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By Simon Chiartano

A global reflection on the design of blast furnace main runner was investigated in this paper. TRB Company used its skills and expertise to understand what the best option for this sensitive component is, including some innovative tools: intelligent block design for safety lining, thermal & thermomechanical numerical simulation, immersive measurement by thermocouples, IR thermal camera, 3D laser scanner.

Oct 1, 2019

By P. J. Rowsell, M. D. Waller

Paper presented at a meeting on: Artificial intelligence in the minerals sector, held in Nottingham, UK, 20 April 1993. The applications of artificial intelligence systems in the upstream petroleum industry are reviewed. Particular emphasis is placed on current and potential applications in drilling engineering. Several recent advances in drilling technology have led to a large increase in the quality and volume of data available. This combined with the escalating cost, particularly of off-shore operations, is testing the traditional reliance on the skill and judgement of rig operators. AI systems offer enormous scope in enhancing and aiding the performance of these operations

Apr 1, 1994

By Jacek Kolacz

A new sensor based sorting system related to complex image analysis has been developed at Comex AS - Norway. It makes it possible to separate different mineral particles regarding their color, shape, texture, size, density and indirectly their composition. The sorting system has been successfully tested and applied for sorting minerals providing high separation efficiency in the range of 95-99.9 %. The main advantage of this system is connected with its universality where many material parameters are analyzed in the same processing unit by a single passage.

Sep 1, 2012

By Arman Hazrathosseini, Ali Moradi Afrapoli

Fleet management systems (FMSs), as a pivotal part of any surface mining operation, need to evolve from conventional to intelligent systems because of both Mining 4.0 requirements and some shortcomings inherent in conventional methods. However, this novel transformation needs to be investigated technically and strategically. To this end, previously published research works on intelligent FMSs are explored to track the latest status of these third-generation frameworks within the surface mining context. Their underlying models are then compared in terms of five categories of allocation and dispatching features to pinpoint the technical gaps ignored. Having drawn the future lines of research, the present work then leverages the popular SWOT analysis method to outline the strengths, weaknesses, opportunities, and threats associated with the advent of these intelligent FMSs in mines of future. By and large, the analysis indicates that advantages outweigh disadvantages. Solutions are offered to address the existing weaknesses and threats.

Apr 1, 2024

By Arman Hazrathosseini, Ali Moradi Afrapoli

Fleet management systems (FMSs) as the pivotal part of any surface mining operation find it essential to evolve from conventional into intelligent systems because of both Mining 4.0 requirements and some shortcomings inherent in conventional methods. However, this novel transformation needs to be investigated technically and strategically. To this end, the previously published research works on intelligent FMSs are explored to track the latest status of these third generation frameworks within the surface mining context. Following that, their underlying models are compared in terms of five categories of allocation and dispatching features to pinpoint the technical gaps ignored. Having drawn the future lines of research, the present article then leverages the popular SWOT analysis method to outline the strengths, weaknesses, opportunities, and threats associated with the advent of these intelligent FMSs in mines of future. By and large, the analysis indicates that advantages outweigh disadvantages. Solutions are offered to address the existing weaknesses and threats.

Nov 10, 2023

By David Brown, Dirk van Dyk

Horizontal rotating mills are being used all over the world associated with different mineral and power generation industries. David Brown South Africa, with over 140 years of experience in gear manufacture and design, has been supplying these industries with innovative designs at exceptional quality. The gearing systems associated with these industries are challenged daily with operating conditions with are not always fully understood. Failures are therefore experienced, over time in the industry, which can therefore not always be fully explained. David Brown South Africa has developed a gear monitoring system, the Intelligent Gearing System, in association with Transmission Dynamics (UK), in order to monitor and analyze these operating conditions in real time. The system has been designed on the principles of Six Sigma, incorporating Design for Six Sigma. The purpose with this system design is to monitor the operating conditions on the pinion, record the information and analyze the data in relation to the rate of fatigue damage to the girth gear and pinion. This is done in real time and unattended. The output from the Intelligent Gearing System can be fed back into the operating system of the mill user, in order to display an alarm for operating conditions exceeding the design criteria as well as information on the rate of fatigue damage due to these operating conditions. When the mill operating conditions are better understood, and the effect on the fatigue life of the mill gearing components, mill users can forecast critical spare holding levels with an increased accuracy. The Intelligent Gearing System also allows early actions to remove reasons for system overloads.

Jan 1, 2007

By D. Van Dyk

Horizontal rotating mills are being used all over the world in different mineral and power generation industries. David Brown South Africa, with over 140 years of experience in gear manufacture and design, has been supplying these industries with innovative designs at exceptional quality. The gearing systems associated with these industries are challenged daily with operating conditions that are not always fully understood. Failures are therefore experienced, over time in the industry, which cannot always be fully explained. David Brown South Africa has developed a gear monitoring system, the Intelligent Gearing System, in association with Transmission Dynamics (UK), in order to monitor and analyse these operating conditions in real time. The system has been designed on the principles of Six Sigma, incorporating Design for Six Sigma. The purpose with this system design is to monitor the operating conditions on the pinion, record the information and analyse the data in relation to the rate of fatigue damage to the girth gear and pinion. This is done in real time and unattended. The output from the Intelligent Gearing System can be fed back into the operating system of the mill user, in order to display an alarm for operating conditions exceeding the design criteria as well as information on the rate of fatigue damage due to these operating conditions. When the mill operating and the effect on the fatigue life of the mill gearing components, conditions are better understood, mill users can forecast critical spare holding levels with an increased accuracy. The Intelligent Gearing System also allows early actions to remove reasons for system overloads.

Jan 1, 2006

By K. C. Tran

This paper reviews the advancement of measurement technologies for the control of raw materials processes in the basic industries. The combination of digital technology and on line spectroscopy enables the development of intelligent instruments for composition and particle size analyses in real- time high- frequency control conditions. In many industries, the applications result in productivity improvement and energy savings. Plant specific examples include operating experience and benefits realized in sorting, blending and beneficiation processes. Instruments of the future not only measure specific parameters of the process and monitor its own health combined with self-corrective mechanics but also acts with intelligence to effect the quality of the process or regulate the primary apparatus.

Jan 1, 2001

By D. Parks, A. Miller, M. McNinch, R. Jacksha, H. Nickerson

Each year hundreds of mine workers are involved in machinery-related accidents. Many of these accidents involve inadequate or improper use of lockout/tagout (LOTO) procedures. To mitigate the occurrence of these accidents, new safety methods are needed to monitor access to hazardous areas around operating machinery, improve documentation/monitoring of maintenance that requires shutdown of the machinery, and prevent unexpected startup or movement during machine maintenance activities. The National Institute for Occupational Safety and Health (NIOSH) is currently researching the application of Internet of Things (IoT) technologies to provide intelligent machine monitoring as part of a comprehensive LOTO program. This paper introduces NIOSH’s implementation of an IoT-based intelligent machine monitoring system to improve safety during operation and maintenance at a concrete batch plant. INTRODUCTION Of the hundreds of machinery-related accidents occurring every year in the mining industry, incidents involving stationary machinery at surface mines continue to be amongst the most frequent [1]. A National Institute for Occupational Safety and Health (NIOSH) study showed that the majority of fatal accidents involving stationary machinery at surface mines occurred at sand and gravel (38%) and stone (26%) operations. Of these accidents, entanglement in conveyor components were the most common cause of fatal accidents (48%) [2]. The same study stated that one-third of these accidents involved improper lockout/tagout (LOTO) procedures as a contributing factor. The U.S. Mine Safety and Health Administration (MSHA) acknowledged this problem, stating in a recent request for information (RFI) [3]: “Since 2007, there have been 17 fatalities related to working near or around belt conveyors, of which 76 percent were related to miners becoming entangled in belt drives, belt rollers, and discharge points. Factors that contribute to entanglement hazards include inadequate or missing guards, inadequate or an insufficient number of crossovers in strategic locations, and/or inappropriate lock out/tag out procedures. Systems that can sense a miner's presence in hazardous locations; ensure that machine guards are properly secured in place; and/or ensure machines are properly locked out and tagged out during maintenance would reduce fatalities [3].” In response to this problem, NIOSH’s Spokane Mining Research Division (SMRD) is exploring the potential application of Internet of Things (IoT) technologies to provide cost-effective intelligent machine monitoring systems for improved worker safety [4, 5]. SMRD partnered with Central Pre-mix CRH Company (Central Pre-mix) to develop and install a proof-of-concept wireless IoT solution to monitor machinery and conveyors during operation and maintenance. The primary goals of the system were to provide real-time monitoring of access points and facilitate the planning and execution of LOTO procedures

Jan 1, 2019

By M. J. Scoble, H. L. Francis, D. F. Salter, G. R. Baiden

Intelligent ore delineation refers to the ability reliably to characterize the geological setting of a mineralized body and its grade distribution. This necessitates using all available geological information in a timely and efficient manner, such that effective geological control is achieved. The importance of geological control is paramount to improving the efficiency and competitiveness of underground mines. As a result, the development of new geosensing tools designed to provide more reliable and timely information should be a priority. However, as the sensing tools advance then so, too, must the decision support system in order to allow the full benefits of these tools to be achieved. One potential system considered able to provide this architecture is ’true 3D-GIS’ (Geographical Information System). GIS promises to provide a seamless data flow and to connect information currently unavailable to the underground mine operations by bringing together previously disparate and spatial data sets in a visually effective and timely way. This paper considers the potential revolution GIS offers over the flow and use of data in mining by focusing on the integration of geosensing data and GIS to facilitate intelligent ore delineation.

Jan 1, 2000

By Satyam Tiwari, Sarat Kumar Das

Tailings from mines and industries impose danger to the environment as evidenced by the recent failures of tailing storage dams. The tailings are mostly non-plastic with silt-size particles, but their behavior is largely dependent on the extreme void ratios of the material. Hence, the critical state provides an appropriate perspective in explaining the behavior of these geomaterials. Based on a comprehensive dataset of non-plastic tailings and non-plastic soils, an attempt has been made here to correlate critical state parameters to extreme void ratios and stress parameters. A hybrid algorithm with multi-objective feature selection (MOFS) and extreme learning machine (ELM) was used to establish the correlation and to identify the most influential input parameters. Based on the information from the proposed hybrid algorithm, a comprehensive prediction model is proposed using multi-gene genetic programming (MGGP) algorithm to facilitate quick estimation of critical state parameters. The performance of both models has been assessed using several performance metrics. The results from the study indicate that hybrid MOFS algorithms perform very well in the prediction of critical state line parameters and the identification of influential features. The findings of the study have significant implications for future research on the safe management of tailing storage facilities.

Dec 22, 2023

By J. Creamer

Pumping plays a major role across multiple process and facility applications in the mining world. Examples include: raw water supply, leach solutions, chemicals, dewatering, and mine drainage, and process water for metal recovery. Mining operations such as grinding, classifying, separating and concentrating minerals all have pumps at the heart of the operations Special purpose pumps such as dewatering, process water and slurry pumps are at the heart of many of these processes. Unfortunately the pumps themselves are often overlooked in terms of energy savings potential as they are often embedded into these sophisticated processes which are the ultimate operational focus.

Feb 23, 2014

By William J. Pardee, Michael A. Shaff

"Deeper materials science knowledge from mathematical models and in situ material property sensors will be exploited in next generation factory process controllers to improve productivity and quality. These intelligent control systems will accelerate productivity growth and materials science application through the ease with which they can be modified to accept new materials knowledge and sensors. Carbonization of resin matrix carbon fiber composites, specifically, is a violent solid state chemical reaction with large stresses due to gas pressure, matrix shrinkage, and differences in thermal expansion. The matrix strength falls sharply, then rises again during the process. At least two competing reaction paths are important; the first cleaves methylene bonds, reduces toughness, density and stiffness; the second reforms those bonds, ultimately resulting in aromatic ring condensation that increases density, strength, and modulus. Since these reactions have different temperature dependencies, one can expect to shift the process towards the second path by changing the heating rate, but that change must be accomplished without producing macroscopic interlaminar crack growth. To accomplish this, we employ gas sensors to infer matrix chemical state and acoustic emission to identify microstructural changes and to recognize brittle fracture. The latter does not prevent delamination, but is important in testing models for the causes of delamination and in improving the processing cycle. This paper describes a control strategy to accelerate the process while still lowering the risk of failure.IntroductionDeeper materials science knowledge from mathematical models and in situ material property sensors will be exploited in next generation factory process controllers to improve productivity and quality. These intelligent control systems will be more easily modified to accept new materials knowledge and sensors, thus accelerating productivity growth. Such a control strategy for carbonization control is described below.Carbon-carbon composites are time consuming and costly to manufacture. Processing methods have been developed empirically and are usually very conservative because the process often fails when any change is made. Apparently minor changes in materials or geometry can produce failures that are difficult to diagnose and correct. We will describe below several essentially unavoidable sources of variability. These are best dealt with by applying materials science to adapt (i.e., closed loop control on materials properties) the process in real time to reduce the effect of unavoidable model idealizations, material variability and environmental noise. The most critical issue in control of the carbonization process control is avoiding catastrophic delamination. The strategy developed below makes use of a priori materials knowledge and real time sensors to accelerate the now very slow process without destroying the material, and without requiring unreasonable resources to determine the statistical properties of the material."

Jan 1, 1988

By Paul J. A. Lever, Robert H. King

Human operators, geological conditions, equipment changes, mining sequences, and roof conditions are some of the continually changing operating conditions that drive a dynamic mining environment. These dynamic characteristics make it difficult to automatically analyze mining data because attributes change as the mining environment changes. Mine monitoring systems could provide mine managers with much more useful information than they do presently, if automatic analysis were possible. Automatic analysis of sensor data is also key to autonomous mining systems. This paper describes artificial intelligence (AI) and sensor fusion based sensor data analysis techniques developed over the past four years. These techniques were used to classify machine operating events by continuously monitoring machine power usage in a continuous miner section at an under- ground coal mine. The result is a report similar to an industrial engineering time study. First, numerical pattern classification techniques broadly identify operating events. However, domain knowledge about inter-machine and intra-machine interactions is necessary to identify and refine dynamic event boundaries. By implementing AI and sensor fusion based techniques we are able to classify machine events more accurately and recognize more specific events. These techniques could easily be applied to many different mining sensor data applications

Jan 1, 1993

By H. Hejny

"The mine of the future will exploit mineral raw materials at greater depths than today, requiring completely different approaches compared to today’s deep mines, in order to get mineral rights. Only these eco-efficient mines will contribute to improved access to domestic mineral resources, secure the sustainable supply of mineral raw materials for Europe and reduce the import dependency. IntelliMine will contribute to realise these concepts of invisible, zero-impact and safe mines. The mine of tomorrow will run an integrated concept in order to guarantee the desired level of sustainability. All operations necessary for the eco-efficient provision of the minerals including waste management will be carried out underground. This will drastically reduce the volumes being transported, minimising above ground installations and thus the environmental impact. IntelliMine will develop necessary innovative methods, technologies, machines and equipment for the safe, eco-innovative, intelligent and economic exploitation of mineral raw materials in the EU, especially at greater depths."

Jan 1, 2011

By V. G. Minenko, A. L. Samusev

For efficient leaching of gold from sulfide ores and the oxidation of sulfides into sulfates, it is necessary to introduce a substantial amount of oxidant - atomic oxygen, hydrogen peroxide, ozone, potassium or sodium hypochlorite. In this paper, hypochlorite electrochemical treatment is proposed as an effective method of intensification of refractory ore leaching. The objective of the study is to increase the gold recovery from refractory ores with the application of chlorinated solutions that are modified by chemical or electrochemical treatment. The advantages of the use of the modified chlorinated solutions instead of cyanide for gold-sulfide leaching are considered to be the following: a high concentration of the oxidizing agent (hypochlorite ions) in solution helps to achieve a high speed of gold dissolution in the form of chloride complexes; the possibility to produce hydrochloric acid solutions that may be used for the recovering gold by electrolysis; the possibility of the processing of carbonaceous, arsenic-bearing and others kinds of refractory gold ores. The mechanism of the interaction of the modified chlorine solutions with gold-bearing sulfides (pyrite and arsenopyrite) was investigated. The efficiency of the application of chemical and electrochemical leaching method was proved. The main factor that limits the rate of gold dissolution is a high concentration of sulfate ions (SO4 2-) formed in the solution by the oxidation of sulfide minerals. The optimal parameters of chemical and electrochemical leaching method and effective ways to remove sulfate ions were determined. The method helps to increase the level of the gold recovery up to 87% from refractory ores. The intensification of leaching by chemical and electrochemical treatment opens up opportunities for the creation of modern efficient and environmentally-friendly technologies that may be applied for gold extraction from refractory gold ores.

Jan 1, 2016

By Bin Xu, Qian Li, Xishan Li, Yongbin Yang, Hongwei Li, Tao Jiang, Yan Zhang

The cyanide leaching rate of gold from a multi-refractory gold concentrate (18.05 g/t Au) containing 1.62% As, 20.76% S, 6.95% C and 1.31% Sb was only 1.33%. The enhancement of gold leaching was studied mainly by the pretreatment of oxidative roasting and alkaline sulfide washing. Results showed that after the two-stage roasting (i.e., I stage of 500 °C, 1 h and II stage of 700 °C, 2 h) most of sulfur (93.84%) and carbon (98.27%) were removed, but the gold leaching rate of calcine just reached 71.33% because the residual arsenic (0.63%) and antimony (1.15%) were still high. After alkaline sulfide (i.e., NaOH and Na2S) washing, the residual arsenic and antimony was further decreased to 0.21 and 0.65%, respectively. The gold leaching rate of the treated calcine by cyanidation could increase to 93.52% substantially. Also, the optimized particle size, NaCN concentration and leaching time were −0.045 mm over 85%, 0.1% and 36 h, respectively.

Mar 1, 2017

By Valery V. Kostjuk, Victor. N. Bredikhin, Alexander I. Shevelev, Evgeny A. Kazban

"The investigations to improve the process data have been done in order to stabilize the functioning of drying units. The scheme of turnings preparation with centrifuging and subsequent thermal degreasing (tandem) is proposed. To improve the efficiency of the process the scheme of reclamation of the centrifuge fugate is developed with production of oil and service circulating water. Empirical dependences of the turnings temperature influence on the lubricant-coolants content in centrifuging are gained. When the turnings temperature is increased to 80 C the residual content of LC is decreased by 1.5%. The investigations aimed to improve the preparation of non-ferrous turnings have allowed to decrease the melting loss by 15-20%; to stabilize the process of thermal drying of turnings; to decrease sharply (by 60- 70%) the volume of LC combustion products; to reclaim the centrifuge fugate and produce oil and servicecirculating water.Non-ferrous turning and primarily aluminum and copper alloys turning is a stable source of secondary raw materials for metallurgical works.Direct by lubricant-coolants (LC) of various types: synthetic, semi synthetic, oily and emulsions.On the base of investigations concerning various methods of the non-ferrous turning processing the favorable one has been selected taking in to consideration the economy, ecology and quality of the finished product (alloy). Two-stage process is developed. The main idea of the process is the elimination of the lubricant-coolants (LC) to the limit specified in advance. The applied method is centrifuging with subsequent final elimination of LC by thermal method.Constant value of LC content at the inlet of the thermal unit excludes practically the oxidation of metal and as a consequence increases the output by 10 –15 % in metallurgical processing."

Jan 1, 2003

By G. G. Richards, Y. Oyediran, V. Chow

The oxygen softening process for partial removal of arsenic and antimony from lead bullion has been in use at Teck Cominco's Trail smelter since 1986. In this process, industrial oxygen is injected into bullion to remove As and Sb with the formation of an oxide slag. In Trail, the levels of these elements are reduced to concentrations suitable for processing in the Betts electrorefining plant. Recent moves toward the treatment of higher arsenic-bearing feeds have necessitated an increase in the process capacity to meet the specifications for drossing plant bullion. Process intensification trials were conducted in-plant to develop an operating strategy for higher bullion processing rates. This was preceded by a study conducted with McGill University to develop a fundamental understanding of the therm ochemistry and kinetics of the process. The results have yielded more effective control of the operation, and identified opportunities for further improvements.

Jan 1, 2008

By Rodrigo Martins, Mauro Trindade

I Reduction of energy consumption in air compressors by the implementation of individualized load control. Reduction of 3,5% from Jun / 18.

Oct 3, 2019