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By Kadri Dağdelen, Matthew Deutsch, Thys Johnson

Nested pit analysis in open-pit long range mine planning is used to define approximate ultimate pit limits and an initial high-level schedule in the early stages of a project. Modern ultimate pit optimizers can solve for dozens, or even hundreds, of nested pits however often a smaller subset of pits which are evenly spaced with respect to contained tonnage are desired for downstream analysis. In situations where that pushback selection process must be automated, such as when performing sensitivity analysis, or when the best subset of pushbacks is required; an optimization procedure is warranted. This paper describes a dynamic programming algorithm for selecting pushbacks following nested pit analysis, which is performant and addresses a long-standing inconvenience faced by long range open-pit mine planners.

Jun 25, 2023

By Milka Madahana, John Ekoru

For efficient management of operations, mining companies are required to be able to predict potential scenarios for main market factors. Competitive advantage and value creation are established through managing the value chain well. The mining value chain is usually faced with challenges from various shifts in commodity markets as well as ongoing uncertainties. Therefore, there is a need for accurate analysis of data from the markets, for the prediction of commodities, for instance, Precious Group Metals (PGM). The main objective of this research work is to apply machine learning methodologies with the aim to identify patterns and trends in the Precious Group Metals, and thereafter analyze and predict the future trends of these markets. Numerous machine learning models are applied to a dataset consisting of 15 years of daily price for eight precious metals namely Platinum, Palladium, Rhodium, Ruthenium, Osmium, Indium, Silver, and Gold. The results reveal the patterns and trends within the data sets and that different machine learning methods could be suited for the prediction of market prices for each of the PGMs. The application of an amalgamation of various machine learning methods may result in more accurate predictions of the PGM markets. Accurate prediction of market prices for PGMs will possibly result in unlocking untapped sources of value in the mining industry.

Jun 25, 2023

By Robert Rennie, Taylor Davies, Ahsanul Rafi

Electric locomotives powered by extensive electrical cabling systems were prevalent in the mining industry in the early days of the 20th Century [1]. Since the movement of tethered electrical mining locomotives was limited, the advent of diesel-powered mobile mining equipment provided more flexibility. This led the mining industry to be dominated by diesel-powered locomotives for most of the 20th Century and the entire 21st Century, to date. However, diesel power has certain drawbacks. Diesel-powered vehicles produce tailpipe emissions such as diesel particulate matter, carbon dioxide, sulfur dioxide, and nitrogen oxide. Mine workers exposed to these emissions were, and continue to be, subject to health issues such as respiratory problems, increased risk of lung cancer, and cardiovascular disease. [2][3]. Extensive ventilation systems are required to dilute the diesel exhaust and dissipate the heat generated by these vehicles. Moreover, as mines are getting deeper due to depleting resources, ventilation costs in diesel-powered mines are becoming increasingly high. These factors, coupled with the trend towards greenhouse gas (GHG) reduction in mine operations, has allowed zero-emission electric locomotive systems to gain traction. As lithium-ion battery technology is becoming more advanced, battery-powered electric vehicles can now perform duty cycles comparable to those of diesel-powered vehicles. Although battery-electric vehicles (BEVs) are comparable to diesel-powered vehicles in terms of mobility, they have certain limitations. For instance, the amount of onboard energy is limited by the battery energy density and specific energy. The MT42 diesel haul truck from Epiroc, for example, has a fuel tank capacity of 580L, which is equivalent to around 1450 kWh of net electrical energy [4]. The electrified version of the MT42, on the other hand, has an onboard battery with 375 kWh of usable energy weighing around 4.9 metric tonnes [5]. Moreover, storing and refueling of diesel-powered vehicles is simple and quick, whereas battery energy storage and charging systems require extensive infrastructure development. Charging time is mostly limited by battery chemistry and design. Due to these limitations, the benefits of battery-powered mining vehicles are more likely to be realized with proper planning and optimization of the BEV fleet. This includes optimizing mining layouts for BEV use, charging infrastructure design, and management of onboard energy storage systems.

Jun 25, 2023

By Jose A. Gomez, Javad Sattarvand

Failures of tailings dams have been happening lately. Due to the lack of laws on particular design criteria and stability requirements related monitoring during construction and maintenance, they are thought to be more fragile than hydraulic dams. Monitoring the dam is therefore necessary to understand its current condition and guarantee its safety. The physical condition of the dam could be evaluated with the early identification of seepage. Additionally, due to their adaptability and capacity for high-resolution data collecting, UAVs are an excellent choice for efficiently covering the tailings dam site. UAVs may capture high-quality photos when equipped with a high-resolution RGB camera, thermal sensors, or multispectral sensors. When these sensors are paired with image processing and machine learning algorithms, the result is a reliable estimate of the dam condition.

Jun 25, 2023

By Cesar Carrasco, Heath Arvidson, Mark Forster

Block models built to represent the geology and rock characteristics of mineral deposits represent huge complex data sets, which form the basis of strategic and business planning, and public reporting of Mineral Resources and Mineral Reserves. Recent advances in cloud computing and database technology developed for the Internet of Things offer a different way of working with these critical data sets. Enabling a cloud based, open data structure with high performance data analytics capability presents a compelling improvement in governance and a democratization of ore body knowledge that can lead to automation use cases that support the digitalization of mining.

Jun 25, 2023

By Paweł Stefaniak, Natalia Duda-Mróz, Sergii Anufriiev, Wioletta Koperska

Due to the high environmental risks and negative impact of a failure, tailings storage facilities (TSFs) need constant monitoring. Advanced mathematical models have been developed in the past to predict the behavior of TSFs and raise alerts if needed. To be precise and reliable, such models need a spatial distribution of soil types within the dam as an input. Getting this data from laboratory measurements is time and costconsuming. In this article, we propose an ANN-powered algorithm, which allows us to accurately estimate the soil distribution based on a cone penetration test (CPT).

Jun 25, 2023

By Kadri Dagdelen, Lee J. Zamalloa

Modern surface mining operations are always seeking for minimizing costs while increasing production rates, among the optimization of other specific tasks that have an impact on the economics of the mine. Specifically, the cost related to the production fleet operation (shovels and trucks), the maximization of the overall performance of the equipment, and the uncertainty to meet the goals at the end of the operational time horizon are always topics of discussion with no apparent simple answer. On the other hand, truck-shovel dispatch systems based on Linear/Non-Linear Programming Algorithms have been in operation since mid-1990’s with different levels of success depending on the correct arrangement of operational resources and the complexity of the mine, but having in most cases some important shortcomings related to the way these systems deal with the decision making of the operational objectives, being necessary to have a human agent (dispatcher) to guide the system when the operational parameters change, creating the possibility of suboptimal decisions due to the human factor. This paper discusses the implementation of a novel methodology based on AI techniques to assist in the decision making of the best goal selection when operating a Fleet Management System, taking into consideration time periods as variables and integrating them as part of the analysis, providing a better overview of the forecast plan completion with respect to previous production numbers and evaluating best alternative to handle future events to minimize losses or maximize profits, resulting in better truck assignments, minimum shovel idle times and overall productivity improvements of the operation at the end of the time horizon.

Jun 25, 2023

By V. C. Koppe, J. F. C. L. Costa, D. M. Marques, A. Amaral

Errors associated with estimating the grade of an attribute of interest in a deposit can compromise planning, sequencing, and mineral beneficiation decisions. Several factors are associated with estimation errors. Among them, we can highlight the factors associated with sample spacing, the size of production volumes, and the variability of the attribute considered in the estimation. The access to estimation error can be obtained by some geostatistical methods, for example, by stochastic simulation. However, this is a process that in some situations is computer intensive and takes time. Previous works have proposed a simplified method to access the Maximum Estimation Error (MEE) associated with different types of grade variables, depending on the sample spacing, at small production volumes and considering specific coefficients of variation ranges. This paper presents an approach to assess the MEE associated with long-term volumes. Considering the methodology proposed, it is possible to approximate if a specific drilling pattern used in a deposit provides an acceptable pre-determined estimation error for Resource Classification. Results and considerations on the impact of the geometry of larger production volumes on the MEE calculation are also presented.

Jun 25, 2023

By Christoph Mueller, Grzegorz Tabak

Basing on five years of experience, this paper discusses modern e-drive systems used in underground transport. This covers Energy distribution and cabling principles, inverters and motors as well as auxiliary aggregates. Also an overview of different regimes for battery charging and the energy management and the method of control of the traction are lined out: This means that throttle and brake are not handled separately, but integrated into “longitudinal control” algorithms which assure that a commanded speed is maintained while synchronizing the multi motor systems and taking into account the constraints imposed by e.g. slope grade and battery parameters.

Jun 25, 2023

By Rodrigo Peroni, Vitor Campos

Carajás is one of the largest open pit mines in the world. The mine is comprised by a haul road network more than 100 km long, where the need for good roads is paramount and determining of the truck performances. This work integrates, regarding the ultimate pit design, an approach to consider an economic value to an originally unfit material, assuming it has the appropriate characteristics for haul road construction, which sometimes lies over economic iron ore. This measure demonstrated an improvement in the utilization of resources and guarantee the necessary material to the haul road design and Mining Pads maintenance.

Jun 25, 2023

By Pratama Mochamad Rizki, Andika Satya

High-risk area in open-pit mining should always be monitored by the operational supervisor because of its nature. One of this type is the soft soil dump area. Due to the unstable bearing capacity of the soil, it’s highly possible for us to find cracks in the area. This paper aims to build computer vision which able to detect truck’s distance from safe limit allowed during dumping activity. The system will warn the truck’s driver if the truck has crossed that predetermined safe limit.

Jun 25, 2023

By Rodrigo Peroni, Euler Victoria

Knowing the depth of contacts between weathering zones in phosphate mines is determinant to define the stripping ratios and the mineralized zones. Contacts are gradational and difficult to define even in the drillhole samples, so the combination with geostatistical simulation techniques helps to define the contact zone and the grade distribution, providing a way to assess the probability of the occurrence and the positioning of contacts between the barren waste and the ore zones. These inputs are used in the scheduling, anticipating risks associated with mine planning scenarios. The results from an application to a case study showed a good improvement when compared to traditional techniques.

Jun 25, 2023

By Clinton Birch

The multiple-criteria decision analysis is a technique that helps to find an optimal solution by evaluating conflicting criteria. In this study, an approach to perform multiple-criteria decision analysis for cut-off grade optimization, which considers the diverse stakeholder groups prevalent in the mining industry, is presented. The optimization model developed in this approach links the resource block model to the financial model, enabling the process to either maximize profit, net present value, revenue to the State, or extend the mine's life. To identify the optimal cut-off grade in each case, the Excel Solver function is utilized. Although it has limitations, the Solver function can still be modified to handle models with thousands of block values for determining input variables based on the target value. Following stakeholder engagement and dialogue, a single weighted average cut-off grade can then be determined. This approach is demonstrated for nine South African Witwatersrand gold mines.

Jun 25, 2023

By Konstantinos Komnitsas, Evangelos Petrakis, Emmanouil Varouchakis

During the modeling of grinding systems, population balance modeling (PBM) which considers a constant breakage rate has been widely used over the past years. However, in some cases, PBM exhibited some limitations, and time-dependent approaches have been developed. Recently, a non-linear framework which considers the traditional linear theory of the PBM as a partial case was introduced, thus allowing the estimation of product particle size distribution in relation to grinding time or the specific energy input to the mill. In the proposed model the simplified form of the fundamental batch grinding equation was transformed into the well-known Rosin–Rammler (RR) distribution. Besides, the adaptability and reliability of the prediction model are among others dependent upon the operating conditions of the mill and the adjustment of the RR distribution to the experimental data. In this study, a series of grinding tests were performed using marble as test material, and the adaptability of the non-linear model was investigated using three loads of single size media, i.e., 40, 25.4, and 12.7 mm. The results indicate that the proposed model enables a more accurate analysis of grinding, compared to PBM, for different operating conditions.

Jun 24, 2023

By Mustafa Fener, Masoud Rostami, Sair Kahraman, Behnaz Dibavar

Roadheaders are commonly used in coal mines for roadway excavations. The prediction of roadheader performance is necessary for the planning of roadway projects and the estimation of costs. Recently, a new rock mass cuttability classification (RMCC) system has been introduced for roadheaders used in coal mines. In this study, the validity of the RMCC system was investigated for different types of roadheaders and different coal mines. Four different coal mines were visited, and the performance measurements of different axial and transverse roadheaders were carried out during the excavation of roadways. Uniaxial compressive strength, volumetric joint count, the strike and dip of joints, joint aperture, the Cerchar abrasivity index, and water ingress were determined in field and laboratory studies to calculate the RMCC index. The analysis of the data demonstrated that the correlation coefficients between the net cutting rates and the RMCC indices were higher than 0.94, suggesting that the RMCC system was valid. It was concluded that the RMCC system could be reliably used for the evaluation of roadheader performance in coal mines.

Jun 21, 2023

By Jorge Armstrong, Sean Warren, JOSEF BOURGEOIS

The application of statistical analysis software programs has proven useful for the investigation of rockfall runout distance along a designed slope. Rockfall modeling programs are continually being upgraded with more sophisticated analysis tools, such as the use of the rigid body versus lump mass models. Engineers at mine sites utilizing the software may have varied experience related to these models, their associated input parameters, and how to interpret the generated results. To address this concern, researchers at the Spokane Mining Research Division (SMRD) of the US National Institute for Occupational Safety and Health (NIOSH) investigated the influence of slope height, slope angle, slope material, and rock size for both rigid body and lump mass models in a 2-D statistical analysis program. Based on a literature search and industry input, specific ranges common to that of an open pit mining environment were chosen for each of the input parameters to determine 90% rock runout distance as well as their sensitivity to change. Data collected from this numerical analysis and simulation will be compared to empirical rockfall data gathered through the duration of the Highwall Safety project conducted by NIOSH from 2022–2026.

Jun 18, 2023

By A. Dell’Era, E. Ciro, C. Lupi

The indium recovery via electrowinning from sulfate baths has recently gained significant attention as it does not present toxic emissions, hermetically sealed system requirements, human health, and environmental hazards. Following previous works related to the optimization process for AISI 316L and Ni cathode, it was observed significant importance of the metal supports on the input and output parameters of the indium electrowinning process from sulfate solutions. Thus, comparing input and output parameters in both cases seems very interesting. Particularly, regarding the input parameters, the attention has been focused on the electrolyte composition, current density, and temperature, while productivity, morphology, and structure have been considered regarding the output parameters. Considering the productivity as the optimal output, the findings for Ni cathode were better than that for AISI 316L in most of the selected conditions studied. In the case of morphology, indium grains appear rounded and dendritic on the AISI 316L, while those on the Ni cathode show stratified lamellar grains. Anyway, the indium deposit obtained on Ni cathode shows bigger grains independently from the used operative conditions with respect to that on AISI 316L. Regarding the structure, it is clearly tetragonal, but preferential orientation, crystallinity, and deformation of the structure strongly depend on the metal support.

Jun 14, 2023

By Rainer Antretter

The city of Garmisch-Partenkirchen in southern Germany is located at a main transit road to Tyrol in Austria and suffers of a very heavy traffic load. Therefore, the Kramertunnel as a by-pass tunnel is built to release/mitigate the traffic through the city centre. The 3,600 m long single tube road tunnel is designed with a parallel but smaller emergency tunnel and with cross passages, fitted with single- and doublesided emergency bays, a vent shaft, and an intermediate ceiling to separate fresh air supply from the road traffic. The tunnel, concrete lined along its entire length provided the challenge to find smart formwork solutions for quick set-up, repositioning, setup and pouring. Three particularly specific sections are discussed in this paper.

Jun 13, 2023

By Stan Tang, Yiming Sun, S. Amir Reza Beyabanaki, N. Sathi Sathialingam

The Kurve mixed-use development project including a 22-story tower at 2801 Sunset Place was constructed on a site consisting of a roughly rectangular-shaped lot at the intersection of Wilshire Boulevard and Hoover Street in Los Angeles. Two Metro Red Line tunnels, with depths of approximately 30 feet and 58 feet, respectively, cross below the building at distances of approximately 1 foot to over 63 feet from the site. This paper presents numerical modeling performed to evaluate the ground and tunnel behavior in response to building construction. Results of geotechnical instrumentation and monitoring undertaken during the building construction are also discussed.

Jun 13, 2023

By Joseph A. Dos Santos

The largest TBM (Tunnel Boring Machine) tunnels are typically along modest slopes, but not always. Occasionally high slope angles are required beyond the capabilities of conventional open trough trailing conveyors. A 2019 project required a large TBM to ascend to an incline angle of 25°. A Sandwich Belt high angle conveyor could easily solve the high angle conveying problem but such a system must include all of the features of the conventional trailing conveyor, particularly the ability to extend with the TBM advance. The writer responded to the challenge and developed a TBM trailing Sandwich Belt high angle conveyor with all of the needed features. The invention (U.S.A. patents awarded October, 2021 and November, 2022) however goes beyond the 2019 project requirements and extends to any high angle incline. This writing first presents the broad Sandwich Belt high angle conveyor development, then its use in various construction and tunneling projects prior to this TBM Sandwich Belt trailing conveyor invention. Finally we present the new TBM Trailing Sandwich Belt high angle conveyor with all of its features and implications.

Jun 13, 2023