Open-pit Mining Projects Research Articles

Advancing sustainability: An integrated decision support framework for fleet selection in open pit mining construction

The process of selecting and configuring equipment fleets for open-pit mining is complex, requiring consideration of both quantitative and qualitative criteria. This paper presents a novel comprehensive framework for selecting loading/hauling fleets in open-pit mining projects. Through an extensive review of the literature, a total of 21 selection criteria are initially identified. With guidance from local experts, these criteria are shortlisted into five primary groups: site conditions, managerial, social, and environmental criteria. The ranking of the identified selection criteria is carried out by employing the analytical hierarchy process (AHP) and multi-attribute utility theory (MAUT) methods, utilizing a questionnaire survey. The most crucial criteria in selecting loading/hauling equipment are identified as the equipment's operating cost, productivity, repair and maintenance costs, and soil condition. An optimization module is developed to optimize the selected fleet, while adhering to sustainability principles and project constraints. The optimization module considers social, economic, and environmental sustainability variables to determine the optimal number, size, type, and capacity of fleets needed to complete the work within the allotted time. As a case study, the proposed framework is validated by experts in these types of projects. The framework's ability to effectively select fleet units for sustainable loading/hauling fleet is confirmed through this validation method.

"Community strengthening through citizen monitoring of water quality: A systematic review".

Citizen participation in decision-making is a fundamental democratic pillar of democracy. However, the degree of citizen involvement and recognition by governmental institutions may be conditioned by the level of competence and knowledge demonstrated. Therefore, carrying out collective projects can contribute to strengthening citizen engagement in water management issues. Nonetheless, there is limited knowledge about the various types of citizen engagement and the practices that have facilitated greater inclusion in decision-making regarding water resources. This study aims to identify and analyze practices that strengthen water community organizations through citizen monitoring-based involvement. A systematic literature review was conducted using the PRISMA method. The research was guided by the following questions: What are the differences in the level of citizen involvement and the degree of transformation facilitated by citizen monitoring of water quality (CMWQ) between the global North and South? What practices strengthen community organizations in decision-making based on CMWQ? Moreover, what challenges do community water organization structures community water organization structures face when based on CMWQ? A total of 161 publications were identified for the analysis of critical themes. After applying the eligibility criteria, 33 documents were selected for content analysis. The reviewed monitoring exercises indicate that the highest level of citizen organization achieved by participants is commonly recognized as "Water Committees". One practice that strengthens these committees is the generation of collaboration agreements among different types of allies, based on a shared objective. However, in the Global South and at the institutional level, there is still resistance to water quality data generated by citizen monitors, especially in regions with large-scale open-pit mining projects. To sustain the efforts of community figures, monitoring programs with public funding need to be established, and public policies supporting these initiatives at the institutional level must be implemented.

Latent Rural Depopulation in Latin American Open-Pit Mining Scenarios

The increasing expansion of open-pit mining and the drastic transformations of land use in Latin America have led to processes of rural depopulation among traditional inhabitants, causing unsustainability in rural life systems. In the context of profound, worldwide territorial and environmental transformations, it is necessary to anticipate change scenarios and identify territories prone to rural depopulation. The objective of this article is to determine rural depopulation propensities through an exploratory multivariate study of the demographic, social, economic, and environmental conditions of territories where open-pit mining projects are being installed. First, a theoretical model is created using the grounded theory method for the literature review. Subsequently, indicators are analyzed using quantitative methods and geographic information systems. The results show that latent rural depopulation tends to be generated in territories with socio-environmental vulnerability, where advanced mining extractivism makes them prone to future depopulation. Some factors possibly leading to decreased rural population include the reduction of water availability; deforestation and depeasantization, due to urban development; gentrification, due to real estate speculation in providing lodging and food services to the mining project; and drastic changes in land use.

Exploring the relation between production factors, ore grades, and life of mine for forecasting mining capital cost through a novel cascade forward neural network-based salp swarm optimization model

This paper aims at exploring the relationship between production factors, ore grades, and life of mine for forecasting mining capital cost (MCC) for open pit mining projects. Accordingly, the relationship between annual mine and mill production (MineAP, MillAP), stripping ratio (SR), reserve mean grade (RMG), the life of mine (LOM), and MCC of 80 open pit mining projects were investigated and thoroughly evaluated. The dataset was then divided into two sections, with 56 observations used to develop the forecast models. The remaining 24 observations were used to test the accuracy of the developed models. Subsequently, the cascade feedforward neural network (CFNN) was developed to forecast MCC based on the influential parameters. In order to improve the accuracy of the CFNN model, the salp swarm optimization (SalpSO) algorithm was applied to train the CFNN model and optimize the weights of the model, called the SalpSO-CFNN model. The benchmark models which were developed in the previous studies, such as support vector machine (SVM), classification and regression tree (CART), and multiple layers perceptron (MLP) neural network, were also developed in this study to compare with the proposed SalpSO-CFNN model in terms of MCC forecast. The results revealed that production factors, ore grades, and LOM are closely related to MCC, and they are statistically significant. The forecast results also indicated that the proposed novel SalpSO-CFNN model provided a good accuracy with a mean absolute error (MAE) of 179.567, root-mean-squared error (RMSE) of 248.401, and determination coefficient (R2) of 0.980. This result is higher by 18% compared with the CART model and 2–6% compared with the remaining forecast models. A sensitivity analysis also indicated that MineAP, MillAP are the most influential parameters on the forecast of MCC, and they should be specially taken into account when forecasting MCC of open pit mining projects.

Geomechanical substantiation of the northeastern pit wall stability in Kurzhunkul mine

Kurzhunkul magnetite deposit is located in the Kostanai Region of Kazakhstan and is an open pit mining project of Sokolovsko–Sarbay Mining and Production Association (SSGPO) since 1983. The current depth of the open pit is 240 m (Level -28 m). It is expected that Kurzhunkul pit reaches the depth of 290 m. The deformation determinant in Kurzhunkul mine is its geological structure represented by complex faulting. Special care and attention should be paid to the northeastern pit wall which is a zone of large and closely spaced tectonic faults essentially extended along the strike and dip of the deposit, and depthward the pit. Unfavorable bedding conditions in combination with weak physical and mechanical properties of fracture fillers can induce movement of rock blocks during extraction of mineral reserves from the weak zone of the northeastern pit wall. This study offers the geomechanical substantiation of stability of NE Kurzhunkul pit wall which is most heavily intersected by tectonic faults and has low strength characteristics. The study was carried out with grant financing in framework of Project No. AR08053358 Rock Mass Control Based on the Integrated Geomechanical Model toward Mining Safety.

A GIS Software Module for Environmental Impact Assessment of the Open Pit Mining Projects for Small Mining Operators in Kazakhstan

This research article presents a software module for the environmental impact assessment (EIA) of open pit mines. The EIA software module has been developed based on the comprehensive examination of both country-specific (namely, Kazakhstan) and current international regulatory frameworks, legislation and EIA methodologies. EIA frameworks and methods have been critically evaluated, and mathematical models have been developed and implemented in the GIS software module ‘3D Quarry’. The proposed methodology and software module allows for optimised EIA calculations of open pit mines, aiming to minimise the negative impacts on the environment. The study presents an original methodology laid out as a basis for a software module for environmental impact assessment on atmosphere, water basins, soil and subsoil, tailored to the context of mining operations in Kazakhstan. The proposed software module offers an alternative to commercial off-the-shelf software packages currently used in the mining industry and is suitable for small mining operators in post-Soviet countries. It is anticipated that applications of the proposed software module will enable the transition to sustainable development in the Kazakh mining industry.

Calculating ultimate pit limits and determining pushbacks in open-pit mining projects

A very important part of any open-pit mining project is determining the ultimate pit limits and optimizing the pushbacks. Currently, block models are the most widely used for calculating mineral resources and reserves. Block models can define the ultimate pit limits through algorithms like floating cone, Lerchs-Grossmann, PseudoFlow, etc. However, only through an economic study will the best pits be selected, from most to least economically valuable, and the different possible pushbacks can then be defined.Based on pre-determined operating costs, all possible scenarios should be studied while varying the selling price in fixed increments between minimum and maximum values that cover all possible future prices. The starting selling price should be very low, and consequently, the only phase that will be economical is the one with adequate grade and a low stripping ratio. As the selling price increases, the ultimate pit limits do not vary or vary only slightly until the price reaches the point at which another of the ore bodies in the deposit becomes economical. This process is repeated as the price increases until the maximum price considered is reached; then, the project reaches the last phase that is economical if economic conditions are very favourable.The data obtained in each phase can be used to simulate different scenarios, since the different phases will not change because operating costs or economic conditions change. The ore is not going to move; what changes is the phase up to which mining will be economical and what profits will be obtained in each phase.

Deciding over the territory governance of mining conflicts. The cases of andalgalá, in catamarca, and famatina, in La rioja, Argentina. (2005–2016)

In recent times, two global phenomena have converged: the growing demand for natural resources and a mobilized citizenry that claims participation in the decisions about their territories. Thus, socio-environmental conflicts often arise where communities, appealing to environmental and cultural values, confront transnational companies and governments interested in natural resources exploitation. Despite the multiplication of literature and environmental governance strategies, these disputes continue to be characterized more by the trend toward radicalized conflict than by consensus and democratic resolutions. Aiming to deepen the understanding of this phenomena, we study the conflicts unleashed from the installation of open-pit mining projects in the provinces of Catamarca and La Rioja in Argentina. We look for the characteristics of the interactions between the State, the civil society and the business sector that hinder the progress towards governance processes that bring by democratic resolutions to mining conflicts. Based on a comparative study at the subnational level, it is shown that mining conflicts are characterized by not developing effective governance processes. We argue that this is related to three central factors. First, a failed articulation between the actors, ineffective negotiation instances, disparate normative and cognitive frameworks, inefficient external agents, and the absence of joint public policy proposals. Second, the lack of will and capacity of the provincial governments combined with the weakness of the institutional mechanisms. And finally, the generation of a deep antagonism in the positions and discourses of the actors provoked by the particularities of the mining projects.

Production Scheduling for Strategic Open Pit Mine Planning: A Mixed-Integer Programming Approach

Production scheduling is a large-scale optimization problem that must be solved on a yearly basis by every open pit mining project throughout the world. Surprisingly, however, this problem has only recently started to receive much attention from the operations research community. In this article, O. Rivera, D. Espinoza, M. Goycoolea, E. Moreno, and G. Muñoz propose an integer programming methodology for tackling this problem that combines new classes of preprocessing schemes, cutting planes, heuristics, and branching mechanisms. This methodology is shown to compute near-optimal solutions on a number of real-world planning problems whose complexity is beyond the capabilities of preexisting approaches.

Developing a novel artificial intelligence model to estimate the capital cost of mining projects using deep neural network-based ant colony optimization algorithm

This study aims to propose a novel artificial intelligence model for forecasting the capital cost (CC) of open-pit mining projects with high accuracy. It is a unique combination of a deep neural network (DNN) and ant colony optimization (ACO) algorithm, abbreviated as ACO-DNN. In this model, MineAP (annual mine production), SR (stripping ratio), MillAP (annual production of the mill), RMG (reserve mean grade), and LOM (life of mine) were used to consider the CC of open-pit mining projects. A series of simple and complex artificial neural networks (ANN) was developed for forecasting CC of 74 copper mining projects herein. Subsequently, the ACO algorithm has been applied to optimize the developed ANN and DNN models to improve the accuracy of them. Finally, an optimal hybrid model was defined (i.e., ACO-DNN 5-25-20-18-15-1) with superior performance than other models (i.e., RMSE of 130.988, R2 of 0.991, MAE of 115.274, MAPE of 0.072, and VAF of 99.052). The findings of this study showed that the DNN models could predict the CC for open-pit mining projects with more accuracy than those of the simple ANN models. In particular, the ACO algorithm played an essential role in improving the accuracy of forecasting models. Also, MineAP, MillAP, SR, and LOM have been confirmed as critical parameters that affect the accuracy of the selected model in forecasting the CC of open-pit mining projects, especially MineAP. In conclusion, this study offers a useful tool to improve resource policies of mining projects, especially copper mining projects.

Aplicación del software DOPPLER en un proyecto minero hipotético de un yacimiento polimetálico

El presente artículo se desarrolla con el propósito de obtener la valoración económica y el agendamiento para un proyecto minero hipotético de oro a cielo abierto mediante el uso de DOPPLER como herramienta informática, esto debido al crecimiento y la importancia que ha adquirido el uso de software especializado en el negocio minero. Para el desarrollo del artículo se definen una serie de parámetros a considerar como los destinos, capacidad de destinos, ángulo de talud, precio del metal, entre otros, a partir de los cuales se ejecutan una serie de agendamientos mediante los diferentes métodos ofrecidos por DOPPLER. Una vez obtenidos los resultados (agendamiento, VPN, etcétera.), se analizan y se comparan entre sí con el fin de determinar cuál es el más adecuado para el proyecto hipotético considerado en este artículo.

Forecasting mining capital cost for open-pit mining projects based on artificial neural network approach

This study considered and developed four artificial intelligence (AI) techniques to estimate mining capital cost (MCC) for open-pit copper mining projects with high accuracy, including artificial neural network (ANN), random forest (RF), support vector machine (SVM), and classification and regression tree (CART); 74 observations of mining projects were collected and analyzed to predict MCC based on five input variables. Root-mean-squared error (RMSE), coefficient of correlation (R2), mean absolute error (MAE), and absolute percentage error (APE), were used to evaluate the performance/quality/accuracy of the models. The results of this study indicated that ANN, RF, SVM and CART models were advanced techniques in predicting MCC with high accuracy. Of those, the ANN model yielded the most dominant accuracy/performance with an RMSE of 138.103, R2 of 0.990, MAE of 114.589, and APE of 7.770%. The remaining models (i.e. RF, SVM, CART) yielded lower performance with RMSE in the range of 172.975–379.691, R2 in the range of 0.924–0.987, MAE in the range of 134.982–301.196, and APE in the range of 10.339%–19.384%. The results of the sensitivity analysis of this work also revealed that production capacity includes MineAP and MillAP, were the two most essential parameters on the MCC predictive models. They should be used as the primary input parameters for estimating MCC in actual.

Automated lithological classification using UAV and machine learning on an open cast mine

ABSTRACTMine planning is directly dependent on the lithological features and the definition of contacts between materials. Geological modelling is a continual duty that is performed using observation data, which includes open faces information. New data must be continuously acquired and more details are added to the model. This task can benefit from the automation of lithological detection. Unmanned aerial vehicles (UAVs) are widely used in open pit mining projects, with low risk to the operators, to the aircraft or third parties. Topographic modelling using UAV imagery is now common in the mining industry. The next step, presented here, is to automate the surface feature detection using machine learning (ML) algorithms to classify a complete detailed geological model. An inexpensive aircraft was used on a Brazilian phosphate mine with point spacing as small as 10 cm.

Valoración y riesgos socioambientales en el cierre de minas

The objective of this paper is come up with proposals that help to understand the risks that mining companies must consider in order to reduce the negative impacts that they currently cause, since apart from the effects that are not con-sidered during the operation of the project, they generally do not carry out an appropriate closure at the end of the project . As a result of the research, the proposal of some indicators that could be applied and that would help to reduce the social and environmental impact is presented; besides reducing the amount of open-pit mining projects . The normative framework of Mexico is used as an example because it has a broader scope for the purpose of this work . It is concluded that the mining activity strengthens and creates economic structural dependencies for most of the countries that practice it, for which it expresses the need to suspend this practice gradually because it harms the environmental, social and economic aspects .

Application of Operations Research in Surface Mining and Metallurgical Engineering Optimization

Optimizing design of the problems in open-pit mining and metallurgy projects not only helps to reduce production costs and increase economic benefits, but also can save resources and protect the environment. By analyzing two examples in mining and metallurgy, this paper shows that operations research can provide scientific decision-making tools and methods for mining and product quality control. Question 1 on the premise of the best overall benefit, arrange ore production at each mine site. This is a 0-1 planning problem, combined with linear programming problem-solving ideas, the establishment of mathematical models, using lingo software solution, come to the best mining program. Problem 2 through the establishment of a mathematical model of linear programming, has been to meet the product quality requirements, and the lowest cost processing program.

V shaped gully method for controlling rockfall on high-steep slopes in China

Large, deep open-pit mining projects lead to rockfall, which becomes an engineering hazard second only to slope stability. The V shaped gully (V-gully) method introduced here was shown to have a significant effect on preventing rockfall through reduction of kinetic energy and rainfall discharge. The method, where a gravel cushion was laid on the V-gully surface, was applied in a typical open-pit mine. A drain dyke should be set at the bottom of the V-gully to discharge rainfall effectively. The slope stability analysis under different drainage rates was calculated by Modified Sarma (MSARMA) software. Slope stability, engineering activities and weathering condition of slope were taken into account to identify the rockfall prone areas. RocFall numerical software was used to calculate the effect of various angle V-gullies on the movements of various rockfall. A striking reduction in kinetic energy of rockfall was achieved, and the effects of V-gully protective measures were studied. Then, a system for controlling rockfall effectively and economically was designed for a particular slope according to the field situation. The effectiveness and reasonableness of design were evaluated through numerical simulations and field testing. This paper provides a theoretical and practical basis for a novel rockfall prevention technique on the high-steep slopes in similar engineering projects.

Optimum location and relocation plan of semi-mobile in-pit crushing and conveying systems in open-pit mines by transportation problem

In-pit crushing and conveying (IPCC) systems have attracted more interest among miners as an alternative to the conventional truck-shovel transportation system. The semi-mobile IPCC (SMIPCC) system is a well-suited type of IPCC system in open-pit mining projects because of its relocation nature. However, it is very important to design its optimum location and relocation plan in a manner that minimises the operating costs. In spite of a few previous works, which propose methods for optimum location and time in order to shift from a truck-shovel system to an IPCC system, a combined optimum location and relocation plan of the SMIPCC has not been investigated. This paper defines the optimum location and relocation plan of the SMIPCC in the context of a transportation problem with different ‘year levels’ as the sources and ‘levels’ as the destinations. This model is able to calculate the optimum solution simultaneously in the case of both location (level) and time (year level). The results show that this method can efficiently be applied as a planning tool for optimising operating and relocation costs, and the location and relocation plan of the SMIPCC.

The Role of Mine Surveying Studies in Preventing Probable Risks that might be emerged in Open Pit Mining Projects

In order to extract mine from the ground in any area, the type of mining to be selected will able to be defined as the result of the pre-investigations and analysis in the intended area. At this stage, economic value of the ore, geologic and tectonic features of the mining field, topographic state of the field, the thickness of the ore and the earth layer that is covering the ore, the excavation ability of the earth, and climate conditions of the concerned area are the leading factors in defining the type of mining (underground mining or open pit mining). In the later stage, these criteria, will be affecting and differentiate the mine measuring activities to be applied on the field, depending on the type of mining that is decided for application on the field. In this study, it is attempted to define the possible field measurement studies that are in the scope of mine surveying and probable risks that might be encountered in case of lacking these activities, during the starting, implementing and finishing the mining activities that are defined in a selected open pit mining area.

Investigation of Stability and Failure Mechanism of Undercut Slopes by Three-Dimensional Finite Element Analysis

Slope failures along a bedding plane were critical issues and mostly happened in an open pit mining project such as the Mae Moh Mine, Thailand. The prediction of maximum width to maintain stable slope after an excavation process is required. This paper presents an investigation of 3D finite element analysis for the stability and failure mechanism of undercut slopes resting on a low interface friction plane. In numerical models, the soil slope was modeled as volume elements with the hardening soil material. Interface elements were used at the bottom plane to simulate the low interface friction plane and at the side support to simulate fully rough surface for the models with side supports. Stage analyses in numerical models were performed following excavation processes in physical models until failure. The effects of the side support and the slope length to increase the stability of undercut slopes were considered. Failure widths, failure mechanisms, and stress distributions associated with slope angles and boundary conditions of side support were discussed and compared.

Socially responsible mining using project stakeholder identification and management

PurposeThe aim of this paper is to conduct an initial exploratory investigation to systematically identify and classify the stakeholders associated with the mining sector in West Africa into key and non-key stakeholders through the use of the comprehensive project stakeholder management tools and processes. The results can be used as an initial identification and classification of stakeholders associated with a typical mining project and can also be used as a basis for confirmation analysis to develop further knowledge and an improved understanding of the management of multiple stakeholders in mining sector projects.Design/methodology/approachThis exploratory work used mine managers from West Africa, asking them to identify stakeholders that are of importance to a typical open pit mining project and also to make some objective assessments of their attitudes and influence of the stakeholders identified. From this, a stakeholder power/interest grid was developed to classify stakeholders into key and non-key stakeholders.FindingsThe findings present an initial exploratory result indicating that the key stakeholders for a mining project are the Environmental Protection Agency, Minerals Commission, Geological Survey Department, Member of Parliament, the Ministry in charge of mining, Forestry Commission, farmers, Lands Commission, non-governmental organizations, Department of Feeder Roads, traditional chiefs, district or municipal assembly and youth associations within the concession area.Research limitations/implicationsThe research was limited to only respondents working in the mining sector in three West African countries.Practical implicationsPractically, this study highlights for mining companies and operators, some preliminary understanding of stakeholders that are critical for engagements to be successful in their operations.Social implicationsThis study, essentially, reveals the importance of the various stakeholder groups interested in a mining project and the level of influence.Originality/valueThis study contributes to the debate on project stakeholder management in the mining sector, especially from a developing country’s point of view.