Scielo RSS <![CDATA[Journal of the Southern African Institute of Mining and Metallurgy]]> vol. 116 num. 3 lang. es <![CDATA[SciELO Logo]]> <![CDATA[<b>Mine Planning and Equipment Selection (MPES 2015)</b>]]> <![CDATA[<b>A few personal memories of David Rankin</b>]]> <![CDATA[<b>Sustainability</b>]]> <![CDATA[<b>Final breakthrough at the Hallandsâs tunnel marks an outstanding pioneering achievement</b>]]> <![CDATA[<b>Estimating cost of equity in project discount rates</b><b>: </b><b>comparison of the Capital Asset Pricing Model and Gordon's Wealth Growth Model</b>]]> Since the Global Financial Crisis (GFC) in mid-2008, capital has been more difficult to access. Mining projects must contend with projects from other industries for scarce capital. A decision to invest available capital in mineral projects requires that valuation be conducted to assess the expected return on the projects. The discounted cash flow (DCF) analysis is generally applied for the valuation of mining projects, whereby future cash flows are discounted to present value using an appropriate discount rate. The discount rate significantly affects the outcome of a valuation. Economic and finance theory provides tools to calculate discount rates. The discount rate must account for factors such as the risk and stage of development of the mineral project; hence the appropriate discount rate to utilize in a project is often a subject of debate. The discount rate is the weighted sum of the cost of debt and equity. There are several methods for determining the cost of equity. This study considers the commonly applied Capital Asset Pricing Model (CAPM) and Gordon's Wealth Growth Model because of their simplicity and availability of parameters required to estimate the cost of equity. This study explores how differences in the cost of equity obtained by these two methods can be explained for a mining environment. Data for empirical analysis were collected from the I-Net Bridge, McGregor BFA, and Bloomberg databases. It was found that Gordon's Wealth Growth Model provides better estimates of the cost of equity compared to the CAPM under depressed market conditions. Therefore, this research recommends that Gordon's Wealth Growth Model be used to estimate the discount rates for mining projects during periods of depressed market conditions. <![CDATA[<b>Estimating mine planning software utilization for decision-making strategies in the South African coal mining sector</b>]]> Mine planning software continues to be an important factor when it comes to the development of the South African mining industry. To contribute to this development, a new methodology to define and measure mine planning software utilization in the South African coal mining sector within an evolving data-set framework was developed. An initial data-set showing the mine planning software providers, their corresponding software solutions, as well as the software capabilities and information on the number of licences was collected and compiled in 2012 in an online database for software utilized in the South African mining industry. Details of the database development and implementation were published in the Journal of the Southern African Institute of Mining and Metallurgy in 2013. In 2014 the data-set was updated with additional and new information. In this paper, using the 2012 and 2014 time-stamps, a methodology for estimating the software utilization is developed. In this methodology, three variables: commodity, functionality, and time factor are used to define and measure the software utilization in order to ultimately inform decision-making strategies for software utilization. Utilization in the coal sector was measured according to six different functionalities, namely Geological Data Management, Geological Modelling and Resource Estimation, Design and Layout, Scheduling, Financial Valuation and Optimization. The methodology is useful for stakeholders reviewing existing software combinations or intending to purchase new software in the near future and wanting to estimate the comparative attractiveness of a certain software package. These stakeholders include mining companies, consulting companies, educational institutions, and software providers. The work presented in this paper is part of a PhD research study in the School of Mining Engineering at the University of the Witwatersrand. <![CDATA[<b>Determination of value at risk for long-term production planning in open pit mines in the presence of price uncertainty</b>]]> Mine planning is a multidisciplinary procedure that aims to guarantee the profitability of a mining operation in changing and uncertain conditions. Mine plans are normally classified as long-term, intermediate-term, and short-term plans, and many factors affect the preciseness of these plans and cause deviations in reaching the objectives. Commodity price is the heart of mine planning, but it has a changing and uncertain nature. Therefore, the determination of mine plans in the presence of uncertain mineral price is a challenge. A robust mine plan reduces the risk of early mine closure. A procedure is presented to determine the value at risk (VaR) in any possible mine planning alternative. VaR is considered together with downside risk and upside potential in order to select the most profitable and least risky plan. The model is tested on a small iron ore deposit. <![CDATA[<b>Impact of the South African mineral resource royalty on cut-off grades for narrow, tabular Witwatersrand gold deposits</b>]]> A mineral resource royalty is payment to the holder of mineral rights for the utilization of the mineral resource. In South Africa, this payment is made to the State as holder of the mineral rights (The Mineral and Petroleum Resources Royalty Act of 2008). The principle purpose of this research paper is to identify if the State is benefitting from the mineral resource royalty by considering its impact on seven individual Witwatersrand gold mines. For this study, a simple financial optimiser model was created in Microsoft Excel that links the ore flow, block listing and the cash flow (excluding or including the cost of the mineral resource royalty). Mixed integer linear programing (the Excel Solver function) is utilised to optimise either profit or NPV (at 9% and 12%) by adjusting the cut-off grade. The impact on each of the seven mines mine was different but overall R7.9 billion is estimated to be paid in mineral resource royalty over their expectedremaining lives. Due to the cost of the mineral resource royalty andincreasing the cut-off grades, the total revenue decreases by R10 billion. Asignificant portion of this lost revenue would have been paid to the State inthe forms of other taxation including company income tax which decreasesby R2.8 billion. It is recommended that an industry wide investigation beconducted to determine if the resource royalty is adding to the State'srevenue, or destroying value including premature job losses. <![CDATA[<b>Rock Strength and Geometallurgical Modelling, Mogalakwena Mine</b>]]> Rock properties have a material impact on mining processes, including drilling performance. An investigation using point loaded index (PLI) data converted to uniaxial compressive strength (UCS) has revealed that a direct relationship between grain size and UCS exists at Mogalakwena Mine. This correlation is best seen in unaltered rock, with lower correlations for altered rock types. Measurements from the new RockMa system installed on drill rigs can be used to obtain rock strength data to validate the current rock strength domains and create additional data for the next benches below. An investigation of penetration rates in different lithologies shows that rock composition plays an important role in determining drill performance. Additionally, there is an inverse relationship between rock strength and drilling penetration rate - a measure of how efficiently a hole is drilled. The domaining of grain-size-adjusted UCS at Mogalakwena Mine will allow more accurate scheduling of drill rigs through increased knowledge of rock strength in various areas. Successful rock strength domaining has the potential to be incorporated into blast indexing and predicting crushing/milling performance. <![CDATA[<b>Microscopic analyses of Bushveld Complex rocks under the influence of high temperatures</b>]]> The South African platinum mines in the Bushveld Complex (BC) have unique features that distinguish them from the gold mines. They have a higher horizontal stress closer to the surface, lower occurrence of seismic activity (caused mainly by pillar failure), and are sited in an area of high geothermal gradient. One of the future challenges of platinum mining is the increasing temperatures as the mining depth increases. High temperatures invariably bring about higher ventilation costs and require different approaches to human factors and ergonomics. Excavation stability would also be another area of concern due to increasing stresses. In this investigation, the effect of temperature on the physical and chemical properties of selected Bushveld rocks (chromitite, pyroxenite, norite, leuconorite, gabbronorite, mottled anorthosite, varitextured anorthosite, granite, and granofels) was studied by means of optical microscopy and scanning electron microscopy using energy-dispersive X-ray spectrometry (SEM-EDX). The rock specimens were heated in a temperature-controlled oven a rate of 2°C /min to 50°C, 100°C, and 140°C and kept at temperature for five consecutive days. Samples were allowed to cool to ambient temperature (approximately 20°C) before image capturing. Micrographs of the specimens were taken before and after heat treatment. All the SEM samples were also subjected to heating and cooling on alternate days for ten days in order to observe the effect of repeated heating and cooling on the rocks. The results of the optical microscopy analyses showed minor physical changes in the rocks. The SEM images revealed that cracks initiating at lower temperatures extend with increasing temperature. The chemical analyses showed that the temperature range considered in this research is not high enough to induce changes in the chemical composition of rock samples. <![CDATA[<b>The effect of geological uncertainty on achieving short-term targets: A quantitative approach using stochastic process simulation</b>]]> Continuous mining systems containing multiple excavators producing multiple products of raw materials are highly complex, exhibiting strong interdependency between constituents. Furthermore, random variables govern the system, which causes uncertainty in the supply of raw materials: uncertainty in knowledge about the reserve, the quantity demanded by the customers, and the breakdown of equipment. This paper presents a stochastic-based mine process simulator capturing different sources of uncertainties. It aims to quantify the effect of geological uncertainty and its impacts on the ability to deliver contractually defined quantities and qualities of coal, and on the system efficiency in terms of utilization of major equipment. Two different areas of research are combined: geostatistical simulation for capturing geological uncertainty, and stochastic process simulation to predict the performance and reliability of a large continuous mining system. The process of modelling and simulation in this specific production environment is discussed in detail. Problem specification and a new integrated simulation approach are presented. A case study in a large coal mine is used to demonstrate the impacts and evaluate the results in terms of reaching optimal production control decisions to increase average equipment utilization and control coal quality and quantity. The new approach is expected to lead to more robust decisions, improved efficiencies, and better coal quality management. <![CDATA[<b>The importance of people in the process of converting a narrow tabular hard-rock mine to mechanization</b>]]> This paper argues that the technology change to mechanization is also going to require a change in people. It presents a model for technological progress and adapts it to the mining industry. It then goes on to motivate the need for mines to become learning organizations in order to achieve maximum value from their people as they become less labour-intensive. In an important sense, mechanization is as much about knowledge as it is about technology. The change when a mine introduces mechanization or a level of automation is not simply one of technology but also a stage in the development of mining from 'art' to 'science'. 'Art' describes a state of technology characterized by tacit knowledge, an understanding that comes only from experience, and has no formal procedures and little structure. In contrast, 'science' represents a state of technology where all the component processes are understood in detail, all knowledge is explicit, and processes and structures are formal. Studies of other industries, including metal part manufacture and aviation, show that each stage in the progression from art to science changes the nature of the organization and requires a different mix of skills from the workforce. Perhaps the most important change is the increase in knowledge and decision-making required as the technology gets closer to science. There is anecdotal evidence that South African underground hard-rock mines are not learning organizations. Mines by their nature are capital-intensive with long lead times from investment to returns, so there is reluctance to change from the original plans or to encourage staff to think independently. Particularly as mines move from art to science, this reluctance must be overcome. The important lesson for engineers involved in introducing mechanization is to understand that success or failure will be determined by the people involved, and not solely by the technology. The process will almost certainly require a culture change on the mine. We recommend that the mechanization team includes an expert in human and organizational behaviour to ensure that a receptive workforce and management are in place to accept the new technology when it arrives.. <![CDATA[<b>Improvement in the overall efficiency of mining equipment: A case study</b>]]> In mechanized mining, poor equipment efficiency (availability, utilization, productivity, and quality) can endanger the success of the operation. This case study will show how an initiative to improve equipment performance developed into a comprehensive turnaround plan for the mine that placed it in the forefront of performance achievement. As part of a company-wide review process, poor overall equipment effectiveness (OEE) was identified as a major reason for the mine not achieving its targets. A project to improve the OEE identified eight improvement areas (elements) that contributed significantly to the poor performances. Measurement metrics were determined for these elements, followed by determination of baseline and target (improved) key performance indicators (KPIs). Cost savings associated with the improved efficiencies were calculated and tracked throughout the project. The mine team determined the specific actions required to achieve the target KPI in each element. These were individually developed and managed like mini-projects with allocated responsibilities for delivery The paper will indicate how this OEE improvement initiative triggered an improvement in almost all sections of the mine. Soon after launch, the initiative gathered momentum as the KPIs starting to improve. A visible tracking system exists at the mine and each employee can see the improvements and feel the success. The original eight elements were extended by five more, and the mini-projects grew as participants saw the success of the initiative. This paper concludes that through management and worker involvement, visible measurement and controls, and carefully chosen improvement elements, the mine was turned around. It is now achieving and exceeding its targets, and employee relations and motivation as well as safety have improved considerably. All of these achievements are reflected in the bottom line. <![CDATA[<b>Trends in productivity in the South African gold mining industry</b>]]> Mining companies globally are currently facing severe economic and financial challenges. In addition to global challenges, the South African mining industry has to face other operational challenges that are unique to the country and which threaten the survival and competitiveness of the industry. Profit margins are being squeezed by rising costs and decreasing commodity prices, while labour productivity is greatly affected by intermittent labour unrest. This paper analyses how the South African gold mining industry has performed pre-, during, and post the global financial crisis of 2008. The competitiveness of the industry in terms of labour productivity and industry cost curve position is analysed for the period 2006-2013 to assess the impacts of both the global financial crisis and labour unrest. An analysis of the South African gold mining industry is presented at company as well as mine level. Productivity measure in this paper is limited to labour productivity, in line with limited reporting on productivity. All the data analysed was obtained from the public domain. <![CDATA[<b>Critique of the South African squat coal pillar strength formula</b>]]> The South African squat coal pillar strength formula, developed by researchers from the Chamber of Mines Research Organization in the 1980s, predicts an exponential increase in coal pillar strength once a critical width-to-height ratio of 5 is exceeded. The arguments that have been proposed in favour of this formula are discussed critically in this paper. Field experience with squat pillars in the USA and evidence from published physical, analytical, and numerical model pillar studies corroborate the fact that a squat effect is unlikely to occur in coal pillars at width-to-height ratios less than 10. Furthermore, an exponential increase in peak strength of coal pillars does not exist. An alternative design criterion for squat pillars in South Africa is therefore suggested.