Analysis and evaluation of fragment size distributions in rock blasting at the Erdenet Mine

Master's Project (M.S.) University of Alaska Fairbanks, 2015Rock blasting is one of the most important operations in mining. It significantly affects the subsequent comminution processes and, therefore, is critical to successful mining productions. In this study, for the evaluation of the blasting performance at the Erdenet Mine, we analyzed rock fragment size distributions with the digital image processing method. The uniformities of rock fragments and the mean fragment sizes were determined and applied in the Kuz-Ram model. Statistical prediction models were also developed based on the field measured parameters. The results were compared with the Kuz-Ram model predictions and the digital image processing measurements. A total of twenty-eight images from eleven blasting patterns were processed, and rock size distributions were determined by Split-Desktop program in this study. Based on the rock mass and explosive properties and the blasting parameters, the rock fragment size distributions were also determined with the Kuz-Ram model and compared with the measurements by digital image processing. Furthermore, in order to improve the prediction of rock fragment size distributions at the mine, regression analyses were conducted and statistical models w ere developed for the estimation of the uniformity and characteristic size. The results indicated that there were discrepancies between the digital image measurements and those estimated by the Kuz-Ram model. The uniformity indices of image processing measurements varied from 0.76 to 1.90, while those estimate by the Kuz-Ram model were from 1.07 to 1.13. The mean fragment size of the Kuz-Ram model prediction was 97.59% greater than the mean fragment size of the image processing. The multivariate nonlinear regression analyses conducted in this study indicated that rock uniaxial compressive strength and elastic modulus, explosive energy input in the blasting, bench height to burden ratio and blast area per hole were significant predictor variables in determining the fragment characteristic size and the uniformity index. The regression models developed based on the above predictor variables showed much closer agreement with the measurements

Advances in Computational Intelligence Applications in the Mining Industry

This book captures advancements in the applications of computational intelligence (artificial intelligence, machine learning, etc.) to problems in the mineral and mining industries. The papers present the state of the art in four broad categories: mine operations, mine planning, mine safety, and advances in the sciences, primarily in image processing applications. Authors in the book include both researchers and industry practitioners

Advanced Techniques and Efficiency Assessment of Mechanical Processing

Mechanical processing is just one step in the value chain of metal production, but to some exten,t it determines an effectiveness of separation through suitable preparation of the raw material for beneficiation processes through production of required particle sze composition and useful mineral liberation. The issue is mostly related to techniques of comminution and size classification, but it also concerns methods of gravity separation, as well as modeling and optimization. Technological and economic assessment supplements the issue

Open source R for applying machine learning to RPAS remote sensing images

The increase in the number of remote sensing platforms, ranging from satellites to close-range Remotely Piloted Aircraft System (RPAS), is leading to a growing demand for new image processing and classification tools. This article presents a comparison of the Random Forest (RF) and Support Vector Machine (SVM) machine-learning algorithms for extracting land-use classes in RPAS-derived orthomosaic using open source R packages. The camera used in this work captures the reflectance of the Red, Blue, Green and Near Infrared channels of a target. The full dataset is therefore a 4-channel raster image. The classification performance of the two methods is tested at varying sizes of training sets. The SVM and RF are evaluated using Kappa index, classification accuracy and classification error as accuracy metrics. The training sets are randomly obtained as subset of 2 to 20% of the total number of raster cells, with stratified sampling according to the land-use classes. Ten runs are done for each training set to calculate the variance in results. The control dataset consists of an independent classification obtained by photointerpretation. The validation is carried out(i) using the K-Fold cross validation, (ii) using the pixels from the validation test set, and (iii) using the pixels from the full test set. Validation with K-fold and with the validation dataset show SVM give better results, but RF prove to be more performing when training size is larger. Classification error and classification accuracy follow the trend of Kappa index

New Methods for ferrous raw materials characterization in electric steelmaking

425 p.In the siderurgical sector, the steel scrap is the most important raw material in electric steelmaking,contributing between 70% of the total production costs. It is well-known how the degree of which thescrap mix can be optimized, and also the degree of which the melting operation can be controlled andautomated, is limited by the knowledge of the properties of the scrap and other raw-materials in thecharge mix.Therefore, it is of strategic importance having accurate information about the scrap composition of thedifferent steel scrap types. In other words, knowing scrap characteristics is a key point in order to managethe steel-shop resources, optimize the scrap charge mix/composition at the electric arc furnace (EAF),increase the plant productivity, minimize the environmental footprint of steelmaking activities and tohave the lowest total cost of ownership of the plant.As a main objective of present doctoral thesis, the doctorate will provide new tools and methods of scrapcharacterization to increase the current recycling ration, through better knowledge of the quality of thescrap, and thus go in the direction of a 100% recycling ratio. In order to achieve it, two main workinglines were developed in present research. Firstly, it was analysed not only the different existingmethodologies for scrap characterization and EAF process optimization, but also to develop new methodsor combination of existing, Secondly, it was defined a general recommendations guide for implementingthese methods based on the specifics of each plant

Method development in automated mineralogy

The underlying research that resulted in this doctoral dissertation was performed at the Division of Economic Geology and Petrology of the Department of Mineralogy, TU Bergakademie Freiberg between 2011 and 2014. It was the primary aim of this thesis to develop and test novel applications for the technology of ‘Automated Mineralogy’ in the field of economic geology and geometallurgy. A “Mineral Liberation Analyser” (MLA) instrument of FEI Company was used to conduct most analytical studies. This automated system is an image analysis system based on scanning electron microscopy (SEM) image acquisition and energy dispersive X-ray spectrometry which can be used to determine both quantitative mineralogical data and mineral processing-relevant parameters. The analyses can be conducted with unconsolidated and solid rocks but also with ores and products of the mineral processing and recycling industry. In consequence of a first-time broadly-based and comprehensive literature review of more than 1,700 publications related to all types of automated SEM-based image analysis systems several trends in the publication chronicle were observed. Publications related to mineral processing lead the field of automated mineralogy-related publications. However, this is with a somewhat smaller proportion than expected and with a significant decrease in share between around 2000 and 2014. The latter is caused by a gradual but continuous introduction of new areas of application for automated mineralogical analysis such as the petroleum industry, petrology or environmental sciences. Furthermore, the quantity of automated mineralogy systems over time was carefully assessed. It is shown that the market developed from many individual developments in the 1970s and 1980s, often conducted from research institutes, e.g., CSIRO and JKMRC, or universities, to a duopoly - Intellection Pty Ltd and JKTech MLA - in the 1990s and 2000s and finally to a monopoly by FEI Company since 2009. However, the number of FEI’s competitors, such as Zeiss, TESCAN, Oxford Instruments, and Robertson CGG, and their competing systems are increasing since 2011. Particular focus of this study, published in three research articles in peer-reviewed international journals, was the development of suitable methodological approaches to deploy MLA to new materials and in new contexts. Data generated are then compared with data obtained by established analytical techniques to enable critical assessment and validation of the methods developed. These include both quantitative mineralogical analysis as well as methods of particle characterisation. The first scientific paper “Use of Mineral Liberation Analysis (MLA) in the Characterization of Lithium-Bearing Micas” deals with the field of mineral processing and describes the characterisation of lithium-bearing zinnwaldite mica - as potential natural resource for lithium - by MLA as well as the achievement of mineralogical association data for zinnwaldite and associated minerals. Two different approaches were studied to comminute the samples for this work, conventional comminution by crusher as well as high-voltage pulse selective fragmentation. By this study it is shown that the MLA can provide mineral data of high quality from silicate mineral resources and results very comparable to established analytical methods. Furthermore, MLA yields additional relevant information - such as particle and grain sizes as well as liberation and grade-recovery data. This combination of quantitative data cannot be attained with any other single analytical method. The second article “Characterisation of graphite by automated mineral liberation analysis” is also located in the field of mineral processing. This research article is the first published contribution on the characterisation of graphite, an important industrial mineral, by MLA respectively an automated mineralogy-related analytical method. During this study graphite feeds and concentrates were analysed. By this study it is shown that it is possible to gather statistically relevant data of graphite samples by MLA. Furthermore, the MLA results are validated by quantitative X-ray powder diffraction as well as particle size determinations by laser diffraction and sieve analysis. The third research paper “Nature and distribution of PGE mineralisation in gabbroic rocks of the Lusatian Block, Saxony, Germany” deals with the scientific field of geoscience. In this study it is shown that it is possible to obtain a significant body of novel mineralogical information by applying MLA analysis in a region previously regarded as being well-studied. The complex nature and relatively large distribution of the occurring platinum group minerals (PGM) is well illustrated by this contribution. During previous light microscopic studies and infrequent electron microprobe measurements only a handful isolated PGM grains were identified and characterised. In this investigation, using the samples of previous studies, 7 groups of PGM and 6 groups of associated tellurides as well as in total more than 1,300 mineral grains of both mineral groups were identified. Based on the data obtained, important insight regarding mineral associations, mineral paragenesis and the potential genesis of the PGM is obtained. Within this context, the value of MLA studies for petrological research focused on trace minerals is documented. MLA yields results that are both comprehensive and unbiased, thus permitting novel insight into the distribution and characteristics of trace minerals. This, in turn, is immensely useful when developing new concepts on the genesis of trace minerals, but may also give rise to the development of a novel generation of exploration tools, i.e., mineralogical vectors towards exploration akin to currently used geochemical vectors. The present dissertation shows that automated mineralogy by using a Mineral Liberation Analyser is able to deliver a unique combination of quantitative data on mineralogy and several physical attributes that are relevant for ore geology and mineral processing alike. It is in particular the automation and unbiasedness of data, as well as the availability of textural data, size and shape information for particles and mineral grains, as well as mineral association and mineral liberation data that define major advantages of MLA analyses - compared to other analytical methods. Despite the fact that results are obtained only on 2-D polished surfaces, quantitative results obtained compare well/very well to results obtained by other analytical methods. This is attributed mainly due to the fact that a very large and statistically sound number of mineral grains/particles are analysed. Similar advantages are documented when using the MLA as an efficient tool to search for and characterise trace minerals of petrological or economic significance.Die Forschung die der vorliegenden kumulativen Dissertation (‚Publikationsdissertation‘) zugrunde liegt wurde im Zeitraum 2011-2014 am Lehrstuhl für Lagerstättenlehre und Petrologie des Institutes für Mineralogie der TU Bergakademie Freiberg durchgeführt. Das primäre Ziel dieser Arbeit war es neue Einsatzmöglichkeiten für die Technik der Automatisierten Mineralogie im Gebiet der Lagerstättenkunde und Geometallurgie zu entwickeln und zu testen. Im Mittelpunkt der wissenschaftlichen Studien stand die analytische Nutzung des Großgerätes „Mineral Liberation Analyser“ (MLA) der Firma FEI Company. Dieses automatisierte System ist ein Bildanalysesystem und basiert auf der Erfassung von Rasterelektronenmikroskopiebildern und energiedispersiver Röntgen-spektroskopie. Mit Hilfe der MLA-Analysetechnik lassen sich sowohl statistisch gesichert quantitative mineralogisch relevante als auch Aufbereitungsprozess-relevante Parameter ermitteln. Die Analysen können sowohl an Locker- und Festgesteinen als auch an Erzen und Produkten der Aufbereitungs- und Recyclingindustrie durchgeführt werden. Infolge einer erstmaligen, breit angelegten und umfassenden Literaturrecherche von mehr als 1.700 Publikationen im Zusammenhang mit allen Arten von automatisierten REM-basierten Bildanalysesystemen konnten verschiedene Trends in der Publikations¬historie beobachtet werden. Publikationen mit Bezug auf die Aufbereitung mineralischer Rohstoffe führen das Gebiet der Automatisierte Mineralogie-bezogenen Publikationen an. Der Anteil der Aufbereitungs-bezogenen Publikationen an der Gesamtheit der relevanten Publikationen ist jedoch geringer als erwartet und zeigt eine signifikante Abnahme des prozentualen Anteils zwischen den Jahren 2000 und 2014. Letzteres wird durch eine kontinuierliche Einführung neuer Anwendungsbereiche für die automatisierte mineralogische Analyse, wie zum Beispiel in der Öl- und Gasindustrie, der Petrologie sowie den Umweltwissenschaften verursacht. Weiterhin wurde die Anzahl der Systeme der Automatisierten Mineralogie über die Zeit sorgfältig bewertet. Es wird gezeigt, dass sich der Markt von vielen einzelnen Entwicklungen in den 1970er und 1980er Jahren, die oft von Forschungsinstituten, wie z. B. CSIRO und JKMRC, oder Universitäten ausgeführt wurden, zu einem Duopol - Intellection Pty Ltd und JKTech MLA - in den 1990er und 2000er Jahren und schließlich seit 2009 zu einem Monopol der FEI Company entwickelte. Allerdings steigt die Anzahl der FEI-Konkurrenten, wie Zeiss, TESCAN, Oxford Instruments und Robertson CGG, und deren Konkurrenzsysteme seit 2011. Ein Schwerpunkt der drei von Experten begutachteten und in internationalen Fachzeitschriften publizierten Artikel dieser Studie war die Entwicklung eines geeigneten methodischen Ansatzes um die MLA-Technik für neue Materialien und in neuem Kontext zu verwenden. Die erzeugten Daten wurden mit Daten die von etablierten analytischen Techniken gewonnen wurden verglichen, um eine kritische Bewertung und Validierung der entwickelten Methoden zu ermöglichen. Dazu gehören sowohl quantitative mineralogische Analysen als auch Methoden der Partikelcharakterisierung. Der Schwerpunkt der Studie zum ersten Fachartikel „Use of Mineral Liberation Analysis (MLA) in the Characterization of Lithium-Bearing Micas“ liegt im Gebiet der Aufbereitung mineralischer Rohstoffe. Er beschreibt die Charakterisierung von Zinnwaldit-Glimmer - einem potentiellen Lithium-Rohstoff - durch die MLA-Technik sowie das Erringen von Mineralverwachsungsdaten für Zinnwaldit und assoziierter Minerale. Dabei wurden zwei unterschiedliche Wege der Probenzerkleinerung des Rohstoffes untersucht. Zum einen erfolgte eine konventionelle Zerkleinerung der Proben mittels Brecher und Mühle, zum anderen eine selektive Zerkleinerung durch Hoch¬spannungsimpulse. Es konnte aufgezeigt werden, dass die automatisierte Rasterelektronen¬mikroskopie-basierte Bildanalyse mittels MLA von silikatischen Rohstoffen Mineral¬informationen von hoher Güte zur Verfügung stellen kann und die Ergebnisse gut vergleichbar mit etablierten analytischen Methoden sind. Zusätzlich liefert die MLA weitere wertvolle Informationen wie zum Beispiel Partikel-/Mineralkorngrößen, Aussagen zum Mineralfreisetzungsgrad sowie Gehalt-Ausbring-Kurven des Wertstoffes. Diese Kombination von quantitativen Daten kann mit keiner anderen analytischen Einzelmethode erreicht werden. Der zweite Fachartikel „Characterisation of graphite by automated mineral liberation analysis“ ist ebenfalls im Fachgebiet der Aufbereitung mineralischer Rohstoffe angesiedelt. Während dieser Studie wurden Edukte und Produkte der Aufbereitung von Graphit-Erzen untersucht. Der vorliegende Artikel ist der erste in einer internationalen Fachzeitschrift publizierte Beitrag zur Charakterisierung des Industrieminerals Graphit mittels MLA-Technik bzw. einer Analysenmethode der Automatisierten Mineralogie. Mit der Studie konnte gezeigt werden, dass es möglich ist, auch mit der MLA statistisch relevante Daten von Graphitproben zu erfassen. Darüber hinaus wurden die Ergebnisse der MLA-Analysen durch quantitative Röntgenpulverdiffraktometrie sowie Partikelgrößen-bestimmungen durch Laserbeugung und Siebanalyse validiert. Der dritte Fachartikel „Nature and distribution of PGE mineralisation in gabbroic rocks of the Lusatian Block, Saxony, Germany“ ist im Gegensatz zu den ersten beiden Artikeln im Gebiet der Geowissenschaften angesiedelt. In dieser Studie wird gezeigt, dass es möglich ist mittels MLA-Analyse eine signifikante Anzahl neuer Daten von einem eigentlich schon gut untersuchten Arbeitsgebiet zu gewinnen. So konnte erst mit der MLA die komplexe Natur und relativ große Verbreitung der auftretenden Platingruppenelement-führenden Minerale (PGM) geklärt werden. Während früherer lichtmikroskopischer Analysen und einzelner Elektronenstrahlmikrosonden-Messungen konnten nur eine Handvoll weniger, isolierter PGM-Körner nachgewiesen und halbquantitativ charakterisiert werden. In der vorliegenden Studie konnten nun, an den von früheren Studien übernommenen Proben, 7 PGM-Gruppen und 6 assoziierte Telluridmineral-Gruppen mit insgesamt mehr als 1.300 Mineralkörnern beider Mineralgruppen nachgewiesen werden. Auf der Grundlage der gewonnenen Daten wurden wichtige Erkenntnisse in Bezug auf Mineralassoziationen, Mineralparagenese und zur möglichen Genese der PGM erreicht. In diesem Zusammenhang wurde der Wert der MLA-Studien für petrologische Forschung mit dem Fokus auf Spurenminerale dokumentiert. Die MLA liefert Ergebnisse, die sowohl umfassend und unvoreingenommen sind, wodurch neue Einblicke in die Verteilung und Charakteristika der Spurenminerale erlaubt werden. Dies wiederum ist ungemein nützlich für die Entwicklung neuer Konzepte zur Genese von Spurenmineralen, kann aber auch zur Entwicklung einer neuen Generation von Explorationswerkzeugen führen, wie zum Beispiel mineralogische Vektoren zur Rohstofferkundung ähnlich wie derzeit verwendete geochemische Vektoren. Mit der vorliegenden Dissertationsschrift wird aufgezeigt, dass Automatisierte Mineralogie mittels Mineral Liberation Analyser eine einzigartige Kombination an quantitativen Daten zur Mineralogie und verschiedene physikalische Attribute, relevant sowohl für die Lagerstättenforschung als auch für die Aufbereitung mineralischer Rohstoffe, liefern kann. Im Vergleich zu anderen etablierten analytischen Methoden sind es insbesondere die Automatisierung und Unvoreingenommenheit der Daten sowie die Verfügbarkeit von Gefügedaten, Größen- und Forminformationen für Partikel und Mineralkörner, Daten zu Mineralassoziationen und Mineralfreisetzungen welche die großen Vorteile der MLA-Analysen definieren. Trotz der Tatsache, dass die Ergebnisse nur von polierten 2-D Oberflächen erhalten werden, lassen sich die quantitativen Ergebnisse gut/sehr gut mit Ergebnissen anderer Analysemethoden vergleichen. Dies kann vor allem der Tatsache zugeschrieben werden, dass eine sehr große und statistisch solide Anzahl von Mineralkörnern/Partikeln analysiert wird. Ähnliche Vorteile sind bei der Verwendung der MLA als effizientes Werkzeug für die Suche und Charakterisierung von Spurenmineralen von petrologischer oder wirtschaftlicher Bedeutung dokumentiert

Doctor of Philosophy

dissertationThis research was undertaken to investigate the impacts of finer rock fragmentation (arising from higher energy blasting) on the unit costs of a hard-rock surface mine. The investigation was carried out at a copper operation in southern Utah, which exploits its deposits by conventional methods, including drilling, blasting, loading, and truck haulage. The run of mine is processed in a three-stage crushing circuit and a two-stage grinding circuit, which feed a flotation plant that produces a copper concentrate. The research was carried out using modeling and simulation techniques. Fifty-five blast designs in total were developed for ore and waste units, with energy inputs ranging from 100 kcal/st to 400 kcal/st. For each design, fragmentation was predicted using the Kuz-Ram method. Crushing of the predicted ore fragment size distributions was simulated using MODSIMTM. Data from pit face imaging and timed motion studies were collected and analyzed for the influence of fragmentation on shovel and truck productivity. Analyses indicated that fragment size distribution alone does not significantly impact this productivity. From simulation of the crushing circuit, it was found that the impact of differences in the blast-generated fragment distribution on the crusher energy is limited to the primary crusher, where a vast range of feed size distributions are introduced. No such relationships were evident at the secondary and tertiary crushers. Energy savings from increasing blasting intensity proved negligible and would not justify the costs of higher energy blasting. There was no evidence from this work that any beneficial influences of blast-generated fragment size distribution reach the grinding mill. Costs were estimated for drilling, blasting, and crushing, which were the principal unit operations inferred to be affected in some meaningful way by the varying intensities of blast energy input. The research shows that, principally as a result of jaw crusher gape restrictions and the significant unit costs of secondary reduction for both ore and waste, the net of all breakage (primary blast, secondary reduction, and crushing) does reduce to a transient minimum before they begin to ramp up again, thus fitting a classical mine-to-mill curve