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By T. Stauffer, B. McGunegle, A. Adu-Acheampong

The Fairmount Minerals, Inc., Maiden Rock underground sand mine historically delivered air to ventilate diesel-powered equipment at its working faces through high-resistance, 15-inch-diameter PVC distribution lines. In support of plans for expanded production, three new, low-resistance ventilation design alternatives were analyzed. The study determined that adequate ventilation for expanded production was possible with various commercially-available, high-volume/low-pressure fans combined with a systematic layout of control structures. The recommended re-design was implemented in 2001, resulting in a significant increase in flow volumes and a noticeable improvement in the mine environment.

Jan 1, 2007

By Jerry D. Pfarr, Gary Loving, David G. McDowall

Introduction The Open Cut is one of the best known landmarks in South Dakota's Black Hills. It is the site of the original discovery of the Homestake ledge, or lead, in 1876. Between that time and 1945, the Open Cut produced about 36 Mt (40 million st) of gold ore, the majority of which was drawn from underground operations. In 1981, a drilling program was undertaken to determine how much ore the old timers left behind. The results of this study indicated an ore body made up of broken and caved ground, and solid blocks in pillars and crowns. Reserves are estimated at about 6.8 Mt (7.5 million st) of gold ore, grading at 4 g/t (0.116 oz per st). Total tonnage of material, including waste, is estimated at more than 60 Mt (66 million st). The mining plan is a combination open pit and underground operations. The bottom 78 m (255 ft) will be mined by the underground panel-caving method. The open pit was designed as a contractor operation up to the expected milling stage or the point of sustained ore production. The pit was designed to avoid disturbance of US Highway 85 near Lead, SD. In 1983, the South Dakota Board of Minerals and Environment approved the mining and reclamation plan. Test mining began in the north of the Open Cut using open pit methods. Upon completion of the test pit, Homestake Mining's board of directors approved an expanded mine plan. They committed an additional $27.1 million to prestrip the ore body that is expected to yield 23 t (750,000 oz) of gold. Project life is estimated at 15 years. Exploration program In early 1980, 10 diamond drill holes were drilled from the surface in the vicinity of the east side of the Open Cut. The reserves delineated by that drilling were too small to justify their development. A continuation of this study attempted to quantify the tonnage remaining in the bottom of the Open Cut in the crushed remnants of old stope-and-crown pillars. This was originally thought to be minable by improved drawhole methods using highly mechanized procedures. By early 1981, however, thinking turned toward surface mining methods. The effort to quantify minable ore tonnage ultimately involved drilling 385 reverse-circulation rotary drill holes. These were drilled from August 1981 to March 1983 in several groups of holes. Each group, or drilling program, had a slightly different immediate goal or purpose. The holes were drilled to various depths using truck-mounted Drill Tech 40 drills with doublewalled 76 mm (3 in.) pipe with 134 mm (5.25 in.) three-cone rotary bits. Initially, wet drilling was employed using a cyclone collection system. Since cutting recovery was not as high as it should have been, all subsequent drilling was dry. The cuttings were collected and deposited by way of a cyclone into the sample bag. The pickup for the cuttings using the three-cone bits was about 50 mm (2 in.) above the bottom of the hole. Overall cutting recovery for the drilling program was estimated at 75%. Samples were taken on each 1.5 m (5 ft) of hole drilled. Each sample was split into three 48-g (1-2/3 assay ton) charges. The accepted value was the straight average of the three charges. Because of the known "nugget effect," assays were nearly impossible to duplicate. Therefore, to validate the regular assays, a series of screen fire assays were run. Based on this method of assays and checks, it was concluded that 10% more ounces would be produced than indicated by mine grade. Test pit The northernmost portion of the mine as planned is known as the Terraville test pit. This portion was mined ahead of the rest and separately. It provided answers to questions on slope stability, reserves correlation, mill recoveries, mining costs, and surface mining conditions in various weather and ground conditions since many boulders and much timber were expected. The mining plan for this portion of the pit was successful. More ore was mined than was expected. Mixing of Open Cut ore with underground ore in the mill feed was successful. Impact on the surrounding communities

Jan 10, 1987

By G. H. Sedahmed, S. A. Nosier, M. H. Abdel-Aziz, A. A. Mubarak, M. A. El-Naggar, E. G. Abdel-Aziz

The performance of a rotating fixed bed reactor in recovering copper from industrial waste solutions by cementation is studied under various conditions. The rotating fixed bed is made of stacked woven steel screens to take advantage of two features of screens: the ability to present large area per unit volume and their ability to promote high turbulence. Variables studied are initial CuSO4 concentration, bed rotation speed, mesh number of the screens and bed thickness. The presence of baffles was found to increase the rate of cementation. The data were correlated by a dimensionless mass transfer correlation suitable for the design and operation of large scale cementation reactors.

By G. H. Sedahmed, S. A. Nosier, M. H. Abdel-Aziz, A. A. Mubarak, M. A. El-Naggar, E. G. Abdel-Aziz

The performance of a rotating fixed bed reactor in recovering copper from industrial waste solutions by cementation is studied under various conditions. The rotating fixed bed is made of stacked woven steel screens to take advantage of two features of screens: the ability to present large area per unit volume and their ability to promote high turbulence. Variables studied are initial CuSO4 concentration, bed rotation speed, mesh number of the screens and bed thickness. The presence of baffles was found to increase the rate of cementation. The data were correlated by a dimensionless mass transfer correlation suitable for the design and operation of large scale cementation reactors.

By Tyler Acorn, Brandon Wilson, Jeff Boisvert

Scenario-level uncertainty is a representation of large-scale differences encountered when considering ultimate mining pits optimized over various subsets of stochastic realizations. Accounting for scenario-level uncertainty allows mine plans to be assessed against several probabilistic subsurface interpretations. Scenario-level uncertainty is found through clustering stochastic geostatistical realizations and optimizing final pits across the realizations in each cluster. Where these pits are geometrically different, plans for each scenario differ. Knowing these differences allows the value of each planning alternative to be assessed based on the value and relative probability of each scenario. These results also facilitate the use of formal decision-making frameworks for planning, leading to optimization that better represents the full statistical characterization of the deposit. An example utilizing this approach evaluates both infrastructure placement and drilling program requirements. In both cases, scenario-level uncertainty improves initial plans by limiting opportunity costs and identifying additional potential.

By Tyler Acorn, Brandon Wilson, Jeff Boisvert

Scenario-level uncertainty is a representation of large-scale differences encountered when considering ultimate mining pits optimized over various subsets of stochastic realizations. Accounting for scenario-level uncertainty allows mine plans to be assessed against several probabilistic subsurface interpretations. Scenario-level uncertainty is found through clustering stochastic geostatistical realizations and optimizing final pits across the realizations in each cluster. Where these pits are geometrically different, plans for each scenario differ. Knowing these differences allows the value of each planning alternative to be assessed based on the value and relative probability of each scenario. These results also facilitate the use of formal decision-making frameworks for planning, leading to optimization that better represents the full statistical characterization of the deposit. An example utilizing this approach evaluates both infrastructure placement and drilling program requirements. In both cases, scenario-level uncertainty improves initial plans by limiting opportunity costs and identifying additional potential.

By Justyna Swolkień, Nikodem Szlązak, Dariusz Obracaj

Polish coal mines are characterized by severe geological conditions and the co-occurrence of natural hazards. These hazards are associated with methane and dust emissions during mining processes which can provide methane, dust or methane-dust explosions. Besides, there are such natural hazards as gas and rock outbursts, rock bursts, spontaneous combustion of coal and environmental heat load. The mutual influences of various geological conditions, as well as the natural hazards, intensify the increase of the methane explosion hazard. The occurrence of methane explosions in the Polish mining industry between 2013 and 2108 are analyzed. Fatal accidents are compared with similar events in the global mining industry. The methods of preventing the explosion hazard as well as methane emission control in the Polish coal mining sector are presented. Methane hazard prevention should be adapted to levels and other natural hazards, especially those related to ventilation of underground mine. The methods of preventing methane emissions into mine excavations are often contrary to the means of preventing other ventilation-related hazards in the underground mine, e.g. the prevention of spontaneous combustion of coal in the goaf of longwall panel. Therefore, the design of longwall panels should be preceded by a detailed analysis of the results of both methane emission prediction and forecast of other ventilation-related hazards.

By Justyna Swolkień, Nikodem Szlązak, Dariusz Obracaj

Polish coal mines are characterized by severe geological conditions and the co-occurrence of natural hazards. These hazards are associated with methane and dust emissions during mining processes which can provide methane, dust or methane-dust explosions. Besides, there are such natural hazards as gas and rock outbursts, rock bursts, spontaneous combustion of coal and environmental heat load. The mutual influences of various geological conditions, as well as the natural hazards, intensify the increase of the methane explosion hazard. The occurrence of methane explosions in the Polish mining industry between 2013 and 2108 are analyzed. Fatal accidents are compared with similar events in the global mining industry. The methods of preventing the explosion hazard as well as methane emission control in the Polish coal mining sector are presented. Methane hazard prevention should be adapted to levels and other natural hazards, especially those related to ventilation of underground mine. The methods of preventing methane emissions into mine excavations are often contrary to the means of preventing other ventilation-related hazards in the underground mine, e.g. the prevention of spontaneous combustion of coal in the goaf of longwall panel. Therefore, the design of longwall panels should be preceded by a detailed analysis of the results of both methane emission prediction and forecast of other ventilation-related hazards.

By G. Tiess, S. Mujiyanto

Indonesia is a fast growing democratic developing country comprising more than 17,000 islands, founding member of ASEAN and a member of the G-20 major economies. It is one of the most highly mineralised countries in the world, the mining sector playing a pivotal role in the country's economy. In 2001, the Decentralization Law No. 22/1999 came into force and caused a transfer of authority and responsibility from central to regional and local administrative governments. The new Mining Law of 2009 substituted its 40 year old predecessor, but lacked detailed regulations for its implementation. These were only issued in 2010, which lead to a period of great uncertainty for investors in the mining industry. The new legislation intends to foster domestic economic development, which may be interpreted as protectionist policy. For the development of a sustainable mineral resources policy, further endeavours will have to be made.

Jan 1, 2011

By Jacob Carr, Christopher C. Jobes, Chenming Zhou, LaTasha R. Swanson, Jennica Bellanca, Jingcheng Li

Magnetic proximity detection systems (PDSs) are used with continuous mining machines (CMMs) to protect miners from striking and pinning accidents. Generators are used in a PDS to create magnetic fields covering the space around a CMM. The PDS determines the proximity of a miner relative to the CMM based on the magnetic flux density detected by a miner-wearable component (MWC) and simultaneously alerts the miner and stops the motion of the CMM if the miner is within a proximity that creates a striking hazard. A stable magnetic field is essential to the accuracy of the proximity calculations performed by the PDS. This paper presents the results of a systematic study of the magnetic influence of two types of steel structures found near a CMM— the body of the CMM itself and the wire mesh used for roof and rib control. The results show that the steel of the CMM body can change the magnetic field distribution and also alter electrical parameters of a PDS by changing its generator current. The study also shows that, depending on the distance between the wire mesh and a generator, the magnetic field can also be altered.

By Jacob Carr, Christopher C. Jobes, Chenming Zhou, LaTasha R. Swanson, Jennica Bellanca, Jingcheng Li

Magnetic proximity detection systems (PDSs) are used with continuous mining machines (CMMs) to protect miners from striking and pinning accidents. Generators are used in a PDS to create magnetic fields covering the space around a CMM. The PDS determines the proximity of a miner relative to the CMM based on the magnetic flux density detected by a miner-wearable component (MWC) and simultaneously alerts the miner and stops the motion of the CMM if the miner is within a proximity that creates a striking hazard. A stable magnetic field is essential to the accuracy of the proximity calculations performed by the PDS. This paper presents the results of a systematic study of the magnetic influence of two types of steel structures found near a CMM— the body of the CMM itself and the wire mesh used for roof and rib control. The results show that the steel of the CMM body can change the magnetic field distribution and also alter electrical parameters of a PDS by changing its generator current. The study also shows that, depending on the distance between the wire mesh and a generator, the magnetic field can also be altered.

By LaTasha R. Swanson, Jennica L. Bellanca

Proximity detection systems (PDSs) for mobile machines have the potential to decrease injuries and fatalities. Early adopters of the technology have identified some challenges, which present an opportunity to explore and improve the integration of mobile PDSs in underground coal mines. The current research study applied the task-technology fit framework to investigate the fit between mobile PDS technology and mining relative to health and safety, from the perspective of leaders at two coal mines. Quantitative results from the study show that mine leaders evaluated mobile PDS favorably for training and ease of use, system feedback, user authorization and experience, and less favorably for safety, compatibility, task completion, and reliability. Qualitative results reveal specific task, mine, and system characteristics that may have influenced leaders’ evaluations. The study includes considerations and suggestions for safe technology integration

By LaTasha R. Swanson, Jennica L. Bellanca

Proximity detection systems (PDSs) for mobile machines have the potential to decrease injuries and fatalities. Early adopters of the technology have identified some challenges, which present an opportunity to explore and improve the integration of mobile PDSs in underground coal mines. The current research study applied the task-technology fit framework to investigate the fit between mobile PDS technology and mining relative to health and safety, from the perspective of leaders at two coal mines. Quantitative results from the study show that mine leaders evaluated mobile PDS favorably for training and ease of use, system feedback, user authorization and experience, and less favorably for safety, compatibility, task completion, and reliability. Qualitative results reveal specific task, mine, and system characteristics that may have influenced leaders’ evaluations. The study includes considerations and suggestions for safe technology integration

By Rambabu Pothina, Rajive Ganguli

The economics of a mineral processing circuit is dependent on the numerous sensors that are critical to optimization and control systems. The sheer volume of sensors results in mines not being able to keep the sensors calibrated. When a sensor goes off calibration, it results in errors which can severely impact plant economics. Normally, these errors are not detected until the error grows and becomes a large (“gross”) error. Undetected errors are not remedied until the next calibration, which on average are a year apart Beamex (2019) [1] across all industries. Classical statistical methods that depend on linear relationships between input and response variables are typically used to find gross errors, but are not effective for highly non-linear and non-stationary operations in mining and mineral processing industries. Calibration of sensors is time-consuming and generally requires physical intervention that results in equipment downtimes causing production losses. Therefore, in situ detection methods are warranted that do not require physical removal of sensors to compare with standard measurements or well-calibrated sensors. Data-mining based techniques and algorithms have high success rate in tackling such problems. This paper presents results from a groundbreaking multi-year big data research project whose goal was to develop data-mining-based original techniques in a multi-sensor environment to identify when sensors start to stray, rather than wait for errors to grow. The carbon stripping (gold) circuit in the Pogo Mine of Alaska was selected for this project. Maintaining strip vessel temperatures at optimum levels is crucial for maximizing gold recoveries at Pogo, and hence the focus was on the temperature sensors of the two strip vessels. An automated algorithm to detect errors in strip vessel temperature sensors was developed that exploited data from multiple sensors in the strip circuit. This algorithm was able to detect with a high success rate when bias errors of magnitude as low as ± 2% were artificially induced into strip vessel temperature data streams. The detection times of about 1 month were much less than the industry average calibration frequency of 1 year. Thus, the algorithm helps detect errors early, without stopping the circuit. The algorithm alarms can serve as triggers when calibrations are done. Experimental methodology along with results, limitations of algorithms, and future research are also presented in this paper.

By Rambabu Pothina, Rajive Ganguli

The economics of a mineral processing circuit is dependent on the numerous sensors that are critical to optimization and control systems. The sheer volume of sensors results in mines not being able to keep the sensors calibrated. When a sensor goes off calibration, it results in errors which can severely impact plant economics. Normally, these errors are not detected until the error grows and becomes a large (“gross”) error. Undetected errors are not remedied until the next calibration, which on average are a year apart Beamex (2019) [1] across all industries. Classical statistical methods that depend on linear relationships between input and response variables are typically used to find gross errors, but are not effective for highly non-linear and non-stationary operations in mining and mineral processing industries. Calibration of sensors is time-consuming and generally requires physical intervention that results in equipment downtimes causing production losses. Therefore, in situ detection methods are warranted that do not require physical removal of sensors to compare with standard measurements or well-calibrated sensors. Data-mining based techniques and algorithms have high success rate in tackling such problems. This paper presents results from a groundbreaking multi-year big data research project whose goal was to develop data-mining-based original techniques in a multi-sensor environment to identify when sensors start to stray, rather than wait for errors to grow. The carbon stripping (gold) circuit in the Pogo Mine of Alaska was selected for this project. Maintaining strip vessel temperatures at optimum levels is crucial for maximizing gold recoveries at Pogo, and hence the focus was on the temperature sensors of the two strip vessels. An automated algorithm to detect errors in strip vessel temperature sensors was developed that exploited data from multiple sensors in the strip circuit. This algorithm was able to detect with a high success rate when bias errors of magnitude as low as ± 2% were artificially induced into strip vessel temperature data streams. The detection times of about 1 month were much less than the industry average calibration frequency of 1 year. Thus, the algorithm helps detect errors early, without stopping the circuit. The algorithm alarms can serve as triggers when calibrations are done. Experimental methodology along with results, limitations of algorithms, and future research are also presented in this paper.

By J. R. Patts, A. B. Cecala, E. J. Haas

Exposure to respirable crystalline silica (RCS) remains a serious health hazard to the US mining workforce who are potentially exposed as various ore bodies are drilled, blasted, hauled by truck, crushed, screened, and transported to their destinations. The current Mine Safety and Health Administration (MSHA) permissible exposure limit (PEL) for RCS remains at approximately 100 μg/m3 , but it is noteworthy that the Occupational Safety and Health Administration (OSHA) has lowered its PEL to 50 μg/ m3 (with enforcement dates staggered through 2022 for various sectors), and the National Institute for Occupational Safety and Health (NIOSH) has held a 50 μg/m3 recommended standard since 1976. To examine a method for reducing RCS exposure using a NIOSH-developed video exposure monitoring (VEM) technology (referred to as Helmet-CAM), video and respirable dust concentration data were collected on eighty miners across seven unique mining sites. The data was then collated and partitioned using a thresholding scheme to determine exposures that were in excess of ten times the mean exposure for that worker. Focusing on these short duration, high magnitude exposures can provide insight to implement controls and interventions that can dramatically lower the employee’s overall average exposure. In 19 of the 80 cases analyzed, it was found that exposure could be significantly lowered by 20% or more by reducing exposures that occur during just 10 min of work per 8-hour shift. This approach provides a method to quickly analyze and determine which activities are creating the greatest health concerns. In most cases, once identified, focused control technologies or behavioral modifications can be applied to those tasks.

By J. R. Patts, A. B. Cecala, E. J. Haas

Exposure to respirable crystalline silica (RCS) remains a serious health hazard to the US mining workforce who are potentially exposed as various ore bodies are drilled, blasted, hauled by truck, crushed, screened, and transported to their destinations. The current Mine Safety and Health Administration (MSHA) permissible exposure limit (PEL) for RCS remains at approximately 100 μg/m3 , but it is noteworthy that the Occupational Safety and Health Administration (OSHA) has lowered its PEL to 50 μg/ m3 (with enforcement dates staggered through 2022 for various sectors), and the National Institute for Occupational Safety and Health (NIOSH) has held a 50 μg/m3 recommended standard since 1976. To examine a method for reducing RCS exposure using a NIOSH-developed video exposure monitoring (VEM) technology (referred to as Helmet-CAM), video and respirable dust concentration data were collected on eighty miners across seven unique mining sites. The data was then collated and partitioned using a thresholding scheme to determine exposures that were in excess of ten times the mean exposure for that worker. Focusing on these short duration, high magnitude exposures can provide insight to implement controls and interventions that can dramatically lower the employee’s overall average exposure. In 19 of the 80 cases analyzed, it was found that exposure could be significantly lowered by 20% or more by reducing exposures that occur during just 10 min of work per 8-hour shift. This approach provides a method to quickly analyze and determine which activities are creating the greatest health concerns. In most cases, once identified, focused control technologies or behavioral modifications can be applied to those tasks.

By Joel Lööw, Jan Johansson, Lena Abrahamsson

Industry 4.0 offers new possibilities to combine increased productivity with stimulating workplaces in a good work environment. Used correctly, digitalization can create attractive jobs in safe control room environments, which provide space for the employee’s full expertise and creativity. This is true also for the mining industry. But, to succeed, it is important to analyze the development from a worker’s perspective. What will happen to their work? What skills will be needed in the mine of tomorrow? We must also consider the risks, such as privacy issues, increased stress, and work-life boundaries. These questions must be understood if we are to create workplaces that can attract a young and diverse workforce to tomorrow’s mining industry. In this article, we try to illustrate what the new technology can mean for the individual miners. We formulate the notion of Mining 4.0 (Industry 4.0 in the mining industry), where we try to create an image of how the future might look from a miner’s perspective and how mining companies may navigate their way to a future that works for all miners. To illustrate the range of possible outcomes, we formulate two scenarios: one utopian and one dystopic. At the end of our article, we bring forward six recommendations that can be considered a beginning of a road map for the human side of Mining 4.0.

By Joel Lööw, Jan Johansson, Lena Abrahamsson

Industry 4.0 offers new possibilities to combine increased productivity with stimulating workplaces in a good work environment. Used correctly, digitalization can create attractive jobs in safe control room environments, which provide space for the employee’s full expertise and creativity. This is true also for the mining industry. But, to succeed, it is important to analyze the development from a worker’s perspective. What will happen to their work? What skills will be needed in the mine of tomorrow? We must also consider the risks, such as privacy issues, increased stress, and work-life boundaries. These questions must be understood if we are to create workplaces that can attract a young and diverse workforce to tomorrow’s mining industry. In this article, we try to illustrate what the new technology can mean for the individual miners. We formulate the notion of Mining 4.0 (Industry 4.0 in the mining industry), where we try to create an image of how the future might look from a miner’s perspective and how mining companies may navigate their way to a future that works for all miners. To illustrate the range of possible outcomes, we formulate two scenarios: one utopian and one dystopic. At the end of our article, we bring forward six recommendations that can be considered a beginning of a road map for the human side of Mining 4.0.

By Shanming He, Jinliang Wang, Xiaoming Wang, Chunfa Liao

Large amounts of manganese-rich slag were generated from smelting low-grade manganese ore containing high iron and high phosphorus in electric furnace or blast furnace, which contain 25–40 mass% Mn. This paper describes an efficient hydrometallurgical process for the utilization of high manganese slag instead of conventional usage of pyrometallurgical route for manganese recovery. Pressure acid leaching of manganese-rich slag using air as pressurized gas is studied systematically. The effects of mass ratio of manganese-rich slag to pyrite, concentration of sulfuric acid, leaching temperature, partial air pressure, leaching time, and liquid-solid (L/S) ratio on the separation of manganese with other main impurity components were investigated comprehensively. Under the following optimal process conditions, weight of manganese-rich slag powder,100 g; mass ratio of manganese-rich slag to pyrite, 20:1; sulfuric acid concentration of 140 g/L; air pressure of 0.6 MPa; leaching temperature of 140 °C; leaching time of 1 h; L/S of 7:1; ore size of 75–80 μm; and stirring rate of 600 rpm, the extraction rate of Mn reached 94%, and the dissolution percentage of Si, Al, and Fe are as low as 2%, 6%, and 10%, respectively. The leaching slurry presented a good solid-liquid separation characteristic. The silicic acid formed during sulfuric acid leaching manganese silicates was converted to filterable dehydrated SiO2 particles which precipitated in the residue under the condition of higher temperature with higher pressure. The effect of adding pyrite may be to reduced iron ions and decreased the output of iron hydroxide colloid and also reduced MnO2 to manganese sulfate in sulfuric acid leaching. Thus the formation possibility of colloid such as silica gel and iron hydroxide was decreased, and higher yield of manganese sulfate could be achieved.