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By M. E. Gershon

Conventional methods of drill hole site selection are reviewed briefly. Two approaches using geostatistics are then discussed, both of which have been shown to yield improved results. Finally, a branch and bound algorithm is described which will select the best locations for drilling from a user specified number of possible drill sites. Two options are discussed. First, the user can specify a maximum drilling investment or a maximum number of drill holes and the program will select the locations yielding the minimum estimation variance. This amounts to getting the most for a given investment. Alternatively, a maximum tolerable estimation variance can be specified and the program will select the number and location of the drill holes to obtain the desired information at a minimum cost. Another benefit of the approach is the quantification of the tradeoffs between investment and information obtained.

Jan 1, 1985

By S. Ripke

Between 2002 and 2004, the performance of a six million ton per year iron ore beneficiation plant dropped significantly. In a classic case of “who done it,” was it the mine, the concentrator, an ore change, or something else? While average annual final product grade decreased 8% (indicated by an increase in silicate gangue from 2.76% to 2.99%), the weight recovery also decreased by 8% (from 37.92% to 34.79%). This represents a loss of 832,000 tons of iron ore worth about $16 million for the two year period! The concentrator had been optimized to produce a high grade wet concentrate as feed to the dry side of the plant. But, did optimizing an individual unit operation’s grade give the best overall plant performance? In this paper, the investigation and solution to this mystery will be revealed.

Jan 1, 2007

By M. J. Price

The usage of Geographic Information Systems (GIS) is increasing rapidly throughout the Mining Industry, especially in the Industrial Minerals sector. GIS provides an efficient and robust link between spatial (often CADD) and tabular (database/spreadsheet) components. Mineral economists and corporate planners employ GIS to perform market analyses, to source raw materials, and to schedule and monitor deliveries to customers. Exploration and acquisition groups apply spatial analysis to identify high quality resources that meet economic guidelines. Mining regulators and environmental affairs departments expedite and monitor permitting, environmental compliance, and best management practices reclamation through GIS data management and Electronic Permitting. Operations staffs monitor overburden removal, material extraction, quality control, and stockpile volumes with GIS. This paper summarizes the many aspects of GIS in Industrial Minerals. It also introduces and addresses issues and concerns commonly encountered during a mining GIS implementation.

Jan 1, 2001

By A. Martikainen

Field tests concerning a fog mesh method for fog removal are discussed. The first tests were performed at the Pyhäsalmi Mine, Finland. As this study gave promising results, further studies were completed at the Orivesi Mine. The results of these most recent field tests are presented and the two studies are compared. The Orivesi test set consisted of four materials. These included air filter fabric, fibrous filter fabric, a plastic greenhouse mesh, and an aluminium mosquito net. The variation of the Orivesi results was more noticeable than what was found previously. The best fog removal effect of all tests was achieved with the aluminium mosquito net, while the plastic green-house mesh performed worst. The humidity reduction by aluminium net was more profound than any of its precedents. More mesh materials will be tested in the near future.

Jan 1, 2007

By R. Adsero

"In view of the decade long decline in worldwide mine equipment productivity and with heavy economic pressures and survival at risk, improvements for those remaining in the game are essential. The latest Multifactor Productivity data for the US mining industry indicates a continuing descent with Australia on a similar course. The world’s mining industry has a fleet of over 400 large draglines moving billions of tons of material annually. The most efficient use of this equipment resource will provide a competitive advantage to those companies who are committed to improving performance. A dragline monitoring system is a requirement for optimum operations. The monitor reports the facts. Focused actions can change the facts and create improved performance. Analyzing monitor data to build knowledge and create understanding is a beginning. Understanding the key productivity indicators for dragline operations and an effective benchmarking process are the basis for improvement. There is overwhelming evidence that adopting new technologies and concepts including AC drive technology can and will bring about a step change in dragline operating cost with improved production performance.STATE OF THE MINING INDUSTRY A high altitude review of the state of the mining industry provided by a study of multifactor productivity shows a continuation of lower and lower output year on year for the capital and labor inputs applied. The story is sadly similar for both U.S. mining and the Australian mining sector. In fact, according to PwC analysts the worlds mining equipment productivity has declined 20% over the past seven years. (Lumley, 2014) Although the reasons for the continuing decline in mining productivity are varied, the need for improvement is clear. The world’s mining industry fleet of well over 400 large draglines moves billions of tons of overburden and ore (phosphate, limestone, etc.) annually.This discussion will review a few of the tools available for improved productivity in dragline operations."

Jan 1, 2016

By Manoj Khandelwal, Minghui Liu, Jian Zhou, Kun Du

The waste rock and tailings backfill into the mined-out areas are the most effective method for solving the environmental pollution and surface disasters for nonferrous metals mines. In practice, the success and availability of backfill operations are dependent on the slurry fluidity and the strength properties of cement backfill. The transport of the slurry through the pipeline to the designated backfilling area relies on its eximious flow properties, while the appropriate strength of the filling body ensures the safe operation of the stope. In this paper, the effects of cement and aggregate types on the slurry fluidity and strength characteristics of cemented backfill are studied in detail, which are often ignored in other pieces of literature. Diffusivity is used as an indicator to evaluate the slurry fluidity. Various slurries whose concentrations ranging from 70%, 73%, 75%, 78%, and 80% are made with different aggregate ratios and cement-sand ratios are tested. It has been shown that slurry fluidity is inversely related to its concentration, but 78% is the “stopping point” for the deterioration of fluidity. The addition of rod-milled sand improves or worsens the cemented backfill (CB) strength depending on the amount of rob-milled sand. The uniaxial compression experiment results on 216 CB specimens produced by different combinations of influencing variables showed that CB specimens made from cement with superior mechanical properties have a higher uniaxial compressive strength (σucs). It has been also found that the effect of aggregate ratio on the CB strength is not singular, but works in conjunction with the curing time and the cement-sand ratio. The longer the curing time and the higher the cement content, the higher the CB’s σucs. To avoid the time-consuming and costly problem of obtaining the strength of the CB from indoor experiments, an SVR model capable of predicting the uniaxial compression strength of CB specimens is proposed, which is optimized by genetic algorithm (GA) and particle swarm optimization (PSO) algorithm. The results of the three performance indexes (MAPE, MSE, and R2) show the superior performance of the GA-SVR and PSO-SVR models and the agreement of the predicted results with the experimental results, which indicate that these two models can accurately predict the σucs of CB.

Feb 3, 2022

By A. Anani

The goal of hot mix asphalt (HMA) design is optimal material blending to meet Superpave specifications. HMA cost minimization has being modeled as linear programing (LP) (Awuah-Offei et al 2011) and mixed integer LP problems (Brown et al, 2012) and solved with commercial software such as LINDO and CPLEX. Often these software, which are designed to solve general optimization problems, have licenses that cost thousands of dollars. The objective of this study is to develop a novel solution algorithm to the HMA optimization problem presented by Brown et al. (2012), which will negate the need for expensive commercial packages and is specific to this problem. This novel algorithm is based on the branch and bound algorithm for solving mixed integer problems. The algorithm is incorporated into a software package with an easy-to-use graphical user interface. The developed algorithm is validated using a real-life HMA problem. Using this solution algorithm will save companies thousands of dollars, otherwise used to purchase software licenses.

Feb 23, 2014

By F. D. Ayhan

The aim of this study was to investigate desulfurization and de-ashing of a mixture of subbituminous coal and gangue minerals by the agglomeration method. For this purpose, experimental studies were conducted on a mixture containing subbituminous coal, pyrite, quartz and calcite. The effects of some parameters that markedly influence the effectiveness of selective oil agglomeration, such as solid concentration, pH, bridging liquid type and concentration, and depressant type and amount, were investigated. Agglomeration results showed that the usage of various depressants (Na2SiO3, FeCI3, corn starch, wheat starch) in the agglomeration medium has a positive effect on the reduction of ash and total sulfur content of agglomerates. It was found that an agglomerate product containing 3.03% total sulfur and 25.01% ash with a total sulfur reduction of 56.71% was obtained from a feed that contained 7% total sulfur and 43.58% ash when FeCI3 was used in the agglomeration medium. Key words: Desulfurization, De-ashing, Agglomeration, Coal, Gangue minerals

Jan 1, 2009

By Brenton Fletcher, Yongjun Peng, Wonder Chimonyo

As a cheap, renewable and non-toxic material, starch can contribute to the sustainability of the flotation process, albeit in a minor way as one type of reagent in systems involving materials with far greater impact. But the physical and chemical versatility of starch can help address another issue, namely, that of processing complex ores with decreasing grades of valuable minerals and increasing mixtures of gangue. This paper compares the results of two lab scale flotation studies where starches (native wheat starch (NWS), dextrin and two oxidised wheat starches) were used to depress two common gangue minerals, copper-activated pyrite and carbon (graphite), over a range of dosages. The oxidised starch with the larger molecular weight structures depressed copper-activated pyrite best, and the oxidised starch with lower molecular weight structures was better at depressing graphite. In both cases, the oxidised starches allowed greater recovery of chalcopyrite, pointing to selectivity potential. The extent to which the carbonyl and carboxyl moieties of the oxidised starches contribute to depressant performance is difficult to quantify, but it should not be discounted. Importantly, the results demonstrate relatively simple modifications of native starch by oxidation can yield structures suitable for depressing gangue minerals with diverse surface properties. The challenge remaining for greater application of modified starch depressants is being able to replicate the desired structures at scale in cold-water-soluble form.

Jan 18, 2021

By Meyer Klein

Decision theory is the formal theory of the logic of decisions in view of the decision maker's objectives, preferences, I beliefs, and available information, It usually deals with weighty economic problems involving irrevocable (or costly to reverse) decisions. Capital investment planning problems constitute an instance par excellence for application of the decision theory concepts. Decision theory as it is presently conceived has evolved in recent years. At first it concentrated on decisions in the face of total lack of information and on games with intelligent adversaries. The results of these efforts proved theoretically interesting, but practically of little applicability. In the last few years, stress has shifted to the introduction of subjective probabilities and preferences, and the results have been eminently successful in applications both in government and with- in business firms in the resolution of complex problems.

Jan 1, 1970

By K. Biswas

In general, it cannot be assumed that the strength of coal pillars remains constant over long time periods. Field observations indicate that a coal seam, especially when it contains a parting layer, deteriorates over time, reducing load-bearing capacity of the pillars. This paper discusses a unique approach to determine the time dependent strength of coal pillars in the field. Three coal pillars that were developed 5, 15 and 50 years ago were chosen for the study. Holes were drilled in coal and parting layers in each pillar and the strength profiles were determined for each hole using the Borehole Penetrometer. The strength data were treated statistically to establish time dependent strength equations for different layers. The results can be used to help estimate the loss of pillar capacity over time.

Jan 1, 1999

By E. Siami-Irdemoosa, S. R. Dindarloo

"Pareto analysis was used to investigate the failures database of a Hitachi EX1900 hydraulic shovel over one year of continuous operation. The hydraulic system and hydraulic links, hoses and piping were identified as the most critical system and subsystem, respectively. A three-parameter gamma distribution function was identified as the best fit for a probabilistic modeling of the time between failures (TBFs). This distribution was used in a Monte Carlo reliability analysis of the hydraulic system. Autoregressive integrated moving average (ARIMA), within the context of a time series analysis of the TBFs, was proposed as a viable alternative to the traditional technique of distribution fitting. The mean absolute percentage error (MAPE) metric was used to compare the two models. The MAPE value that resulted from the ARIMA was 66 percent smaller than that from the traditional technique in predicting the TBFs.Resumen ¦ Se usó análisis Pareto para investigar la base de datos de fallas de una pala hidráulica Hitachi EX1900 durante un periodo de un año de operación continua. Se identificó al sistema hidráulico y a los enlaces hidráulicos, mangueras y tuberías como el sistema y subsistema más importantes, respectivamente. Se identificó una función de distribución de tres parámetros gamma como el más apto para un modelado de probabilidades del tiempo transcurrido entre las fallas (Tabes por sus siglas en inglés). Esta distribución fue usada en un análisis de confiabilidad Monte Carlo para un sistema hidráulico. El promedio de movimiento integrado auto-regresivo (ARIMA por sus siglas en inglés), dentro del contexto de análisis de serie temporal de los TBFs, fue propuesto como una alternativa viable a la tradicional técnica de ajuste de distribución. Se usó el porcentaje de la media absoluta de error (MAPE) para comparar los dos modelos. El valor MAPE que resultó de la ARIMA fue 66 por ciento menor que el resultado obtenido con la técnica tradicional de predicción de TBFs."

Jan 1, 2015

By S. Frimpong, E. Siami-Irdemoosa, S. R. Dindarloo

"Electric and hydraulic shovels are the dominant loading machinery in surface mining operations. Despite their critical role in production and their high capital and operating costs, no reliable and comprehensive quantitative performance metric is available. In this paper, a stochastic shovel effectiveness (SSE) measure is proposed for the purpose of quantifying the performance effectiveness of these shovels. The SSE is based on the widely used method of overall equipment effectiveness (OEE) in the manufacturing industry. The OEE measures the performance effectiveness of equipment by multiplying its mechanical availability, utilization and production quality. In manufacturing processes, quality rate is the ratio of the total number of products minus the number of defective products – equivalent to the number of acceptable products – to the total number of products. The SSE similarly uses the mechanical-availability and utilization terms, but instead of quality rate it uses a new parameter named bucket rate.The variability or randomness of the input data, that is, availability, utilization and bucket rate, are further incorporated into the SSE, and a final stochastic SSE distribution is derived in the form of a probability density function. One hydraulic and one electric shovel in a surface mining operation were selected to test the validity of the proposed method. The SSE scores for the two shovels, operating continuously for one year, were derived and compared. As with the OEE, the three-parameter SSE method yielded more representative results for overall performance measurement than a single-parameter approach. Using Monte Carlo simulation, a three-parameter Weibull and a normal distribution were derived for quantifying the overall effectiveness of hydraulic and electric shovels, respectively. As a decision aid, the proposed methodology promises to render a more informative tool than traditional metrics for mine equipment maintenance and management."

Jan 1, 2015

By R. E. Cook

"Mineral deposits require substantial amounts of energy to transport and be processed into useable form, and as such present a real processing challenge in that the deposits are never homogeneous and ore body compositional characteristics are all over the map! Extracting the desired mineral(s) from the deposit at sufficient profit margin, despite severe fluctuations in market price, requires process automation architecture capable of supporting an integrated enterprise solution. Such an architecture will encompasses the activities of individuals, process units, process areas, plant level activities, mine management and business planning and accounting systems. Key to the automation process is the aspect of value generation. This paper brings together the various requirements for the automation of a mining enterprise and presents the different aspects of how to obtain value across the entire mining operation.INTRODUCTIONMinerals’ processing sites are historically long lived, 20 year life of mine is not uncommon and 75 years is not unheard of. Considering that hardware technology advancements are introduced every six months, or less, it is prudent to select process automation systems that adhere to “open” industrial standards versus proprietary based systems. In the minerals processing industry, the key to survival is driving the cost of production per unit volume to the lowest possible level and provide enough profit to sustain operations. Control system architecture and Business information technology are rapidly becoming important tools in the quest for productivity. Getting key dynamic business performance information at the right time to the right person or process unit is crucial to successfully achieving corporate goals. The process automation architecture selected must therefore be able to integrate to the various networking enterprises and business systems.The mining industry is generally known as an “extractive” industry that is very physically-oriented with respect to operations and the activities in which workers engage. Large numbers of people performing manual tasks in difficult surroundings, produce very variable outputs. But, times are changing – and so are industry best practices. While the nature of work still consists of activities such as ore extraction, ore movement, ore concentration, refinement and logistics, automation innovations are starting to change the nature of many of the production steps. The industry has transitioned from requiring more physical activities by workers, to more information management, automated control and collaboration within the operation. Humans are good at situational intervention and non-linear reasoning and do best when empowered with an overall production perspective. Machines and automation are good at repetitive functions, steady state operation, and managing transitions. Thus, a combination of advanced technology solutions, reliable and useful information and full human contribution are necessary to mining operations for value generation."

Jan 1, 2015

By R. E. Cook

"Mineral deposits require substantial amounts of energy to transport and be processed into usable form and, as such, present a real processing challenge in that the deposits are never homogeneous and orebody compositional characteristics are all over the map. Extracting the desired mineral(s) from the deposit at sufficient profit margin, despite severe fluctuations in market price, requires process automation architecture capable of supporting an integrated enterprise solution. Such an architecture will encompasses the activities of individuals, process units, process areas, plant level activities, mine management and business planning, and accounting systems. Key to the automation process is the aspect of value generation. This article brings together the various requirements for the automation of a mining enterprise and presents the different aspects of how to obtain value across the entire mining operation.Minerals’ processing sites are historically long lived, with 20-year life-of-mine not uncommon and 75 years not unheard of. Considering that hardware technology advancements are introduced every six months, or less, it is prudent to select process automation systems that adhere to “open” industrial standards versus proprietary based systems. In the minerals processing industry, the key to survival is driving the cost of production per unit volume to the lowest possible level and provide enough profit to sustain operations. Control system architecture and business information technology are rapidly becoming important tools in the quest for productivity. Getting key dynamic business performance information at the right time to the right person or process unit is crucial to successfully achieving corporate goals. The process automation architecture selected must, therefore, be able to integrate to the various networking enterprises and business systems.The mining industry is generally known as an extractive industry that is physically oriented with respect to operations and the activities in which workers engage. Large numbers of people performing manual tasks in difficult surroundings, produce variable outputs. But times are changing – and so are industry best practices. While the nature of work still consists of activities such as ore extraction, ore movement, ore concentration, refinement and logistics, automation innovations are starting to change the nature of many of the production steps. The industry has transitioned from requiring more physical activities by workers to more information management, automated control and collaboration within the operation. Humans are good at situational intervention and nonlinear reasoning and do best when empowered with an overall production perspective. Machines and automation are good at repetitive functions, steady state operation, and managing transitions. Thus, a combination of advanced technology solutions, reliable and useful information and full human contributions are necessary to mining operations for value generation."

Jan 1, 2015

By Dongjie Zhang, Shuxin Liu, Jianduo Wang

Broken rock mass and unreasonable stope structure parameters can cause excessive ore loss and dilution in sublevel caving; this is the main problem faced by caving mining in recent years. This paper proposes a stope structure parameter optimization method suitable for steeply inclined medium-thick broken ore bodies and evaluates the reliability and effectiveness through case studies. To solve the problem of large ore loss and dilution in the high-end wall sublevel caving method of Xilinhot fluorite mine, it is necessary to select proper stope structure parameters. Based on the theory of random media, an end-wall ore drawing experiment was carried out, and the bulk flow parameters needed to optimization of stope structure parameters were determined. In the experiment, it was found the draw-out body of high-end wall ore drawing showed a fine top and a thick bottom; the granular media had good fluidity. The reasonable caving step is determined to be 1.2 m instead of the 1.6 m originally used. Through the optimization experiment of the mining route position along the vein, the study found that the best route position is different with the ore body inclination. When the inclination angle of the ore body was 90°, the reasonable route was located in the center of the ore body. When the inclination angle of the ore body was between 85° and 90°, the route moved from the center of the ore body to the footwall at a rate of 22.5%. When the inclination angle of the ore body was between 80° and 85°, the route moved to the footwall at a rate of 54.8%. When the inclination angle of the ore body is not greater than 80°, the route should be arranged on the boundary of the footwall. Field application results showed the dilution rate reduced by 7.66% and the recovery rate increased by 7.31%. Field test results verify the effectiveness and applicability of the optimized stope structure, which corroborates the effectiveness and applicability of the optimized stope structure.

Mar 10, 2022

By F. Seymour

A dynamic programming algorithm is presented that takes a series of nested phases, a fixed mining rate schedule, a fixed plant production capacity schedule, and finds the mining and cutoff grade sequence that maximizes the Net Present Value. This tool allows the Mining Engineer to quickly look at project sensitivity to various production capacities, commodity prices, and costs. A description of the algorithm is given along with examples of how it has been used at Newmont.

Jan 1, 1995

By D. Bogunovic

The objective of this research was to conduct field-scale experiments at an operating surface coal mine in order to determine the impact of the bucket fill factor on dragline production rate and energy consumption. Data collected from a dragline monitoring system were recorded in a specifically designed software tool and the relationship among these parameters was established. an algorithm for the determination of the ?best? fill factor was developed and integrated in the software. It was determined for the analyzed dragline in the mine that energy consumption in the digging phase can be reduced by 36% and production rate can be increased by 1.4% for a bucket fill factor of about 80%, a fill distance of 19.8 m (65 ft) (i.e., 3.1 bucket lengths) and a bucket fill time of 15 sec. the method developed and applied in this study may help dragline operators to determine the fill factor that will increase production rates and reduce energy consumption in specific surface coal mines. Mining Engineering, 2011, Vol. 63, No. 8, pp. 48-53. Official publication of the society for Mining, Metallurgy and Exploration, Inc.

Jan 1, 2011

By Y. S. Roditis

Traditionally, open pit optimization has been used to produce a single outline which can guide the pit design. This paper describes how a series of optimum nested pits are utilized to: a. produce different mining sequences and to help in mine planning and phase design; b. evaluate different metallurgical processes, production scenarios and equipment size; c. investigate the sensitivity of a project to prices, recoveries, production rates, costs, ultimate pit slopes etc.

Jan 1, 1993

By J. A. Rusnak, K. M. Mohamed, M. A. Van Dyke, M. M. Sears, G. Rashed

"Researchers from the National Institute for Occupational Safety and Health (NIOSH) recently developed a coal-mass model to realistically simulate the deformation and loading behaviors of the ribs of coal pillars in underground coal mines. The scale-dependent properties (stiffness and strength) of coal material were considered in the coal-mass model. In this paper the orientation of face cleat with respect to driving direction was integrated in the coal-mass model. The controlling parameters (dimensionless coal-mass scale and fracture strains) of the modified coal-mass model were calibrated using a published case study of coal pillar strength. Numerical models with wide ranges of controlling parameters were conducted to simulate the test pillar. The best match between the numerical modeling results and the measured stresses and deformations was achieved by using a coal-mass scale of 30 and fracture plastic shear and tensile strains of 3.25% and 0.325 %, respectively. INTRODUCTION The failure of coal pillar ribs by itself are a major hazard in underground coal mines. Furthermore, failing ribs can indirectly contribute to roof and floor instability by increasing opening widths across intersections and entryways. Over the past decade, rib failures have resulted in 12 fatalities, representing 28% of the ground-fall fatalities in U.S. underground coal mines. Mining depth has always played a very important role in assessing rib stability. Gauna and Mark (2010) completed an analysis of rib fatalities that occurred between 1996 and 2010. One of their most prominent and influential findings was the identification of a relationship among fatalities, depth, and mining height. Therefore, Coal rib stability will continue to be a challenge for future deeper mines in U.S. coal basins. In the past several decades, research efforts have focused on roof support. The current rib control practice in U.S. coal mines is to select rib bolts through a trial-and-error approach (Mohamed et al., 2015a). Rib failure incidents can be can be substantially reduced or even eliminated by adopting an engineering-based coal rib design approach. The factors affecting rib stability in coal mines are numerous and mutually dependent. These factors include but not limited to mining height and overburden depth, interburden thickness for multiple-seam mining, coal strength, cleat density, entry direction with respect to cleat orientation, existence or absence of partings in the coal, percentage of extracted roof and/or floor rock, density of rib bolt support (Mohamed et al., 2015a). Moreover, it is difficult to isolate the particular effect of a specific factor on the overall rib stability. Therefore, a reliable empirical rib design approach is not achievable because it requires a significant number of case histories to be collected in order to have a reasonable range of all of the critical parameters. However, numerical modeling can be a practical tool to assist with rib support design if the modeling is realistic, which can only be achieved through calibration and validation of the numerical model against field data."

Jan 1, 2018