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By K. A. du Preez, P. J. van Staden, M. van Rooyen

Mine-impacted water, including acid mine drainage (AMD), is a global problem. While precipitation of dissolved metals and neutralization of acidity from mine-impacted water is accomplished relatively easily with lime addition, removal of sulphate to permissible discharge limits is challenging. This paper presents a high-level comparison of four sulphate removal technologies, namely reverse osmosis, ettringite precipitation, barium carbonate addition, and biological sulphate reduction. Primarily operating costs, based on reagent and utility consumptions, are compared. Each process is shown to be subject to a unique set of constraints which might favour one over another for a specific combination of location and AMD composition. Access to and cost of reagents would be a key cost component to any of the processes studied. The total cost calculated for each process also depends on the type of effluents that are allowed to be discharged.

Oct 1, 2021

By S. Kok, D. Delport, J. Calitz

Altering the microstructure in order to improve the tensile properties of bow shackles resulted in inconsistency in the fatigue performance. This raises the question whether the inconsistency in fatigue life can be attributed to microstructural changes along the profile of the shackle or to decarburization at the surface. Bow shackles forged from 080M40 (EN8) material were subjected to different heat treatments in order to alter the microstructure. The shackles were subjected to five different fatigue load cases, which represented typical loads experienced at termination points for an overhead power line with a span length of 400 m, with changes in conductor type, configuration, wind, and ice loading. Although the change in microstructure does improve both the tensile and fatigue performance, we found that the depth of the decarburization layer has a greater effect on the high cycle fatigue life of bow shackles than the non-homogeneous microstructure.

Oct 1, 2021

By A. F. Silva, J. M. G. Sotomayor, V. F. N. Torres

Geotechnical monitoring plays an important role in the detection of operational safety issues in the slopes of open pits. Currently, monitoring companies offer several solutions involving robust technologies that boast highly reliable data and the ability to control risky conditions. The monitoring data must be processed and analysed so as to allow the results to be used for several purposes, thereby providing information that can be used to manage operational actions and optimize mining plans or engineering projects. In this work we analysed monitoring data (pore pressure and displacement) and its correlation with the tension and displacement of the mass of an established failure slope calculated using the finite element method. To optimize the back-analysis, a Python language routine was developed using input data (point coordinates, parameter matrix, and critical section) to use software with the rock mass parameters (cohesion, friction angle, Young’s modulus, and Poisson’s ratio). For the back-analysis, the Mohr-Coulomb criterion was applied with the shear strength reduction technique to obtain the strength reduction factor. The results were consistent with both the measured displacements and the maximum deformation contours, revealing the possible failure mechanism, allowing the strength parameters to be calibrated according to the slope failure conditions, and providing information about the contribution of each variable (parameter) to the slope failure in the study area.

Oct 1, 2021

By M. Shamsi, M. Nehring

One of the most challenging aspects in semi-mobile in-pit crushing and conveying (SMIPCC) system design is determining the optimum depth at which to change from a purely truck-based haulage system to a conveyor-based haulage system. We used scenario analysis to determine the optimum transition depth between a truck and shovel (TS) system and a SMIPCC system. Traditional pit-limit algorithms were used to generate the final pit limit on a copper deposit, which was then divided into four pushbacks. The final operating pushbacks (phases) were designed for both TS and SMIPCC. The end depths for each phase are viewed as candidate transition points to switch from the TS to SMIPCC haulage system. Economic calculations were applied for five different scenarios, including adopting SMIPCC from the outset (pure SMIPCC), after the first, second, and third phases, and finally not using the SMIPCC system (pure TS) at all. The analysis indicates that the second scenario, at a depth of 335 m, results in the lowest cumulative discounted cost (CDC). In this case, the CDC is 17.6% lower than that for the pure TS scenario and 10.7% lower than for the pure SMIPCC system scenario.

Sep 1, 2021

By H. Askari-Nasab, S. Upadhyay, A. Moradi-Afrapoli

Material handling in surface mines accounts for around 50% of the operational cost. Optimum truck dispatching plays a critical role in the reduction of this operational cost in truck and shovel surface mines. Researchers in this field have presented several mathematical models to solve the truck dispatching problem optimally. However, a critical survey of the literature has shown that three significant drawbacks exist in the available truck dispatching models. The published models underestimate the importance of the interaction between truck fleet, shovel fleet, and the processing plants. They also disregard goals set by strategic-level plans. Moreover, none of the available models account for the uncertainty associated with the input parameters. In this paper we present a new truck dispatching model that covers all of these drawbacks, using a fuzzy linear programming method. The performance of the developed model was evaluated through implementatin in an active surface mining operation. The results show a significant improvement in production and fleet utilization.

Sep 1, 2021

By T. R. Marshall

SAMREC (The South African Code for the Reporting of Exploration Results, Mineral Resources and Mineral Reserves) Clause 7 notes that ‘Documentation detailing Exploration Results, Mineral Resources and Mineral Reserves from which a Public Report is prepared must be prepared by, or under the direction of, and signed by a Competent Person.’ Similar statements with respect to Competent Valuators (CVs) and Qualified Reserves Evaluators (QREs) are contained in the SAMVAL (South African Code for the Reporting of Mineral Asset Valuations) and SAMOG (South African Code for the Reporting of Oil & Gas Resources) codes respectively. What does it mean to be a Competent Person (CP) in the context of compiling/signing-off on SAMCODE (South African Mineral Code) compliant documents? What do the registration and experience requirements mean? Who is ultimately responsible for the report and what does such responsibility prescribe?

Sep 1, 2021

By K. G. Lomberg

The density used to covert volume to tons is critical in determining the real in-situ tonnage of Mineral Resources. However, the methods used to determine density and the use of different technical terms are seen to be inconsistent throughout the industry. Probably the best discussion addressing the determination of density was presented by Lipton (2001). This paper does not try to replicate this excellent work, but rather to review current industry practice and present a comparison of the approach to density in public reporting. Some of the technical terms used in reporting and the common methods applied are also discussed.

Sep 1, 2021

By I. J. Geldenhuys

South Africa’s mining and metals industries have an illustrious history dating back to the Late Iron Age. We live in a complex and data-intensive world that has already fundamentally changed how we work and live. The outbreak of the global COVID-19 pandemic in 2020 resulted in immeasurable suffering worldwide, but the crisis also accelerated many technological developments and altered the way we think about, and experience, technology and work. Problem-solving requires new and rapidly changing skills to manage the data tsunami. Whether at the rock face or on the processing plant, the fundamentals have not changed, although how we interact with minerals and their properties has changed dramatically. Sustainable processing and design are non-negotiable if we genuinely want to achieve the aim of the cradle-to-cradle principle. As we venture forth, what can scientists, engineers, technologists, and mathematicians learn from history? History is data presented in a context; sometimes, the context is also important. We exist in an age of data, with most of the world’s data created in only the past two years. History can enhance our understanding of the present and enhance our future outcomes. Lessons from history can help provide insights into making ethical and sustainable choices related to technology or engineering in the mining and metallurgical industry. Shifting the perspective of mining and metallurgy professionals from a narrow focus on complex technical solutions towards a broader context for problem-solving and designs that includes the entire ecosystem is crucial. In other words, using or reflecting on historical process development is, at its core, systems thinking.

Sep 1, 2021

By S. R. Grobler, S. Bilessuris, M. E. Greenway

Ensuring that all the head ropes on a multi-rope friction winder share the load equally has been a design and maintenance issue since they were first developed. Accurate machining of the rope grooves is necessary to meet this objective. Early analysis of the change of rope loads for ropes in grooves that are mismatched in depth treated the grooves as rigid. Groove depth tolerances deduced from this analysis are stringent and difficult to achieve in practice. Test work indicated that the inherent flexibility of groove lining materials alleviates the load-sharing problem. However, no analysis of rope load changes due to mismatched flexible grooves has been published. In this paper we develop new equations for the rope load variation for flexible grooves. By allowing flexibility to reduce to zero, the corresponding rigid rope groove equations are obtained. New criteria for tolerable groove depth variations are developed from this analysis, which depend on the flexibility of the groove lining material.

Sep 1, 2021

By P. C. Pistorius, M. P. Maphutha, J. D. Steenkamp

Advanced high-strength steels (AHSS) are sophisticated materials being developed by the steel industry to mitigate challenges related to the performance of motor vehicles. To meet the requirements of AHSS, the ferromanganese alloys (FeMn) utilized in the production of the steel are required to contain acceptable levels of unwanted impurities, i.e. P, S, N, H, and C. The focus of the current study was to investigate dephosphorization of ferromanganese to produce a low-P alloy that could be effectively utilized in the production of AHSS. The study involved conducting laboratory-scale testwork to study the efficiency of CaO-based slag systems to dephosphorize FeMn alloys. The addition of Na2O, CaF2, and BaO to MnO-CaO-SiO2 slag was considered. The test work was carried out in a 25 kW induction furnace at temperatures of 1350°C, 1400°C, and 1450°C. The P partition coefficient (Lp) remained small at <1, which is an indication that dephosphorization had not been achieved. The baseline slag, comprising 40%CaO-40%SiO2-20%MnO, reported higher Lp values. Addition of Na2O and CaF2 did not show any further benefit. Substituting half of the CaO by BaO, resulted in similar Lp values to those of the baseline slag under conditions of 1350°C and 1450°C at 30 minutes. In summary, based on the Lp values obtained, the conditions investigated with the CaO-based slags appeared to have been unfavourable for dephosphorization of FeMn alloys, as most of this impurity element remained in the alloy.

Sep 1, 2021

By B. McFadzean, M. Tadie, T. Dzingai, M. Becker

Ores from a single deposit may exhibit extensive variability in their mineralogy and texture. The ability to quantify this variability and link it to mineral processing performance is one of the primary goals of process mineralogy. This study focuses on the effect of alteration in three platinum group element ore samples from the Great Dyke in Zimbabwe – two of which were more pristine compared to the third, which was locally classified as ‘oxidized’ ore. These ores are known to be characterized by varying degrees of alteration, resulting in numerous challenges in flotation and affecting both grade and recovery. Alteration, by near-surface oxidation, of the valuable base metal sulphides and platinum group minerals resulted in lower flotation recoveries of Cu, Ni, Pt, and Pd. Evidence of incipient oxidation was more readily observed in the base metal sulphide assemblage than the platinum group mineral assemblage, even though the loss in recovery (because of oxidation) was most significant for Pd. Alteration through hydration resulted in a significant increase in mass pull and dilution of concentrate grade through the inadvertent recovery of naturally floating gangue comprising composite orthopyroxene and talc particles. In this study, the amount of naturally floating gangue was more strongly correlated with the talc grain size distribution than the grade of talc in the flotation feed. The oxidation and hydration alteration reactions are not necessarily mutually exclusive, although one may be more dominant than the other, giving rise to ore variability.

Sep 1, 2021

By Z Bagheri, E Moosavi

Identifying the exact borders of geological domains and assessing the uncertainty of these borders are crucial steps in resource estimation. This potential field method was designed to build 3D geological models from data available in geology and mineral exploration, namely the geological map and a digital terrain model, structural data, borehole data, and the geologist’s interpretations. The resource evaluation of a copper ore deposit is often performed in three steps: (i) delimitation of the boundaries of the units corresponding to the various geological formations or ore types; (ii) estimating densities; and (iii) estimation of grades within each unit. In simple cases (e.g., a series of sub-horizontal layers), the geometric model can be built using 2D geostatistical techniques (kriging or co-kriging of the elevations or thicknesses of the various horizons) which also quantify the uncertainty of the model. A 3D model of Cu grade is generated using ordinary kriging; however, the indicator kriging method is run to design a 3D model of rock types by incorporating the drilling results. Block models of geophysical and geological characteristics are included in a similar 3D mesh to investigate their relationships in copper mineralisation.

Sep 1, 2021

By M. S. Shishvan, J. Sattarvand, R. S. H. Meij

Navigating miners during an evacuation using a smart evacuation technology can significantly decrease the evacuation time of an underground mine in case of an emergency. This paper presents a mathematical programming model to calculate the most efficient escape path for each miner as a critical component of the smart evacuation technology. In this model, the total evacuation distance of the crew is minimised and scenarios with blocked pathways, and stamina categories for the miners are simulated. It was found that all the tested scenarios are technically feasible. Using the feature that filters out blocked pathways has no downsides, as safer routes are calculated, and there is no penalty in the computation time. The paper also discusses the social and technical issues that need to be overcome before the algorithm can be implemented as an actual escape solution.

Sep 1, 2021

By N. Duda, P. Śliwiński, P. Stefaniak, B. Jachnik

Ventilation and air-conditioning are some of the most energy-consuming processes in deep underground mining. Additionally, the energy consumption of these processes systematically increases along with the expansion of the mine. Therefore, proper energy efficiency assessment and consumption forecasts of these systems are particularly important in modern mines for ongoing tracking and planning of the likely costs. In the article, a short-term prediction model for surface air–conditioning stations is described. This model takes into account dependencies that were identified, based on the data from the supervisory control and data acquisition (SCADA) systems. These dependencies between the response value and the external conditions are then incorporated into the model. This way, for example, the ambient temperature or the total number of specific days of the week (with sometimes significantly lower or higher than the weekly average energy consumption levels) are included. Taking into account these dependencies, and e.g. forecasted average monthly temperatures allow us to include the seasonality of energy consumption in the presented model. In the article, a sample energy efficiency analysis of the A/C system based on an example of the KGHM Polish Copper Polkowice-Sieroszowice mine is performed. The results of the solution proposed in the article are then evaluated, and compared to the currently functioning, more basic forecasting methods. However, given the general nature of the dependencies used in the model, similar solutions could be used in other case studies.

Sep 1, 2021

By H. Dudycz, A. Skoczylas, P. Stefaniak, P. Pyda

In the era of Industry 4.0, technologies such as Big Data (BD) and the Internet of Things (IoT) play a key role, especially for multi-site manufacturing companies. In such companies, the challenge is to collect and process massive amounts of data from industrial devices and extract key information from this data in real-time for ad hoc decision-making. The ability to analyse data from industrial devices translates directly into streamlined production processes, cost optimisation, prevention of unplanned events, and safety during operation. In this context, particular attention should be paid to Big Data Analytics (BDA), whose main source is the Industrial Internet of Things (IIoT). The purpose of this paper is to propose an IT system architecture incorporating BD and the IoT for a mining company. The paper presents results from a literature review focusing on available BD and the IoT solutions for industry (mining in particular) for the purposes of the acquisition, integration, and advanced analysis of data. The advantages and disadvantages of the different solutions were indicated and gaps in the accessibility to dedicated functionality are identified. Based on the analysis of a multi-site mining company, the main challenges faced by such companies planning to implement BD and IoT solutions are identified. Also, a proposal for an IT system architecture incorporating BD and IoT for a mining company is described in the paper. The contribution of the article consists of the identification of the challenges faced by mining companies planning to implement BD and the IoT solutions, and the proposal of an IT system architecture that allows BDA whose main source is the IIoT.

Sep 1, 2021

By A. Melkumyan, M. Balamurali, J. Zigman

Understanding the contribution of geophysical variables is vital for identifying ore indicator regions. Both magnetometry and gamma-rays are used to identify the geophysical signatures of the rocks. Density is another key variable for tonnage estimation in mining, and needs to be re-estimated in areas of change when a boundary update has been conducted. Modelling these geophysical variables in 3D will enable investigation of the properties of the rocks and improve our understanding of the ore. The Gaussian Process (GP) was previously used to generate 3D spatial models for grade estimation using geochemical assays. This study investigates the influence of the following two factors on the GP-based autonomously generated 3D geophysical models: the resolution of the input data, and the number of nearest samples used in the training process. A case study conducted on a typical Hammersley Ranges iron ore deposit using geophysical logs, including density, collected from the exploration holes, is examined in this paper.

Sep 1, 2021

By S. Yaw Amponsah, E. Ben-Awuah, P. M. Takouda, P. Eme

Mining production scheduling is the process of determining the sequence of block extraction over a period of time that will yield the maximum net present value for a mining operation. The block extraction sequence needs to occur under certain resource constraints which presents an NP-hard problem that is computationally intractable and complex to solve for large scale problems using exact mathematical models such as Mixed Integer Linear Programming (MILP). In this paper, we used a metaheuristic optimisation model based on a Genetic Algorithm (GA) to solve the production scheduling problem. The problem definition and resource constraints are formulated using a mining specific GA that enforces block extraction precedence and mining capacity constraints through a normalisation method. A case study is implemented with the GA model, and the results and computational time are compared with that of a MILP model with CPLEX solver which is based on a branch-and-cut algorithm.

Sep 1, 2021

By S. V. Lukichev, O. V. Nagovitsyn, V. V. Laptev

In this paper the authors describe the developed algorithms of short- and medium-term planning of underground mining operations. The algorithms were developed using the example of the flat-back cut-and-fill method, and provide multifactor accounting of mining conditions, technical and technological limitations: state and properties of the rock mass; the current mining situation; mining rules; availability of safety pillars; properties of the filling; additional characteristics of technological objects that complicate the driving of workings; sufficiency of human and technical resources; employee specialisation; existing machinery and equipment; opportunities and limitations of the transport scheme of the mine, and work schedule. The paper is presented by means of a dynamic model of mining development, which shows the sequence of mining operations in the mine workings. Besides animation, the tool provides an opportunity to form tabular and graphical reports.

Sep 1, 2021

By Z. Levinson, R. Dimitrakopoulos

A mining complex is an engineering system where raw materials are extracted from several mines, processed, transported, and sold to the market. The uncertainty and local variability of material grades and their locations within the related mineral deposits are critical for determining the optimal life-of-mine extraction sequence, destination policy, operating modes, and capital investment decisions, which define the production schedule of a mining complex. Infill drilling is used to further characterise a mineral deposit and reveals information that changes the representation of the resource model and potentially the resulting optimal long-term production schedule. A self-learning reinforcement learning approach is proposed to determine the optimal drilling locations that maximise the net-present value of the long-term production schedule and the associated financial forecasts by adapting the schedule to additional information. A case study at a copper mining complex demonstrates a $70 M increase in project value by collecting drilling information with a $1 M budget.

Sep 1, 2021

By M. Salimov, J. Sattarvand

The conventional visualisation method of remote equipment is through the installation of one or more cameras on the machine, and sending a live feed to the operator’s flat display. However, the performance of the teleoperation can be enhanced using better visualisation through virtual reality (VR). This paper presents the process of the design and manufacturing of a robotic platform that will be used in the next phase of the project for a VR-assisted teleoperated excavator. The robot consists of a loading boom and arm arrangement installed on the undercarriage of a CAT300-9D. All hydraulic cylinders are replaced with electric actuators, and crawling motors are substituted by electric motors. The pieces of the boom and the arm, as well as the bucket were designed in Autodesk Inventor, and manufactured from aluminium sheets using a desktop and CNC machine. Parts are joined by pins and welding as needed. An Arduino-based control system is developed for the robot, and motor controllers are used to convert the power commands from the microcontroller to the high-amperage actuators. The control system is capable of communicating with a wireless Play Station controller to operate remotely. The manufactured robotic excavator is planned to be utilised in multiple autonomy research projects.

Sep 1, 2021