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By V. Králová

The TESCAN Integrated Mineral Analyzer (TIMA), an automated mineralogy system, enables fast and quantitative mineral analyses of rocks, ores, concentrates, tailings, leach residues or smelter products. It combines BSE and EDX analysis for identification and measurement of mineral concentrations, particle size distribution, and liberation/locking parameters. In addition, it can provide bright particle searches for PGM, gold-silver ores, and/or REE. With the newly developed Automated Loading System (AutoLoader), the TIMA has become the world?s first automated mineral analyzer which permits robust, continuous and unattended sample loading. With the AutoLoader (robotics) system, the TIMA has emerged as a powerful plant support instrument. It increases the sample throughput, minimizes manual labor and enables 24/7 operations. As such, it can be used in daily, continuous mineralogy for mine geology/ore control, concentrators, leach operations, and smelter support. It will also increase the capabilities of technical service centers for mining companies, commercial laboratories, large drilling programs or pilot test campaigns. In combination with a highly automated sample preparation lab (sizing, potting and polishing), TIMA technology can establish high-throughput and fast-turnaround automated mineralogy lab modules for mine-site production support.

Feb 23, 2014

By C McMahon, S G. Walters

Mineral maps of æintactÆ and large particle textures have been produced routinely from optical microscope images. Polished thin sections of large particles (1 - 3 mm) provide a balance between representative sampling and the preservation of primary rock textures. Optical microscopy is an efficient way to generate mineral maps suitable for geometallurgical applications. The automated optical mineral identification was carried out using a Leica DM6000¬ microscope with a high precision stage suitable for direct tiling of image frames and good registration of multiple image layers. Standard images collected were 10 x 10 frames (20 mm x 16 mm). Four image layers were recorded: ætransmitted light plane polarisedÆ, ætransmitted light crossed polarsÆ, ætransmitted light crossed polars with 1l tint plateÆ and æreflected lightÆ. All image analysis was carried out using Definiens Professional V5¬. The four image bands were read directly in 12 greyscale bands. A segmentation algorithm produced objects based on homogeneity across all bands. These objects were then classified using a complex set of rules (Process Tree) that are based on image brightness in all 12 bands. Opaque and non-opaque minerals were classified in the same sample. Using this protocol up to 12 minerals can be satisfactorily classified in one sample. The opaque minerals were recognised using colour ratio and reflectance intensity in the reflected light image. Non-opaque minerals are more difficult because of the complex variable colours of many minerals and the complexity of interference colours. However, object-oriented classification using three transmitted light image layers and multiple rules is a powerful technique for recognition of these minerals.

Jan 1, 2008

By Y Gu, R Fandrich

Traditionally, characterisation of the mineralogy and textures of ore and rock samples were based on observations of hand specimens and thin sections using an optical microscope. The extent of the data collection was limited by the available tools and thus variations in mineralogy and texture were generally not described by quantitative data. These qualitative to semi-quantitative approaches, even though well established over the years, resulted in variable observations and data sets. The data were unlikely to be representative of a sample and limited statistical validity meant the results could not be reliably used in modern digital mining design and planning. With recently developed SEM based quantitative mineralogy tools and the corresponding methodologies, ore textures can be quantified and compared numerically. The numerical data can not only enhance the understanding of an orebody in geological terms, but can also be used in the creation of metallurgical models for mine and mineral processing design and simulation. These capabilities provide valuable inputs to risk assessment studies and the evaluation of mineral projects.

Jan 1, 2007

By D. Burrows

Traditionally, characterisation of the mineralogy and textures of ore and rock samples were based on observations of hand specimens and thin sections using an optical microscope. The extent of the data collection was limited by the available tools and thus variations in mineralogy and texture were generally not described by quantitative data. These qualitative to semi-quantitative approaches, even though well established over the years, resulted in variable observations and data sets. The data were unlikely to be representative of a sample and limited statistical validity meant the results could not be reliably used in modern digital mining design and planning. With recently developed SEM based quantitative mineralogy tools and the corresponding methodologies, ore textures can be quantified and compared numerically. The numerical data can not only enhance the understanding of an orebody in geological terms, but can also be used in the creation of metallurgical models for mine and mineral processing design and simulation. These capabilities provide valuable inputs to risk assessment studies and the evaluation of mineral projects.

Jan 1, 2007

By C McHugh, F Oppolzer, B Rogers, A Stokes

Rio Tinto has embarked on a journey to use automation to improve the performance of its surface mines. The driver for automation has more to do with improving the accuracy and consistency of mining processes and less to do with cost savings through labour reduction.A key task in most surface mines is blasthole drilling. The degree to how well this is done cascades through the downstream mining process. It impacts scheduling, excavation, slope stability, material handling, beneficiation, ore loss and final product blending. Improved blasthole drilling was identified as an objective that has a significant business case in most of Rio TintoÆs surface mines.This paper describes Rio TintoÆs multi-drill automation project, which has developed a robust system for automating most of the functions on several Caterpillar SKSS16 drill rigs. Automated drilling is currently being trialled in production at the West Angelas iron ore mine in the Pilbara region of Western Australia. A description of the essential elements of the automated multi-drill system is given together with an overview of how automated drilling is performed remotely from the operating bench.A review of the performance and benefits of the automated multi-drill system is given together with future plans to extend the functionality of automated drills.CITATION:McHugh, C, Stokes, A, Oppolzer, F and Rogers, B, 2012. Automated multi-drills in Rio Tinto, in Proceedings Eighth Open Pit OperatorsÆ Conference , pp 83-88 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 18, 2012

By J Franke, C Gonzalez

One of the regular tasks of geotechnical and mining engineers is the measurement and management of deformation in underground excavations. Although several methods are used to do so, the incumbent methodologies for monitoring deformation and ground support serviceability are limited to the use of visual observations or measurements at discrete points, resulting in a qualitative assessment only. The introduction of LiDAR technology allows a quantitative assessment across the entire excavation volume and its rock surface, by collecting a full three-dimensional image of the entirety of an excavation such as an underground drive, decline, or a tunnel. Comparisons between epochs of complete 3D data coverage allows for change detection over time that doesn’t feature otherwise typical omissions. The implementation of regular scanning has shown to be highly advantageous for mines with swelling or squeezing ground, but also at mines with rapid deformation. Despite the LiDAR potential, its adoption has been slow. A key reason for that is that working with point clouds is foreign to most geotechnical engineers. Point clouds have long been the realm of surveyors, but to fully adopt their use in geomechanics requires retraining, upskilling, and devotion by the individuals and the company. Sites are already stretched, so often there are insufficient resources to be applied to bringing the new technology into use. The solution to this hurdle is to partner with subject matter experts to achieve the desired high-quality outcomes without the commitment of time by geotechnical personnel. This paper presents a new solution of fully automated raw LiDAR point cloud data processing that not only enables geotechnical engineers to avoid having to learn unrelated skills by allowing for deformation monitoring without associated training or expertise, but it also provides instant reporting results as well as a sophisticated database with features otherwise not available. All data processing time and effort is completely replaced by an automated process which at the same time opens up the opportunity to monitor many more excavation volumes at a higher frequency than is possible with conventional tools and methodology.

Nov 29, 2022

Brand se Baai, on the North-Western Cape Coastline of Southern Africa, is the site of the Namakwa Sands Limited Heavy Mineral Sands Mining Operation. The mine is a 14 000 000 tonnes per annum open-cast strip-style mining operation using truck and excavators to mine the sand. The orebody consists of relatively unconsolidated sands reworked by fluvial, marine and aeolian mechanisms. The total orebody includes three primary ore types, namely the Red Aeolian Sands, the Dorbank (a hardcap layer) and the Orange Feldspathic Sands, which forms the bulk of the resource. Mine planning and scheduling is done using a 50 m + 50 m variable bench height system with three primary bench heights. The Aeolian and Dorbank each have a bench that varies with their thickness of up to a maximum eight metres and the Orange feldspathic sand, a standard bench height of eight metres. For a number of years Namakwa Sands used a complex 2D, Datamine Based, macro system to perform the resource evaluation and mine design. As the mining operations expanded it became clear that a complete system redesign was required to cope with the increasing operational pressures coming to bear on the old system. The biggest challenges facing any replacement system are the sheer scale of the mining operation (16 km long and 7 km wide resulting in a minimum of 30 000 individual 50 m + 50 m mining blocks), the size of the geological data files (up to one gigabyte) and representing the benching system accurately (as the benches follow the topography and are not horizontal). In addition to these large-scale issues, the ability to run multiple mine design scenarios was required, an aspect which the old system was unable to perform adequately. Based upon these primary difficulties, a new business process was developed which required a complete rethink of the mine design methodology as well as the creation of a new system to deplete the resource model, produce monthly reconciliation evaluations and create a ultimate pit limit based on the operations mining cost model. Using a system based on the Earthworks Mine2-4D Mine Design and Scheduling System (with its mine design and scheduling specific tools), as well as a small, customised program, massive time-savings have been made. It is now possible to run several life of mine scenarios in the same timeframe that a single life of mine run took under the old system. This paper will present the methodology and business decisions behind the new Namakwa Sands system, and detail the restructuring and development used to deal with the large data set sizes and long processing times inherent in the old system. Future enhancements to the system that will make it more generically applicable to open-cast mining scenarios will also be dealt with.

Jan 1, 2003

By Joel L. Volterra

Since 1910, Mueser Rutledge Consulting Engineers (MRCE) has regularly provided professional engineering services including inspection of pile load tests. Historically, such services included on-site inspection of the driving of test piles and subsequent static load tests by qualified Geotechnical Engineers. Load testing procedures are specified by local or State Building Codes, locally the 1968 Building Code of the City of New York (1968 BCCNY). Between 1968 and 2008, the 1968 BCCNY required a minimum 48-hour hold period for standard loads per pile type, an extended 96-hour hold period for higher capacity piles, and a settlement criterion that the pile maintain a test load equal to two times the design load with less than 0.012 inches of settlement over the last 48 hours of the hold period. Effective July 2008, the new 2008 BCCNY shortened the hold period and relaxed the settlement criteria to that which is more similar to other governing codes and standards such as the International Building Code (IBC 2006) and the American Society for Testing and Materials (ASTM). MRCE implemented an automated load test monitoring system to reduce costs and to alleviate or minimize overnight and off-hour staffing for load test readings. Initially, a series of linear variable differential transformers (LVDTs) and data loggers were included in the Contractor?s load test setup to electronically record pile head settlement and where applicable, settlement of telltales installed to varying depths in the pile. A pressure gage was subsequently added in the hydraulic line, then a load cell, strain gages, and remote access using modems. The ease of the setup and modular adaptive nature of this system have proven it to be a useful tool and improved our ability to better serve our clients and manage our pile load testing services.

Jan 1, 2008

By Yu. P. Astafyev

The, control of drilling and blasting is a complicated dynamic system whose aim is to ensure safety and prepare rock of required grade and the standard level of broken material reserves Unlike other processes drilling and blasting, as an object have the following features: -a large variety of drilling and blasting methods due to specific conditions of blasting, various types of drilling equipment, schemes-of blasting, types of explosives and others; -relative continuity of drilling, the character of mammoth blasts being discrete; -increased requirements to the safety of blasting;; -a great. number of control parameters, some of them having a qualitative characteristic but not a quantitative one; -availability of feedforward and feedback with other mining processes in terms of time and space. These features predetermine the hierarchical structure of an automated system of planning and control of drilling and blasting (fig.1). The system is implemented on the basis of unity of the data base and in interre lation with other problems of controlling mining operations. An automated system of this kind makes it possible to take optimal decisions actually on all the levels and stages of operations, with rock having been blasted before extraction.

Jan 1, 1986

By A. Melkumyan, K. Silversides

Chemical assays collected from blast holes have the potential to greatly improve the local accuracy of grade models. Assays must be assigned to the correct domain or they will introduce errors. Boundary surfaces created from the widely spaced exploration holes (~50m) do not provide sufficient resolution to correctly delineate domain boundaries between closely spaced (3-5m) blast holes. This paper demonstrates a probabilistic method for classifying production blast holes near domain boundaries. Gaussian processes models are applied to identify the assays and assay ratios most suited to distinguishing particular domains. These models are combined with the exploration based surfaces to classify the blast holes that can be confidently assigned to a particular domain. A reiterative method is used, where information from the blast holes closest to the exploration holes is used to label blast holes further away. This is tested on two domain boundaries in a banded iron formation-hosted iron ore mine.

Sep 1, 2021

By T Mattiske

The Fimiston Open Pit (commonly referred to as the æSuper PitÆ) is a part of the Kalgoorlie Consolidated Gold Mines Pty Ltd (KCGM) operation in Kalgoorlie-Boulder. KCGM manages the Fimiston Open Pit, the Mt Charlotte underground mine, the Fimiston Mill and the Gidji Roaster for its Joint Venture Owners, Newmont and Barrick Australia. KCGM produces up to 850 000 ounces of gold per year. The KCGM operations are located on the historical Golden Mile on the outskirts of the City of Kalgoorlie-Boulder, about 600 kilometres east of Perth Western Australia. This traditionally underground mining centre has been worked since 1893, yielding in excess of 50 Moz of gold from ore with an average head grade of 10 g/t. This represents approximately ten per cent of the gold produced in Australia and one per cent of the gold produced in the world. The Fimiston Open Pit is essentially an aggregation of what were known as the Judd, South, Paringa, Croesus/Eclipse, Central, Brownhill, Drysdale, Morrison, North and Horseshoe pits into one continuous large-scale operation. The old Fimiston Underground Operations (included the Main, Croesus, Chaffers, Lake View, and Perseverance shafts) were also located within the area of the Fimiston Open Pit. The underground operations closed in 1992 due to high mining costs.

Jan 1, 2002

By Robert Fritzsch, Ragnhild E. Aune, Mark William Kennedy, Behzad Mirzaei

"The quantitative particle concentration can give important information about the cleanliness of melts for quality control in primary and secondary production of aluminum. Manual quantification of the particle concentration is normally a time consuming process and human control can bias the acquired images and particle count.The present paper explains the automated image-processing steps for the quantification of SiC-particles, with equivalent diameters from 2 to 25 µm, in solidified A356. A total of 700 micrographs, acquired with a standard white light microscope with 10 x magnification, were analyzed. The applied software (Image Pro-Plus 7.0 from MediaCybemetics®) allows for programming of macros which in tum provides the user with a higher degree of control. The automated results are compared with the results obtained by manually counting the particles in the same micrographs. The impact of the automated results on the estimated filtration efficiency was established to be only -3%.IntroductionInclusions are both indigenous and exogenous particulates that are present in commercial metals such as aluminum. If large individual or large numbers of inclusions are present, they can have a significant negative impact on the appearance, mechanical and chemical behavior of products produced from the metal. Aluminum is known to contain large numbers of inclusions: =50 µm in size, e.g. typically <l ppm by volume or <100,000 inclusions of>20 µm per kg of metal as detectable using a Liquid Metal Cleanliness Analyzer, LiMCA [1]. Depending on the final application of the aluminum, inclusions can render the metal 'not fit for purpose', and result in serious economic consequences to metal producers.It is not surprising that the aluminum industry has developed a number of treatment processes to improve metal cleanliness, given the large number of high value products whose quality can be adversely affected by inclusions. CFFs are the most commonly applied filtration process and have been used to filter >50% of the world production of aluminum since the 1990's [2].Inclusions in aluminum may be particles, bifilms [3] or clusters of: oxides (Al2O3 , SiO2), spinels (MgO· Al2O3), carbides (SiC, Al4C3), nitrides (AlN), borides (TiB2), sulfides, phosphides and intermetallics [ 4]."

Jan 1, 2013

By C. Kim

The integration of three-dimensional (3D) data with infrared thermography has received much attention for its potential use as input data for building energy simulations. Therefore, researchers have proposed methods to integrate 3D data with infrared thermography obtained by different sensors. These studies show the potential of the integration of 3D data and infrared thermography using various systems. However, these studies have ignored property aspects of infrared thermography, such as the low resolution of infrared thermography and external environmental influences. Thus, their proposed methods to integrate 3D data and infrared thermography are inadequate because these problems can affect the resulting building energy simulation. This research proposes a framework that integrates infrared thermography and 3D data while accounting for the resolution and shadow effect of infrared thermography. The proposed framework consists of three steps. In the resolution enhancement step, bi-cubic interpolation is proposed. In thermal data correction from the shadow effect, the shadow area is detected from the visible image, and then the shadow effect is removed from the registered infrared thermography. Finally, enhanced infrared thermography is mapped to the 3D data obtained by a laser scanner. The performance of the proposed framework was evaluated using test images obtained from a building in operation. The experimental results show that the proposed framework provides a 3D thermal model that is useful and accurate in simulating building energy. It is expected that the 3D thermal model can be used for accurate energy simulation of existing buildings. In addition, the proposed framework can be applied in defect detection for buildings. Furthermore, this novel approach enhances infrared thermography using visible images.

Aug 1, 2013

By Pentti Niskanen

"The ventilation system of the Pyhasalmi Mine is described. The mine is located in an area where the annual atmospheric temperature may vary from +30°C to -30°C. Natural ventilation causes serious difficulties because the underground mine is connected by drifts and finger raises to the bottom of the 120 m-deep open pit.The natural ventilation tends to make the ventilation net unstable. The paper describes how the instability characteristics of the ventilation net can be studied and how they have been taken into account when automating the control of the ventilation. In addition, the software, hardware and costs of the system are described. The system consists of 12 automated ventilation doors, two mine fans, 8 elements for sensing the air flow and temperatures, a control panel and a process computer."

Jan 1, 2014

By P Hofmeyr, D Pretorius

Iron ore, which is transported by rail from the iron ore mines at Sishen in the Northern Cape, to the Saldanha Iron Ore Terminal in the Western Cape, needs to be analysed while loading to be exported. Every shipment will be sampled and an average analysis of the ore will be produced which is required by the purchaser at the receiving port. On arrival at the iron ore terminal at Saldanha, the ore is tipped from the rail trucks onto conveyor belts to be either stockpiled or direct-loaded. The conveyor belts run under the sampling plant and the ore is sampled periodically by means of an automated cross-belt sampler. This is the first iron ore port sampling facility in which the automated sampler is situated above the conveyor belts and not adjacent to them. A portion of the primary sample taken off the belt is moved to the dedicated sampling laboratory situated behind the cross-belt sampler and over the conveyor belt lines. The sample is split in the laboratory, one split being used for moisture and particle size determination and the other part is dried and then analysed by means of X-ray fluorescence spectrometry (XRFS) on fusion beads for major and minor elements. Particular care is taken to obtain high quality data for penalty elements.This sampling plant is completely automated and from the primary cross-belt sampler to final analysis by XRFS no manual steps are involved. This has meant that some processes are used which are suitable for automation and are ISO compliant but not necessarily ISO-certificated. The ISO manuals were developed with manual laboratory processes in mind. Precautions are also taken to maintain the integrity and representativity of the samples. This paper is a case study?describing?the automated sampling systems used at the Saldanha Iron Ore Terminal sampling facility and laboratory from conveyor belt to analysis.CITATION:Hofmeyr, P and Pretorius, D, 2012. Automated sampling of iron ore for analysis at the Saldanha Iron Ore Terminal in South Africa, in Proceedings Sampling 2012 , pp 25-32 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 21, 2012

By J. M. Rebstock

Recent re-classification of crystalline silica as a potential human carcinogen has resulted in a new limit of 0.1% free silica in bulk powdered minerals. Detection of silica at this level can be expected to severely challenge or exceed the capabilities of existing protocols for x-ray diffraction, the traditional method for free silica determination. Automated SEH-EOS analysis provides an attractive alternative method, with direct analysis of individual particles for the determination of the concentration of free silica, and a direct measurement of silica particle sizes. This paper will discuss automated SEH analytical procedures, sample preparation, and statistical considerations.

Jan 1, 1990

By J. Gallegos, R. Faber, T. Cox

"An innovative method to reduce acid rock drainage (ARD) and sediment loading of a recreational lake was used in the Red River watershed in northern New Mexico. The Red River drains a mining district that contains multiple naturally occurring hydrothermal alteration zones that release ARD and sediment to the river during episodic summer rain storms. A lake is near the mouth of the watershed and is filled with water from the river through a sluice gate and diversion. An automated actuator was installed on the sluice gate to close when the river is impacted by high-suspended sediment. Water quality probes were installed at the sluice gate to monitor the river water for turbidity, specific conductivity and water depth. If high turbidity is measured, the sluice gate closes automatically. Remote access is setup with a computer view screen to review the real-time system status. Once the turbidity drops below a threshold, the sluice gate is reopened remotely. The automated sluice gate has successfully reduced the amount of ARD and suspended sediment entering the lake. This reduction has resulted in an improved aquatic habitat for the fishery and benthic macroinvertebrate community. BACKGROUND The Red River is located within the Sangre De Cristo Mountain Range in northern New Mexico. The river drains an area of approximately 190 square miles and spans elevations from 6,600 feet at its confluence with the Rio Grande to its headwaters near 12,000 feet (Figure 1). The river generally flows to the west along most if its length.The Red River watershed includes several hydrothermal alteration zones. The alteration zones were created by intrusion of high-silica granites and subvolcanic porphyries, with associated hydrothermal fluids, into the volcanic rocks of the Questa Caldera. The hydrothermal alteration is also responsible for the molybdenum deposits in the area. Rapid chemical weathering and physical erosion of pyrite-rich hydrothermally altered rocks has resulted in the formation of alteration scars. The alteration scars are characterized by steep, erodible slopes with little vegetation and incised gullies. Debris fans from the drainages containing active alteration scars have formed and typically consist of poorly sorted sand and gravel that is distinctly pale yellow in color. Some of the more prominent scars are located in the Hansen, Straight and Hottentot Creek drainages downstream of the town of Red River."

Jan 1, 2018

By M. K. Elmouttie, G. V. Poropat

Mapping of exposed rock walls provides data on geological features such as joints, bedding planes, faults etc critical to the economics and the safety of mine operations. Traditional, manual methods of mapping can be time consuming, error prone and limited in their coverage. New methods have been developed to map exposed faces remotely and safely however the benefits of these methods are only fully realised when exposed structures can be quickly and easily mapped using automated methods. This paper describes the application of an automated method of analysis of 3D images that provides users with the capacity to map exposed structures automatically. The method is based on the use of vector classification methods used in some neural network systems and provides rapid and reliable identification of exposed planes. CSIRO Exploration and Mining is applying these methods to 3D images for a range of applications from pit mapping to machine automation.

Jan 1, 2006

By William Gray

It has been ten years since the Mine Safety and Health Administration (MSHA) promulgated a safety standard requiring the use of Automated Temporary Roof Support (ATRS) systems in underground coal mines. The use of ATRS systems with roof bolting machines and continuous miners equipped with integral bolters has all but eliminated fatal roof fall accidents associated with manually setting temporary roof support. The last ten years have seen an evolution of the ATRS systems themselves and of MSHA&apos;s policy regarding ATRS systems. These changes are a response to operational and safety issues regarding ATRS systems often brought about by the ever-changing coal mining environment. As a result, MSHA&apos;s Technical Support personnel receive numerous inquiries from all segments of the coal mining industry on various ATRS topics. These requests for technical assistance range from an interpretation of a facet of the ATRS standard to an in-depth evaluation of a prototype ATRS system. This paper will address the aforementioned evolution of ATRS systems and will also summarize the factors MSHA Technical Support uses to evaluate these systems in the field. In addition, some of the more common misconceptions regarding the design, use, and regulatory requirements regarding ATRS systems will be covered.

Jan 1, 1998

By J M. F Clout

Geological, textural and mineralogical classification of iron ores is routinely conducted by mine and exploration geologists on reverse circulation percussion, blasthole cone and bulk samples for grade control, defining ore and waste, determining lump:fines ratio and predicting downstream processing characteristics. Classification is based on physical hardness, colour, streak and other visual characteristics. However, logging is generally restricted to the five to 20 per cent of chips above about 2 mm. This means that most of the sample is too fine to be reliably logged for anything but colour or streak and the textural types must be inferred from other information. A recently developed software package called æRecognitionÆ allows automated identification and classification of iron ore textural types and gangue on a particle basis in polished section down to 0.01 mm using processed digital images. It is not designed to be used as a routine logging tool, but is applicable where higher definition is required at the resource evaluation stage on selected percussion, drill core or bulk samples. æRecognitionÆ processes data obtained after optical image analysis of fine iron ore samples. It contains several parts, like æRecognitionÆ, æCompositionÆ, æLiberation by Total IronÆ, æLiberation by PhasesÆ and æStatisticsÆ, which allow vast and diverse information to be obtained about the iron ore samples being studied. Identification and classification of the textural type of each particle is performed according to the CSIRO-Hamersley Iron Ore Group Classification Scheme. The recognition procedure encompasses a good knowledge of different ore types and a logical knowledge tree, managing fuzzy boundary problems and the potential for a few different ore types in the same particle to be considered. This new technology introduces strict criteria to make the process of identifying particles more objective. Automated recognition standardises the identification procedure and significantly saves time. It enables users without a strong background in mineralogy to perform accurate texture identification. The æRecognitionÆ package has a modern user-friendly interface and Word compatible output. The combination of all the features mentioned makes the package a convenient tool for detailed studies of fine iron ores.

Jan 1, 2005