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By W. L. Hollinshead

For more effective and cost-saving production in tunnels, the machinery used on construction sites in the future will be equipped with guidance systems combined with working-procedure management systems. This paper describes sensors for these systems and vari¬ous system configurations. A project is described that uses a computerized guidance system on an underground mining machine for guidance and profile control.

Jan 1, 2000

By W. L. Hollinshead

For more effective and cost saving production in tunnels, the machinery used on construction sites will be equipped with guidance systems combined with working procedure management systems. This paper describes sensors for these systems and various system configurations. A project is described which uses a computerized guidance system on an underground mining machine for guidance and profile control.

Jan 1, 1999

By A Melkumyan, M Balamurali

Geological domains describe the mineralisation state and stratigraphic location of different geological regions of mines. They play a very important role at the geological modelling stage as weight percentage of chemical elements information within each geological domain is assumed to be correlated while information coming from different geological domains is considered uncorrelated. Having correct domain assignments to both the chemical assays and the 3D space of modelling is critical for building a reliable geological model of the mine.As standard practice significant effort is invested into the interpretation of the deposit and identification of the geological domains for the chemical assays and the 3D geological space. Despite these efforts, there are some chemical assays with ambiguous geological domain where the exploration assay domain and the block domain do not match. Incorrectly including a sample in the wrong domain can cause a large change in the predicted weight percentage of chemical elements estimation for that block. Therefore, the major challenge of grouping the spatially correlating weight percentage of chemical elements is how to determine which of these domains best fits these misclassified samples.This work proposes machine learning based autonomous technique for identifying to which geological domain (the exploration assay domain or the block domain) the misclassified sample belongs. The proposed methodology is based on Gaussian Process (GP) classification. The GP machine learning approach consists of training and inference stages. At the training stage the GP automatically learns the properties of different geological domains using the chemical assays with unambiguous domain assignment. Then, at the inference stage the GP makes predictions for the geological domains of the assays with ambiguous initial domain assignment.We tested the proposed technique by conducting a case study for an iron ore deposit located in Western Australia. The results demonstrate that the application of the proposed GP technique removes statistically significant deviations in the assay values in many regions: mineralised ore region, unmineralised region, highly weathered region and intrusive material that is highly variable. In this case study the proposed methodology autonomously identified the geological domains for more than 50 per cent of samples which are initially ambiguously classified. For the majority of the assays the GP predicted domain agrees with the geological domain assigned by the exploration assay.CITATION:Balamurali, M and Melkumyan, A, 2014. Automated identification of geological domains for exploration assays with ambiguous initial domain assignment in an iron ore deposit, in Proceedings Ninth International Mining Geology Conference 2014 , pp 99–106 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By Garland Likins

Where soil conditions are favorable, augercast piles have significant economic advantages, but they also have some uncertainty due to the in construction methods. To confirm structural integrity, static testing can be performed on a small sample of piles. Other Non-Destructive Evaluation methods like Pulse Echo are frequently specified for a large percentage of the remaining production piles. However, such NDE methods require testing the pile after the grout/concrete has hardened. If problems are found, then the repair or replacement can be relatively expensive. The confidence in the quality of these piles can be improved by automatically monitoring the grout pumped as a function of depth during the grouting phase of installation. If a low grout volume is detected, the pile can be redrilled and regrouted immediately while the piling rig is still in place and the grout still fluid. This considerably reduces remedial costs. To be effective, such installation monitors must accurately determine both grout volume and depth during installation and be rugged simple to operate. Such an equipment can be of great help to the installation crews. The assurance gained may reduce the need for subsequent NDE tests. The quality of inspection of driven piles depends heavily on the inspection personnel. While inspection is critical in a good installation, it is sometimes assigned a low priority. Inspection personnel in many cases are technicians with little pile experience. They may not understand the project needs or even how the pile driving equipment works. The task is often monotonous and any distraction makes accurate record keeping difficult. In some cases inspection is totally ignored for lack of qualified personnel. Electronic systems can automatically and accurately monitor driven pile installations and include documentation of certain hammer performance parameters. This paper describes equipment available and routinely in use for automated monitoring of both augercast and driven piles and demonstrates applications on typical construction sites. The paper also discusses benefits and limitations of the alternative NDE tests. KEYWORDS: Augercast Piles, Piles, Installation Monitoring, Pulse Echo Method, Integrity Testing

Jan 1, 1999

By P Valenzuela

Joint mapping is a fundamental input for rock mass characterisation and slope stability analysis. The usual way to do it is using a compass in the field or digitising structures on a screen, with a software package.In this paper a method to identify and map joints automatically along a rock face is presented; it is called the Concentric Shells (CS) algorithm. The method scans a point cloud sequentially, tests if selected points are ‘true pivots’ within an inner shell, and then it searches for points inside a wider sphere (outer shell).The algorithm, developed by the author, was applied in real data. It reproduces the main features obtained from conventional (compass) and digital mapping (software package). Execution times are approximately 45 seconds for two point sets holding of 3.1 million points. Obtaining the same results via digital mapping takes approximately 3–4 working days.Key advantages of this method are: significant time reductions; elimination of mapping bias; and the ability to manage very large data sets (>2 million points) without the need of scanning the cloud on the screen. These advantages make this method an attractive tool for engineers and geologists wanting to increase productivity.CITATION:Valenzuela, P, 2017. Automated joint mapping using the concentric shells algorithm, in Proceedings Tenth International Mining Geology Conference 2017, pp 257–262 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Sep 20, 2017

By R Grobler, D Burger, L Alberts

The current climate in the mining industry is allowing mining companies to further broaden their views and investigate technologies to improve the safety, efficiency and cost-effectiveness of their operations. Furthermore, underground mine environments will become more demanding for mining equipment and personnel as orebodies become deeper in weaker ground conditions with more extreme environmental conditions. Loading and hauling can represent significant components of the production cycle of an underground mine and automation of these activities can offer considerable benefits. Sandvik has accumulated a long history and experience in loading and hauling automation in underground mining. Since the late 1980s Sandvik has actively participated in several major research and development automation programs leading to the commencement of the development of an integrated system for semiautomated loading in 1999. Development work was later conducted to expand the capabilities of the system for automated hauling during 2001 and the AutoMine« system became commercially available. The first delivery of the AutoMine« system was completed in August 2004 in South America, where the system continues to operate in a full-scale production environment and is being expanded as the production area enlarges. Further systems have been delivered and are operational in North America, Africa and Europe. This paper focuses on the AutoMine« system deployed in Block 4 at De Beers Finsch Mine in South Africa. An overview of the mine and the process used to acquire the system and the key drivers which led to the selection of an automated solution are described. An overview of the initial system installation, subsequent expansions and future plans are presented. This is followed by a summary of the implementation and operational experiences associated with automated underground operations. The paper concludes by summarising the benefits that have been realised.

Jan 1, 2008

By Kanaan Hanna

A joint research program between the U.S. Department of the Interior's Bureau of Mines and Cyprus-Yampa Valley Coal Company is being conducted at the Foidel Creek Mine, Oak Creek, Colorado. This program goal is to study the effects of state-of-the-art, high-speed, automated longwall mining on health and safety, and primarily, ground stability under various geological conditions. The Bureau installed an automated data monitoring system, known as the Ground Control Management System (GCMS), to monitor in real-time the effect of rapid mining on pillar and face loading, stress redistribution in and around the longwall panel, and caving characteristics of the roof. The Bureau's GCMS, combined with the company's existing monitoring systems, which include environmental monitoring, a computer programmable conveyor belt system, and gamma ray roof control thickness indicators, has been effectively used to improve safety at the face, increase productivity, and reduce production costs.

Jan 1, 1991

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

For years traditional optical microscopic techniques have been used successfully to carry out mineralogical studies on processing products. Essential information could be obtained by supplementing microscopic data with X-ray powder diffraction data, chemical analyses, etc. However, most of the time the mineralogists working on plant related issues, would supply qualitative information to the metallurgists, due to quantification not being possible in the available time. Since the late-80s, the use of semi-automated to automated techniques for mineral quantification has impacted positively on the use of mineralogy for optimising processing plants. Rustenburg Platinum Mines (now Anglo Platinum) were the first mining company to purchase a Qem*Sem in 1987. With the success achieved in quantifying the minerals in the concentrator streams of the Rustenburg Platinum operations, a second instrument was purchased soon after. These instruments have proven invaluable tools in understanding the flotation behaviour of the sulfide and gangue minerals in the various reefs of the Bushveld. Restrictions in the resolution of these earlier instruments, as well as the time involved in searching for and correctly identifying the fine-grained platinum-group minerals (PGM), meant that these investigations focused on the deportment of the more abundant base metal sulfides, rather than on the actual PGM. The Mineral Liberation Analyser (MLA), which became available in the late 1990s, was well suited to detect and analyse minerals occurring in trace amounts such as the PGM. Anglo Platinum was the first mining company to purchase such an instrument and now has fourteen systems operating at the AR Crown Mines site. One of the applications of these systems involves the study of feeds, concentrates and tailings from the various concentrators on a monthly basis. These routine investigations provide information on a variety of mineralogical parameters, including liberation, association, and grain size. Results are used to emphasise areas for improvement, and specifically underline those areas where improvements will have the most impact on recovery. After new or different technologies have been implemented, mineralogical characterisation of the different process streams is an essential component in the assessment of the impact of these changes on flotation performance. In addition, the knowledge is databased for future reference to draw trends across the various concentrators around the Bushveld complex, and is also used for comparative studies when plants experience high losses to tailings. Due to the success of these investigations the question was posed whether it was possible to obtain data on a daily basis, as compositing samples could hide the impact of daily events. Although the instruments currently used are suitable for a research environment, these are not ideal for mine-site implementation. For that reason Anglo Platinum, together with FEI embarked on a development program to develop a system that can be implemented on-site to measure the important mineralogical characteristics on a daily basis. Important requirements for such a system include time-to-data, ease of use and regular quality control. Highlighting some results from concentrator studies, the presentation will review the progress on the development of automated mineralogical techniques for fast, automated mineral measurements. This is an abstract only. No full paper was prepared for this abstract.

Sep 13, 2010

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 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 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 F. M. Ramadhan, M. R. Pratama

Monitoring open-pit mine road conditions has become very critical nowadays. There are several benefits to in conducting research on this field such as opportunity to improve truck’s speed which directly influences truck’s productivity. This research aims to provide a semi real-time, and sensors-based automatic road damage detector that predicts the road quality through road damage exact location tracing, road damages auto-classification, and real-time instruction in the form of work order format to mining road maintenance, and repair authorities through mobile apps and maintenance unit’s in-cabin display. It will also provide the maintenance/repair activity performance evaluation via integrated dashboards. The artificial neural network algorithm is applied during the process of data training regarding classifying road damages and severities which resulted in a valid model. The road damage classification model has a precision level of 80.5% in predicting whether the road is damaged or not. Using this approach, we are expecting to visualise a road quality map of all active roads on mine site.

Sep 1, 2021

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

By Thierry Bernard

New technology to automatically design a blast based on autonomous drone. The process of flying a drone, calculating the 3D cloud of points, generating the critical face profiles and placing holes automatically according to burden specification becomes fully automatic. A nice time saving with more efficiency

Feb 1, 2020

By F. Sundqvist, B. Skawina, J. Greberg, A. Salama, M. Astrand, P. Ekbeck

Today’s mining operations require fast reporting and rapid rescheduling based on updated information. An automatic mine scheduling system could not only quickly reschedule but also propose alternative solutions. To avoid the financial and physical risks associated with testing such a system directly in operation, it could be first evaluated via discrete event simulation models. This would offer a safe environment to evaluate different operating rules and algorithms. In this study, this is achieved by integrating automatic scheduling software with a discrete event simulation model.

Jun 1, 2021

By CK Tsang, Jack Muir, Dharman Gersch, Joshua Barry

Correct face pressure is critical to safe operation of a closed face TBM. If inadequate face pressure is applied, this will lead to excessive ground movement, and may result in collapse of the tunnel face. Face pressure calculations are performed manually every few meters along the tunnel alignment. With the application of a 3D ground model, ground profile information can be extracted for automatic computation. This will significantly improve the efficiency and accuracy and is adaptable to changes in design parameters. This paper will discuss the development of automatic computation techniques in extracting information from a 3D ground model.

Jun 13, 2021