Up until now, global mining companies have failed to create a fatality free environment for their employees, whether it be through increasingly difficult conditions or inadequate safety management approaches. Desiring to maintain the social license to operate, these companies are now looking into alternate ways of safety management with the aim of mitigating fatalities in the workplace. In this study, a new risk management approach was applied to mitigate fatal incidents through the utilization of critical controls. The aim of this study was to create a scalable, minimally invasive proof-of-concept for AngloGold Ashanti that can successfully be implemented at any of the company’smining operations. The foundation for this implementation was laid through a literature study blending contemporary safety and risk management approaches with Business Intelligence systems thinking and a perspective on industry best-practices. Subsequently, a framework of organizational requirements was set up based on 26 interviews with stakeholders in various departments within the company. Both design and implementation were conducted on-site at an AngloGold Ashanti operation in Western Australia. The system was designed by adhering to organizational requirements, and ensuring that it is suitable to any mining environment. The designed Critical Control Management System was subsequently implemented at Sunrise Dam, one of AngloGold Ashanti’s Australian mining operations. To ensure that critical controls were also assessed at the operational level, a workplace inspection process was modified to generate control data. All sources of data subsequently were fed into a Business Intelligence environment enabling insight into critical control performance to all company stakeholders. Doing so informs decision-making on safety priorities company-wide, based on real-time data generated on the operational level. Two case studies were performed to assess two of the most significant hazards at Sunrise Dam. The studies showed that the effectiveness of reactive controls changes irrespective of their compliance and performance. Furthermore, the influence of human factors within risk management remains difficult to quantify. Finally, it demonstrates the potential for integration of incident data into the Critical Control Management System, thus creating both leading and lagging indicators for safety performance. The conclusion of this study is that an effective and scalable Critical Control Management System can be successfully implemented in a mining operation if the right conditions are generated. The approach of integration in existing processes demonstrates that companies can achieve greater control over fatality prevention without the need for an additional safety management system. On this basis, it is recommended that other operations are supported in creating an environment suitable for adaptation before Critical Control Management is implemented.

The main goal of this research is to get a better understanding of the manganese refining path in the steelmaking converter process. This study focuses primarly on manganese refining due to manganese mass transfer, between metal containing droplets and oxidized slag in the metal-slag emulsion zone, in the top part of the steelmaking converter. Manganese and iron content in the slag heavily influences the slag formation path. Controlling the slag viscosity is essential for controlling the efficiency of the steelmaking process and to preserve the quality of the final steel product. Manganese refining in the steelmaking process occurs in three phases, the primary oxidation phase, the reversion phase and the secondary oxidation phase. This manganese reversion phase is hard to predict and influences the final amount of manganese in the end steel product. In order to raise understanding of the reversion behaviour of manganese in the converter, unique data gathered from in situ measurements done in the EU funded IMPHOS project is utilised. The following research questions were formulated and answered in this study: 1. Are thermodynamic models for manganese distribution calculation applicable for the prediction of the three different behavioral phases of manganese in IMPHOS? 2. What is the influence of the slag-metal emulsion droplets size on the manganese refining behaviour? 3. What is the influence of metal-slag data input obtained from 2 different heights in IMPHOS, on the final resulting manganese behaviour in the kinetic model made in python? 4. Were there any chemical deviations in different zones of the hot metal bath during IMPHOS project sampling? IMPHOS heat S1836, S1841, S1844, S1845 were selected and analyzed on their theoretical thermodynamic equilibrium behaviour for manganese. This analysis was done with Suito No. 3 and Morales and Fruehan equilibrium partition model. Furthermore, the heats slag composition data, hot metal data and converter process variables were used as input in a kinetic model. The model is simulating the micro and macro kinetic behaviour of manganese in the converter emulsion zone with a fixed time step of 1s. The mass transfer in the model is based on Fick's first law of diffusion and uses penetration theory by Higbie, to describe mass transfer along metal droplet boundaries. Parameters such as the manganese mass transfer and the predicted manganese content in the hot metal bath were evaluated to validate the model with the measured concentration reported in the IMPHOS study. Bulk chemical analysis is done on physical samples from heat S1836 cup height 2. This is done to check the inhomogeneity in the hot metal bath and the possibility of different reaction zones in the converter process. The thermodynamic evaluation performed on IMPHOS data showed the difficulty of thermodynamic models derived from laboratory tests, to describe the manganese equilibrium behaviour within the converter. Suito no 3 model gave a better prediction of the manganese distribution than the Morales and Fruehan model. The results from the kinetic model showed a slower primary oxidation and reversion behaviour of manganese compared to the original data. This is mainly due to the manganese equilibrium behaviour of the thermodynamic model and the negligence of the manganese refining in the jet impact zone and metal-slag interface. The model gave a better prediction when a small size droplet range was considered, which implies that the smaller size droplets less than 100 micron are significantly contributing to the manganese transfer from metal to slag and vice versa. The present study reveals that droplet size play an important role and thus need further investigation to accurately describe the size fraction for the accuracy of the kinetic model. The difference between metal-slag data input from the different IMPHOS cup height 4 and 5 on the outcome of the thermodynamic evaluation and kinetic model results, proved to be small enough to be considered negligible. The results from the sample analysis showed deviations for carbon and phosphorus in the new examined cup height 2. These measurements were taken at a high position in the hot metal bath and were different from the measured concentration in the bottom of the hot metal bath. This can indicate deviations in chemical content in the hot metal bath during the original IMPHOS research. More heat data of height 2 , close to the bath surface, is required to confirm this finding.

Starting from the 1950s, plastic has found its way into many aspects of life; from packaging to transportation and construction. The annual global plastic production was estimated to be 330 million metric tons in 2017 and will be doubled within 20 years if the current growth rate persists. In Europe, packaging accounts for 40% of the annual plastic production. To decrease dependence on fossil fuels and the related emissions and reduce the negative impact of plastics that enter the environment, the EU targets to recycle 55% of plastic packaging material by 2025. A steady production of large quantities of high-grade plastic recyclate is essential to sell the recycled material on the market and substitute virgin plastics. But, achieving this high grade is difficult due to the wide range of polymers, including additives and fillers. This research focuses on the sorting step of post-consumer packaging waste in a Material Recovery Facility (MRF) that takes place before recycling. In MRF's, Near Infrared (NIR) sensor-based sorting systems are state of the art to create high-grade sorting products. NIR's use reflection spectra to identify and distinguish a range of materials including different types of polymers. However, while sorting, False Calls (FC) occur when particles are incorrectly classified leading to a loss of valuable material or contamination of the product. Thus, this research aims to increase the understanding of false calls of NIR sensor systems, contributing to higher quality sorting products. To reach this goal, possible causes of FC's and their dependencies on the feedrate, feed composition and feeding mechanism were identified. These causes were arranged into a framework consisting of six types of FC's. A distinction was made between errors that are working range related and those that are not. Particles outside the working range may be classified incorrectly even when fed in a monolayer and under perfect circumstances due to the properties of the particle. The created framework was applied to a NIR in an MRF in the Netherlands which was tasked to separate non-plastic particles and PVC from plastic particles. Experiments were performed to single out the probability of each type of error to occur for 13 material classes. Next, the test results were implemented in a statistical model and a Monte Carlo simulation was performed. In this research, the varying input values were used to imitate the changing feed composition. Three scenarios of adjusted feed characteristics were analysed using the statistical model. It was concluded that to optimize the sorting performance of the analysed NIR, all types of False Calls should be tackled. The feed of the analysed NIR contained a large share of particles outside the working range. So, even if the particles were to be fed in a monolayer the average grade of the product is expected to be around 85%. The combination of the experiments and the statistical model allows for an effective evaluation of the sorting performance and a clear indication of the most problematic aspects of the feed characteristics.

The purpose of this thesis is to aid in the development of vertical cutting mining as a mining method. In order to do so, the technical feasibility and viability, and environmental benefit of vertical cutting as a complementary mining method were investigated. The investigation was performed for the case of the Victor Diamond mine in northern Ontario, Canada, where open pit mining ends by the end of 2018 or beginning of 2019. Vertical cutting has been used for several decades for the construction of water retention walls in the civil engineering industry. By placing the vertical cutter system directly on top of an ore target and cutting straight, vertical trenches up to a maximum depth of 150 m, it is intended to cross over to the mining industry. Extraction with vertical cutting can occur according four extraction scenarios. Three of the scenarios are land-based, the fourth assumes flooding of the mine, and has not been considered for the Victor project. Checkerboard mining is the base case extraction scenario with an extraction rate of approximately 30%. The long trenching scenario would increase the recovery with an additional 15% but induces a high risk of instability in the existing pit walls and the kimberlite in between the trenches. Application of backfill is the third scenario and achieves a recovery of 98%. Backfilling of the trenches requires the movement of significant volumes of additional rock as well as induces time delays due to the curing time of the backfill. Financial evaluation of the vertical cutting scenarios shows a high dependency of the project value on a decreasing cutting performance. Cumulative cash flow analysis and NPV suggest that extending the mine life at the Victor Diamond mine with vertical cutting is favourable. Even in the case of increased rock strengths, as expected in the deeper parts of the Victor pipes, vertical cutting has a positive net present project value. Long trenching, which is considered to be of high risk for pit stability has only marginally greater project value than the base case. The development of alternative mining solutions also aims to reduce the impact of the mining operations on the surrounding environment. Vertical cutting combines multiple mining processes into one operating piece of equipment. It reduces the GHG emissions, improves the safety of extraction process and is expected to increase the support from stakeholders. Extending operational life using conventional methods would require large expansion of the mine involving the increase of the operational fleet, pumping capacity and land usage. The application of vertical cutting has the ability to prevent the negative impact of enlarged open pit mining while maintaining the benefit of continued production.

An efficient production is essential for an economic continuation of most gold mining companies, due to a moderate gold price and a competitive market. Recently, the Ahafo South Mining operations owned by the Newmont Mining Corporation and located on a Proterozoic gold belt in the south west of Ghana, indicated that the cost of production must be reduced in order to viably continue the mining operations. For this research, the Ahafo South Mine Site was used as a case study. A site visit of 90 days provided insight in where the efficiency of productivity could possibly be improved. During this visit, historical production- and financial data [2014-2016] were gathered from a diverse group of engineers on site. Several audits were conducted to form a solid hypothesis with regards to the optimization of rock fragmentation. The hypothesis of this research states that improved rock fragmentation will result in a reduction of operational costs and delays along with an increase in crusher- and mill throughput. This case study was used to investigate the effect of a varying fragmentation on shovel loading time and crusher- and mill performance. The financial impact of a potential blast pattern change was also investigated. After a statistical analysis of the available data on post-blast fragmentation, it was observed that the desired run of mine (ROM) P80 target of 350 mm is rarely met. It was concluded that the "Kuz-Ram" model used to predict the fragment size distribution is incorrectly applied, which resulted in a planned blast design that produces a coarse fragmentation with an excessive presence of boulders. This is referred to as "bad fragmentation" and proved to contribute significantly to redundant wear-and-tear of mining equipment, delays at the shovel loading operations and the primary crushing station. A correlation between fragmentation and loading time was found after a statistical analysis on the daily average loading time of three Liebherr 9400 shovels. It was concluded that the shovels are only able to produce at the desired rate of 2.4 minutes per truck load when the fragmentation of the ROM meets the P80 target. The Six Sigma principle Define, Measure, Analyze, Improve, Control (DMAIC) was applied to define an accepted interval range of shovel loading time variation (2.4 m. ± 20 s.). This so called target interval was generally not achieved by the shovels. All three shovels show an increase in average loading time during period where the ROM fragmentation was coarser. Data generated by a VisioRock™ camera showed, in combination with the throughput of the mills, that an appropriate fragmentation is crucial for an efficient milling process. A detailed analysis of the available data, categorized in "periods of high interest", demonstrated that the power consumption of the mills significantly increased when the feed consisted of relatively coarse fragments. It was observed that the post-crushed fragmentation was more coarse when a high fraction of the feed originated directly from the pit. This observation proved that the primary crusher is not able to eliminate all boulder related issues prior to the crushing operations as a result of inadequately planned blasts. Due to inaccurate or unreliable data on mill feed, it was concluded that a full mine to mill survey is required to obtain data needed for an accurate optimization of mill performance. Newmont Ghana Gold Limited (NGGL) stated that at least 2.3M US$ has been saved on a yearly basis since 2015, as a result of the reduction of explosives used through a blast pattern widening. The cost impact analysis showed that it is uneconomical to save costs on explosives by widening the blast pattern, due to the potential downstream effects when the fragment size distribution is affected. The financial data was inconsistent and it is therefore recommended to conduct a detailed analysis to provide insight in the actual overall (financial) benefits of a blast pattern optimization. It is recommended to investigate both "double-benching" and the purchase of a continuous surveying camera system. Another recommendation is to narrow the blast pattern down to 3.5 m. by 4 m. so that fragmentation related issues are avoided which are currently to be expected for the continuing production in the Subika- and Awonsu Pit.

Surface mining operations can have a significant visual impact on the surrounding landscape and communities. There have been numerous cases of local populations pushing back against the development of mining operations near their communities. This study aims to determine whether it is possible to assess the visual impact of surface mining operations before the development has started. With this assessment it would become possible to make informed decisions as to pitshell development and selection in terms of visual impact. A tool was developed to determine whether it is possible to make this assessment. This tool must be able to be used to determine the visual impact of two or more scenarios in the pre-feasibility phase of development to assist in the decision of which scenario will be developed further in the feasibility phase. In this context, the visual impact is defined as the perceived change in the landscape as a result of mine development on local communities around the surface mine development. The scenarios are defined as the option of pitshells designed during the pre-feasibility phase of mine development. The tool makes a distinction between the physical changes in the landscape caused by the surface mining operation and how this physical change is perceived by anyone viewing the operation. The tool is GIS based and utilizes the free open-source software QGIS to calculate the physical change in the landscape. The tool calculates the vertical and horizontal visibility angle. The visibility angle describes the extent that the change in the landscape takes up in the view of an observer. In addition to that, the tool calculates the contrast between the changed colour in the landscape and its surroundings, which describes how much the change stands out. It requires two sets of data to work: a digital elevation model of the prospected surface mine pitshell and the surrounding landscape and a RGB satellite image of the surrounding area. The DEM provides elevation data for every square metre of the landscape to the GIS, while the satellite image provides RGB colour data. All other data can be generated from the previously mentioned data features. The tool is tested using a case study, in which several distinct pitshell scenarios are compared against one another on their visual impact. The case study is based on the extension of a limestone quarry in Belgium, which aims to secure reserve for future operations. The area of interest is surrounded by several small to medium size villages, which would be affected visually by the extension. Therefore, a comparison should be made regarding the visual impact of the several pitshell scenarios. The results showed it is possible to determine the visual impact of surface mining operations before the development has started. On this basis, it is possible to compare different pitshell scenarios and determine which scenario would be least impactful in terms of visual impact on the local community and surrounding landscape. The reliability of the tool can only be assessed theoretically, however a high level of accuracy is achieved by adhering to guiding principles which are set out in this thesis.

The metal cobalt is essential in creating a sustainable society, as it is an important component in lithium- ion batteries and wind energy turbines. About half of the Earth’s land-based cobalt reserves can be found in the Democratic Republic of Congo (DRC). This study focusses on characterising cobalt-bearing copper ore from a DRC based mining operation and linking characteristic ore properties to the comminution behaviour. Portable X-ray Fluorescence (pXRF) is used to determine the geochemistry, while QEMSCAN, CT scan and InfraRed (IR) spectroscopy are used to assess mineralogy on different length scales. In terms of geotechnical properties, the surface hardness of the ore is determined using a rebound hardness tester. The comminution behaviour is assessed by crushing selected ore samples below 3.35 mm and by grinding the crushed samples for 21 minutes using a ball mill. The energy consumption required for different ore types is quantified using the crushing and sieving simulation package Bruno. The chemical characterisation of ore samples showed significant variation in cobalt content, as the cobalt grade measured in the samples using pXRF varied from 0% to 33.5%. By applying QEMSCAN analysis to samples coming from different locations within the deposit, two different mineralogical zones have been identified: a weathered, and a sulphide zone, with large differences in modal mineralogy. In the weathered zone kolwezite and heterogenite are the principal cobalt bearing minerals, in the sulphide zone carrollite is the only mineral containing cobalt. The CT scan confirmed the unique mineralogy of certain samples, as the mineralogy of pure carrollite nodules found using QEMSCAN showed to continue in 3D. Both QEMSCAN and CT scan were able to detect differences in mineral texture of the studied samples. In terms of geotechnical properties, differences between surface hardness of the samples were observed using the rebound hardness tester. An empirical formula has been derived to adjust the measured surface hardness of drill core samples with a mass below 300 grams. This formula aided in identifying the differences in surface hardness for the distinct mineral textures of the sulphide zone. Influence of mineralogy on the sur- face hardness has been observed, as areas containing only carrollite showed to have a lower surface hardness than areas with a mixture of Mg silicates, quartz and carrollite. Fourier Transformed IR (FTIR) spectroscopy was used to identify a range of gangue minerals within the samples. Carrollite could be identified if it was present in significant proportions and no other IR active minerals were present. FTIR spectroscopy also allowed to refine mineralogical data, as it was possible to differentiate between talc or serpentine and muscovite or illite in the studied samples, which was not possible using QEMSCAN. In total 8 minerals were identified using IR spectroscopy. The relative proportions of the modal mineralogy showed to be in agreement with the mineralogy found through QEMSCAN. The comminution experiments led to the identification of three different comminution classes. These three classes can again be linked to the identified mineral texture types. The surface hardness showed to be correlated to the p80 of samples with the same mineral texture. After 21 minutes of milling, the samples with a higher surface hardness had a coarser p80. Simulation showed that the crushing energy requirements differ up to a maximum of 27% for different comminution classes. This research provides a foundation towards identification of geometallurgical domains in the sulphide section of the investigated cobalt-bearing copper deposit. This MSc thesis was carried out at Camborne School of Mines (University of Exeter) as part of the NERC funded Cobalt: Geology, Geomicrobiology and Geometallurgy (CoG3) project.

The main waste products of ironmaking at Tata Steel IJmuiden are CO2¬(g) and a solid waste stream consisting of mainly carbon and iron-bearing compounds. This solid waste is generally called Zn rich filter cake which contains too much Zn to be reintroduced into the iron making process. Besides Zn, Pb and Cd are also present. These filter cakes originate from the flue dusts that are expelled from the top of the blast furnace. Currently the solid waste is separated based on size distribution which allows the recycling of most of the materials and concentrates the heavy metals into the Zn rich filter cake. Previous research has shown that these cakes are resistant to regular leaching methods for selectively dissolving the contained heavy metals. This is due to their sulfide form. The methods that do work (such as acid leaching) also dissolve additional material such as iron, which is the main component of the waste stream. Therefore Tata Steel Europe is investigating whether alternative options are available to selectively extract these heavy metals and reintroduce the remaining material as secondary ore back to ironmaking. In this research the option of adding oxidants with and without additional microwave treatment is investigated. Based on what is applicable in reality, literature and thermodynamic evaluations several oxidants were selected to oxidize the metal-sulfides to metal-oxides which can be readily leached in ammonia based media. Furthermore the material was characterized and an investigation was done on where the sulfur originates and whether this stream can be reduced or avoided. The quality of the results was verified by comparing the heavy metals dissolved into the leaching solution by ICP analysis and by determining the heavy metal content in the solid material before and after leaching with XRF. It was found that 98% of the sulfur originates from the blast furnace and only 2% from the addition of sodium sulfide at the water cleaning department. Leaching experiments were done with a 40 °C leaching solution, a 5:1 liquid to solid ratio. Leaching solutions were all ammonia based due to its selectivity to heavy metals. Leaching the sample material without microwaving or addition of oxidants the highest Zn, Pb and Cd recovery was 54%, 0.5% and 24% respectively. Potassium permanganate as the oxidant resulted in the highest extraction of Zn at 67% in a 2M ammoniumsulfate, 9M ammonia leaching solution. Ferric chloride in a 2M ammoniumsulfate, 9M ammonia leach solution reached extractions of Zn and Cd at 64% and 45% respectively for the IJmuiden filter cake. For Pb the best extraction was 5% in a 2M ammoniumcarbonate, 9M ammonia leach solution with the same oxidants. Microwaving the sample during leaching resulted in a higher extraction for both Pb and Cd, whilst matching the non-microwave oxidant leaching extraction for Zn. The highest extractions were 61%, 42%, 83% for Zn, Pb and Cd respectively. Aging has also been proven to have an detrimental effect on the extraction of heavy metals, however the aging effect is negated when using microwave treatment or oxidants. Extractions for lab reactor leaching of fresh samples without added oxidants or microwaving with an ammonia sulfate solution, resulted in extractions of 62%, 0%, 40% for Zn, Pb and Cd respectively. It has been verified that most of the sulfur comes from the blast furnace. Further it has been reaffirmed that the metal sulfides this sulfur forms are difficult to leach out. One study states that metal sulfides can and will form in the blast furnace. The current study supports that, even though no direct study of the blast furnace itself was done. Oxidants and microwave assisted leaching seem to work well for Pb and Cd, but are less effective on extracting a higher percentage of Zn. It is recommended to use this method in combination with another process, a different ironmaking process such as HIsarna would be preferable due to the reduction of ZnS to ZnO which is readily leached with an ammonia leaching solution.

Mining projects around the world face a significant challenge to reduce their footprint and be more environmentally friendly. Research has shown that mineral processing is of major influence, due to the use of heavy chemicals that are both expensive and polluting. Currently, electrowinning (the electrodeposition of metals) is only used in the last purification step of the process. So far, the majority of the studies on cobalt have focused on non-electrowinning possibilities. Therefore, it is of interest to investigate the electrochemical behaviour within different environments to obtain more information and gain a better understanding. This thesis focuses on the electrochemical behaviour and deposition of cobalt-bearing minerals, which will be evaluated with the help of cyclic voltammetry (CV) and the electrochemical quartz crystal microbalance (EQCM). These techniques use the help of multiple variable input parameters, which will be investigated and compared to gain the optimised condition to perform the experiments. Furthermore, the sensitivity of the techniques to different input parameters and different solutions will be investigated. This is done to investigate what the origins are for the differences in the electrochemical behaviour of copper-cobalt minerals in aqueous solutions using analytical, synthetic and real ores, and to find a correlation between the obtained results using the graphs generated using CV and EQCM-techniques. This is done to investigate to possibilities using selective electrowinning, meaning the electrodeposition of multiple elements within the same electrolyte solution. Based on a review of the literature, the experimental setup used for the experiments will be discussed to gain better understanding of the specialised equipment and corresponding software. Cobalt chloride, cobalt sulphate and copper sulfate solution will be evaluated first, after which two synthetic cobalt-bearing minerals containing iron will be tested. With the help of CV, the electrochemical behaviour, e.g. redox- reactions, can be analysed. Using the EQCM, accurate measurements of the mass change per unit area of the electroplated cobalt will be recorded. Synthetic minerals will be used to discover how much can be recovered using this technique. Finally, six samples from the Democratic Republic of Congo (DRC) will be evaluated to obtain the same data as for the synthetic minerals. For this QEMSCAN data is used to evaluate the mineral composition. Analysis of the results demonstrated that under different circumstances in different environments, similar electrochemical behaviour and the occurrence of copper, iron and/or cobalt deposition is observed. However, for special cases these reactions do not occur. This difference can be explained by a varying mineralogy, where bornite and chalcopyrite have a positive effect on the electrochemical activity. Regarding the shape of the voltammogram, the number of electrons involved in the reaction has the largest influence. Furthermore, alkaline conditions have a positive effect on the electrodeposition of cobalt. No overall correlation has been found between the samples. For all experiments similar reactions and electrochemical activity is observed regarding the peak potentials and within the same environment, correlations can be found. Recommendations for further research are to investigate the influence of changes to parameters such as temperature, magnetic field and impurities on the electrochemical behaviour of the reaction and changes in the yield of electrodeposited material, to generate more data to validate and calibrate the characteristic potentials that can be used for selective electrowinning and to gather more data of the selective electrowinning experiments in terms of additional (rare) elements, such as lithium.

The frequent occurrence of catastrophic tailings dam failures underscores the urgent need to improve safety practices and minimise associated risks. This study introduces an advanced tool to evaluate the total Probability of Failure (PoF) of existing tailings dams systematically and effectively, supporting the rational prioritisation of mitigation efforts and minimise risk within the 'As Low As Reasonably Practicable' (ALARP) principle. The tool utilises a semi-quantitative approach, combining observation frequency and expert judgment. A baseline PoF for each dam construction method and failure category is established using a database of 450 tailings dam incidents and accidents developed in this study. This baseline PoF is subsequently modified based on site-specific factors influencing failure prevalence. A total of 255 key contributing factors are identified based on a fault tree analysis, the Global Industry Standard on Tailings Management (GISTM), and experts in the field. The factors encompass site conditions, design elements, and the level of practise, which address all major credible failure modes and mechanisms. The factors are linked to the failure categories they influence and assigned relative weights through the analytical hierarchy processing method for each dam construction method and failure category. Subsequently, the weights are multiplied by modifiers to account for the effects of site-specific conditions (favourable: 0.2, neutral: 1, adverse: 5, and unknown: 2). Within the tool, users can choose fulfilment conditions for each factor from drop-down menus and the selected inputs are connected to the modifiers. The adjusted weights are multiplied by the baseline PoF of each failure category, given the dam construction method. The summation of these products yields the total PoF of the investigated dam. The results provide preliminary insight into factors significantly affecting the total PoF for the dam under investigation, aiding in evaluating whether the PoF reduction justifies costs. It facilitates preliminary, rational prioritisation of mitigation measures in accordance with the ALARP principle, contributing to ongoing efforts to improve tailings dam safety. To validate the tool’s capabilities, two case studies with available data are analysed: the Aznalcóllar failure to examine the ability to identify high-risk factors and a recently improved dam to evaluate if the mitigation efforts are adequately reflected. The studies demonstrate the tool’s potential but also reveal uncertainties, inaccuracies, and limitations. These stem from discrepancies in the baseline PoF, weightings, modifiers, and unaccounted factors. Therefore, caution is warranted in the tool’s utilisation. Recommendations include various improvements and further verification and validation across a broader range of case studies. Value can be added by incorporating additional components and adapting the tool for new dams.

The current plan of bottom to top bottom sublevel stoping for the Kearney gold vein at the Cavanacaw mine, Omagh, Northern Ireland may not be the most effective in terms of stability. The Kearney ore body is a narrow vein gold deposit, which has been previously exploited through an open pit and is currently being developed as an underground operation using sublevel stoping (modified Avoca mining method). Stability within the mine is one of the key factors to be considered when it comes to hard rock mining. It should be considered equally as important from a safety and economic point of view. The extraction sequence plays an important role when considering the stability of a designed mine. This thesis aims to establish if the current planned sequence of extraction of bottom to top sublevel stoping is the most effective in terms of overall rock stability, or whether an alternative plan would be better? In the context of this thesis, the modified Avoca mining method is a form of sublevel stoping where material is extracted (stoped) between two drives (blind tunnels) and then backfilled. The project addressed, a conceptual study, field testing and laboratory testing in order to yield the information required to build several numerical models. The numerical modelling was carried out on several different stoping orders which met the constraints set out by Galantas, using the Hoek-Brown model within Plaxis2D. The analysis was conducted on the total displacements, phase displacements, predicted failure points and safety factors. The analysis of the different models showed that an alter- native stoping method of middle to top bottom to middle sublevel stoping peformed better in terms of stability. This improvement in stability was shown by an increase in the minimum safety factor from 3.20 to 3.50, over the current plan. There is further evidence in the reduction of the total number of predicted failure point by 25%.

To extract raw materials responsibly and sustainably, the minerals industry has to continuously optimise the mine-to-metal process and requires an entirely different valuation model. Currently, most operational decisions (e.g., ore-waste boundaries, short-term scheduling, blending policies, dispatch decisions) are evaluated using a revenue-based model. Such a model derives the value of the material from its estimated metal content (grade ⇥ tonnage). However, metallurgical attributes which largely define the processing costs (revenue losses) are left out of the equation since they are either missing or unreliable. In a future optimisation step, it should be possible to offset the anticipated revenue against an aggregated metallurgical cost based on, for example, energy consumption, throughput, recovery and reagent consumption. This drives the need for an improved method to describe the to-be-processed material, which determines the influence of geological behaviour (the material type) on the processing performance (associated with the costs)....@en

Industrial minerals are essential to human activity. The products derived from them make an integral part of a wide range of materials that are ubiquitously present in our daily lives. The performance and attributes of these materials depend significantly on the properties and quality of the industrial minerals and the products generated from them. These characteristics are ensured by the selection and mining of adequate ores, and by using various beneficiation and processing strategies to modify or enhance the original properties of the minerals. One example of these strategies is calcination, in which the minerals are subject to thermal treatment. The success of the generation of high-quality products by using this technique partly depends on the capability of the plant to detect the factors that can degrade the quality of the raw ore, feed for calcination and final product. It also depends on its ability to inform and adapt the operations according to the presence of such factors. A possible approach for doing this is to characterise the minerals and materials with sensor technologies that can generate information on-site and in real-time, focusing on the identification of the degrading factors. Their timely detection can give operational feedback to the process and aid in the generation of high-quality products. This Thesis aims to develop methods for the detection of factors that determine the quality of industrial mineral products by using data derived from infrared sensors, which have the potential to be implemented in mining and process control. For doing this, kaolin, perlite and diatomite have been selected as commodities that are relevant to the market and that represent different applications. This research shows the capacity of infrared sensor-based technologies to retrieve information, directly or indirectly, about the factors that affect the quality of industrial minerals at a lower cost and with comparable efficiency to other analytical methods. @en

Utilisation of reverts in sinter production is nonetheless challenging considering physical and chemical characteristics: physical by means of presence of extreme amount of fine material (<1mm) and chemical in terms of heavy metals, alkalis and uneven distribution of materials. Poor granulation, affecting permeability and degrading of cold strength of produced sinter are negatively influencing sinter processes. On the other hand, reverts contain valuable materials as carbon- and iron-bearing materials, and can affect the sinter process positively. Steelmaking companies generate large quantities of reverts, however the impact of reverts on sinter processes and sinter quality is not fully investigated. With this in mind, this study investigates the impact of revert blends utilised in sinter blend on sinter processes and quality.

Sensor-based particle-by-particle sorting is a technique in which singular particles are mechanically separated on certain physical and/or chemical properties after determining these properties with a sensor. Sensor-based sorting machines can be incorporated into mineral processing operations in order to remove waste or sub-economic ore prior to conventional treatment. This has potential to reduce the consumption of energy and water during mineral processing and thereby decrease processing costs. Furthermore, sensor-based sorting can be used to separate different ore types in order to enhance control of the feed to mineral processing facilities and improve processing efficiency. For most ore types no sensors are known that can be used to detect the grade of ore particles. This is because many ores are polyminerallic rocks in which the economically important minerals occur in relatively low concentrations and in small grain sizes. However, the deposition of ore minerals during the formation of hydrothermal ore deposits is often related to specific hydrothermal alteration zones. This means that it might be possible to characterise the grade of such an ore by using sensors that are capable of detecting differences in hydrothermal alteration mineralogy. Sensors can be applied throughout the entire mining value chain to collect information on the characteristics of the mined ore in real-time. The information that sensors provide can be used to improve deposit models, improve ore quality control and optimise mineral processing. However, the applicability of real-time sensor technologies has not yet been assessed for many types of ore deposits. The aim of the study was to explore the opportunities and potential benefits of using sensors for real-time raw material characterisation in mining and investigate the opportunities for sensor-based particle-by-particle sorting at hydrothermal ore deposits. Investigating sorting opportunities was aimed at researching the applicability of real-time sensors to segment waste particles from ore particles and to distinguish between ore particles that represent different ore types. This is based on samples taken from the Los Bronces porphyry copper-molybdenum deposit, the Lagunas Norte epithermal gold-silver deposit, and the Cortez Hills carlin-style gold deposit. For all the deposits included in the study, a fraction of the waste could be segmented by using a Visible to Near-InfraRed (VNIR) and Short-Wavelength InfraRed (SWIR) spectral sensor to detect the hydrothermal alteration mineralogy. For Lagunas Norte and Cortez Hills, this sensor could also be used to distinguish between different ore types. The ability to segment waste was based on indirect relationships between certain alteration mineral assemblages and the copper or gold grade. Since these relationships correspond to the alteration-mineralisation relationships that generally occur at each deposit type, there is potential that sensors can also be used to segment waste at other porphyry, epithermal or carlin-style deposits. For all three deposits additional research is required to investigate whether it is economically feasible to use the discrimination capabilities of the VNIR-SWIR spectral sensor for sensorbased particle-by-particle sorting. The feasibility may be limited by surface contaminations of the ore particles feeding the sorter, the influence of water on the discrimination capabilities of the VNIR-SWIR sensor, and the sorting efficiency resulting from misclassification. @en

The rising demands for mined products lead to the extraction of materials in geologically complex regions. This calls for mining process changes and interventions driven by technology and advanced data analytics. The dynamic development of state-of-the-art sensor technologies and their potential use in mining is projected to significantly reduce costs in the industry. However, despite rapid advances in sensor technologies, there is still a demand for novel data analytical approaches to enable accurate characterisation of material along the mining value chain, as advanced data analytics is key to gain knowledge from the complex sensor-derived data. Therefore, sensor technology, coupled with advanced data analytics is crucial for the rapid and accurate characterisation of material in mining operations. Access to rapid and accurate data on the key geological attributes (e.g., mineralogy and geochemistry) along the mining value chain has significant implications for the production process efficiency in commercial mines. Such data would greatly assist the improvement of deposit models, optimise ore processing, specify product quality and improve operational decision-making. Sensor technologies operate over a specific range of the electromagnetic spectrum and provide information on certain aspects of material properties that are of potential interest for mining extraction. However, a single sensor might not provide a sufficiently comprehensive description of a material’s composition. This introduces uncertainty into both resource estimation and requirements definition for mineral processing. Thus, it is necessary to utilise strategic sensor combinations to improve accuracy, minimise uncertainty, and enhance specific insights of material compositions. Combinations of sensors can be implemented using a data fusion approach. The fusion of sensed data can be realised at different levels: low-, mid-, and high-level, when the integration occurs at the data level, features level and decision level, respectively. This research aims to develop methods for the characterisation of raw materials using multiple sensor technologies and sensor combinations concept (data fusion at different levels), that can be potentially applicable to mining operations. The study involved the multispectral and hyperspectral imaging techniques, such as red-green-blue (RGB) imaging, visible and near-infrared (VNIR) and short-wave infrared (SWIR) hyperspectral imaging, and point spectroscopic techniques, such as mid-wave infrared (MWIR), long-wave infrared (LWIR) and Raman spectroscopy to acquire spectral information over a wider range of the electromagnetic spectrum. First, an investigation was conducted on the usability of the individual sensor technologies coupled with data analytics for the characterisation of a polymetallic sulphide deposit at different levels. The different levels of material characterisation aimed to allow mineral mapping, ore–waste discrimination, fragmentation analysis, and semi-quantitative analysis of elements and minerals. The positive outcomes of the use of the individual techniques led to the development of a data fusion framework that enables data integration (including multi-scale and multi-resolution data) at different levels (e.g., low-level and mid-level). The developed data fusion concept was implemented and validated using different test scenarios...