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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

By Q Wang

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

Sep 26, 2011

By P Hatherly, A Melkumyan, D Wyman

Chemical species distributions in rock sequences can be modelled using Gaussian processes (GPs) to predict the weight percentage between known data points. This method can be improved by dividing the modelled area into regions of different mineralogy. In the context of many iron ore deposits, marker shales give the initial guidance of where these regions may lie. These shales give rise to distinctive peaks in the natural gamma downhole logs, which are conventionally identified by hand. A GP method has been developed to automate this task.Once the appropriate boundary has been located on the basis of shale occurrences, chemical assays from exploration drill holes are used to find the exact boundaries of interest. These boundaries divide the drill hole stratigraphy into regions of different mineralogy, each of which display their own distinct correlations between the main elements and oxides (Fe, SiO2 and Al2O3). Iron ore shows a negative correlation between Fe and Al2O3, but in banded iron formation (BIF) there is a positive correlation between these species. Similarly, SiO2 and Al2O3 have a positive correlation in the shales and ore but a negative correlation in the BIF. Correlations obtained within ore-, BIF- and shale-dominated regions are therefore better than those obtained using the entire log and can be used to improve the results obtained when modelling.

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 Youngtak Ko

The northeastern Pacific shows the highest nodule abundance among the oceans in the world, and thus has been drawing international attention for deep-sea manganese nodule development. The objectives of this study are to construct database using geostatistics and geographic information system (GIS), to quantify rating value using probability and statistical methods, to suggest suitable sites for manganese nodule development, and to verify results using three statistical approaches. The copper and nickel contents of the nodules were determined by chemical analysis. Factors related to slope, aspect, water depth, and topography were obtained from multi-beam echo sounding data. The transparent layer thickness was determined using a sub-bottom profiler. The probability method was used to calculate each factor's rating, and the layers for different factors were summed to produce the development potential index (DPI). Result maps were constructed for manganese nodules development. The distribution pattern of DPI showed to be controlled of nodule abundance and metal contents. Verification was performed by comparing the results with sampling data in three ways: success and prediction rate, linear regression, and test of independence.

Sep 14, 2011

By Sven Petersen

The southern Mid-Atlantic Ridge (SMAR) is one of the least-explored spreading centers in the world with respect to hydrothermal activity. In the past 8 years research focused mainly on the ridge segments close to Ascension Island, discovering hydrothermal fields as far south as 14°20?S (Haase et al., 2007; German et al., 2008; Tao et al., 2011). However, the vast majority of the SMAR ridge axis has never been thoroughly investigated for hydrothermal activity. In the spring of 2013 we used segment-scale AUV deployments as well as conventional CTD surveys to identify areas of hydrothermal activity along 16 mid-ocean ridge segments between 13° and 33°S, thereby covering close to 5 % of the global ridge axis in a single cruise. During cruise MSM25 of the German research vessel Maria S. Merian, we tested longrange (>100 km lines per dive) AUV deployments of GEOMAR?s AUV ABYSS (a Remus 6000 vehicle) along the spreading axis for their capability to locate active venting in a fast and efficient way on regional surveys. Since the missions covered long distances,

Sep 14, 2011

The chemical composition of the nodules varies with the type of manganese minerals and the size and characteristics of their nucleus but those who have an economic interest have nucleus, generally : Mn> Fe> 6> Si> Al> Ba> Ni> Cu > Co. The Pacific Rim is an area of abundant occurrence of polymetallic nodules and the Pacific sea floor of the Clarion-Clipperton Zone (CCZ) is one of the most interesting areas in regard to the genesis of polymetallic nodules. Their abundance in the ocean floor is very variable, as there are places where they cover more than 70% of the ocean floor. The nodules can be found at any depth, but the highest concentrations are between 4000 and 6000. Hydrothermal processes that occurs near the East Pacific Rise at 21° N, may inputs metallic elements to nodules and to pelagic sediments, especially in regions close to the dorsal, as a greater influence hydrogenetic processes are present westward Metals such as Cu, Co, Ni, Sn, Fe, Mg, Pb, Zn and Ba show a relationship with the East Pacific hydrothermal activity and sea currents carry these metals in solution to the Clarion-Clipperton fracture area, where there are hydrogenic metals sources (Al, Fe and Mn).

Sep 14, 2011

By S. Kim Juniper

Ocean observatory technologies permit uninterrupted, real-time observation of dynamic seafloor environments such as gas hydrate deposits and hydrothermal vent fields that are of both scientific and economic interest. Such observations enable new discoveries of linkages between physical, chemical and biological processes and could permit continuous monitoring of environmental variables during mining operations. Ocean Networks Canada operates the NEPTUNE and VENUS cabled observatories in the Northeast Pacific Ocean. The offshore NEPTUNE observatory supports instruments at two gas hydrate sites on the continental margin off Vancouver Island, and in the hydrothermal vent fields of the Endeavour segment of the Juan de Fuca Ridge. The primary focus of the gas hydrate field observations is to understand the dynamics of the growth and stability of outcropping and sub-seafloor hydrate deposits. Outcropping hydrates at 840 m depth in Barkley Canyon have been monitored for the past 3 years with a mobile instrument platform known as Wally, which is operated over the Internet by a research group in Germany. This tracked vehicle carries standard oceanographic sensors, acoustic current metres, cameras and methane sensors. Data indicate a relationship between degassing of hydrates and tidal currents. In 2012-2013 two high-resolution sonar towers were added to the hydrate field to provide precision tracking of Wally and to monitor volume changes in the outcropping hydrate mounds. A large subsurface hydrate deposit occurs at the Clayoquot Slope site, where bottom depth is 1260 metres. Monitoring instrumentation is currently being established at this location. Gas bubble release from this deposit is being monitored by a sector scanning sonar mounted on a

Sep 14, 2011

By Carsten Rühlemann

Between 2008 and 2013, the German Federal Institute for Geosciences and Natural Resources (BGR) carried out five exploration cruises to the German license area in the eastern Pacific Nodule Belt. The first two expeditions were mainly dedicated to multibeam mapping to obtain an overview of the seafloor topography and acoustic backscatter strength. These data were used to identify ten to fourteen prospective nodule fields for potential future mining, which together cover about 16% of the total license area of 75,000 km2. During the last three cruises, three of these potential mining areas were explored in detail. For this purpose, the BGR developed a suite of exploration methods to map nodule size distributions and nodule abundances. These methods include acoustic surveys with vessel-based multibeam systems as well as near-bottom video mapping complemented by in situ sampling. The economically most valuable field has a size of ca. 2,000 km2, of which 34% is covered by medium to large nodules (> 4 cm long axis of nodules) with an average abundance of 22.4 kg/m2 and 44% is covered by small nodules (< 4 cm) with a mean abundance of 17.5 kg/m2. The total mass of nodules in this field comprises more than 30 million tons wet weight and could sustain deep-sea mining for at least 10 years.

Sep 14, 2011

By Ye Jun

Until now, more than 200 sites of sea-floor hydrothermal activities are known on the midocean ridge but few of them are documented on South Mid-Atlantic Ridge (SMAR). This on some extent restricts our directly understanding of the hydrothermal mechanism on SMAR. In 2011, During the Cruise 22 of R/V Dayangyihao, a masive sulfide field was discovered in the center part of the first-order ridge segment that bounded between Cardno Fracture Zone and Saint Helena Fracture Zone, near 15.16°S/13.35°W, which give us an opportunity to recognize the mechanism of hydrothermal systems on SMAR directly. This newly discovered hydrothermal field, which informally called SMAR 15°S, is situated in a SE-NW offset depression of an axial neovolcanic ridge, with water depth of about 2793m. In the water column around this field, strong turbidity and temperature anomalies were detected. Ten meters high venting chimneys, hydrothermal mounds as well as a large amount of hydrothermal vent shrimps were also observed and recorded by ROV and Deep tow camera on the ocean floor. The samples we collected from this field include sulfide chimney fragments, massive sulfides and basaltic rocks. In this study, we are focusing on the mineralogy and sulfur isotope geochemistry of sulfide samples for preliminarily uncovering the geological characteristics and hydrothermal processes of this hydrothermal field.

Sep 14, 2011