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By J Ferreira

To speed up multivariate geostatistical simulation it is common to transform the set of attributes into spatially uncorrelated factors that can be simulated independently. One decorrelation method is the method of minimum/maximum autocorrelation factors (MAF), where a two structure linear model of coregionalisation is assumed. The transformation decorrelates the theoretical model exactly, but the actual data are only approximately decorrelated. The MAF transformation can therefore be seen as a special case of a non-orthogonal approximate diagonaliser of a set of symmetric matrices. A more general approach for approximate joint diagonalisation (AJD) has been developed in the context of blind source separation. For these AJD algorithms no assumptions are made beyond symmetry of the individual matrices and so they can be applied to a family of experimental semivariogram matrices. In their application there are no restrictions on the number of structures in the linear model of coregionalisation (LMC) thus removing one of the conditions placed on the subsequent modelling of the spatial structure of the factors. In this paper the general background for the U-WEDGE AJD method is presented. It is shown that the U-WEDGE method achieves better spatial decorrelation than the MAF method. The factors derived from U-WEDGE are simulated using conditional turning bands simulation and then backtransformed to attribute space.

Sep 26, 2011

By B Tutmez

Determination of stress-strain behaviour of rocks plays a crucial role in understanding the response of rocks during loading. However, it is a tedious, expensive and a time-consuming process to obtain such characteristics both in the laboratory and in situ. On the other hand, non-destructive testing methods such as ultrasonic velocities can produce a reliable and fast solution to indentify state of strain and stress in rocks. The present paper aims to provide insight into the relations amongst ultrasonic wave velocities, amplitudes and deformability properties of porous siltstone under compressive loading. For this purpose, pulse (vP) and shear wave velocities (vS) along with amplitudes (AP - AS), and applied loads with resultant strain were measured simultaneously so that response of siltstone to compression can be evaluated. In addition, initial vP and vS were recorded at the beginning of each test to calculate dynamic elastic properties of the specimens. This provided a comparison between static and dynamic elasticity properties of siltstone. Crack damage associated with the onset of dilation was also investigated. The results showed that there is a non-linear logarithmic relation between velocities and stress-strain level for siltstones.

Sep 26, 2011

By F Grobler

Many projects fail because project performance in unfavourable economic conditions was not anticipated at the investment decision stage. This type of failure may have been avoided through the selection of a strategy that enables the project to perform well under a range of possible future economic conditions (a ærobustÆ strategy); rather than an æoptimalÆ strategy for expected future conditions that will never eventuate. This paper describes a method of rapidly generating mine plans for a number of project strategies, and then evaluating it against a representative range of equally likely economic conditions. The key performance indicators derived for each strategy are the mean value and the distribution of values (variance). A prudent investor will identify prospective strategies not only on the merit of highest mean values (as a proxy for economic reward), but also on the probability of not meeting specified investment hurdles (a proxy for risk). A robust strategy will achieve its financial objective even under adverse economic variations. This paper focuses on the effect of commodity price uncertainty; particularly around the choice of mining and processing capacity levels. Results from enumerating 2000 prices scenarios against 63 strategy combinations show how processing and mining capacity can be manipulated to manage the risk-reward trade-off.

Sep 26, 2011

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 B Olsson, R Norman, M Volz

Australia has seen unprecedented demand for coal exports in the last ten years and this demand is set to expand further still according to many analysts. This rapid increase in demand has placed pressure on multi-user coal chains to guarantee the capability to meet the required demand, in terms of both current operations and capacity expansion.The projects required to deliver these forecast tonnages take place in an increasingly complex commercial and technical environment. These challenges include brownfield and greenfield projects, multiple rail and terminal service providers as well as a myriad of mine operators, all needing to operate in an increasingly integrated manner to get the most out of expensive shared assets.Increasing complexity and integration drives the need for more holistic and sophisticated analysis tools. The capacity of coal chain subsystems, such as mine, rail and port, can no longer be determined effectively in isolation. Understanding the nature of the interactions between these subsystems and the resultant capacity of the integrated system is the key to maximising value. TSG advocates the use of a total integrated system approach to understand the behaviour and performance of complex coal chains.Recently, TSG has worked in conjunction with the Integrated Logistics Company and a number of stakeholders in the Dalrymple Bay Coal Chain to deliver the first independent system master plan. This master plan has provided a quantitative and rational assessment of coal chain capacity in its current state and a prediction of its capacity once a pipeline of committed capacity improvements is in place. It is underpinned by a highly detailed discrete-event simulation model of the complete coal chain as an integrated system, including mine load-outs, rail, terminal and port operations.This paper provides an overview of the study and describes the differences between subsystem and total integrated system model performance.

Sep 26, 2011

By A Galli

Traditionally pit optimisation and scheduling is carried out assuming that the resources, the commodity prices and production costs are all known. Once the pit contour and the mining schedule have been determined, geostatistical simulations can be used to assess the impact of the uncertainty in the resources on the pit design and the schedule, and likewise stochastic simulations can be used to test its robustness to fluctuations in costs and prices. But it would be more interesting to have a dynamic procedure for optimising the pit as the resources become better known and as economic factors such as commodity prices and costs evolve over time. This paper presents a novel approach for doing this. Rather than working with millions of small selective mining units, it was decided to work with large blocks, called macro-blocks. Mining sequences are defined as the quantities to be extracted from each macro-block in each time period. Feasible mining sequences are mining sequences that respect the accessibility constraints, and also the geometric constraints on the amounts that can be extracted from any one block over time, or from all the active blocks at a given time. Having defined feasible mining sequences, their mathematical properties were studied. It was found that natural breakpoints occur in the sequences when one set of blocks have been completely mined out, thereby opening up access to others. It was discovered that families of sequences exist, and that they are convex and closed under certain types of row permutation operations. Convexity is an advantage when optimising. The closure property opens up the possibility of mixing and matching subsequences of rows in the sequences. Another interesting property is that the sequences form branching families, rather like the binomial and trinomial trees used to model prices in finance and in real options.It is easy to generate large numbers of feasible mining sequences randomly. A two-step procedure is used to find the best one (or the best few) using three economic criteria: expected NPV,the probability of a negative NPV, and the percentage of years when the cash flow is negative. The procedure was tested on a synthetic gold mine based on the characteristics of the Essakane mine in Burkina Faso. The results were encouraging.

Sep 26, 2011

By C Niemann-Delius

The problem of long-term open pit mine planning is a large combinatorial problem, which canÆt be solved easily by mathematical programming models because of the large problem size. In this paper a new metaheuristic algorithm, which has been developed based on the ant colony optimisation (ACO) and its efficiency, have been discussed. To apply the ACO process to a mine planning problem, a series of variables is considered for each block as the pheromone trails that represent the desirability of the block for being the deepest point of the mine in that column for the given mining period. During implementation several mine schedules are constructed in each iteration. Then the pheromone values of all blocks are reduced to a certain percentage and additionally the pheromone value of those blocks that are used in defining the constructed schedules are increased according to the quality of the generated solutions. By repeated iterations, the pheromone values of those blocks that define the shape of the optimum solution are increased, whereas those of the others have been significantly evaporated. By using this algorithm a high degree of complexities could be considered in objective function and constraints of optimisation model. In addition it can improve the value of the initial mining schedule up to 34 per cent for some cases in a reasonable computational time.

Sep 26, 2011

By E Rubio, N Morales

Currently, mine plans are optimised by using several criteria as objective functions, like profit, life-of-mine, concentration of some pollutants, mining costs, confidence level or ore resources, with consideration of constraints related to production rates, plant capacities and grades. Whilst this approach is successful in terms of producing high value production schedules, it uses a static opening sequence of the drawpoints and therefore the optimisation is made within the level of freedom left by the original opening schedule, and as a result it is far from the true optimal value of the project. This paper presents a model to optimise the sequence of drawpoint opening over a given time horizon. The emphasis is in the precedence constraints that are required to produce meaningful operational sequences considering the exploitation method (panel or block caving), physics considerations and logical rules. Further on, while it applies the standard approach of maximising net present value (NPV), it considers other targets for optimisation, like the robustness and constructability of the plans. Finally, it applies the model to real data to obtain feasible plans by means of this model. The first tests were done varying the production capacity of the mine.

Sep 26, 2011

By I Douglas, L Allen

Localised indicator kriging was developed following a similar approach used by Marat Abzalov (2006) in his paper titled æLocalised uniform conditioning (LUC): A new approach for direct modelling of small blocksÆ. Abzalov introduced the idea of mapping panel distributions from uniform conditioning onto selective mining unit-sized blocks that were created using ordinary kriging. This concept of remapping panel distributions was applied to multiple indicator kriging histograms.At Newmont a program was developed that made the remapping of MIK histograms to SMU sized blocks extremely efficient and was subsequently tested on several gold deposits. The results have been encouraging as the localised indicator kriging (LIK) method has eliminated many issues that have plagued both ordinary kriging and multiple indicator kriging. Use of localised indicator kriging methodology limits the smearing of high-grade and the over-smoothing of grade that is common and difficult to control in OK but retains the ability for localising grades. LIK also simplifies change-of-support corrections, eliminates un-mineable slivers of low or high-grade when dealing with small tonnages, and allows for the mapping of linear and non-linear estimates into the same block.

Sep 26, 2011

By P Moarefvand, M Osanloo

The anticipated economic life of the mine, which defines the rate of mine production, is dictated initially by the design capacity of the mill/concentrator and the production capacity of the mine relative to the grade and tonnage of ore that can be encompassed by the pit design. A small pit will result in smaller investment and cash flow; in contrast, a larger size of pit will increase capital investment and annual revenue. Since open pit mine design and long-term production sequencing are essentially based on three-dimensional block models, changes in block dimensions leads to different mine sizes, and therefore changes in the mine life. The physical characteristics of the deposit, such as reserve tonnage and ore grade, affect the expected future revenues from the mining project, and consequently they affect the life of the mine. Large blocks will increase the recoverable ore reserves and production rates and hence increase the mine life. This paper discusses the effects of the block dimension on the commercial ore reserve, grade-tonnage curve and its effect on the production rate, ultimate pit size, mining cost and consequently the mine life. The result shows that block height is the most effective parameter governing the economical life of the mine.

Sep 26, 2011

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 S D. Dessureault

The largest surface coal mine in North America requires complex materials handling infrastructure to fulfil the highly variable quality specifications of its contracts. These diverse demands, reflected in the arrival of numerous customer trains every day, necessitate the integration of information in every stage of production. To meet this goal, quality measurement, train line-up and mine planning processes are being integrated into local and remote control rooms. The effectiveness of such a system can only be measured by comparing decisions that are made with, and without, each of the individual integrated control systems. Traditionally, mine controllers use their experience, intuition or a variety of trial-and-error spreadsheets to determine the ideal materials handling flows needed to achieve the correct quality. These balanced decisions are complex since many factors must be considered such as the mine plan, fleet costs, quality variability and others; consequently mine controllers usually have widely varying success between crews.An evaluation model was developed to assess the impact of a decision support system (DSS) integrated in a control room for controlling the coal blending process. To this end, an ARENA-based simulator representing the whole production process can be used to pull performance and current materials handling settings directly either from the real-time systems in the mine, or from historical data. In this way, the same shift (breakdowns, cycle rates, etc) can be simulated and performance compared. Different settings of the DSS, in terms of what information is displayed and the methods for doing so, can be tested for effectiveness. The historical data are extracted directly from a corporate data warehouse, without altering the everyday working databases. At the same time, the simulator writes its results back into the same data warehouse structure, allowing the same KPI reports to be used to measure simulated shifts.

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 P Knights, M S. Kizil

Truck/shovel operations constitute 50 - 60 per cent of the cost of open pit mining operations. Mining companies, therefore, are constantly seeking to close the gap between actual truck/shovel productive capacity and maximum potential truck/shovel capacity. This paper analyses the performance of a mixed truck/shovel fleet in an open cut coal mine in Australia. It analyses operating delays, and proposes a novel graphical means of determining truck-limited or shovel-limited operations. A goal seeking algorithm is advanced in order to maximise truck/shovel match factors (MF) and hence optimise fleet productivity.

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