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By Gregory A. Johnson

Operations and Maintenance departments have long had an adversarial relationship. The widespread evolution and adoption of modern management techniques such as Reliability Centered Maintenance (RCM) and Lean Production however has driven interest in working co-operatively to optimize overall plant performance. Mining and minerals operations have long adopted RCM in maintenance, and are now adopting Lean throughout the organization. Modern management initiatives like these explicitly call for co-operation between the two disciplines of maintenance and production and many advances have been made in the realms of people and methodology. One area that has lagged behind in supporting these developments however is information systems. Enterprise Asset Management (EAM) systems in maintenance and newer Manufacturing Execution Systems (MES) in operations have not been truly integrated in the way needed. Complicated plants, different software architectures, continually changing conditions and many variables have lead to systems problems which have contributed to the maintenance/operations divide. Master data synchronization (the ?plant tree?) and integrated reporting of real-time data with transactional data are just two of the issues that are being solved by new approaches in information technology including web services and service orientated architectures. New technologies are coming on-stream to enable the final ?bridging of the gap?.

Feb 1, 2008

Operations and maintenance departments have had a long-standing adversarial relationship. The widespread evolution and adoption of modern management techniques, such as reliability centered maintenance (RCM) and Lean, however, has driven interest in working co-operatively to optimize overall plant performance. Mining and minerals operations have long adopted RCM in maintenance and are now adopting Lean throughout organizations. Such modern management initiatives explicitly call for co-operation between the two disciplines of maintenance and production and many advances have been made in terms of people and methodology. One area that has lagged behind in supporting these developments, however, is information systems. Enterprise asset management (EAM) systems in maintenance and newer manufacturing execution systems (MES) in operations have not been truly integrated in the needed ways. Complicated plants, different software architectures, continually changing conditions and many other variables have led to systems problems, which have contributed to the maintenance/operations divide. Master data synchronization (the plant tree) and integrated reporting of real-time data with transactional data are just two of the issues that are being solved by new approaches in information technology, including web services and service orientated architectures. New technologies are coming on-stream to enable the final bridging of the gap.

Jan 1, 2009

By M. E. Rossi

Reconciliation of long-term block model reserves and mine production frequently shows significant discrepancies. This reconciliation can be done comparing the long-term block model reserves against a grade control model (generally, a model based on blast holes or production data). in this paper called an FI factor for tonnages, grade, and ounces; and also it should be done comparing the grade control model to the mill feed (or loaded to heaps) tonnages, grades and ounces (called an F2 factor). The long-term model usually contains blocks with dimensions larger than the size of the selective mining unit (SMU) of the operation. The smoothing effect of an estimator such as kriging will generally result in a grade-tonnage curve that does not match the grade-tonnage curve of the SMU's to be recovered. This problem is partly to blame for the reconciliation discrepancies found. In addition, in-pit perfect selection is impossible. and therefore the grade-tonnage predictions based on blast holes also need to be assessed, considering both unplanned dilution and the errors of estimation of the grade control model. This paper will focus on using conditional simulations to assess the uncertainty of the predicted grade-tonnage curve in terms of minable reserves, and in the framework of long-term mine planning. Quantifying the uncertainty in no uncertain terms is done in conjunction with a popular pit optimizer, which will yield not one, but several possible minable reserves, and therefore a range of possible minable tonnages and grades per pit shell or scheduled phase. This is a step further from the usual sensitivity analyses that are performed for deposit evaluation or development planning. Specifically, this approach takes into account the volume-variance relationship, the selectivity of the mining operation, planned and unplanned dilution. and carries the local uncertainty implicit in grade estimation into the mine design and mine planning phases. The motivation for the approach is discussed through an example, as well as a description of the procedures and steps involved.

Jan 1, 1998

Improving Pelletisation of Pyrite Cinder by High Pressure Roller Grinding As an important secondary resource for ironmaking, pyrite cinder is characterised by coarse particle size, low specific surface area, high porosity and poor surface activity, which leads to high bentonite dosage, low strength and too high moisture of green balls and high roasting temperature. In this paper, a study of improving the pelletisation of pyrite cinder containing feed by using high pressure roll grinding (HPRG) was presented, which aimed to improve the quality of green pellets and reinforce roasting performance pellets. It is shown that pyrite cinder is characterised by complicated mineral compositions dominated by haematite and metal sulfides, porous surface and middle class ballability, leading to higher balling moisture, higher bentonite dosage and higher firing temperature for pellet hardening. The pelletisation of pyrite cinder can be improved by high pressure roller grinding and blending with magnetite in the pellet feed. The former is probably ascribed to the increase in specific surface areas of pellet feed from 850 cm2+g to 1690 cm2+g when the pellet feed passes through roller twice. Good quality green balls and fired pellets can be made from feed comprising 40 - 60 per cent pyrite cinder and 60 - 40 per cent magnetite concentrate at small scale under the following conditions: 1.2 per cent bentonite, feed passing through roller twice at 7 per cent moisture at 1.5 ton pressure, balling at 13 per cent moisture for 13 min, preheating at 1050¦C for 12 min and firing at 1300¦C for 8 min. Green balls possess such properties as drop numbers of 6.5 times, compressive strength of 19.1 Newton and thermal shock temperature of 533¦C. Fired pellets are imparted high compressive strength of over 3000 Newton per pellet. Small scale tests have been proven by pilot scale tests that high grade fired pellets are made, assaying 63 per cent Fe and minor other impurities, such as sulfur and phosphorus except for copper content. The fired pellets made of three blends possess excellent metallurgical performance, such as reducibility index higher than 65 per cent, reduction swelling index lower than 15 per cent and low temperature reduction degradation lower than2 per cent. Especially the compressive strength after reduction is higher 719Newton per pellet.

Sep 13, 2010

By M Xu and, P F. Wells, A N. Kerr, Y Shields

Triethylene tetramine (TETA) has been used in combination with sodium sulfite (sulfite) for pyrrhotite depression at Clarabelle Mill since 1998. This combination has been highly successful at reducing pyrrhotite levels in the bulk (Ni/Cu) concentrate. Although highly effective, the roles of TETA and sulfite are not well understood. Treating bulk samples of the circuit feeds through the miniplant enabled the effects of circuit configuration on the performance of the pyrrhotite rejection circuits at Clarabelle to be determined. Reasons for the different performance of the non-magnetic pyrrhotite rejection circuit in the miniplant were investigated and tested in the laboratory. The effect of different grinding environments in the laboratory was examined to better understand the depressing mechanisms of TETA/sulfite. Modification of the grinding chemistry improved the selectivity of pentlandite over pyrrhotite in the presence of TETA/sulfite at current plant dosages.

Jan 1, 2005

Improving Pentlandite Selectivity Over Pyrrhotite Using Reagents

Sep 13, 2010

By D. J. Turk

Faced with decreasing production from the gold heap leach operation, Robinson implemented a drilling and blasting program on the leach pads in 1993. This program offset some of the negative effects of low ore permeability and short circuiting of leach solution that resulted in lower than optimum recoveries. The drilling and blasting program created new solution flow paths and increased gold recovery. Production and pulp assays at depth intervals, prior to and following drilling and blasting, reveal the degree of short circuiting and benefits of the program.

Jan 1, 1995

Laboratory tests were conducted in a full-scale continuous miner test gallery to evaluate resulting dust levels for changes in face airflow, spray water quantity and pressure, and mining height. The minimum and maximum values tested for each parameter were as follows: airflows between 1.42 and 6.14 m3/sec, water flows between 56.8 and 132.5 lpm, nozzles pressures between 413 and 1379 kPa, and mining heights between 1.52 and 2.74 m. Each of these parameters were evaluated for four common spray system designs. Respirable dust samples were collected in the operator's cab on the miner and in the immediate return. Second-order polynomial models were used to represent expected dust levels and multiple stepwise regression was used to identify significant control parameters for inclusion in the models. Separate models were developed for dust levels at the operator and return locations and for each individual spray system. Interaction between control parameters and curvature effects were found in most models. The analysis indicated that at the operator location, airflow and mining height had the most significant impact on respirable dust levels. In the return, airflow and water pressure were typically the most significant parameters. The models developed for each spray system design can be used by mine operators to guide application of control parameters for a variety of operating conditions and mining heights.

Jan 1, 1994

By M. Akser, M. Tomas

Six Sigma is a methodology that uses a structured and disciplined approach to improve process performance (higher throughput, better recovery, lower cost, shorter cycle time, etc.). Specially trained people called “black belts” lead and manage Six Sigma projects. Black belts, with assistance from their team, ensure that projects follow the DMAIC (define, measure, analyze, implement and control) process phases. Timely completion of each project, with measurable deliverables, is key to Six Sigma’s significant financial success. Implementation of Six Sigma has been growing in recent years in a wide range of industries. The heavy mineral industry, like many other industries, could benefit from what Six Sigma has to offer. Specific Six Sigma project examples are included from DuPont’s Heavy Mineral Production Plant in Florida.

Jan 1, 2005

By R. J. Snoby, J. K. Alderman

Although once fairly common as a method of coal preparation in the United States, dry cleaning has virtually disappeared. Low-rank coals used for power generation in the western U.S. are suited for dry cleaning because water has limited availability in the American west. Surface moisture added through wet cleaning offsets energy improvement achieved from mineral matter reduction. Information will be presented on the commercial application of dry cleaning in North America, the historic development and current status of the technology, and the introduction of modern processing theory and control technology to the design of dry cleaning equipment and plants.

Jan 1, 2001

"Exploitation of an ore deposit can be optimized by adapting the beneficiation processes to the properties of individual ore blocks. This can involve switching in and out certain treatment steps, or setting their controlling parameters. Optimizing this set of decisions requires the full conditional distribution of all relevant physical parameters and chemical attributes of the feed, including concentration of value elements and abundance of penalty elements. As a first step towards adaptive processing, the mapping of adaptive decisions is explored based on the composition, in value and penalty elements, of the selective mining units.Conditional distributions at block support are derived from cokriging and geostatistical simulation of log-ratios. A one-to-one log-ratio transformation is applied to the data, followed by modelling via classical multivariate geostatistical tools, and subsequent back-transforming of predictions and simulations. Back-transformed point-support simulations can then be averaged to obtain block averages that are fed into the process chain model.The approach is illustrated with a ‘toy’ example where a fourcomponent system (a value element, two penalty elements, and some liberable material) is beneficiated through a chain of technical processes. The results show that a gain function based on full distributions outperforms the more traditional approach of using unbiased estimates."

Jan 1, 2015

By T. J. Otto, G. C. Lindeque

Productivity is improved by increasing the ratio of output to input. In an operating open-pit mine, improving the productivity of heavy mining equipment (HME) enables the unit cost of production to be reduced. To optimize HME productivity, the Kolomela open-pit iron ore mine transitioned to an enhanced short-term mine planning (STMP) process that supports the application of a manufacturing-type operating model. At the core of the enhanced STMP process is a focus on integration across the open-pit mining value chain. The interdependencies between mining activities are highlighted and emphasized, thus ensuring that mining activities are synchronized. The improvements related to HME productivity were monitored from 2019 to 2020. The utilization of mining area in the Leeuwfontein pit improved from 71% to 90%, and the blasting frequency reduced by 14% while the average blast size increased by 17%. The distance travelled during shovel relocations between mining phases reduced by 16%, and the lost time associated with drills relocating reduced by 53%. These productivity improvements resulted in an 11% increase in the loading rate of the main waste shovel at Kolomela from 0.9 Mt/month in 2019 to 1.0 Mt/month in 2020. The enhanced STMP process can be adapted to other open-pit mining operations.

Nov 1, 2021

By Nick Lewis

Farce Mining of Texas is a surface coal mine located in Laredo, Texas. Farce mines and sells approximately 600,000 tons /year of bituminous coal. A map showing the location of Laredo is provided in Figure 1. As shown, Laredo is located on the border between the United States and Mexico. The mine property runs to the Rio Grande River, the border between the two countries. Farce pumps water from the Rio Grande for use in their coal preparation plant. Laredo’s climate is quite dry with annual rainfall averaging about 12” per year. Also, due to the southern location, Laredo is quite hot. It is common for the temperature to reach 100” F in March and maintain these temperatures through September.

Jan 1, 1994

By M. Turek

Cost management in the conditions of increasing competition and unforeseen market turbulence constitutes one of the key areas of the enterprise?s activity. In the last two years the demand for hard coal on the domestic and global market of non-renewable resources has increased significantly. Polish hard coal mining industry, as an industry in the stage of decline, received a chance for rejuvenation. However, one of the most significant conditions of seizing this opportunity is the rationalization of mining costs and improvement of production effectiveness. Due to the significance of this issue, the main objective of the paper is to identify the possibilities of improving the production effectiveness in the hard coal mining industry. In order to meet such an objective, in the first part of the paper we measured effectiveness in the Polish hard coal mines in years 2006- 2011. The research encompassed three out of five mining enterprises operating in the country. Then based on the received results, guidelines concerning the improvement of effectiveness of production were created, taking into consideration infrastructural, technical, economic and organizational determinants. Furthermore, opportunities and threats for improving the production effectiveness, stemming from the external conditions have also been indicated.

Aug 1, 2013

By S. G. Britton

Thin seam mining presents unique challenges when management or economic conditions require significant productivity increases. These challenges are increased depending upon the presence of various external factors such as labor unions, Federal and state regulations, and market characteristics. This paper explores the turn-around situation occurring at Tanoma Mining Company (TMC), a medium-sized underground coal mining company in central Pennsylvania, USA. Using a systematic approach of improving management controls and direction, labor relations, and communications, coupled with an intensive upgrade/rebuild/replacement program for equipment and systems used at the mine, TMC has begun reversing its' cashflow position from negative to positive within two years.

Jan 1, 1991

By I. Yelkin, Erico Tabosa, Alex Jankovic, R. Hayashida, R. Faveere

"The mining industry faces growing challenges from more complex and lower grade deposits, rising costs, limited energy and water availability, and increasing societal pressure to operate more sustainably. Mining operations need to be more efficient, not just to reduce environmental impact, but also to remain economically viable.To maximize profitability and sustainability, existing operations and new projects must consider integration and optimization of all stages of production. A mining operation is essentially a series of inter-connected processes, with the performance and outputs of each stage affecting the subsequent ones. Optimizing stages in isolation can result in sub-optimal overall performance.The industry has long recognized the benefits of holistic optimization using the Mine-to-Mill concept, and there are many well documented successes. However, it is increasingly common to observe operations simply increasing explosive consumption in the mine and expecting optimization of the entire value chain (mining and processing). For true holistic optimization, blast intensity is not necessarily increased, but rather adjusted to best suit the requirements of the different types of ores treated, the circuit configuration and equipment, installed comminution power and the downstream beneficiation processes. It is a fully integrated effort with optimization of many aspects in the mine, comminution and separation processes.To be successful, optimization of the production chain from mine to process requires a site-specific, structured methodology supported by extensive ore characterization, auditing, surveys, data analysis, mathematical modelling simulations and a cost / benefit analysis. Following this methodology, optimization strategies are rapidly identified and implemented considering mine and plant constraints. Management needs to set up appropriate KPIs and site personnel need to be trained for the new operating strategies to be successfully incorporated into site practices and procedures in the production environment. This will ensure the benefits are achieved and maintained. This paper describes the methodology employed by Hatch to improve overall efficiency and profitability from mine to process. Two case study examples at Russian gold operations and benefits achieved are presented."

Jan 1, 2018

By Gianni Bartolacci, Patrice Nadeau, Szatvanyi. Gerard, Carl Duchesne, Claude Chrétien

"Combustion is used throughout the mineral processing industry to produce steam in boilers, to dry concentrates in rotary dryers, and to apply heat treatments in pyrometallurgical furnaces. Tight combustion control is very important in latter type of furnace since the combustion conditions directly affect final ore quality. However, achieving tight combustion control is not straightforward since most of the flames encountered in industry are turbulent non-premixed flames, they are affected by several unmeasured disturbances and are often produced by burning several types of fuel simultaneously, some of them coming from other parts of the plant. A novel method is proposed in this paper to improve process and product quality control as well as to optimize the combustion conditions based on digital flame color images. Multivariate Image Analysis and Regression is to used extract the flame color characteristics from images to predict the solids discharge temperature of an industrial rotary kiln. It is shown that this method yield extremely good 10 minutes ahead forecast of the temperature and should lead to a substantial reduction in product quality variability as well as in fuel consumption.INTRODUCTIONFuel-fired furnaces are often used in the mineral processing industry for various purposes, such as for the production of steam (utility boiler), in conjunction with rotary dryers to dry mineral concentrates or in pyrometallurgical processes for induration, roasting, and so forth. These furnaces are necessary in the supply chain from the mine to the metals, but their operating costs are constantly rising due to the fluctuations in fuel prices. Moreover, these processes are now targeted by the Kyoto Protocol since they are energy intensive and they produce significant amounts of CO2 and other pollutants such CO, NOx and SO2. To achieve both a reduction in operating costs (i.e. fuel consumption) and in pollutant emissions while maintaining or improving product quality, one needs to have a very good control of the combustion process."

Jan 1, 2005

By Elliott Giles

"Measuring a blast’s performance based on the bucket fill time or “diggability” has always been achallenge due to the subjectivity generally involved. The diggability of a blast is often based onopinions and speculation without the data to properly support the claim. This paper focuses howthe blast design can impact diggability and how it can be properly measured."

Jan 1, 2016

By B. M. Coombes

The McCracken and Stacey (1989) method of assessing geotechnical risk for largediameter raisebored shafts has been the basis for most Australian pre-construction raisebore investigations for the past 20 years. At the time of its publication, the McCracken and Stacey (M&S) Method did not include a database of raisebore diameter and rock mass conditions versus actual performance. It did, however, provide a chart that quantified geotechnical risk in terms of proposed shaft diameter and the raisebore rock quality index, QR. Two parameters, RQD/Jn and Jr/Ja were identified as being critical to raisebore stability, but the contribution of these to overall raisebore stability was not quantified. Peck and Lee (2008) published a database of raisebore performance from Australian case histories. Raisebore diameter and ground conditions, in terms of a Lower Bound QR value, were presented for 50 cases versus raisebore performance. This paper updates the database with further case histories and corrected SRF values. This paper further evaluates the reasons for the variable raisebore performance for similar RSR values. For all case histories, three parameters, RQD/Jn, Jr/Ja and Jw/SRF are investigated to assess their influence on raisebore performance.

May 1, 2011

By L. B. Hales

Expert control of grinding and flotation plants has been successfully used in the minerals industry since the 1970?s. The earliest of these systems were written in a hard-coded fashion in FORTRAN, BASIC or Pascal. Second generation systems were built using the first experimental expert system shells that were being developed in the artificial intelligence community. Later systems were deployed in expert systems designed for real-time processing plants that also include the ability to model the process with neural network models and optimize setpoint selection through the use of genetic algorithms. [1,2] In spite of the fact that significant performance increases have been achieved using these systems they are not perfect and can be improved. They suffer from the static nature of their rules and to a degree the process models. There is an opportunity to further increase system performance by systematically taking advantage of the tremendous amount of data produced by the expert system to improve the design, the heuristic rules, the model topologies and the use of the models. Data mining refers to extracting or mining knowledge from large amounts of data where the objective is to automatically analyze, classify and summarize the data to automatically discover and characterize trends in it and to automatically flag anomalies. [3] Clearly, modern process control systems are capable of collecting vast amounts of data. Without a doubt, these data contain important information on the operation of our plants and their ultimate optimization. Coupling the information mined from these data with Expert Control Systems should produce more effective control and greater knowledge of the grinding process and the flotation process. Now, with the advent of effective monitoring of entire minerals plant electric consumption it is possible to not only optimize plant production in real-time it is possible to analyze total plant electrical consumption and incorporate it into the plant control logic thereby improving the overall plant economic performance. This is particularly important with the ever more complex power contracts that plants operate under.

Jan 1, 2012