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By M Fimeri, R Williamson

Sample sizing in the iron ore industry requires significant manual effort to collect, transport, and sieve the samples as well as record, process and report the data. Efforts have been made to automate this process, which essentially emulate the manual process, except that a person is replaced by a robot. Even in these cells, the sieving and sizing operation consumes a significant proportion of robot time. The proposed doubling of production from AustraliaÆs iron ore mines over the next five years will place increasing pressure on sample sizing and interest is increasing in alternative automated methods. One such method is the adaptation of computer vision technology which has been successfully introduced into the mining industry in a range of applications including feed size distribution to SAG mills and oversize detection from screening stations. The limitation of this technology is that only the top surface is visible and this is used as an indicator of total size distribution. Obviously in a sample plant, where 100 per cent of the sample must be measured for acceptable quality assurance, this approach is unacceptable. In order to capture 100 per cent of the sample using computer vision technology a monolayer must be formed either by spreading the sample across a moving surface, such as a conveyor or vibrating platform, and passing this under a camera. This will become a æsurgingÆ load which presents specific problems for some types of computer vision systems, namely those relying on a 2D approach. In this paper a 3D computer vision technology will be described which overcomes the problems associated with measuring particle size in a monolayer and experimental results will be presented which demonstrate its effectiveness for lump and fine iron ore sample size measurement.

Jan 1, 2008

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. 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

By J Fisher, M Castro, A Hariyadi

The train haulage system being designed for PT Freeport Indonesia’s Grasberg Block Cave (GBC) will be located within the mine at an elevation of almost 3000 m above sea level on the west side of the island of Papua, Indonesia. The developing block cave is beneath the active Grasberg Open Pit and will transport 160 000 t of ore per day from multiple chute galleries to the underground crushing plants. The design entails 28 km of rail and 119 ore chutes, which will be brought online over the course of ten years.The train haulage system will be driverless and fully automated. Sequentially, the system includes remote controlled rock breakers at the top of the chute grizzlies, followed by remote controlled chute loading of the trains, then autonomous train haulage and autonomous unloading. An overhead catenary system (OCS) will power the locomotives, which are equipped with on-board batteries to drive through the loading and unloading sections. Service locomotives with drivers move material-laden freight cars in and out of the service shaft, destined for workshops, the magazine and batch plants. Service locomotives are also used for haulage level maintenance. Highly reliable and redundant control and communications systems are required to manage 12 trains in simultaneous operation.This paper provides an overview of the train haulage system’s technical complexities and the associated support systems interactions. The paper also highlights the project management issues and successes of this globally sourced project.CITATION:Hariyadi, A, Castro, M and Fisher, J, 2016. Automated train ore transport, in Proceedings Seventh International Conference and Exhibition on Mass Mining (MassMin 2016), pp 563–570 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2016

By M J. Thurley, L Lindqvist, D Degerfeldt, J Nyström, R Nordenskjöld

Rock breakage is a major component of all mining and mineral processing operations with the particle size distribution linked to productivity through the comminution chain. Optimisation and automatic control of comminution, material handling, and agglomeration processes is a complex task with large potential for gains in productivity, and energy efficiency. A key factor in realising these gains is the requirement for fully-automated online particle size distribution measurement to provide the necessary feedback and input for control. Moreover, to enable automatic control system it is necessary to provide a consistent, reliable size distribution measurement that avoids the significant errors resulting from under-sizing overlapped particles and over-sizing clusters of fine particles. Published literature and observation of commercial systems indicate a body of predominantly 2D photographic based particle size measurement systems that suffer from a number of significant errors except in the simplest case of a monolayer of particles under good illumination with limited colour variation in the material. In order to overcome these limitations a university and industry collaboration developed three-dimensional particle measurement (3DPM) between 2006 and 2012, based on 3D surface profile measurement of the visible material on conveyor. 3DPM avoids particle delineation errors due to variation in material colour and shadows, detects overlapping versus non-overlapping particles, and identifies areas of fine particles as fines and not large rocks. 3DPM measures: the visible material and calculates its particle size distribution, bulk volume, detects boulders, and conveyor belt fill factor in an automated consistent manner. Furthermore, 3DPM’s advanced algorithms allow observation of particle variation that would otherwise be undetected without the capacity to identify visible areas-of-fines and overlapped particles. Boliden Mines has installed 3DPM at three operations for measurement between the stockpile silo and grinding mill, and measurement after the primary crusher. Fragmentation measurements across multiple years of measurement are presented with some observations of plant behaviour. In the future 3DPM results will be incorporated into automatic control strategies for plant optimisation. 3DPM is used across a wide range of material types and applications that also includes; limestone aggregate for quality control in manufacturing, agglomerates for closed-loop automatic control in chemical production, and measurement of coke for size-based blending feed control to the blast furnace in steel production. CITATION:Thurley, M J, Degerfeldt, D, Nyström, J, Nordenskjöld, R and Lindqvist, L, 2018. Automated, online measurement of bulk material size distribution on conveyor using 3D profile imaging at Boliden Mines, in Proceedings 14th AusIMM Mill Operators' Conference 2018, pp 641–652 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 29, 2018

This paper presents a review of computer techniques for the automatic contouring of geological and geophysical data with output as interactive display on graph plotters or graphics terminals and passive display on automatic drafting tables. The advantages of the method of fitting a triangulated surface to randomly distributed data using an advancing front algorithm are described, as well as the technique for determining interpolated values for the production of contour line segments and a contour smoothing algorithm. This contouring method is employed by the Geological Survey of Queensland and is implemented as an interactive system. An alternative method ideally suited to randomly distributed data involves the use of piecewise parametric cubic splines. This method which is ideal for sharp variations in magnitude and areal extent typical of geophysical anomalies is discussed. The mathematics of surface interpolation using non-parametric splines and an explicit piecewise surface fitting technique are discussed. Curve tracing techniques which are suitable for automatic contouring are also presented and the inherent advantages of interactive contouring using on-line plotters and graphics terminals for previewing of displays are described.

Jan 1, 1977

By Denholm WT

Current control practice is reviewed for agglomeration processes, including pelletising, sintering and induration; and for smelting processes, including blast and reverberatory furnaces, flash smelting, the intensive bath smelting processes together with converting. The importance of sensors for on-line control and the status of mathematical modelling is discussed.Future progress in automatic control will require improved component specific sensors and the use of validated mathematical models running in parallel with the process. The possibilities in both these areas are reviewed in light of the trends towards more intensive smelting processes.

Jan 1, 1985

By Toro HCH, Von Borries GH

A brief description of the semi-autogenous grinding (SAG;) facilities of Compania Minera Disputada de Las Condes is given. A data-logging and computer system was connected to the plant inter facing the existing analog control system in a supervisory s, control philosophy. The development of a control straiov,v t,) maintain maximum power of the SAG mill atsubjected to process restrictions is shownThe present control scheme is discussed inalgorithm was designed based on correlations onLween vartaoles. Associated with this, a direct level of control was developed be, on classical control algorithms, process inter-active tuning has been included. Also, an algorithm to prevent overloading of the is discussed. Control scheme tests are presented in comparison t manual operator control under the same conditions. It is shown t the control strategy gives a more stable operation and a higher plant throughput.

Jan 1, 1985

By V Gau, L Overmeyer, M Kesting

Economically efficient mining processes can be significantly assisted by the implementation of sensor technologies for the detection of materials and boundary layers between materials inside the stratum. These sensors are meant to facilitate the machinery operator and illustrate furthermore the prerequisites in assisting tools towards fully automated mining equipment. Therefore, project æSensory Identification of Material Type and Detection of the InterfacesÆ (SIMT) aims at the integration of ground penetrating radar (GPR) and geoelectric sensor technology by endowing with them a bucket of a bucket wheel excavator. For this reason, a sensor bucket was developed and tested in the Inden Mine of RWE Power AG. The feasibility of integration and deployment of such sensor technology has been proven effective for the conditions of open cast mining. The main focus of current research lies on developing algorithms to analyse the acquired measurement data from the sensors to automatically detect layers and materials. A computer network receives the GPR and geoelectric measurement data as well as the positioning data of the sensor bucket. The positioning data mainly consists of GPS and encoder information, which is merged with the sensor data by using the UTC time stamp. With the aid of consecutive processes the relevant information will be extracted and provided to the user. The aim of SIMT is to replace material identification, traditionally carried out by the operator, by implementing a continuous operating interpretation system in mining equipment based on GPR and geoelectric sensor technology, resulting in more detailed information regarding the working face during an excavation. This detailed information provides an opportunity for efficient planning and controlling of selective mining of natural deposits, such as the process of lignite mining.

Sep 26, 2011

Geologists often classify ore textures on the basis of the origin of the rock in which they form and the grade of one or more minerals within the ore (Sinclair and Blackwell, 2002, pp 32-36).  Metallurgists, on the other hand, need to know how best to process the ore in order to extract the valuable minerals from it (Petruk, 2000). Geological classification has the following disadvantages:it requires the services of skilled economic geologists, of whom the supply has been dwindling for many years;it is subjective, depending on the perceptions of the individual geologists who make the classification; andit may relate only weakly to processing requirements of the ore. We describe methodology for automatic classification of ore textures from images of drill core. The images analysed are æclassifiedÆ images, in which a particular mineral (or mineral group) is assigned to each pixel. The new methodology is intended to:provide a quantitative and reproducible alternative to traditional geological texture classification,relate to process mineralogy of the ore, andimprove the ore-texture-related input to orebody domaining and geostatistical block models.

Jan 1, 2008

By M Wagner, H Assimi, F Neumann, C Garcia, B Koch

Run-of-Mine (ROM) stockpiles are the inventory of valuable materials extracted from the mine. Depending on the customer requests, a selective addition of ore from stockyards should be selected at the required tonnage. In the stockyard, stackers and reclaimers are the machines which load and unload ore, respectively. Currently, humans determine the reclaiming/stacking planning sequence in the stockyard by rules of thumb. However, this is a complex task subject to multiple operational constraints, such as where undesirable mineral properties should not exceed certain limits in a request. Human planning can lead to limited decision support and lower ability to consider the upcoming blends and requests. This kind of decision making can cause perturbations in the assumed profit and unexpected loss in practice. Therefore, an intelligent decision-maker and sequence planner would be highly valuable to automate stacking and reclaiming operations in practice. The benefits are reducing variability in decision-making and operation costs. This paper considers a stockyard with available mineral information in the stockpiles using load and dump locations from GPS data feeds. We present an optimisation problem to find a solution which results in reclaiming more ore in a shorter time. To solve the problem, we develop an automatic search strategy based on the greedy search algorithm independent of the type of machine used in reclaiming. The proposed method plans a sequence for stockyard recovery blend optimisation to meet multiple customer demands in a timeframe. Blend optimisation is subject to various constraints such as the elemental composition of the valuable materials and penalty elements. We present three case studies using EKA’s simulator, to fulfil two to four requests from four stockpiles. We compare the obtained results with a pilgrim step reclaiming heuristic and we show how our proposed search strategy outperforms the current strategy used in practice.

Nov 10, 2020

This paper describes a plant built at The Broken Hill Associated Smelters, Port Pirie to sample lead sinter automatically. As the plant is still in the commissioning stage results on the precision and accuracy of the sampling are not yet available, but some of the difficulties experienced during commissioning are discussed.

Jan 1, 1976

By Stone AM, Romensky G

The requirement for economic operation of unit trains carrying bulk materials has dictated that rapid and accurate bulk loading methods be provided. The train loading station at Phosphate Hill, built for Queensland Phosphate Ltd. to load rock phosphate, provides this facility and whilst the concept used is not unique, it contains a number of novel features that are considered to advance the "state of the art'' in this field. This paper briefly reviews some alternative concepts evaluated, and describes the design and operation of the scheme ultimately selected as being most appropriate to the project requirements. it is one which utilises a variable speed belt feeder whose speed is controlled in proportion to the weight rate of material moving on the belt as measured against a set point

Jan 1, 1978

Nippon Telegraph and Telephone Corporation (NTT) developed a new construction method (the M-2 method) that could drive a long, curved small-diameter tunnel (4>1.2 m) without human labor. This method employs the cast-in-place lining system, using quick-hardening resin mortar, so that it can greatly increase the driving distance and execute both long distance driving (longer than 500 m) and curved driving with a radius of curvature of 200 m. Furthermore, the central control system with a mini-computer in a vertical shaft enables all work in a small-diameter tunnel, i.e., excavation, lining, and transportation of excavated soil and materials, without human labor. NTT conducted several field tests and a Practical Application Test (P.A.T.) under a public road bearing great traffic. Good results were obtained and the practicability of this method was demonstrated. Therefore, from now on, NTT will apply this ii-2 method to drive telecommunication cable tunnels in urban areas. This method will also be applicable to constructing public tunnel facilities, such as for water, sewage, electricity and gas.

Jan 1, 1987

By M D. Griffith

Oct 12, 2022

By S Mundell, J Armstrong, M Evans

"Automation is a common goal within the coal industry for reasons such as efficiency, reliability and sustainability. However, it requires standards and frameworks so business systems can communicate effectively. Automation of sample analysis processes has been difficult to establish due to a lack of direct business system communication between commercial laboratories and mining companies. This has resulted in manual procedures that have contributed to problems relating to analysis instructions, sample identification, results formats and visibility of status.These problems result in loss of data and confidence in data validity, loss of process efficiency and inability to react to issues. An Australian Coal Association Research Program project (Evans, Armstrong and Arboleda, 2014) has addressed these issues through the Coal Quality Data Exchange methodology for direct business system communication between coalminers and commercial laboratories to optimise the transfer of coal quality data.The benefits to the coalminer of the framework are:increased clarity and auditability of what is being sent to the laboratory and what was requestedreduced potential for error introduced through manual transcription tasksincreased speed of loading of analytical results to the customer Geoscientific Information Management Systemimproved turnaround time for analytical resultsincreased knowledge about what took place in the laboratory with respect to the determination of the analytical resultsincreased visibility of the status of a ‘work order’. The benefits to the technology companies and commercial laboratories is a common framework on which to build a sustainable solution that gets away from the multitude of formats catered for today and time consuming manual processes. The common framework significantly advances the future possibilities for the automation of sampling and analysis processes in a production environment.CITATION:Armstrong, J, Mundell, S and Evans, M, 2014. Automating communications between laboratories and mines – a case from the coal industry, in Proceedings Ninth International Mining Geology Conference 2014 , pp 351–360 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Aug 18, 2014

By B Delaney

For worker safety, mining companies are required to stop production and inspect hoist ropes. Visual inspection is generally done daily and EM inspection occurs every three to four months. During visual inspection, rope speed is generally reduced so an inspector can look for problems. In EM testing the LMA and LF traces are printed on a paper strip chart and a skilled operator interprets these traces. Mining companies only find large defects during visual inspection and are sometimes concerned about the content of EM trace information. This paper will present research outcomes that show how muck can be hoisted while performing a complete visual rope inspection at full speed. Other research results will show that digital signal processing can increase the amount of information available to the EM rope inspector. The research was funded by Inco, C-CORE, three AMIRA International sponsors and six sponsors from the Canadian Deep Mining Research Consortium (DMRC). The research will be commercialised in 2005.

Jan 1, 2005

By Smith P

The past 20 years have seen the replacement of hydraulic control of longwall mining systems by the neater. smaller and better controlled electronic units.Early problems of moisture and other effects on reliability were overcome to see electronically controlled supports chosen for Corrimal Colliery ten years ago. Lessons from Corrimal and elsewhere, with following improvements and sophistication led to wider use as exemplified by Meco and other electronically controlled supports used in more recent installations in New South Wales, Queensland, USA and Czechoslovakia of the total of over 80 electronically controlled support installations worldwide in the past decade. Present work is toward a fully "integrated face" of British Coal by 1993, incorporating the Meco automatic face straightening system already due for practical use in the UK later this year. However the manless face still appears to be some way off although the present minimum crews and close monitoring, including early warning, are promising stages.

Jan 1, 1991

By I Sherrell, R Jain, P Jansson

With the depleting iron reserves and difficult market conditions, precision in separation efficiency is of utmost importance. Classical local control options are predominant in the industry, but their inability to adjust to resolve application problems of interest has furthered the need of developing and implementing continuous control methodologies.This paper highlights the recent development in control of Outotec SLon® vertically pulsating high gradient magnetic separator (VPHGMS) including programmable logic controllers (PLC) coupled with distributed control system (DCS), on-site human–machine interface (HMI) control panel, advanced process control, continuous online sampling using Courier® 8 and additional modernisation packages including level control and cooling monitoring. These modern control options result in improved efficiencies, promote safer operation and at the same time reduce operational manpower needs.CITATION:Jain, R, Sherrell, I and Jansson, P, 2017. Automation for efficient separation with the Outotec SLon® vertically pulsating high gradient magnetic separator, in Proceedings Iron Ore 2017, pp 211–214 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Jul 24, 2017

By Ulvelin K, Antila K

Large scale cut and fill mining in narrow silver-lead-zinc orebodies began at Mount Isa in 1964. Initially each orebody was one stope and access was via raises from the level above. Upholing was the principal mining method, although flatbacking was employed where ground conditions were more difficult. Developments since have included access via footwall inclines and connection of all stopes with major crosscuts. Flatbacking is the principal method. The most recent cut and fill operation is now fully mechanised using drilling jumbos, rockbolting jumbos and load-haul-dump units. Improved ground support and drilling and blasting practices have enhanced safety, recovery and productivity in all cut and fill operations.

Jan 1, 1988