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By R J. Hardy

The aim of this study is to examine the volumetric and mass movement characteristics of load and haul operations using statistical modelling of relatively large samples of bucket loads that are transported as small samples in the form of truck payloads. Generally, the factors influencing bucket load variability are random, difficult to predict and to control. In the process of loading trucks the underlying variability of individual bucket loads will determine the variability of truck payloads. Bucket loads of material prepared by drilling and blasting for loading into trucks are fundamental quantities in open pit mine production. A study of payload data from a large surface mining operation indicates that bucket loads and truck payloads that are a small sample of bucket loads are normally distributed. Truck payloads have a reduced dispersion compared with bucket loads that is an inverse 0.5 power function of the number of passes per truck payload. Comparison of statistical modelling results with the æ10/10/20Æ policy promoted by Caterpillar Global Mining Inc, indicate that compliance with the æ10/10Æ part of the policy, applying to truck overloading is facilitated, as the coefficient of variation of truck payloads decreases, as a result of the increasing number of loading passes. Compliance with the more stringent æ20Æ part of the policy, relating to safe steering and braking is also facilitated, albeit at lower coefficient of variation for similar reasons.

Sep 26, 2011

By D M. Silva, J C. Alves

According to the literature, material transportation represents 50 per cent of the operating costs for an open pit mine. In this context, this paper proposes a multistage approach for dynamic truck dispatching in real open pit mine environments, implemented in the commercial package SmartMine®, marketed by Devex SA. The first stage of this approach defines the optimal number of trucks that maximises the tonnage production by means of a robust linear programming model, which considers the operational constraints of a real mining process. The second stage uses a dynamic dispatching heuristic joining computational simulation and multicriterion optimisation techniques for decision making for truck dispatching. Another relevant contribution of this work is the publication of realistic instances collected from a dispatching system managing an iron mine, containing information about the hauling and loading fleet, the equipment situation when the working shift starts, cycle times, the time line of special occurrences (such as equipment stoppages and loading equipment reallocation in order to satisfy the mine planning) and the tonnage produced. These instances were generated with the purpose of submitting the method to the test of a real situation that considers the uncertainties existing in the process studied. The proposed approach was validated by means of a discrete event simulation model applied to the previously designated instances. Using this multistage approach as a mechanism for dispatch decision making, it is shown that the haulage fleet productivity increased when compared with the real values reported from the instances. These results are important because they show that the proposed approach generates efficient dispatch decisions for trucks operating in a real environment, reducing operating costs, increasing production and making the mine more competitive.

Sep 26, 2011

By D Misra, R Ganguli, S Bandopadhyay

The objective of this paper is to assess the accuracy and applicability of recent state-of-art methods such as the machine learning algorithms (MLA) for mineral resource estimation. Conventional methods such as geostatistics have been predominantly used in the mining industry for this purpose with varying success. Recent advances in the use of MLA have provided a fresh approach to obtain improved accuracy in the estimation of mineral resources. Two MLA methods: the neural network (NN) and the support vector machine (SVM) have been used to estimate a polymetallic ore deposit in Alaska.The general characteristic of SVM and NN emphasises the fact that they can approximate any multivariate non-linear relation among variables. Although neural network models are able to capture the nonlinear spatial relationships that may be present in the data, they are usually difficult to optimise under sparse data settings. Of the various NN alternatives, despite their effectiveness, the model selection and estimation process is typically difficult as it involves solving complex integration and optimisation of parameters. In support vector modelling (SVM), estimating of parameters involves optimisation of a convex cost function. The working principle of SVM makes it robust against noisy and extreme value data. At the same time, it can capture the spatial distribution of ore grade more effectively with careful modelling and selection of SVM parameters.The outcome of the MLA methods were compared to those of the geostatistical ordinary kriging (OK) application to study their generalisation ability. The comparison was made using the following goodness of fit criteria: mean-squared error; mean absolute error; mean error; and coefficient of determination. The results indicated that the MLA methods may improve the predictability of ore deposits and thereby reduce the inherent risk in mineral resource estimation.

Sep 26, 2011

By C Claassen, R Balusu

Computational fluid dynamics (CFD) models have been developed based upon field data collected from a longwall mine in New South Wales, Australia to study the behaviour of goaf gas flow in both active and sealed goaf areas. A base CFD model was built to represent the goaf situations when the active longwall retreats near the finish-off line. Results from the base model were calibrated and compared against field goaf gas monitoring data. The base model was then used to carry out parametric studies to investigate a number of operational scenarios and their impact on goaf gas behaviour. CFD modelling results indicate that the overall goaf gas flow pattern changes as the operating longwall retreats towards finish-off line. In all cases, oxygen penetration into the active goaf remains high, reaching 15 per cent or higher, even at some 800 m behind the longwall face.The modelling results also indicated that it would be difficult for early detection of an active goaf heating (on the maingate side) based upon CO readings in the return airflow, as the main stream of the gaseous product will be flowing into the sealed deep goafs in adjacent longwall (LW) panels. Monitoring points (such as tube bundles and bag sampling points) should be selected at deep seated seals along the active goaf so that abnormal CO or C2H6 readings can be picked up for early detection and location of potential heating spots; goaf inertisation can be better achieved by injecting inert gas such as nitrogen at deeper points (>200 m) behind the operating longwall; the injection of in-seam drainage methane into the goaf areas will only have a limited impact on goaf inertisation as much of the injected methane will migrate towards deep and higher parts of the goaf due to its buoyancy effect.

Sep 26, 2011

By J A. M Luz, A T. Bernardes

HukkiÆs law is an empirical law, which does not take into account several events of energy loss during the fragmentation processes. Since experimental results are very difficult to obtain, for a large range of fragment sizes, the verification of the law is very difficult. The relation between fractures and fragmentation processes with fractal geometry was proposed some decades ago. Empirical laws known in this context show basic features of fractal geometry, mainly self-affinity and power law behaviour. Thus, in this work a model was developed to simulate the fragmentation process and to check the relation between energy consumption and fragment sizes. The model is represented on a regular lattice. Links can represent pathways for fracture processes. The events of fragmentation have energy given by a probability distribution function. In the model there is no mass loss. Propagation of fractures occurs as self-avoiding random walks on the regular lattice.

Sep 26, 2011

By S D. Dessureault

In one of North AmericaÆs largest mines, which contains more than six active coal-producing faces, mine controllers must meet the complex challenge of adhering to the mine plan while also ensuring customer quality. Fleet management systems (FMS) provide many different avenues to control production flows, from the faces to the various pit crushers. Nonetheless, mine controllers must balance a variety of factors such as unplanned downs, differing customer demands, their own daily key performance indicators (KPIs) related to equipment utilisation, among others. Deviating from the short-term mine plan is the most common means of balancing the other factors, since adherence to the plan is traditionally only measured during the weekly variance meeting with engineering staff. However, such deviation may be one of the most costly responses, as long-term scheduling issues may arise such as multi-face dead-heading or insufficient stripping. This paper focuses on the development of a system for real-time adherence to mine plan within a control room environment. This system is part of a larger blending-focused, multi-million dollar project with elements of a centralised remote control room, developed at the University of ArizonaÆs Mining Information Systems and Operations Management (MISOM) Mine Control Center (MC2). The mine plan (MPL) component of the overall blending system integrates both historical and real-time FMS data with mine plan requirements directly sourced from original systems (no additional input required). The measures, displayed largely as graphs, have tools to help controllers manage the production to facilitate adherence to the plan. Some measures are designed to motivate crews to perform by inciting competition between crews, softened through a study of the controller culture. The MPL component was deployed at the mine, and the before and after deployment adherence was measured. This paper discusses the technical development of the new tool, its deployment, and an ethnography (study of culture) to understand controller motivation.

Sep 26, 2011

By E A. Gunn, J Zhou

In this paper a project to develop a joint optimisation/simulation model for production planning in a mine-mill complex is presented. The system involves a mill receiving ore from a number of different locations, each with a unique mineral composition. The mill consists of several crushing and grinding circuits that function in series and parallel. Scheduling the flow of materials through the mill is complex due to constraints on throughput imposed by the millÆs design, the length of time material can be stockpiled on the surface, varying input mineral composition, and throughput targets for a range of output products.An optimisation model is used to create a set of campaigns (ore feed rates) over a given planning horizon under the assumption of deterministic mill throughput. A simulation model is used to evaluate the production plan under assumptions of stochastic machine failure and operational losses created by the need to cycle between input feeds. Campaign scheduling has two important implications for the simulation. First, during any campaign, multiple ore types may need to flow through the mill. However, the mill must be controlled to ensure that only one type of ore can be in a crusher, a grinder or a storage bin at any point in time. Second, as the mill switches from one campaign to another, the set of ores being processed may differ. Thus, the flow of ore through the equipment during a campaign changeover must be controlled to ensure that one or more of the ores from the current campaign can be completely eliminated before the ores from the new campaign are introduced.The simulation architecture employed for this project is Visual Basic for Applications (VBA) combined with MS-Excel as a user interface. A fixed step discrete event orientation is assumed as the simulation framework. A set of model constructs was built for the project with a specific Canadian milling operation in mind, but was designed to be representative of a broad class of milling operations. The constructs are implemented as class objects within the VBA structure, each with a number of properties and methods. The collection of VBA objects forms a composable modelling toolkit. These objects can be linked together by users, via MS-Excel, to represent a broad range of milling operations.

Sep 26, 2011

By S Van Duin, I Porter

This paper discusses how advanced manufacturing technology (AMT), which is fundamentally reliant on and developed via multi-disciplinary skills, has benefitted non-mining industries, and what lessons can be derived from this experience to benefit the mining industry, particularly underground coal mining. Examples of AMT use in æconventionalÆ industry, some drawn from the more than 25 years experience in many different industries of the Automation and Robotics team at the University of Wollongong, are described to show typical benefits, risks and opportunities expected in using AMT. Applying AMT to mining brings many unique challenges and this paper expands on these and then provides practical examples of how a multi-disciplinary team can develop new processes and systems leading to productivity, safety and other benefits for underground coal mining.

Sep 26, 2011

Longwall mining operations have been in place in Australia since the early 1960s. This mining method is currently used to extract the bulk of coal obtained from underground mines in Australia (CSIRO, 2010). Despite the high tonnages extracted the expected utilisation of much equipment remains relatively low. To some extent this level of utilisation is influenced by the variability in conditions inherent in the mining process. This variability in production rates presents challenges to those attempting to design a coal clearance system. The difficulty is to design a system that has sufficient capacity to support production, without over capitalising or incurring high operating costs. The need to allow for a series of largely unplanned events in the design of a coal clearance system makes simulation modelling an ideal technology to employ. Simulation modelling is a methodology that allows a system with interacting components to be modelled over time, while explicitly taking into account unplanned events that may disrupt operations.This paper discusses how dynamic simulation models have been used to assist in the design of coal clearance systems. Typically this type of modelling has been used to look at the likely profile of production rates from the Longwall shearer and to determine how well various proposed combinations of belts, bins and stockpiles would support production.

Sep 26, 2011

Visual computing opens the design process to a wider audience and allows rapid communication of mine plans to all stakeholders. The integration of software and hardware technologies that take advantage of a graphical environment will continue to improve both long-term and short-term mine design (Figure 1). A good design must be adaptive to respond to decision changes as the mine develops and more information becomes available. The constraints on mine design predicate careful analysis in order to operate the mine as efficiently and safely as possible.Continuous improvement in mining is assured by developing innovative technologies that target mine survey, drill and blast, modelling, short-term design and pit and stope optimisers. The design life of a mine has to be sufficiently long to ensure the mine is commercially successful, justifying the high start-up capital costs. Being able to execute a plan so that it honours the design realises the rewards of computerised mine planning and the long-term investment in data acquisition.

Sep 26, 2011

By A Huebner, A Noack

Companies all over the world are very sensitive concerning their IT and network security. In most network connected technical installations and machines however, network security is not taken into account to a significant extent: insecure protocols are run, unencrypted information is exchanged freely and even broadcasted wirelessly and networked machines are accessible via insecure file transfer protocol (FTP).What happens in case of malfunctions of such technical installations? Who is responsible? Who can be held liable in case of accidents? The first computer worm for automation systems (æSTUXNETÆ) (Symantec, 2010) was discovered during 2010.The paper is intended to create sensitivity among decision makers for potential security and resulting safety leaks and points out the current status quo in technical network security. It outlines best practices for secure networking and procedures for remote access and remote software updates on stationary equipment and mobile mining machinery. It describes how to ensure authentic and genuine configurations and software targets and how to ensure secure communication for autonomous and remote controlled equipment. For such equipment in particular, the following statement should apply: æThere is no safety without network securityÆ.

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

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 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 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

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