors of this paper is not a coincidence, based on of their long experience, showing that this type of model is the most suitable to provide support for decision-making and management of supplies of consumables in mines.In order for the problem?of?consumables?supply?management to be reviewed, in whole and objectively from the aspect of risk, experimental tests of the stochastic model in real conditions were performed at the limestone open pit mine æZelenikovecÆ near Skopje, the capital of Macedonia. The scope of the experimental research enabled reliable analysis. The results obtained confirm the efficiency and reliability of the stochastic model and two separate manipulative-operational positions regarding its application, which may have an important influence on the optimisation of supplies.

Sep 26, 2011

By P Lukic

The definition of the working sections that will be used in a mine is usually initially made in the field by the geologist supervising the drilling program. These initial definitions are often made on the basis of rules of thumb such as æcoal less than 30 cm thick cannot be mined separatelyÆ; æpartings more than 30 cm thick will be mined separatelyÆ; and æif a coal seam is less than 50 cm thick and the parting above or below is thicker than the coal, the coal will be wastedÆ. These decisions are also often made based on the requirement for a minimum sample mass for analysis, and the desire to collect data at the minimum resolution to conserve the exploration budget.In many cases the geological models based on this data are produced at a resolution that is inadequate to allow the mining engineer to produce a mine plan that will maximise project value. This problem is generally unrecognised.Where data is collected to a higher level of resolution the subsequent processes employed in the production of geological models and mine plans often discards the inherent value that is hidden in this data. Again this problem is generally unrecognised.This paper highlights this problem and then presents a methodology that ensures that the optimal working section is selected and compares the outcomes of applying this methodology versus adherence to the usual rules of thumb.

Sep 26, 2011

By C Augustin, M Hahn, K Nienhaus

Operators of mining machinery like haul trucks or excavators have very limited information about the exact distance to other equipment as well as to the natural boundaries like berms, walls and structures such as crushers. The industry is seeking solutions to provide safety and positioning. The authors have developed a solution approach which is being used in several installations. This solution consists of three parts: first robust and compact two-dimensional (2D) radar scanners that provide range and angular information of the environment especially under difficult conditions like dust, rain, snow and fog; second an intelligent data processing framework flexible enough to adopt to different machines and operation modes like speed, inclination, visibility, tire friction, GPS position, orientation and acceleration; and third a high quality and easy to use interface giving highly condensed data to the operator, not blinding the operator at night and being sunlight readable. The truth of present proximity detection sensors is that they not only have a high false alarm rate but furthermore cover only a fraction of the possible scenarios. This makes them unsuitable for stand-alone collision avoidance systems. On the other side, mine dispatch systems only deliver database and GPS information, but no information regarding the real environment. The indurad company and its Australian partner CTS (http://www.cts.com.au) addressed these aspects by developing smart productivity enhancement driver assistance tools like lane and crusher dumping assistance.An innovative driver assistance tool developed in cooperation with the coal shearer manufacturer Eickhoff and the RWTH Aachen University has been awarded with the annual research award of its customer RAG, being the largest German hard coal producer, as well as with the bauma Innovation Award in 2010.

Sep 26, 2011

By M Armony, J F. C L Costa, J C. Koppe

Linear kriging methods fail to estimate local grades and local reserves for highly skewed variables due to three reasons: it uses only part of the available data information, it has no physical principles associated with the mathematical proceedings to minimise the problems, and it works with continuous variables while data are discrete because of the limited precision of any equipment. The techniques commonly used up to now to solve the highly skewed variables estimation problems were unsuccessful, unless mathematical rigor is abandoned. Even the method of multiple indicator kriging is not satisfactory. This paper presents a new framework, the field parametric geostatistics (FPG) that transforms noisy variograms into well-behaved variograms and justifies mathematically empirical procedures commonly used, as trimming or capping arbitrarily very high values. The method, when applied to non-skewed variables, yields similar results to classic kriging. The methodology is illustrated in a case study at a gold deposit in Brazil, and compared to results obtained by usual techniques.

Sep 26, 2011

The cloud transform simulation is a technique used to generate realisations of correlated attributes. The principle of this technique is to partition the scatter diagram between the input attributes into several interval classes and derive for each class a cumulative distribution function (CDF) using only the data pairs of the scatter diagram in that class. The simulation then proceeds like a traditional Monte Carlo simulation but using the derived CDF in each class.The cloud transform simulation has the advantage of being a simple and fast technique that is able to reproduce the uncertainty in the relationship between the two input attributes regardless of whether the relationship is linear or not. However, the technique has three major drawbacks. First, the number of classes has an impact on final simulated results and there is not a robust approach to define such number. Second, simulated results exhibit some saw tooth variations that are unrealistic and third the reproduction of the spatial continuity of the simulated attribute is not guaranteed.This paper presents the use of the quantile regression approach in order to overcome the first two disadvantages of the cloud transform simulation. Details of the technique and how it can be coupled with the cloud transform simulation are presented along with a real case study.

Sep 26, 2011

By F Ramos

Conventional techniques for resource estimation generally involve the laborious analysis of variograms and the specification of parameters for covariance functions. In large deposits, construction of resource models and their update require significant amount of manual work, expert knowledge and time. In this paper we take a machine learning view to the problem of resource estimation. This is a non-parametric Bayesian method, leading to automatic parameter estimation (learning). Through Bayesian learning, the parameters of the model can be obtained by optimising a quantity known as the marginal likelihood. The main advantage of this approach over conventional maximum likelihood estimators is that the objective function incorporates the OccamÆs razor principle. This allows the comparison of different statistical models û for example, models designed with different covariance functions û and naturally penalises complexity, thus avoiding overfitting. Our technique presents significant flexibility for the definition of mean and covariance functions and permits the usage of more sophisticated models.The second contribution of this work is the formulation of a data fusion mechanism that continuously updates the resource model. As mining progresses, more information becomes available. For example, the hardness of the rocks can be measured while drilling blast holes, grades of ore and contaminants are obtained from cone logging. This information is in general available at a finer spatial resolution but can be more uncertain. The data fusion mechanism can seamlessly estimate the uncertainties of the different types of information and fuse them as new measurements are acquired. This procedure can significantly improve the quality of the resource model, defining new grounds for stochastic mine planning. We demonstrate the effectiveness of our approach in estimating iron ore deposits by integrating information about different grades.

Sep 26, 2011

By R Razanatsimba, A Galli

A mining company has entered into contractual commitments to supply certain quantities of its product to clients in each time period. Failure to fulfil its obligations would damage its reputation as a reliable supplier. The planned production would normally be sufficient unless major problems such as highwall failures, roof falls, natural disaster, or strikes that interrupt production or delays in obtaining environmental permits, occur. To overcome these difficulties, the company may be able to obtain more of the commodity: from its strategic stockpile (if there is sufficient there); by buying it on the spot market; or for some commodities such as gold and uranium, by leasing it. Two sources of uncertainty, the spot price of the commodity and the occurrence of serious incidents that interrupt production, are considered. For simplicity it is assumed that the commodity price follows a geometric Brownian motion, that productions incidents have a binomial distribution, that they are independent from one time period to another and that they do not affect prices. A branching tree structure is used to model the joint evolution of prices and production incidents. The aim of this research project was to evaluate the companyÆs options for fulfilling its contractual commitments. When evaluating these options, multi-stage stochastic programming with recourse was used to solve this problem because in addition to providing the dollar value of the project, it gives decision-makers the æroadmapÆ to reach the optimal value. That is, how much material should be bought/sold on the spot market, how much to add to/subtract from the stockpile, how much to lease and in the worst case what the shortfall would be, for each time period as a function of the current spot price and breakdown status. A case-study over a five-year period is used to illustrate the proposed procedure. In this study the production would be sufficient to cover the companyÆs contractual commitments unless production incidents occur. Focus is on evaluating the impact of the quantity initially in the stockpile on the value of the project when the commodity market is tight, that is, when only small quantities can be bought on the spot market or by leasing.

Sep 26, 2011

By V Gau, L Overmeyer, M Kesting

Economically efficient mining processes can be significantly assisted by the implementation of sensor technologies for the detection of materials and boundary layers between materials inside the stratum. These sensors are meant to facilitate the machinery operator and illustrate furthermore the prerequisites in assisting tools towards fully automated mining equipment. Therefore, project æSensory Identification of Material Type and Detection of the InterfacesÆ (SIMT) aims at the integration of ground penetrating radar (GPR) and geoelectric sensor technology by endowing with them a bucket of a bucket wheel excavator. For this reason, a sensor bucket was developed and tested in the Inden Mine of RWE Power AG. The feasibility of integration and deployment of such sensor technology has been proven effective for the conditions of open cast mining. The main focus of current research lies on developing algorithms to analyse the acquired measurement data from the sensors to automatically detect layers and materials. A computer network receives the GPR and geoelectric measurement data as well as the positioning data of the sensor bucket. The positioning data mainly consists of GPS and encoder information, which is merged with the sensor data by using the UTC time stamp. With the aid of consecutive processes the relevant information will be extracted and provided to the user. The aim of SIMT is to replace material identification, traditionally carried out by the operator, by implementing a continuous operating interpretation system in mining equipment based on GPR and geoelectric sensor technology, resulting in more detailed information regarding the working face during an excavation. This detailed information provides an opportunity for efficient planning and controlling of selective mining of natural deposits, such as the process of lignite mining.

Sep 26, 2011

The paper provides an overview of the development and content of APCOM symposia since their inception in 1961. This development is set within the context of the academic environment in which much of the research published at APCOM symposia is conducted. This environment includes rigorous external assessment of research quality at national levels and against international benchmarks, which carries significant consequences for funding and for the continued existence of the academic minerals industry disciplines. Adverse consequences that undermine the academic provision of mining and resource engineering will impact negatively on the minerals industry by reducing the level of research and education resources available to it.The traditional reductionist approach to research is contrasted with the inter-disciplinary approach that is required to address the complex systems problems that the minerals industry will have to address to ensure its technical, economical and environmental sustainability. Such an approach offers a means of raising research profiles, of establishing mutually beneficial academic-industry engagement and provides an opportunity for APCOM to take a lead role in identifying the research and development agenda for the future

Sep 26, 2011

By Q Wang

Net present value (NPV) has been the main criterion in mining project evaluation and production plan optimisation. It is a common practice in NPV calculations to take into account only the tangible cost items in the corporate accounting system. The costs incurred due to damage to the local ecosystem and environment are left out and treated as externalities. Such practice on the one hand underestimates the total cost of a mining operation and, on the other hand, ignores the difference in ecological/environmental impacts between different mine plan alternatives. This paper attempts to measure the ecological costs of mining and to incorporate such costs into the evaluation scheme in mining project evaluation and mine planning. The ecological costs of mining are estimated based on the areas and types of land (eg forest land, grazing land, crop land) damaged by mining activities and the carbon emission from fossil fuel consumption. For the land areas (and their associated ecosystems) directly damaged by mining activities, the ecological costs are measured by the prevention and restoration costs, the lost values of eco-services of the damaged land, including bio-product production, soil erosion control, water run-off control, oxygen release, air pollutant absorption and formation of soil nutrients. The ecological cost of carbon emission from the energy consumption of a mining operation is measured by the cost of cultivating the equivalent forest land required to uptake the emitted carbon. A case study on a large-scale open pit mining project is presented to demonstrate the influence of ecological costs on the mine planning outcome.

Sep 26, 2011

By R Paterson, A Christensen

The routine use of gravity gradiometry for the detection of orebodies with no outcrop is now being undertaken. The commodities and orebody styles range from banded iron ore formations to volcanogenic massive sulfide (VMS) style polymetallic deposits. This recent innovation of flying gravity gradiometry was pioneered by BHP Billiton and Lockheed Martin with the Falcon technology (Lee, 2001), and now two additional systems, also using Lockheed Martin instruments, are deployed. In South Africa, magnetic gradiometry is being developed and deployed with the same objectives in mind. In this case, a system from Institute of Photonic Technology (IPHT) is being used. The detectable wavelengths from such systems have decreased to less than 200 m in the last year, and it is expected in 2011 that wavelengths to less than 100 m, with anomaly signal strengths of less than 2 Eotvos for gravity gradiometry will be viable. The key to these advances lies in the improvements of processing software and geological modelling. In particular, methods using all the tensor components are starting to be routinely deployed to filter, level and grid the observed signal. These methods do, however, require full insight and understanding of the reference coordinate systems used by the various instrument designers and survey operators. The digital terrain models need also to be observed to an accuracy of better than 20 m cell sizes, using such techniques as Lidar. Then the terrain effects can be modelled. The topographic surface represents the largest and most proximal density contrast encountered in an airborne survey. Hence terrain effects can have significant impact on airborne gravity gradiometry data. A decorrelation of the terrain effect with the observed signal requires a method of best fitting with a regional surface density. A novel technique has been developed for this purpose. This technique uses a tensor algebra to estimate a density between 1 - 4 g/cc that explains the average observed signal. Armed with this result, the anomalous buried bodies can be revealed by subtraction.

Sep 26, 2011

By E Cunha, D Roldao, TáTamantini, J F. C L Costa, T Webber, C Monteiro

The main problem of geostatistical simulations is to reproduce the real characteristics of the mineral deposit when there are few conditioning data. In this case, the geological interpretation, based on structures, geophysics and geological maps, plays the major role in terms of resource evaluation.The paper investigates the use of principal component analysis (PCA) to help classify multiple geostatistical categorical simulations considering the similarity among them and the interpreted model, herein referred as training image (TI).An iron deposit with four lithological facies, in a specific horizontal plane, was used as case study for two-dimensional (2D) simulations. Sequential indicator simulations (SIS) was used to obtain ten equally probable 2D images, which were generated and compared against the interpreted model (TI).In this study, 11 random variables are comprised by the vector of ten SIS realisations plus the training image (TI). The similarity between the TI and each SIS realisation is measured using the angle between the TI and SIS vectors projected in the new coordinate systems (PCA factors). It is possible to order the SIS realisations from the highest to the lowest PCA factor taking into account the TI similarity.The visual analysis of the images shows coherence in the PCA results as a method to measure similarity. This methodology can be used as a post-processing tool to rank simulation results and to select the ones which better represent the prior known geology or to compare the quality of different methods of simulation.

Sep 26, 2011

By G van Niekerk, M Wortley

Screening is a critical part of many mineral processing circuits and keeping the aperture of the screening media within specification is vital to ensure efficient performance of the processing plant. Typical ways of estimating and/or measuring the wear of the screening media vary from very subjective methods (for instance, using the human eye) to manually checking the width of a few of the more severely worn gaps with a measurement device. Subjective methods can be flawed by human error while manual checking can distort the polyurethane or rubber materials that are used in several types of screening media. All of these errors can cause either premature replacement of panels or, even worse, poor screening of the material.Metso Process Technology and Innovation (PTI) and Metso Screening Media Solutions (SMS) have developed an innovative method that measures screen aperture using advanced image processing techniques. Field trials of the device are presented in this paper, which shows the comparison between the different methods of measuring apertures. Case studies demonstrate how the system, when combined with ScreenTrack, MetsoÆs industry leading maintenance system, and screening media, is providing users with the best possible screening solutions.

Sep 26, 2011