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By Shawn Healey, Ray Norcross

"Site IdentificationNew Britannia MineA 50/50 WX Gold Inc. - High River Gold Mines Ltd. Joint VentureTVX Gold Inc. is the OperatorLocationThe New Britannia Mine is located in the town of Snow Lake, Manitoba, which is situated between Flin Flon and Thompson, 420 miles north of Winnipeg.Brief Description of OperationNew Britannia Mine processes 2000 tonnes per day at an average grade of 4.5 g/t. Mill recoveries are currently 91 YO, accounting for forecast of 98,000 ounces for 1998.New Britannia Mine's mill complex incorporates conventional crushing, grinding and carbon-in-pulp technology. The design capacity of the New Britannia Mine mill is 1850 tonnes per day. The mill has processed upwards of 2300 tonnes per day, with no required upgrades.Gold recovery averaged 89.8% for 1997 compared to the planned 87% recovery expected from projected metallurgical test work. Year to date recovery mid December 1998 stands at 91.1 %Cash costs for the 1998 year to date were down to U.S. $221.49 per ounce, down 12% from the 3rd quarter of 1997. Milling costs for 1998 YTD were at Cdn. $9.38 per tonne and Cdn. $73.50 per ounce.Geology - (Orebody Description)The Snow Lake gold deposit is located within the Aphebian Flin Flon / Snow Lake Greenstone belt. This belt is composed of an assemblage of poly-deformed volcanosedimentary supercrustal sequences intruded by pre and sin tectonic ultra mafic and mafic intrusions and sin to post tectonic granitoid.The principal gold bearing rock at the New Britannia Mine is made up of quartzcarbonate material in sequence of basic and acidic volcanic rocks contained within a shear zone. The ore itself is gold associated with the sulphide mineral arsenopyrite and contains some pyrite, pyrotite, plus chalcopyrite. Proven and probable reserves at December 31, 1997 were at 4.04 million tonnes at 4.6 g/t and underground exploration continues to confirm the extension of the ore zones to depth."

Jan 1, 1999

By Frank W. Schmechel

The subsidence monitoring program at the Old Ben No. 24 Mine was planned in 1976 as part of the on- going demonstration of longwall mining. The construction and installation of the network of surface subsidence monuments was started in Play of 1976 and completed four weeks later after which an initial reference survey was made of all surface monuments. Mining of the first longwall panel started in September of 1976 and was completed in May of 1977. Mining of the second panel started in August of 1977 and is continuing at this time. The Automatic Data Acquisition System (ADAS), which is the subject of this paper, was installed over the second panel on March 29, 1978 near the panel center (Figure 1) and approximately 104 meters (370 feet) in front of the face position at that time. Mine No. 24 is located approximately 5 kilometers (3 miles) Northwest of Benton, Franklin County, Illinois. Coal is being mined from the Illinois (Herrin) No. 6 seam which is at a depth of about 189 meters (620 feet) at the site. The Herrin No. 6 is up to 2.7 meters (9 feet) thick in the mine but a constant thickness of 2.1 meters (7 feet) is being mined by the demonstration longwall with both roof and floor coal being left for stability. Although the seam is flat laying at the mine, it dips north- ward regionally. Topographically, the surface over the demonstration panels is essentially flat and low laying with several areas of standing water. The Rend Lake Dam (United States Army Corps of Engineers) is about 305 meters (1000 feet) north of the demonstration site.

Jan 1, 1979

By Moatassem Abdallah

Buildings in the United States account for 72% of electricity consumption, 40% of energy consumption, 13% of water consumption, 39% of carbon footprint, and 30% of waste output. In order to minimize these negative environmental impacts, many public and private owners are requesting that their buildings be more sustainable and certified under the widely known programs such as leadership in energy and environmental design for existing buildings (LEED-EB). To accomplish this, buildings are increasingly integrating green building measures including energy efficient lighting, motion sensors, thermal pane glass, geothermal heat pumps, EnergyStar rated HVAC systems, photovoltaic systems, and wind turbines. This research paper presents the development of an automated decision support system (DSS) that is designed to optimize the selection of green building measures which can be used to upgrade existing buildings. The developed DSS incorporates two optimization models that are capable of (i) minimizing the total upgrade costs required to accomplish a specified LEED-EB certification level such as silver or gold; and (ii) maximizing the number of accredited LEED-EB points within a specified budget of upgrade costs. The DSS is designed to identify a set of optimal upgrade decisions that accomplishes these two optimization objectives. An application example is used to illustrate the capabilities of the DSS and to validate its result.

Aug 1, 2013

By Magdy Ibrahim

Detailed as-built project schedules are necessary to close out construction projects, benchmarking, forecasting, dispute resolution, and improving cost estimates of future projects. Manual procedures for developments of as-built documentation is time consuming, involves numerous interfaces and human interventions. This paper presents computational framework that encompasses automated site data acquisition and generates schedule updates utilizing commercially available project scheduling software. The work is carried out collaboratively with a Hydro Quebec team. The site data is captured employing mobile computing using iPad® type computers and Wi-Fi. The information is directly compiled in a centralized database server. The synchronization tool is a bi-directional application and is used on servers to communicate with iPad® computers deployed onsite. The captured data is stored in Microsoft SQL® relation database that consists of 63 entities. Computer software application has been developed in Microsoft Visual Basic® (vb.net) environment for extracting the collected site data, linking the database to the as planned schedule, and generating the actual, also known as as-built schedule. The development can be utilized in automated progress reporting, evaluating future bids, generating master schedules and a wide range of efficient EVM applications.

Aug 1, 2013

By Juan J. Monsalve, AMAN SONI, ALEX PFREUNDSCHUH, Nino Ripepi

Ground control failures are one of the main causes of accidents in the underground stone mining industry. Some of the fundamental tools for rockfall hazard identification are related to rock mass characterization and geotechnical discontinuity mapping. Recent technological advances in these methods are related to remote sensing techniques and pointcloud processing software for automated discontinuity mapping. Remote sensing techniques, such as LiDAR and photogrammetry, generate multimillion-point clouds with millimetric precision, capturing the structure of the rock mass. The automated point-cloud processing tools offer alternative algorithm-based methods to characterize and map these discontinuities. However, their applicability is constrained by multiple factors, such as site-specific conditions of the rock mass and the parameters used within the mapping algorithms. This paper evaluates the performance of automated discontinuity extraction software compared with manual virtual discontinuity mapping. Sampling windows from laser-scanned sections in an underground limestone mine are defined and mapped using the Discontinuity Set Extractor (DSE) opensource software. Results from the virtual discontinuity software are compared with manually extracted fractures from I-Site based on reviewing orientation, trace length, spacing, number of extracted discontinuities, and processing time.

By Juan J. Monsalve, AMAN SONI, ALEX PFREUNDSCHUH, Nino Ripepi

Ground control failures are one of the main causes of accidents in the underground stone mining industry. Some of the fundamental tools for rockfall hazard identification are related to rock mass characterization and geotechnical discontinuity mapping. Recent technological advances in these methods are related to remote sensing techniques and point cloud processing software for automated discontinuity mapping. Remote sensing techniques, such as LiDAR and photogrammetry, generate multimillion point clouds with millimetric precision, capturing the structure of the rock mass. The automated point cloud processing tools offer alternative algorithm-based methods to characterize and map these discontinuities. However, their applicability is constrained by multiple factors such as site specific conditions of the rock mass and the parameters used within the mapping algorithms. This paper evaluates the performance of automated discontinuity extraction software compared with manual virtual discontinuity mapping. Sampling windows from laser-scanned sections in an underground limestone mine are defined and mapped using discontinuity set extractor (DSE). Results from the virtual discontinuity software are compared with manually extracted fractures from I-Site based on reviewing orientation, trace length, spacing, number of extracted discontinuities, and processing time. The analysis determined that the automated mapping algorithm was able to identify the same discontinuity sets that had been manually mapped. The automated mapping software mapped an excessive amount of smaller fractures, which caused the comparison of both mapping techniques to be unsuccessful in terms of trace length and spacing.

Mar 19, 2021

By J Välivaara

The mining industry will face numerous challenges over the next 10–15 years as new deposits are likely to be more remote and lower grade and existing deposits will be mined deeper. As a result, mines and mining contractors operating in deep-mine conditions will need to focus on the quality of drilling and blasting to minimise unnecessary waste rock excavation to keep costs at an acceptable level. In addition, increased demand for improved safety and operator ergonomics will set greater demands on original equipment manufacturers of mining equipment. Finally, difficulties finding a skilled and experienced workforce, particularly in remote mine locations, have already negatively impacted mines’ ability to achieve high productivity and low operating costs.This paper introduces techniques and shares practical experiences in increasing productivity and reducing the costs of excavation in underground face drilling. The paper uses Sandvik’s new DD422i automated mining jumbo as an example of the type of equipment needed to deliver the features and corresponding benefits for future mine development. Case studies using this equipment are presented to illustrate the points made in this paper.CITATION:Välivaara, J, 2016. Automated drilling features for improving productivity and reducing costs in underground development, in Proceedings Seventh International Conference and Exhibition on Mass Mining (MassMin 2016), pp 723–730 (The Australasian Institute of Mining and Metallurgy: Melbourne).

May 9, 2016

By Tao Cheng

Previous research and applications in construction resource optimization have focused on tracking the location of material and equipment. There is a lack of studies on automated monitoring of the interaction between workers and equipment for safety purposes. This paper presents a new approach for measuring the safety performance of construction personnel particularly when they work in very close proximity to moving equipment as well as static hazards such as chemical and flammable substances. A method of generating hazardous zones according to the geometric and kinematic characteristics of the considered hazard is introduced. The spatio-temporal relationships between the hazardous zones and workers? positioning data collected by real-time location sensing technology are automatically analyzed. This approach has been validated in a controlled test bed environment that simulates a construction site. Results indicate that worker?s safety performance of selected activities can be automatically and reliably measured using the developed approach. Furthermore, a heat map is generated for visualizing proximity related issues in the test bed using the computed results.

Aug 1, 2013

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