Mining Method Selection Research Articles

Reducing mining tailings and operational dilution: a new application of the room-and-pillar mining method

The selection of an underground mining method stems from a multivariate analysis that considers geomechanical, geological, economic, and operational parameters. Even after identifying the most compatible method, there is no assurance that the mining company will achieve the best performance. The geological complexity of some deposits requires adaptations of methods described in the literature to obtain more selectivity and reduce mining waste. There are some studies on geometry of underground structures, but a methodology that describes an adaptation of a room-and-pillar mining method for ore bodies with down-dip varying from 20° to 25° is novel. The present work aimed to reduce dilution by adapting the traditional room-and-pillar mining method (TRP) to inclined ore bodies. This new method is entitled short-hole room-and-pillar (SHRP). The equations that measure the dilution are defined according to the geometry of stopes and openings. The results comprise comparative analyses of the operational and planned dilutions to measure the performance of the SHRP method. The average operating dilution of the SHRP method was more than five times lower than the planned dilution according to the TRP method. Low operational dilution indicates high selectivity of the method and its potential to reduce underground mining tailings.

A Causal Analysis of the Influential Criteria in Underground Mining Method Selection

A Causal Analysis of the Influential Criteria in Underground Mining Method Selection

Sustainable mining method selection by a multi-stakeholder collaborative multi-attribute group decision-making method

How to protect the ecological environment during mineral resource exploitation is a crucial issue for the survival and development of human society. In this context, mining method selection requires simultaneous achieving environmental protection and resource exploitation, while involving the coordination of multi-agent interests. Therefore, this study develops a multi-stakeholder collaborative multi-attribute group decision-making approach for mining method selection. This method enables multiple stakeholders and experts from different fields to make decisions together. First, a conflict resolution model is proposed to resolve cognitive conflict and interest conflict among multi-stakeholders. Then, the 2-tuple linguistic representation model is used to deal with the decision maker's fuzzy preference. Next, the comprehensive attribute weights are calculated and the alternatives are prioritized. A case study for mining method selection in a gold mine in Shandong Province, China, is presented to verify the validity of the proposed method. This method considers not only the coordination between mineral resource exploitation and ecological environment protection but also the conflicting views of stakeholders. The proposed method is a useful tool for the assessment and selection of development schemes involving multiple stakeholders.

SIMULTANEOUS EVALUATION OF CRITERIA AND ALTERNATIVES FOR MINING METHOD SELECTION (CASE STUDIES: GOL-E-GOHAR NO. 3 IRON ORE AND CHAHAR-GONBAD COPPER ORE)

Selecting a mining method is an essential step in the initial phases of mining. The selection of an inappropriate mining method can have consequences, such as the potential loss of a portion of the ore deposit. Sometimes, changing the mining method can result in high costs that render the entire project economically unfeasible. For the past two decades, qualitative patterns and numerical scoring have been replaced by multi-criteria decision-making methods. In this study, the Simultaneous Evaluation of Criteria and Alternatives (SECA) multi-criteria decision analysis method was introduced for the first time in the selection of mining methods. The SECA was used to select the mining method in two ore bodies: Gol-E-Gohar No. 3 Iron ore and Chahar-Gonbad Copper ore. The final ranking compared with the results obtained from the fuzzy TOPSIS decision-making method. The satisfactory results indicated that the open-pit method was selected as the appropriate approach for both cases. The SECA method has lower computational complexity because it does not require the use of weight vectors as inputs. However, it does require a precise decision matrix. This method can be considered the foundation of artificial intelligence for selecting a mining method.

Application of Z-numbers theory to study the influencing criteria in underground mining method selection

The purpose of this study was to prioritize and determine the importance of effective factors in selecting the appropriate underground mining method (UMM). This study also evaluates the uncertainty and various life-threatening/mortal and financial risks associated with these criteria. In the present study, 43 influencing criteria for underground mining method selection (UMMS) were identified and classified into two main groups. Then, a model was proposed by employing the Z-numbers theory (Z-NT). A total of 25 specialists from around the world were approved for the study, and 10 of them returned questionnaires. By applying Z-numbers and using the proposed model, the uncertainty of the experts' opinions was highly reduced. Finally, the model was applied to the Angouran Lead and Zinc (L&Z) Mine in the northwest of Iran for verification. The findings indicate that within every group of criteria, the weighting of factors determined in this study is in good harmony with the key factors considered in the selection of mining method at Angouran Mine. Also, based on the technical reports of Angouran Mine, the mine is facing various risks. Therefore, this research has also been examined from a risk assessment perspective, and the findings of the proposed model have been put against the factors influencing the various risks in the Angouran Mine. The results show that the factors that have the highest weight in risk proneness are stope collapse, underground water inflow into the stope, and machines’ downtime.

Comparative Analysis of AHP and TOPSIS Multi-Criteria Decision-Making Methods for Mining Method Selection

Comparative Analysis of AHP and TOPSIS Multi-Criteria Decision-Making Methods for Mining Method Selection

Applying Nonnegative Matrix Factorization for Underground Mining Method Selection Based on Mining Projects' Historical Data

Applying Nonnegative Matrix Factorization for Underground Mining Method Selection Based on Mining Projects' Historical Data

Application of the FUZZY TOPSIS method for selecting an underground mining method

Selecting the underground mining method is one of the most difficult decisions any mining engineer makes when designing a new mine or opening new parts in an existing mine. The underground mining method selection depends on many mining-geological, technical and economic factors. The process of selecting a mine excavation method is a multi-criteria decision-making process since many factors are considered when selecting a mining method. The selection of the most suitable mining method is of great importance for each mine, and this is especially evident in the phase of preparation and excavation of the ore deposit and optimization of the total cost of excavation. This paper uses the Fuzzy TOPSIS method to select the underground mining method for metallic mineral resources as one of the most important multi-criteria decision-making methods. The methodology presented will enable the application of other fuzzy methods to solve problems related to the mining method selection.

Investigate the potential of using fuzzy similarity in decision making under uncertainty for mining projects

Multi criteria decision-making methods are used in mining engineering, in which various aspects are involved, such as selecting mining methods, mineral processing sites, etc. Decisions in this field can be made using a variety of techniques. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is one of the most widely used decision-making methods based on multi criteria to make a decision. As part of this research, an attempt was made to investigate how fuzzy measurements can be applied to mining projects to improve the TOPSIS methods' efficiency. A full investigation of the mining method selection process, the waste dump site selection process at Gol-e-Ghar mine Area 3, the location of Bahabad Pelletizing plant, the appropriate site selection for crusher machine Sarcheshmeh copper mine, and loading-haulage equipment selection for Sungun copper mine has been carried out in order to achieve this goal. Accordingly, an area north of the pit was selected as the best location for the waste dump, open-pit mining was selected as the best mining method for the Gol-e-Gohar mine, Cite Number 2 was selected as the best location for the Bahabad Pelletizing Plant, the East side of the Sarcheshmeh copper mine is presented as the most suitable one, and shovel-truck-belt conveyor selected as the transportation method for Sungun copper mine. For mining projects, fuzzy similarity logic in the TOPSIS method provides both accurate and efficient results, as well as reducing the number of calculations. It also provides accurate results based on linguistic, numeric, and fuzzy values and determines whether all alternatives are feasible. Finally, it is shown that the TOPSIS based on fuzzy similarity for considering uncertainty in mining projects that are involved the decision-making process can be practical and useful.

Underground Mining Method Selection with the Application of TOPSIS Method

Multi-criteria decision-making methods are widely used to solve various problems in the industry, as well as to support the planning and designing industrial processes. Mining is a very complex and responsible activity, so when making a major decision, it is necessary to take into account several parameters and perform their detailed analysis. Due to the importance of proper decision making, multi-criteria optimization methods have a very wide application in mining. One of the most complex and important things in mining is the choice of mining method for underground exploitation, where the application of multi-criteria decision-making methods can help a lot in making the right decision. This paper will present the choice of the method of mining excavation by the TOPSIS method, according to which it was obtained that the Sublevel Caving is optimal for a given case. Keywords: Multi-criteria decision-making methods; TOPSIS method; Underground mining method selection.

Mining method selection for extracting moderately deep ore body using analytical hierarchy process at mindola sub- vertical shaft, Zambia

Mining method selection for extracting moderately deep ore body using analytical hierarchy process at mindola sub- vertical shaft, Zambia

Improving the technology of underground mining of polymetallic ores at the Korbalikhinsky mine of Siberia-Polymetals JSC

Introduction. The article contains the results of research on an effecient and safe technology for underground mining of polymetallic ores of the Korbalikhinsky deposit, located in Western Siberia in the south of the Altai Territory, 1.5 km north of the town of Zmeinogorsk. The deposit is developed by underground technique of the Korbalikhinsky mine of Siberia-Polymetals JSC, which is part of the Ural Mining and Metallurgical Company JSC (UMMC JSC) holding corporation. Research objective is to find new technological solutions for the Korbalikhinsky mine of SiberiaPolymetals JSC that allow changing the technology of ore extraction with the ability to ensure the annual production capacity of the mine of 1.5 million tons of ore. Methods of research included the selection of alternative, safe and suitable mining method that is suitable for the Korbalikhinsky deposit by analyzing the mining and geological conditions and mining factors. Methods of research also included geomechanical justification for mining method structural element parameters, the development of underground mining technology and ore bodies sequence of mining. Results. From the mining methods proposed by the authors, the specialists of the mine selected the chamber mining method with reduced design parameters and backfilling. It is cost-effective and safe at the same time. Absence of people in the developed space, higher mining productivity and optimal recovery factor are its advantages. The proposed technology of underground ore mining will allow the mine to reach the level of annual production capacity of 1.5 million tons by 2025.

A literature review of Multi Criteria Decision-Making (MCDM) towards mining method selection (MMS)

Mining Method Selection (MMS) is one of the important decisions in the mining design. The appropriate decision guarantees economic exploitation and an unsuitable selection may lead to mining losses. The decision on mining method depends on several parameters such as geometric factors, geotechnical, geological conditions, economic and environmental factors, etc. The past decades, empirical models were using to select the mining method. There are shortcomings with empirical models, such as limitations in the number of criteria and options, decision-making in crisp and certain situations, unclear answers and dependence on experience and so on. The using of Multi Criteria Decision Making (MCDM) has been considered to select the best mining method recently. In this research, a comprehensive literature review are presented in order to uncover and interpret the current research on MCDM applications in MMS. For this purpose, a reference bank has been established based on a classification scheme which includes 55 research papers already published in 18 scholarly journals up to 2020. Quartile Scores in the web of knowledge (Q) was used for validation of the articles. Distribution of the articles throughout the world and according to different ore bodies was also evaluated. Results showed that AHP and TOPSIS were the most preferred methods used in selection of the mining methods. Fuzzy decision making has recently gained more importance for consideration of uncertainty. Also, the important role of criteria in different ores is presented as a guide for MMS.

Application of Entropy Method for Estimating Factor Weights in Mining-Method Selection for Development of Novel Mining-Method Selection System

Mining-method selection (MMS) is one of the most critical and complex decisionmaking processes in mine planning. Therefore, it has been a subject of several studies for many years culminating with the development of different systems. However, there is still more to be done to improve and/or create more efficient systems and deal with the complexity caused by many influencing factors. This study introduces the application of the entropy method for feature selection, i.e., select the most critical factors in MMS. The entropy method is applied to assess the relative importance of the factors influencing MMS by estimating their objective weights to then select the most critical. Based on the results, ore strength, host-rock strength, thickness, shape, dip, ore uniformity, mining costs, and dilution were identified as the most critical factors. This study adopts the entropy method in the data preparation step (i.e., feature selection) for developing a novel-MMS system that employs recommendation system technologies. The most critical factors will be used as main variables to create the dataset to serve as a basis for developing the model for the novel-MMS system. This study is a key step to optimize the performance of the model.

Application of Cascade Forward Backpropagation Neural Networks for Selecting Mining Methods

Decision-making is very important in many fields, such as mining engineering. In addition, there has been a growth of computer applications in all fields, especially mining operations. One of these application fields is mine design and the selection of suitable mining methods, and computer applications can help mine engineers to decide upon and choose more satisfactory methods. The selection of mining methods depends on the rock-layer specification. All rock characteristics should be classified in terms of technical and economic concerns related to mining rock specifications, such as mechanical and physical properties, and evaluated according to their weights and ratings. Methodologically, in this study, the criteria considered in the University of British Columbia (UBC) method were used as references to establish general criteria. These criteria consist of general shape, ore thickness, ore plunge, and grade distribution, in addition to the rock quality designation (ore zone, hanging wall, and foot wall) and rock substance strength (ore zone, hanging wall, and foot wall). The technique for order of preference by similarity to ideal solution (TOPSIS) was adopted, and an improved TOPSIS method was developed based on experimental testing and checked by means of the application of cascade forward backpropagation neural networks in mining method selection. The results provide indicators that decision makers can use to choose between different mining methods based on the total points given to all ore properties. The best mining method is cut and fill stopping, with a rank of 0.70, and the second is top slicing, with a rank of 0.67.

A new multi-objective optimization ratio analysis plus full multiplication form method for the selection of an appropriate mining method based on 2-tuple spherical fuzzy linguistic sets.

The selection of an appropriate mining method is considered as an important tool in the mining design process. The adoption of a mining method can be regarded as a complex multi-attribute group decision-making (MAGDM) problem as it may contain uncertainty and vagueness. The main goal of this paper is to propose an extended multi-objective optimization ratio analysis plus full multiplication form (MULTIMOORA) method that is based on a 2-tuple spherical fuzzy linguistic set (2TSFLS). The MULTIMOORA method under 2TSFL conditinos has been developled as a novel approach to deal with uncertainty in decision-making problems. The proposed work shows that 2TSFLSs contain collaborated features of spherical fuzzy sets (SFSs) and 2-tuple linguistic term sets (2TLTSs) and, hence, can be considered as a rapid and efficient tool to represent the experts' judgments. Thus, the broader structure of SFSs, the ability of 2TLTSs to represent linguistic assessments, and the efficiency of the MULTIMOORA approach have motivated us to present this work. To attain our desired results, we built a normalized Hamming distance measure and score function for 2TSFLSs. We demonstrate the applicability and realism of the proposed method with the help of a numerical example, that is, the selection of a suitable mining method for the Kaiyang phosphate mine. Then, the results of the proposed work are compared with the results of existing methods to better reflect the strength and effectiveness of the proposed work. Finally, we conclude that the proposed MULTIMOORA method within a 2TSFLS framework is quite efficient and comprehensive to deal with the arising MAGDM problems.

Fuzzy Logic for Underground Mining Method Selection

The Selection of the mining method for underground minerals extraction is the crucial task for the mining engineers. Underground minerals extraction is a multi-criteria decision making problem due to many criteria to be considered in the selection process. There are many studies on selection of underground mining method using Multi Criteria Decision Making (MCDM) techniques or approaches. Extracting minerals from the underground involves many geological characteristics also called as input parameters. The geological characteristics of any mineral deposit vary from one location to another location. Thus only one mineral extraction method is not suitable for different deposit characteristics. There are many mineral extraction methods available for different characteristics of the ore deposit. As of now only MCDM approach or Hybrid MCDM approaches or MCDM approaches with fuzzy logic were used for selecting a mining method for underground metal mine. In this study, only fuzzy logic approach is used for selecting a mining method for different deposit characteristics. The proposed model considers five deposit characteristics as input parameters and seven underground mining methods output parameters The developed fuzzy logic based approach is also validated by the deposit characteristics of two Indian mines. The model produced the suitable mining method for extraction of the minerals at the specified Indian mines and the same mining methods are used by the mine authorities.

Review on the Development of Mining Method Selection to Identify New Techniques Using a Cascade‐Forward Backpropagation Neural Network

The most crucial event in a mining project is the selection of an appropriate mining method (MMS). Consequently, determining the optimal choice is critical because it impacts most of the other key decisions. This study provides a concise overview of the development of multiple selection methods using a cascade‐forward backpropagation neural network (CFBPNN). Numerous methods of multicriteria decision‐making (MCDM) are discussed and compared herein. The comparison includes several factors, such as applicability, subjectivity, qualitative and quantitative data, sensitivity, and validity. The application of artificial intelligence is presented and discussed using CFBPNN. The Chengchao iron mine was selected for this investigation to pick the optimum mining method. The results revealed that cut and fill stoping is the most appropriate mining method, followed by sublevel and shrinkage stoping methods. The least appropriate method is open‐pit mining, followed by room and pillar and longwall mining methods.

Application of UBC methodology for underground mining method selection

The total operating costs of each mine largely depend on the method of mining. Therefore, the appropriate choice of the method of mining excavation is very important and great attention is paid to this issue. There are several procedures for the selection of the mining method, among which the most important and most commonly used numerical method is the UBC methodology for the selection of the mining method. According to this methodology, the choice of the method of mining excavation is based on the mining-geological parameters of the ore and adjacent rocks. In this paper, the UBC methodology for the selection of the mining excavation method for a specific case will be applied. According to this methodology, it was obtained that Cut and Fill method is best ranked for specific conditions and the most appropriate way of mining.

Sensitivity analysis of fuzzy-analytic hierarchical process (FAHP) decision-making model in selection of underground metal mining method

This study aims to analyse the sensitivity in decision-making which results in the selection of the appropriate underground metal mining method using the fuzzy-analytical hierarchy process (FAHP) model. The proposed model considers sixteen criteria for the selection of the most appropriate mining method out of the seven. The model consists of three-layer viz. the first layer represents the criteria (factors which influence the mining method), the second layer represents the sub-criteria (categorisation of the factors) and the third layer represents the alternatives (mining methods). The priority of the different mining methods was determined based on global weights. The global weights of seven mining method were determined using a different fuzzification factor under different decision-making attitudes (optimistic, pessimistic and unbiased). The sensitivity of the decision-making results was analysed in order to understand the robustness of the model.