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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 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 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 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

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

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 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 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

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 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 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

By E Nettleton, A Melkumyan

A probabilistic system for autonomous tracking of excavated ore in mining would be highly valuable. Currently, mine sites can have a vast array of sensors; examples include excavator load cells, bucket volume estimators and haul truck strut pressures which can be used to gather information about the excavated ore at different locations. These sensors can be utilised efficiently to increase the accuracy of mine estimates by introducing a real-time ore tracking system. This requires the introduction of a probabilistic ore tracking framework to consistently fuse information from any sensor input. Current modelling practices are manually intensive, deterministic (no recognition of the quality of data) and generally not a complete end-to-end system. This paper will provide a novel method for tracking extensive ore properties (mass, volume) and intensive ore properties such as chemical composition (eg Fe per cent, SiO2 per cent, Al2O3 per cent). This method is proved to ensure that correct correlations between states are conserved as material is transferred, combined and/or separated at different locations with any configuration of sensor inputs. This ensures that consistency of estimates is maintained and other benefits such as real-time probabilistic reconciliation can be implemented. A method for combining material of different mass and chemical compositions is also developed to enable accurate and efficient operation of the system. Representative experiments on a small-scale and a larger field trial which mimic the mining processes of excavation, haul and unload to ROM Stockpile will be used to verify the approach.

Sep 26, 2011

By J Berg, M Hahn, R Winkel

Imaging sensor systems designed for the mining and minerals industry incorporate different physical measurement technologies that can be used to detect the machine environment, such as laser, ultrasonic/sonar, video and RF-sensors. The underlying physical measurement principles cannot be employed in most applications near the face without regular maintenance due to the harsh environmental conditions like dust, dirt or moisture. However, that is the area, where imaging sensors are most valuable to the machine operator. In the domain of 2D radar sensors these have been either restricted by the angular coverage area or by limited adaptability of signal processing algorithms. The unique full digital solid state design will establish a generation step in mining applications.In order to fill this gap of terrain imaging sensors, the Institute for Mining and Metallurgy Machinery (IMR) of the RWTH Aachen University, in cooperation with the radar company indurad, developed an imaging sensor based on radar technology employing the digital beam forming (DBF) concept. Through multiple transmitting and receiving antennas the sensor delivers high accuracy range and angular information. Using adaptive digital signal processing with multiple imaging algorithms and target detection routines, data of the surrounding environment can be used to enable automation functions in mining.A comprehensive range of radar scans in different environments have been evaluated and benchmarked by using laser scanners. Accuracy measurements in range and angular direction have shown minimal differences. Experimental measurements have been performed at slopes, on conveyor belts and hot cement clinker silos. The experimental system uses a frequency modulated continuous wave (FMCW) front-end combined with a processing unit for signal analysis and target detection.

Sep 26, 2011

By S D. Dessureault

In large coal strip mines, there are many different processes at work: stripping, overburden removal using trucks/shovels, cast blasting, slot dozer pushing, more fragmentation and further truck/shovel benches. A key component to each of these steps is the use of machines. In modern operations, most machine costs are tracked within Enterprise systems that transact costs and repair work order management. Similarly, in contemporary mines most machines are tracked using technology that provides precise performance measures for each key process. Such technologies include productivity monitors on draglines, dozers and drills and fleet management systems for trucks and shovels. Linking these two sources of seemingly disparate data û costs and performance by machine û would allow for the precise calculation of unit costs by specific machine. This is similar to an activity-based costing system, except in this machine-based system, calculations are made at an even finer granular level. There are many uses for such an integrated information system in mine planning and performance management, both in real-time and through historical analysis.A real-time fleet costs (FLC) measurement process was developed as part of a larger blending-related, multi-million dollar project centred on a centralised remote control room developed at the University of ArizonaÆs Mining Information Systems and Operations Management Mine Control Center. The FLC component of the overall blending system would allow a mine controller to manage the equipment fleet by viewing its cost in real time and, when mixed with other revenue-related components, the exact profit. For example, a mine controller may show high utilisation while still maintaining a production surplus. This could occur, for example, if the equipment is driven long distances. This might appear in traditional performance metrics as æhigh production performanceÆ, but in reality may prove less profitable. This paper discusses the technical development of the FLC, its deployment and its impact on controller performance, and compares mine profitability before and after its application.

Sep 26, 2011

By Adrián Del Carpio

Desde 1995 la planta de Lixiviación de Toquepala desarrolló un sistema de control automático para los procesos de extracción por solventes y electrodepositación. Sin embargo, con el desarrollo de la tecnología y las nuevas versiones de control, dicha plataforma se tornó arcaica. En ese sentido, el presente texto señala la modernización de los sistemas relacionados con el control y supervisión de las áreas de extracción por solventes, depositación electrolítica y áreas auxiliares. Como consecuencia de ello, se incrementó la operatividad, disponibilidad y fiabilidad con cero paradas por perturbaciones eléctricas, así como redujo el tiempo utilizado para el diagnóstico y solución de problemas.

Sep 12, 2011

By Doris Hiam-Galvez

The latest technologies that improve mining and mineral processing efficiency and significantly reduce the emissions and effluents will be briefly reviewed. In this sense, the paper point out that the water treatment using techniques such as nanofiltration through membranes to achieve purity levels equal to the incoming water supply is now possible and examples of how this is done will be presented. Membrane technology using nanofiltration can be effectively used for recovering valuable products in water from mining operations and also to remove contaminants. The resulting water is of prime quality equalling potable water standards. The technology can be adapted to most mining operations.

Sep 12, 2011

By L Keeney

Geometallurgy is not a mechanism designed to replace current geological and metallurgical deposit characterisation but an added component required to understand orebody variability. Current geological characterisation approaches focus on understanding deposit genesis aimed at identifying new mineralised regions and metallurgical characterisation determines parameters required for engineering design of processing plants. Geometallurgical integration has the task of drawing on aspects of each stream to enable spatial mapping of performance indices across a deposit. It is a complimentary activity to current practice and adds a new dimension to orebody knowledge. Although the notion of conducting an integrated geological and metallurgical analysis is not a new concept, limited publications exist in the field proposing integrated methods, with several technical issues existing in current geometallurgical integration approaches. An iterative method drawing on existing geological and metallurgical characterisation and new measurement tools and inputs is proposed. The integrated method comprises of discrete components dynamically linked together through iterative feedback loops with each component having a specific purpose achieved by applying a range of data acquisition technologies and statistical tests. The key outcomes of the method are:overcoming the lack of optimised geometallurgical domains relevant to processing performance,development of a rigorous approach to identifying parameters controlling processability,improved protocols for relevant metallurgical test data and sample selection, andability to generate greater data support to enable rigorous geostatistical modelling of geometallurgical attributes. This paper outlines the integrated mapping and modelling method developed and draws on multiple data acquisition technologies applied within the AMIRA P843 GeMIII Project.

Sep 5, 2011

By G Turner-Saad

An improvement to cut-off grade optimisation theory based on geometallurgy has been completed. The improvement fundamentally consisted of taking into account mineralogical and textural characteristics instead of grades. These characteristics are related to the spatial variability of mineral abundance, association, particle size and liberation properties. Additionally, the improve- ment considered the spatial variability of mineral processing liberation and selectivity properties associated with mineralogy and texture. The enhanced optimisation enables estimation of the economic value of mining operations based on an optimum cut-off policy attributed to liberated and selected ore minerals.The enhanced optimisation was developed as an essential component of a joint cut-and-fill mining and mineral processing methodology based on mixed integer mathematical programming. The formulation considers static and dynamic modifying factors that vary over the projected life of mining. The objective function of the mathematical formulation consists of maximising the realistic expected economic value of concentrates or products of liberated and selected ore minerals, whilst minimises liberated and selected gangue minerals. The optimal solution is obtained when the objective function is subject to geological, mining, processing, marketing, smelting, refining, environmental and financial constraints. The methodology accesses geometallurgical multivariate resource models, which integrate the spatial variability of mineralogical and textural characteristics and mineral processing liberation and selectivity properties.The geometallurgical process concurrently optimises stope geometries, ore reserves, mining sequences, and mining and mineral processing production based on the enhanced cut-off of liberated and selected ore minerals. In addition, the process considers additive and non-additive transfer functions associated to mutually exclusive geometallurgical spatial domains. The transfer functions also take into consideration the blending of mineralogical and textural characteristics with mineral processing liberation and selectivity properties.This contribution presents an example of cut-off grade optimisation via mineralogical and textural characteristic, and liberation and selectivity processing parameter optimisation for a spatially variable orebody.

Sep 5, 2011