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By S. R. Dindarloo

"Truck-shovel systems are the dominant material loading and haulage machinery in open pit mining operations. Optimal selection, sizing, and allocation of this capital intensive equipment is highly desirable for both achieving production targets and improving the mine’s economics. In this study, discrete event simulation technique was applied for modeling material transportation in Golegohar open pit iron ore mine in Iran. Direct observation of the material loading and haulage for duration of three months resulted in statistical modeling of the operation in the form of probability distribution functions. These probability models were used as the inputs of a stochastic simulation model constructed in GPSS/H simulation language. The model was validated through comparison with the actual operation and was used to test different what-if scenarios and sensitivity analysis of the current system. Some modifications in the number of trucks, shovels, and dispatching strategies were proposed. Simulation resulted in considerable improvements in the mine’s production and economics.INTRODUCTION There are three different mechanisms of discrete, continues, and hybrid material transportation in open mines, including but not limited to: i) in-pit crusher and conveyor belts (hybrid), ii) slurry piping (continues) and iii) truck-shovel system (discrete). Although, each mechanism has its advantages, the truck-shovel system is the dominant method of material loading and handling in open pit mines owing to its high production rate, excellent flexibility, relatively low operating and capital costs, and good maintainability. General objectives of optimal equipment selection include: i) meeting the long and short term requirements of production rates, ii) human & equipment safety, iii) environmental protection, and iv) economic operations (Figure 1).The two most important decision factors on a truck-shovel system selection and sizing are the equipment geometry and size. Geometry (equipment width, weight, turning radius, swing angle, etc.) is mostly controlled by mine’s designs and layouts, as well, as operational constraints. After selection of a favorable geometry based on the constraints; the next step is to select the equipment manufacturer. Once the geometry and manufacturers are selected; the next step is to decide on models (e.g. Bucket size) and required number of each unit"

Jan 1, 2015

By Ping Zhang, Xu Ma

Perturbations arising from mining operations significantly affect the stability of rock masses, and the influences aggerates with the rapid increase of mining-operation depths during recent years. The subsurface structures with major discontinuities subject to seismic hazards resulted from the shear-slip behaviors of rock masses. In order to identify the shear-slip regime of discontinuities and calculate seismic moment and seismic energy involved with shear-slip behaviors, we use discrete element modeling to study the shear slip failure along discontinuities in an underground mine. The recorded characteristic and properties of sub-contacts in DEM provide a basis for computing and visualizing the temporal and spatial distribution of seismic moment and seismic energy with mining operations. We computed the seismic energy and seismic moment using the numerical modeling method and the analytic method. We compared the result of summing seismic energy and seismic moment from the subcontacts of numerical models and the result of the analytic method. We confirmed that this tool can be used in comparative analyses. We also found that seismic moment and seismic energy, associated with shear stress drop and shear displacement increase, accumulate in the vicinity of major discontinuities. Mining operations at a greater depth cause greater changes of seismic moment and seismic energy, leading to a higher risk of inducing seismic hazards. Quantifying seismic potential using discrete element modeling can greatly facilitate the investigation of instability of geological discontinuities and thereby can help estimate the potential of seismic hazards.

Jan 21, 2023

By Yao Yevenyo Ziggah, Victor Amoako Temeng, Solomon Evans Kweku Koomson

Tyre hours/life deficit is a major operational challenge facing the mining industry which adversely affects materials production and costs. An accurate forecast of the tyre life is key in addressing this menace. This study for the first time employed the hybrid intelligent technique by utilising three metaheuristic optimisation algorithms, including particle swarm optimisation (PSO), genetic algorithm (GA), and whale optimisation algorithm (WOA), as trainers for the parametric weights and biases to optimise multilayer perceptron neural network (MLPNN) for enhancing prediction of on-site dump truck tyre life in the mine. Four hybrid models known as PSO-MLPNN, WOA-MLPNN, GA-MLPNN, and BP-MLPNN were developed using a total of 157 tyre dataset records obtained from a surface mine in Ghana. In assessing the prediction performances for the models developed, five statistical performance metrics of variance accounted for (VAF), Nash–Sutcliffe efficiency index (NASH), coefficient of determination (r2), mean absolute percentage error (MAPE), and correlation coefficient (r) were utilised. Moreover, ranking, uncertainty analysis and Bayesian information criterion (BIC) techniques were utilised to establish the most effective hybrid model, whereas sensitivity analysis was conducted on the input parameters. Results achieved showed that PSO-MLPNN was the best for prediction because it had the least MAPE value of 1.196% and relatively high values of VAF (99.642%), NASH (0.996), r2 (0.996), and r (0.998). Besides, PSO-MLPNN had the best selection criteria values of 6, 7.1725, and 444.834 for the ranking, uncertainty analysis and BIC respectively. Hence, PSO-MLPNN is recommended for the prediction of on-site dump truck tyre life for the studied mine.

Mar 11, 2024

By Nilabjendu Ghosh, Satyendra Kumar Singh, Gautam Banerjee, Harshit Agrawal

High-production methods like longwall mining with hydraulic powered supports are necessary to increase underground coal production in India. Longwall mining had a mixed success record for Indian geo-mining conditions. In this paper, an analysis is presented to optimally design an array of chain pillars in multi-seam longwall mining panels in the deepest coal mine in India. The study found that a chain pillar of 80-m width and 195-m length is necessary for long-term stability without any reinforcement. It was also observed that an optimum chain pillar can be designed by providing suitable side reinforcement (side bolting) which will reduce the chain pillar dimensions to 55-m width and 160-m length. Optimum design of chain pillars will reduce the coal locked up in these chain pillars by ~ 77%. This will also reduce the gestation period of longwall mining panel development. This paper also evaluates the maximum tensile subsidence strain induced at the surface and finds that the values are within the safe working limit of 3 mm/m. Thus, this paper finds direct application in the design of future multi-seam retreating longwall mining panels in Indian geo-mining conditions.

By B. Briggs

Over the past 15 years, the tunneling industry has pushed towards a higher degree of mechanization in nearly every phase of construction. The overall objective of the mechanization was to increase production and the level of safety in tunnel operations. However, the overall complexity of some systems have been a hindrance to a seamless transition to the newer technologies as increased maintenance requirements and re-training of skilled workers has altered the benefit curve for some innovations.

Jan 1, 2010

By D. R. Willmer

An understanding of how health and safety management systems (HSMS) reduce worksite injuries, illnesses and fatalities may be gained in studying the behaviors of health and safety leaders. These leaders bear the accountability for identifying, understanding and managing the risks of a mining operation. More importantly, they have to transfer this knowledge of perception, recognition and response to risks in the mining environment to their workers. The leaders’ efforts to build and maintain a mining operation’s workforce that consistently executes safe work practices may be captured through more than just lagging indicators of health and safety performance. This exploratory study interviewed six leaders in occupations such as site-level safety supervisors, mine superintendents and/or general managers at surface and underground stone, sand and gravel and metal/nonmetal mine sites throughout the United States, with employee populations ranging from 40 to 175. In exploring leaders’ perspectives on how they systematically manage health and safety, examples such as approaches to task training, handling near-miss incidents, identifying future leaders and providing workers with feedback offer insights into how leaders translate their knowledge and management of site-level risks to others.

Jan 1, 2018

By D. R. Willmer

An understanding of how health and safety management systems (HSMS) reduce worksite injuries, illnesses and fatalities may be gained in studying the behaviors of health and safety leaders. These leaders bear the accountability for identifying, understanding and managing the risks of a mining operation. More importantly, they have to transfer this knowledge of perception, recognition and response to risks in the mining environment to their workers. The leaders’ efforts to build and maintain a mining operation’s workforce that consistently executes safe work practices may be captured through more than just lagging indicators of health and safety performance. This exploratory study interviewed six leaders in occupations such as site-level safety supervisors, mine superintendents and/or general managers at surface and underground stone, sand and gravel and metal/nonmetal mine sites throughout the United States, with employee populations ranging from 40 to 175. In exploring leaders’ perspectives on how they systematically manage health and safety, examples such as approaches to task training, handling near-miss incidents, identifying future leaders and providing workers with feedback offer insights into how leaders translate their knowledge and management of site-level risks to others.

Jan 1, 2017

By F. Rudloff, C. Karageorgos, J. Moyo, I. Boadi, M. Struble, B. Lumsden

Over it’s more than 100-year history, the Kennecott operation has often been at the forefront of innovation; driven by the demands of the lower grade ore-body and the higher costs of operating in the US where wages are generally higher and regulation more restrictive. One way of reducing operating costs in c/lb is to increase the lbs produced at minimal cost. Despite the relatively coarse grind at Kennecott - about 30% >150μm, approximately 20% of the Cu lost to tail is liberated chalcopyrite in the <20μm fraction, and about 30%-40% in the <37μm fraction. In 2020 Kennecott undertook a detailed plant scale test of the magnetic aggregation technology to increase copper recovery by reducing fine copper losses. A paired statistical plant test of magnetic conditioning on one rougher line showed a 1.12% increase in Cu recovery to 97% statistical confidence. The next challenge, unforeseen at the start of the project, was the fabrication and transportation to site of the equipment for the three remaining rougher rows, during the severe supply-chain constraints of the Covid pandemic in 2021. This resulted in delays and unforeseen costs as world-wide transportation became chaotic, particularly transportation via west coast USA. Nevertheless, the project was completed and commissioned, with only minor delays and cost increases, due to a flexible approach to overcoming the hurdles encountered.

Feb 1, 2023

By C. J. Bise, M. F. Sindelar

Regulations, such as the MINER Act of 2006, require the installation of redundant and secondary communication systems to assure that contact can be established with coal miners who may become trapped underground as a result of an event such as a fire, explosion or inundation. For half a century, the orientation towards underground communications has been that more complex systems better serve the coal miner. However, if a goal is to provide for an alternative means of establishing communication between the surface and trapped miners underground, then some of the technology employed should be simple, reliable and cost-effective. Coal mines spend hundreds of thousands of dollars on exploratory drillholes to characterize reserves, sometimes decades ahead of mine development. During the pre-mine planning phases, certain exploratory drillholes could be located and then outfitted with a simple communication link that would remain compatible with the continuing evolution of communication systems. Inexpensive links, whose locations would be accurately recorded, would be exposed by continuous miners during mine entry development, thereby allowing an underground phone to be connected to a surface station in the event of an emergency. A latent network of these communication links could be installed for less than $500 each, minimally affecting drilling and grouting operations, and could be designed to be compatible with many communication devices. This research examines methods and materials for incorporating an embedded communication link during pre-mine exploration drilling, addresses significant factors affecting its implementation, and presents a recommended design. Since mine plans are known to change, the objective is to minimize cost so that, if not used, the investment is minimal for a potential secondary means of communication between the surface and underground workings.

Jan 1, 2014

By Manuel R. Lastra

Critical to successful dump and heap leaching for gold, silver, copper and uranium are factors such as permeability, solution delivery to the ore, and solution recovery. This paper deals with possible techniques for successful accomplishment of these three factors. New developments as well as older techniques are discussed, together with rationale for use of some techniques in reference to others. The authors hope to present a checklist so that the ideal application to individual mine situations can be achieved. This involves a discussion of the merits of each different method and the situations for most logical application. It is hoped that such discussion will broaden the geographic areas where dump and heap leaching can be applied to include greater winter cold and tropical regions of large amounts of rainfall.

Jan 1, 1984

By Milka Madahana, John Ekoru

For efficient management of operations, mining companies are required to be able to predict potential scenarios for main market factors. Competitive advantage and value creation are established through managing the value chain well. The mining value chain is usually faced with challenges from various shifts in commodity markets as well as ongoing uncertainties. Therefore, there is a need for accurate analysis of data from the markets, for the prediction of commodities, for instance, Precious Group Metals (PGM). The main objective of this research work is to apply machine learning methodologies with the aim to identify patterns and trends in the Precious Group Metals, and thereafter analyze and predict the future trends of these markets. Numerous machine learning models are applied to a dataset consisting of 15 years of daily price for eight precious metals namely Platinum, Palladium, Rhodium, Ruthenium, Osmium, Indium, Silver, and Gold. The results reveal the patterns and trends within the data sets and that different machine learning methods could be suited for the prediction of market prices for each of the PGMs. The application of an amalgamation of various machine learning methods may result in more accurate predictions of the PGM markets. Accurate prediction of market prices for PGMs will possibly result in unlocking untapped sources of value in the mining industry.

Jun 25, 2023

"Tell us how you got involved in mining and about your career path.My dad was a coal miner and my uncle was a metallurgist, so when I enrolled at Penn State’s New Kensington Campus, I chose the College of Earth and Mineral Sciences — exact majors didn’t get picked till the end of your sophomore year. Penn State New Ken had an associate degree in mining program and one of the guys in my carpool was going to take Mining 30 in the evening and the other guy (mechanical engineer) was also able to take an evening class. I didn’t want to break up the carpool, so I took Mining 30, complete with essay tests. I could write, so I did well, and the professor said I should go into mining engineering. Fast forward to the end of the next term at University Park, and I realized there wasn’t enough chemistry in mining. Switching to metallurgy would have meant another term at that point, so Dr. Lovell, my advisor, trotted me down the hall and to the next building and said I was a mineral processor. That stuck. I was a summer student at U.S. Steel Research between my junior and senior year and they paid for my master’s degree — all about clay and macerals in coal flotation. During that time, the steel industry tanked, and I thought a Ph.D. would be a good idea — I could always teach at the university level if I had those credentials. The Electric Power Research Institute had a Coal Cleaning Test Facility in Homer City, PA, and I conducted my Ph.D. research on rate and residence time in conventional coal froth flotation cells there and at a local cleaning plant. I went to work at the test facility in 1987 (later CQ Inc.) and stayed there until I started PrepTech Inc. in 1997. PrepTech offers some consulting services for coal cleaning plants and sells mineral processing equipment, mostly to coal companies. I can’t believe it’s been 21 years.And what about your SME career?Of course, I was a student SME member at Penn State. We used many of the SME books in class, so who wouldn’t want the student discount? While in Homer City, I became involved with the Appalachian Plateau Subsection of the Pittsburgh Section. We’d hold quarterly meetings with interesting speakers and had good attendance. I was the secretary. I’m still the secretary and also get the bank statements. We’ll need to close that out some time, but I guess I’ve been hoping for resurgence in the Indiana/Cambria/ Somerset area."

Jan 3, 2018

By Aldin Ardian, Mustafa Kumral, Jagjit Singh

Risk assessment of mining projects is a requirement in the mineral industries. In this process, many risk variables are timedependent, and the only available data are historical time series. Moreover, in the case of a multivariate scenario, conventional forecasting methods fail to capture conditional dependency across the variables, which is important when there is an underlying causal relationship that needs to be modeled for accurate project evaluation. Thus, we investigated the use of copulas to capture the conditional distribution of the factors involved in a mine risk assessment study. We employed a multivariate copula-based time-series approach to model several uncertain variables. The Autoregressive Fractionally Integrated Moving Average - Generalized Autoregressive Conditional Heteroscedasticity (ARFIMA-GARCH) model was used for the conditional mean and copulas were used to model the error distribution, thus capturing the collective variation and dependence pattern across the variables. The method was implemented to model gold prices, copper prices, and the 10-year US Treasury bond yields and to determine the project’s net present value and probability of being economically feasible. The proposed approach can be used for cases where simulation of multivariate time-series is conducted.

Apr 13, 2021

By J. E. Carr

A bewildering number of continuous thickeners and clarifiers are used in mineral industries and other heavy industries. General types are: 1. Conventional Thickeners (Fig. 1). 2. Thickeners with Flocculating Feedwells (Fig. 2). 3. Solids Contactors (Fig. 2). 4. Tray Thickeners (Fig. 3). 5. Lamellas (Fig. 4). 6. Conventional Thickeners with Lamellas 7. High Flow, Fluid Bed Thickeners (Fig. 5). These units must be adapted to varied applications. They must provide operating flexibility to meet process needs. Such factors multiply the decisions which must be made prior to the selection of a thickener. The seven types of thickeners listed above, with their variations, share design concepts which limit their application and which can be used to evaluate their performance. Some of these are listed: 1. Feed velocities must be limited and/or controlled. 2. Natural or reagent flocculation is necessary. 3. Horizontal settling area is the basis for capacity. 4. Overflow velocities must be limited and/or controlled. 5. A controlled underflow is necessary. Applying these needs to the basic process concepts is thickener selection. The basic function of a thickener in the minerals industry is the separation of a thickened sludge containing fine solids from water. To this primary separation function are frequently added others to give a list as follows:

Jan 1, 1977

By Morgan M. Sears, Gamal Rashed, Michael M. Murphy, Brent Slaker

In this study, a parametric study was conducted using FLAC3D numerical models to examine the impact of oblique loading, generated from seam dip, on the strength and the failure propagation pattern of a stone pillar using two simplified geometry types. In type 1, the sidewalls of the pillars were assumed to be perpendicular to the roof and the floor, while in type 2, the sidewalls of pillars were assumed to be vertical. The complex pillar geometry in dipping mines was frequently modeled using these two geometries. To capture a complete picture of the effect of seam dip on pillar stability, the modeled width-to-height (W/H) ratio of the pillars, in situ stress field, and pillars roof/floor interfaces were systematically varied to account for the potential distribution of values for these parameters across the underground stone mines in USA. Results from the numerical modeling indicate that dipping pillars have reduced strength compared with horizontal pillars. Also, an asymmetric failure propagation pattern could be obtained depending on an interaction between the W/H ratio, seam dip, in situ stresses, and pillar geometry.

Feb 5, 2021

By Thomas E. Ban

During recent years fuel consuming industries of the United States have been caught between environmental restrictions and the uncertainty of obtaining an inexpensive fuel. With the advent of the National Energy Act of 1978 there has been added impetus to switch from gas and oil to coal. For industrial furnaces and boilers that were designed to bum coal, returning to an available compliance coal might be feasible. However, furnaces and boilers designed for gas or oil cannot reasonably be converted to coal unless the coal is initially gasified. All cases, nevertheless, depend upon the availability of an adequate structured coal of a compliance composition, a challenge to the coal mining industry. The foregoing problems have contributed to the current energy-coal crisis of today&apos;s economies. It therefore would be worthwhile to capitalize on previous experiences of the mineral processing industry.

Jan 1, 1979

By T. Braun

In 1911, a young mining engineer named Bartlett Thane assembled a large claim block, 4 miles southeast of Juneau, Alaska. Across the Gastineau Channel on Douglas Island, the Alaska Treadwell Gold Mining Company had, by 1904, produced gold valued at more than three times the purchase price of Alaska in 1867 (Kelly, 2010). Thane knew his deposit was lower grade than other mines or prospects in the area; however, if the deposit was developed on a large-scale, the trend and size of the deposit made the project potentially economic. In 1911, Thane developed a business plan for the project and successfully attracted investor interest. In 1912, Daniel C Jackling visited the property at the request of an east coast investment group. Upon inspection of 5 years of production records for the Perseverance Mine, Jackling saw an opportunity to apply the low-grade/high volume milling technology which was widely adopted to the copper porphyry deposits of the southwestern U.S. With a design capacity of 6,000 tons per day (5,454 tonnes/day), Jackling’s innovative mill design would require high volume underground mining methods and the power of two new hydroelectric projects. By 1915, the Alaska Gastineau Mining Company was in full production. Between 1915 and 1919, the mine and mill set production records for haulage and throughput. The hydroelectric projects proved to be successful engineering marvels. Operational difficulties related to ore grade, refractory elements and labor shortages interrupted production on an increasing basis. In 1921, the mining company permanently shut down operations. INTRODUCTION The Juneau Gold Belt begins at Windham Bay near the southern end of Stephens Passage and extends approximately 100 miles north to Berners Bay (Figure 1). The first large-scale and sustained underground mine, operated by the Alaska Treadwell Gold Mining Company in the late 1880’s, established the Juneau-Douglas area as the regional hub for transportation and development. In the mid-1890’s, the combined population of Juneau and Douglas reached approximately 3,000 residents, largely driven by employment and support demands of several small to mid-size underground gold mines in the region. By 1904, the value of the cumulative gold production of the Alaska Treadwell was five times greater than the purchase price of Alaska in 1867 (Kelly, 2010). By the turn of the 20th century, economic growth in the Juneau-Douglas area relied on supplies delivered from the lower 48. Passenger and freight shipping lines required 3 to 4 days to make the one-way trip from Seattle to Juneau. Established shipping routes required experienced crews due to navigation hazards and adverse weather conditions. Even with precautions at the time, steam ships and freighter vessels experienced breakdowns or encounters with natural hazards that resulted in damage or in some cases, sinking. Interestingly, with no roads or railroads connecting Juneau to other communities in southeast Alaska, Juneau still relies on seaborn shipping in the 21st century.

Jan 1, 2019

The Global Mining Standards and Guidelines Group (GMSG) is building an international, multi-stakeholder community to advance the availability and use of standards and industry guidelines for the global mining community. Standards and guidelines are key strategic tools for operational excellence, enabling companies to move forward with efficient, innovative operations with reduced risk. Launched in May 2012, the GMSG is the first international center to bring together information, resources and collaborative projects for mining standards and guidelines, in an open, knowledge-sharing forum. The GMSG is supported by five partner organizations providing outreach and helping to guide GMSG activities: the Canadian Institute of Mining, Metallurgy and Petroleum (CIM), the Society for Mining, Metallurgy and Exploration (SME), the Australasian Institute of Mining and Metallurgy (AusIMM), the Southern African Institute of Mining and Metallurgy (SAIMM) and the Surface Mining Association for Research and Technology (SMART). GMSG was formed under the CIM Surface Mining Society, though its mandate extends to include underground mining as well. ?SME is supporting the GMSG as a key international activity to advance the implementation of standards and guidelines in our industry, and to provide a forum for our members to access, and contribute to, projects and information to assist their operations,? said SME Executive Director David Kanagy. ?We see the GMSG as a good example of ways the major mining associations can work together for the benefit of all our members.? The GMSG charter encompasses all standards and guidelines that apply to mining; however, a number of subject areas are now being spearheaded by six working groups, namely: ? Access and usage of data from mobile mining equipment onboard systems. ? Operational safety. ? Situational awareness (namely, a unified equipment operator interface). ? Underground operations. ? Asset management and operations data definitions and KPIs. ? Energy in communition.

Oct 1, 2013

By Wei Victor Liu, Na Zhang, Chengkai Fan, Bei Jiang

The truck haulage data from open-pit mine sites are usually massive and multidimensional with multi-peak Gaussian distributions. Artificial neural networks (ANNs) are well-known machine learning algorithms to handle massive and multidimensional data for building models. Moreover, Gaussian mixture modeling (GMM) is a suitable option for processing the data under multi-peak Gaussian distributions and improving model accuracy. For the first time, this study used a back propagation neural network (BPNN), an extreme learning machine (ELM), and a Bayesian regularized neural network (BRNN) coupled with GMM to deal with the complex truck haulage data and build three weighted ensemble models (WE-BPNN, WE-ELM, and WE-BRNN models) to predict truck productivity at mine sites. Decision tree (DT), random forest (RF), gradient boosting machine (GBM), and extreme gradient boosting (XGBoost) were used to build models to be compared with the weighted ensemble models. The results showed that the WE-BRNN had a higher accuracy than the WE-BPNN and WE-ELM models. The proposed weighted ensemble models performed better than the benchmark models in predicting truck productivity, indicating that a weighted ensemble approach based on the GMM analysis significantly improved the model accuracy. Based on the relative importance analysis, haul distance was the most crucial input variable for predicting truck productivity. This study provides a new approach to predicting truck productivity, which will help mining companies make sound budget decisions and improve mine planning.

Mar 2, 2023

By JUAN DIAZ, Kray Luxbacher, Steven Schafrik, Dionissios T. Hristopulos, Zach Agioutantis

Methane gas is emitted during both underground and surface coal mining. Underground coal mines need to monitor methane gas emissions to ensure adequate ventilation is provided to guarantee that methane concentrations remain low under different production and environmental conditions. Prediction of methane concentrations in underground mines can also contribute towards the successful management of methane gas emissions. The main objective of this research is to develop a forecasting methodology for methane gas emissions based on time series analysis. Methane time series data were retrieved from atmospheric monitoring systems (AMS) of three underground coal mines in the USA. The AMS data were stored and pre-processed using an Atmospheric Monitoring Analysis and Database Management system. Furthermore, different statistical dependence measures such as cross-correlation, autocorrelation, cross-covariance, and variograms were implemented to investigate the potential autocorrelations of methane gas as well as its association with auxiliary variables (barometric pressure and coal production). The autoregressive integrated moving average (ARIMA) time series model which is based on auto-correlations of the methane gas is investigated. It is established that ARIMA used in the one-step-ahead forecasting mode provides accurate estimates that match the direction (increase/decrease) of the methane gas emission data.

Aug 2, 2022