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By M. -H. Fillion

"Geotechnical stability analysis and design in open pit mines requires access to representative geological, structural, hydrogeological, and rock mass models. The quality and quantity of collected geomechanical data used to build such models can have significant implications in the design of safe and economically viable slopes. Data collection is a continuous process throughout the life of a mine. The process starts from exploration to conceptual/preliminary feasibility, feasibility, design and construction, operations (early production/late production), and mine closure.As geomechanical data is often limited at an early stage of a project, the estimated variability of the geotechnical factors may be larger than the actual data variability. This can potentially result in a conservative selection of the pit slope angle. Collecting additional geomechanical data at later stages of the mine development may contribute to reducing the uncertainty associated with the geotechnical properties and a steeper slope angle may be used for the design. This can result in significant economic benefits.This paper investigates the impact of access to new data over time, following a series of geomechanical data collection campaigns, on design decisions. This is illustrated by comparing the resulting slope design, at three stages of the mine project, at a South African open pit mine. To demonstrate this, a series of slope stability analyses were performed using limit equilibrium tools. For each project stage, the slope angle design was modified until a similar probability of failure of 5% or less was obtained. The corresponding factor of safety distributions for each project stage were then compared to evaluate the impact of collecting additional data on the resulting slope design.The results showed that data variability can differ significantly from one project stage to another. Data variability may be greater at more advanced project stages (i.e. a wider distribution of the factor of safety). Furthermore, the results showed that, even for the cases with greater variability, steeper slope angles were possible at more advanced stages for the proposed design requirement (probability of failure < 5%). In this investigation, as more data became available, the uncertainty associated with data variability could be sufficiently reduced to allow the selection of less conservative slope angles. This can be used as a managerial tool in developing data collection strategies and allocating the necessary funds, and can lead to important economic benefits to the mining operation."

Jan 1, 2016

By N. B. Prenn, R. H. Robinson

"The model described is a design and economic planning tool for analyzing surface mineral deposits. Mineralization, topography, costs and significant geologic features are input to the model. The results are:(i) final pit limits yielding the maximum total profit,(ii) annual cut-off grades and plant sizing yielding the maximum present value, and(iii) annual maps of the pit and annual production statistics for the mine, concentrator and smelter.Additionally, summaries are printed of the block mining sequence and cash flow. A special feature is an option to include dump-leaching operations. Stockpiling of material can also be simulated by the model. The model is built around theories of dynamic cut-off grades and a pit design algorithm. The dynamic cut-off grades maximize present value by examination of all economic and physical constraints for the optimum combination. The pit design algorithm is a set of rules formulated to find the maximum value from a special graph. The graph is different from graphs of analytical geometry, being made up of points and arrows connecting some of the points. These graph elements describe the relationship between any point in the deposit and the material which must be mined to get at that point. The model was designed to bring together the interdependent theories of economics, pit design and production scheduling."

Jan 1, 2014

By E. P. Preis, R. C. W. Webber-Youngman

The real cost of any mining incident has, empirically, proven to be estimation-driven, rather than factdriven. One of the main reasons for this lies with the complexity of the cost composition of any given mining incident. Incident costs comprise both direct and indirect cost factors, and in many cases the costs associated with these factors are incurred during different time periods following the incident. In this paper we aim to identify the various cost factors arising from mining incidents, provide a thorough understanding of all the potential cost factors identified, and draw general conclusions on the knowledge obtained. Furthermore, recommendations are made on how mining companies could use the results, in order to assist them in calculating the costs of mining incidents. The paper also provides suggestions for further research, with the emphasis on the most significant immeasurable cost factors, namely the costs of implementing job accommodations following an incident, the harm to company reputation, and the decreased productivity due to low worker morale/psychological factors following an incident. If mining companies are aware of and understand which factors could contribute to the cost of any given incident, future planning and incident cost estimations could be easier. It should, however, be noted that although this study provides a comprehensive list of cost factors (and detailed explanations), other unknown cost factors relating to mine incidents could prevail in extreme cases.

Jan 1, 2021

By M. L. Pududu, B. Ceki, K. Mohajane

This study was aimed at determining the effects of industrial action on profitability in the South African platinum mining sector. We compared companies where employees engaged in industrial action (affected companies) to strike-free companies (competing companies). Industrial action refers to strikes by rockdrillers, as these strikes typically result in the shutdown of production at the mines affected. A t-statistics analysis of significant differences in revenue and earnings of affected and non-affected platinum companies was conducted using data from platinum mining companies listed on the Johannesburg Stock Exchange from 2011 to 2015. Contrary to international studies, which suggest that the spillover effects of industrial action positively affect competing companies, our findings show that profits in the platinum sector decrease significantly during strike periods for both affected and competing companies. The results indicate industrial action is a threat to the profitability of all companies, and that employee demands should be prioritized and negotiated before they result in industrial action. Improved dialogue between management, labour unions, and employees in the platinum mining industry is recommended. The study contributes to the scanty literature on the effect of industrial action on the profitability of mining companies in a developing economy.

Dec 13, 2022

By L. C. Woollacott

Some of the factors that may influence the reliability of a consistent material balance derived from plant data were investigated, data taken from a sampling of the Iow-grade tin-flotation circuit at Rooiberg A Mine being used as the basis for the investigation. The importance of subjecting a calculated balance to a thorough analysis of its sensitivity to erors in assay and flow rate measurements is highlighted. Several simple guidelines are derived from the analysis of the Rooiberg data, and these appear to be generaly applicable to process-evaluation exercises and to the technique used for the smoothing of material balances.

Jan 1, 1987

By C. Musingwini, A. S. Nhleko, P. M. Muke

Open-pit mine planning includes the determination of a long-term open-pit mine production scheduling (OMPS) plan. The OMPS plan is generally a three-dimensional (3D) block extraction sequence that seeks to maximise the net present value (NPV) of future cash flows, while complying with technical and operational constraints. The OMPS problem is computationally complex because it involves the analysis of large datasets, while simultaneously incorporating both multiple hard and soft constraints. The OMPS problem has been solved using deterministic or exact approaches, heuristic, and metaheuristic models. When compared to heuristic and metaheuristic models, deterministic approaches tend to take much longer to solve the OMPS problem when the number of constraints increases. Therefore, this paper presents a metaheuristic model which utilises a genetic algorithm (GA) framework to solve the OMPS problem. The GA-based model was applied to the Newman1 and Zuck Small mining instances, which are publicly available from the online MineLib database. The NPVs for the OMPS plan generated using the GA-based model for the two case studies were compared to the best-known published MineLib solutions obtained using the TopoSort heuristic model at the time of this study. For the Newman1 instance the equivalent annual NPVs were approximately US$6.6 million for the GA-based solution and US$5.1 million for the TopoSort solution. For the Zuck Small mining instance, the equivalent annual NPVs were approximately US$99.8 million for the GA-based solution and US$102.5 mil for the TopoSort solution. These results show that the GA-based model produced comparable solutions to some of the best-known solutions, thus, indicating strong potential application of GA-based models to solve OMPS problems.

Sep 1, 2021

By R. S. McDonald

Auburn began operations 40 years ago with an office in Sudbury, Ontario, Canada, to provide services to Inco Limited. Over the next 40 years, operations expanded considerably, with projects being undertaken around the world, servicing the smelting and refining industry. Operating bases have been established in Canada, United States, Mexico, Chile, and Spain, with further growth expected to continue with an operating presence in South Africa. The Auburn Group of companies has serviced the smelting and refining industry for over 35 years. Auburn services a variety of metallurgical plants, and our worldwide experience has gathered considerable knowledge on industry processes and maintenance solutions. Today, the ?Business of Smelting? tackles demanding challenges, and operators search for opportunities and solutions to improve smelter maintenance, reduce operating costs, and decrease downtime. The Auburn Group has developed project teams, technologies, and equipment that provide specialised and innovative solutions to the non-ferrous metal industry to help address these challenges. Our Furnace Services team offers a variety of repair and maintenance services for metallurgical furnaces. Our specialised team has proven methods for completing projects quickly and safely. Our worldwide experience includes turnkey project management, construction, and various scopes of work for demolition and refractory repairs on all types of smelting and refining furnaces. Auburn developed the Results FirstTM programme to provide optimized solutions and results for smelter projects. The programme utilises a proven three-step model for improved results for schedule, budget, safety, and ramp-up to production. Our experienced Project Management teams can handle the planning and construction management of capital projects and plant shutdowns. Our projects have involved smelter/refinery modifications, oxygen plant installations, and sulphuric acid plant audits and maintenance. Our Equipment & Products division supplies specialised equipment and products, which are used in the metals industry for plant maintenance tasks. Our capability to design unique equipment, combined with our ability to source products worldwide, makes us a useful resource to find the best-suited equipment to meet the work-site demands. We specialise in custom remote-control units to handle specific maintenance solutions for smelters and refineries, and custom equipment designs for catalyst handling for Acid Plant maintenance. Our extensive knowledge of and experience with industrial technologies allows us to provide a wide range of Industrial Services. These services include vacuuming, high-pressure water blasting, chemical cleaning, pelletizing, dredging, ore bin clearing, roaster repairs, baghouse/ESP services, and manpower supply for both industrial plants and mines. Auburn?s combined strength of personnel experience, knowledge of industry processes, innovative project methods, and equipment technology make Auburn a unique resource for problem solving on every facet of smelter operations.

Jan 1, 2006

By D. Orynbassar, N. Madani

This work addresses the problem of geostatistical simulation of cross-correlated variables by factorization approaches in the case when the sampling pattern is unequal. A solution is presented, based on a Co-Gibbs sampler algorithm, by which the missing values can be imputed. In this algorithm, a heterotopic simple cokriging approach is introduced to take into account the cross-dependency of the undersampled variable with the secondary variable that is more available over the entire region. A real gold deposit is employed to test the algorithm. The imputation results are compared with other Gibbs sampler techniques for which simple cokriging and simple kriging are used. The results show that heterotopic simple cokriging outperforms the other two techniques. The imputed values are then employed for the purpose of resource estimation by using principal component analysis (PCA) as a factorization technique, and the output compared with traditional factorization approaches where the heterotopic part of the data is removed. Comparison of the results of these two techniques shows that the latter leads to substantial losses of important information in the case of an unequal sampling pattern, while the former is capable of reproducing better recovery functions.

Aug 1, 2021

By K. G. Philo, R. C. W. Webber-Youngman

mining, where data-driven decision making optimizes resource extraction, enhances safety, and ensures sustainability. The adoption of digital technologies like artificial intelligence (AI) and the Internet of Things has amplified the importance of digital information. However, the integrity and security of this information are paramount, leading to the exploration of blockchain technology as a potential solution for secure digital value exchange in mining. This research examines blockchain's capabilities, drawing insights from its applications in sectors like banking, government, healthcare, and entertainment, and evaluates their relevance to mining's core value chain processes. The study identifies blockchain's distributed ledger technology, cryptographic security, and decentralization as unique advantages that can revolutionize mining by enhancing transaction speed, reducing costs, and improving supply chain transparency and compliance with sustainability standards. Blockchain's transparent and auditable records can enhance business transparency, fostering trust among stakeholders, including investors and regulatory bodies. The technology's consensus mechanisms and smart contracts further promote trust in collaborative ventures. This research provides a foundational understanding for decision-makers in the mining industry to evaluate blockchain's feasibility and potential return on investment, guiding strategic planning and resource allocation for blockchain applications. By leveraging blockchain, mining companies can optimize operations, improve sustainability practices, and establish a robust foundation for future growth, positioning blockchain as a transformative technology in the sector

Jul 10, 2024

By T. P. Letsebe, L. Magwaza, T. A. Sethu, S. M. Rupprecht

"The authors were tasked with introducing safe and efficient drilling and blasting practices to a small artisanal mine located in the Eastern Province of Rwanda. The current mining methods employed at the mine are inefficient as rockbreaking is conducted utilizing hammer and chisel, or by drilling and blasting with no understanding of the rockbreaking process. The paper discusses the drill and blast cycle, as well as the associated activities necessary to support the mining cycle. The challenges and critical aspects in implementing drill and blast activities are discussed, as well as some of the technical aspects, i.e.drilling pattern, initiation and timing of the blast, and handling of misfires. Ancillary issues such as ventilation, training, communication, effective planning, logistics, and human relations are also examined. IntroductionRockbreaking accounts for 60% of the direct mining costs in small-scale mining. When drilling and blasting practices are poorly implemented the process becomes inefficient and dangerous. The introduction of a proven drill and blast system to artisanal mining offers a number of challenges, with safety being considered the backbone of any sustainable operation and a standard that cannot be compromised.The paper is based on a project at an artisanal cassiterite (tin) mining operation in a small village in the Kayonza District in the Eastern Province of Rwanda. A drill and blast programme utilizing industry best practice was introduced at an underground development end; a raise developed at an inclination of 23 degrees. The underground working is accessed via a 17 degree incline shaft with an operating length of 105 m and serviced by a single drum winder. The winder operates at a speed of about 3.5 m/min hoisting two 1 t wagons from the bottom of the incline to surface for tipping (Figure 1)."

Jan 1, 2017

By S. F. Böde, K. Böde

This paper focuses on developing a comprehensive and pragmatic information technology (IT) strategy for low-margin construction activities. This forms part of the realignment of the general business strategy, and refocusing the operational model. The main elements of the IT strategy formation are analysis of the current IT environment in terms of software and hardware, carrying out a gap analysis, and developing individual functional digitalisation strategies in construction execution based on Building Information Modelling (BIM), business administration processes, communication, business intelligence (BI) and reporting, and data security. Further, substantial emphasis is given to the sustainable strategy implementation in terms of hardware and software readjustments, their integration, user training, and defining the way forward.

Sep 1, 2021

By A. F. van der Merwe, R-D. Taylor, M. Jacobs, F. H. Conradie

Total bound moisture (TBM) is a typical quality indicator of industrial-grade gypsum. This gypsum is comprised of three distinct phases, namely anhydrite, dihydrate, and hemihydrate, of which only the latter is of much industrial use. TBM analysis is a lengthy laboratory procedure, and an artificial neural network (ANN) TBM inference measurement is proposed as a fast and online alternative. An ANN inference model for gypsum TBM based on plant data was developed. The inputs to the network were primarily focused on the plant's calciner, and different network topologies, data divisions, and transfer functions were investigated. Furthermore, the applicability of the TBM value as a quality indicator was investigated based on a gypsum phase analysis. A strong correlation between TBM and the gypsum hemihydrate and anhydrite content was found, validating the plant target TBM of 5.8% as a quality indicator. A network topology consisting of one hidden layer with logarithmic-sigmoid (logsig) and pure linear (purelin) transfer functions showed the best performance (R > 90%).

Oct 3, 2023

By S. Gan, E. van Niekerk, L. Birrell, D. Robbertze, L. Ncubi, B. Zhao

Quality assurance and quality control (or QAQC) plays a key role in safeguarding the level of confidence of the data generated during mineral exploration and mine development, and is also part of the reporting code requirements for resource estimation and reporting, as well as mining investment. Implementation of good policies and working protocols in quality management will result in the generation of reliable information, which is critical for decision-making on the future of the mining project. The use of certified reference materials, i.e., standard, blank, and duplicate samples, proves effective and efficient for ensuring the level of data confidence in terms of precision, accuracy, and sample contamination. This is well demonstrated by the practice of QC in the exploration programme for the chrysotile tailings storage facilities of Havelock Mine, using 1254 samples from 53 drill-holes. Different statistical tools were applied to analyse the assay results from these samples. The outcome substantiates that the QC practice established during the Havelock exploration project is aligned to best practice guidelines in the industry. The resource delineated indicates that the tailings material at Havelock could potentially become a significant source of supply to the global magnesium market.

Jul 2, 2022

By M. E. Rossi, C. Badenhorst

Conditional bias occurs when the expected value of the true grade conditional on the estimated grade is not equal to the estimated grade. It is a quantification of how the average of estimates differs from the true value. Conditional bias is present in all resource estimates due to the unavoidable properties of kriging, and indeed all linear estimation (regression) methods. In a mining resource estimation context, the degree of conditional bias is dependent on the spacing of the conditioning data; more data leads to the expectation of less conditional bias This paper discusses conditional bias from two perspectives: 1. 2. Estimates seeking to eliminate, as much as possible, conditional bias; and Estimates that accept a larger amount of conditional bias in resource models, in order to achieve a specific outcome. The problem of conditional bias in estimation can only be fully appreciated if the objective or purpose of a resource model is understood. There are instances where conditional bias should be avoided because it is not reasonable to make decisions using estimates that are known to be wrong in expected value; for example, when making a final decision in grade control with respect to the destination of the material. In most instances in the mining resource estimation context, however, the estimated values will not be “final estimates”, but “interim estimates”, meaning that in the future more data will be obtained, and the ”interim estimate” will then be updated. In this context, the most useful resource model is an interim model that is able to predict the final model estimates, despite not having all the data available that will be collected in the future. This is the objective, for example, of a recoverable “long-term” model developed prior to operating a mine, for example at the feasibility stage. It attempts to predict the ore that a processing plant will receive, well into the future. In such cases, it can be unequivocally demonstrated that conditional bias is not only unavoidable, it is a necessity.

Sep 1, 2021

By F. Dinter, C. McGregor, Q. G. Reynolds, L. Hockaday

The necessity of reducing greenhouse gas emissions to limit the impact of anthropogenic climate change means that all industrial processes should investigate their options towards decarbonization. Iron, steelmaking, aluminium, and cement production produce the most industrial emissions. Although most research focuses on decarbonizing these industries, minerals processing industries must be decarbonized to achieve net zero emissions goals by 2050. Incorporating renewable energy sources and avoiding the combustion of fossil fuels are two ways to reduce greenhouse gas emissions. This paper reports on the results from a dynamic process model developed to investigate the feasibility of concentrating solar thermal pretreatment of manganese ores to pretreat carbonate-rich manganese ores for increased ferromanganese smelter productivity and reduced greenhouse gas emissions. The results indicate that pretreated ores reduce the energy requirement for smelting significantly for some ores and lowers total carbon dioxide emissions by 13 to 19% compared to the traditional smelting route. A high-level economic evaluation shows that solar thermal treatment is financially viable for low cryptomelane, high braunite ore that is common in the Kalahari Manganese Field.

Dec 11, 2024

Falls of ground (FOG) still account for around 35 per cent of all fatalities in underground southern African mines. To help reduce FOG, appropriate support technology needs to be implemented, and a mindset and cultural change are required to make a significant change. Discipline plays a major role and needs attention, whilst appropriate first-world support technology is available to assist in the reduction of injuries and the improvement of productivity. Section 54 mine stoppages due to FOG are costly. Appropriate support should reduce these unnecessary stoppages. Coal mining has adapted leading support technologies over the years. Platinum and chrome mines have shown significant moves towards adopting leading and appropriate support technologies, seeing noteworthy changes in injury statistics for the better. In typical conventional underground mining operations, the use of temporary support components offers some protection to workers while the permanent and generally more elaborate support systems are installed or constructed. Nonetheless, FOG continue and still result in injuries to people. The author wishes to explore the options and practicality of making use of new-generation support products and technology to provide not only safer support operations, but to also enhance productivity at the working faces. This paper will examine the use of appropriate support technology as a means to making the working stope or development end a safer and more productive workplace.

Jan 1, 2012

By D. F. Malan

This paper provides an overview of the concepts of citations and journal impact factors, and the implications of these metrics for the Journal of the Southern African Institute of Mining and Metallurgy (JSAIMM). Two key research literature databases publish journal impact factors; namely, Web of Science and Scopus. Different equations are used to calculate journal impact factors and care should be exercised when comparing different journals. The JSAIMM has a low impact factor compared with some of the more prestigious journals. It nevertheless compares well with journals serving other mining sectors, such as the Canadian CIM Journal. The problems associated with journal impact factors are discussed. These include questionable editorial practices, the negative impact of this concept on good research, and the problem of a few highly cited papers distorting the journal impact factor. As a consequence, there is growing resistance to the use of journal impact factors to measure research excellence. The San Francisco Declaration on Research Assessment is a global movement striving for an alternative assessment of research quality. As a recommendation, the Editorial Board of the JSAIMM should adopt a pragmatic approach and not alter good journal policies simply to increase the journal impact factor. The focus should remain on publishing excellent quality papers. Marketing of the Journal, the quality of the published papers, and its open access policy should be used to counter the perception that journals with high impact factors are better options in which to publish good research material.

Sep 1, 2022

By G. J. McTeer, D. J. Rioux

Teck Metals Ltd operates an integrated zinc-lead complex at Trail, British Columbia, Canada. Since 1997, KIVCETTM flash smelting technology has been utilized for the treatment of zinc plant residues and lead concentrates. Trail Operations’ furnace uses four water-cooled jackets for bullion tapping. This paper provides an overview of KIVCET bullion tapping for the past 16 years, and discusses successes and challenges encountered with respect to operations, training, and monitoring.

Jan 1, 2014

By S. Langea, H. Lieberwirth

Impact crushers are common machines in comminution plants. Their high size-reduction ratio and relatively simple design, make them a preferred tool even when subjected to harsh wear, and producing a large quantity of fines in some applications. Until now the alignment of the operational parameters was an operator’s responsibility. Due to the random process characteristic this is mostly done based on empirical values and sensor data, such as power consumption. This paper describes a new approach for online process monitoring of the horizontal-shaft-impact crusher. The application of robust, low-cost acceleration sensors enables the permanent observation of the process characteristics. The operational and evaluation methods are determined on the basis of experiments. Subsequently the recorded measurements are analysed in regards of throughput, rotational speed and product particle size distribution. Occurring signal characteristics are described based on physical and technical principles. The measured data of the acceleration sensors at varying operation conditions provide insight in the course of process. The accurate utilisation yields the determination of the preferential process conditions providing the best balance between the pros and cons of an impact crusher. Both the experimental method and the data processing is discussed from a scientific perspective, displaying a completely new approach for the operation of impact crushers. Keywords: Impact crusher, acceleration sensors, data processing, particle size

Jan 1, 2020

By D. T. Jordan, L. C. Coetzee, G. Kalenga, T. Mahlangu, W. J. Shipman

Although online free cyanide analysers are widely available and used in gold leaching operations worldwide, reliable automated free cyanide concentration control is not consistently achieved in many of these operations. Effective cyanide concentration control is complex owing to amongst others, the long residence times and ore feed variations. Model Predictive Control (MPC) has been proven to provide superior cyanide concentration control over traditional proportional-integral-derivative (PID) control, leading to savings in operational costs and reduced leachable gold losses. In the first example reported in this paper, MPC has improved control of the free cyanide concentration by keeping it within the required range 73% of the time during testing, compared to the previous PID controller that only achieved this target 30% of the time. This represents a 143% improvement. Another example demonstrates a 22% reduction in cyanide usage as a result of using MPC. MPC functionality is rarely available on the programmable logic controllers (PLCs) and control systems installed at gold plants, hence it is implemented on a personal computer (PC) networked to the cyanide analyser and plant infrastructure. Mintek has developed an embedded MPC that installs into the Mintek Cynoprobe analyser, adding MPC functionality without the need for additional PC and network infrastructure, reducing installation costs. This allows plants to minimise their expenditure on additional infrastructure while gaining the benefits of superior MPC technology for multiple cyanide dosage points. This paper will present results showing that the embedded MPC performs as well as Mintek’s existing PC-based StarCS MPC controller, making it a viable alternative for infrastructure-constrained gold plants. Keywords: Model predictive control, gold cyanidation

Jan 1, 2020