Application of an improved mining complex for opencast mining of ore deposits

The purpose of the study is reducing the loss of mineral raw materials and increasing the efficiency of mining operations using a mining complex through the introduction of a new design and engineering solution that improves the equipment functionality. The study involves the analysis of known designs of mining equipment capable of providing the transformation of cyclic scooping of rock mass into its continuous loading, as well as screening of fine fractions from the ore mass. High productivity mining complexes are referred to a promising direction of mining equipment development. The article proposes an improved design of the mining complex, which allows to combine the extraction and loading process and ore mass grading. The improved mining complex is equipped with an annular conveyor with vibrating grids through which fines are screened into the accumulation hopper. From the accumulation hopper the small fractions are sent by means of a pneumatic conveying system to the bunker sections of a special-purpose hauler while the oversize product is loaded into a dump truck by a dump conveyor. The fine fractions of substandard ore collected in the bunker sections are sent for heap leaching. The fine fractions of conditioned ore are sent to the concentration plant to be processed. The proposed design and engineering solution employing an improved mining complex will reduce the cost of works and increase the recovery factor of mineral raw materials in the development of complex-structured deposits of ores characterized by natural concentration of small classes. Removal of fine ore fractions directly during the excavation and loading process can significantly reduce the dusting and decrease the loss of mineral raw materials from blowing and spilling of fine fractions.

A new global optimum solution model based on multi-value dynamic programming for the cut-off grade optimization in a surface mining complex

In techno-economic concern, cut-off grade (COG) optimization is the key for efficient mineral liquidation from thehuge metalliferous surface mining sector. In this paper, a sequentially advancing algorithm based on discretemulti-value dynamic programming (MDP) has been developed to calculate the global optimum COG of alarge-scale open-pit metalliferous deposit. The proposed COG optimization algorithm aims to overcome thelimitations of straightforward classical techniques in determining the optimum COG. This discrete COG-MDPmodel is the first of its kind and has the novelty of dealing with the simulation of eight dynamic possibilities toachieve the maximal global Net Present Value (NPV). A high-level programming language (Python) has been usedto develop the computer model to deal with the complexity of handling a minimum of 500 series of dynamicvariables. This model can generate results in polynomial-time from the complex of mining, milling, and smeltingand refining system corresponding to various limiting conditions. The prime objective considered in the model isto optimize the COG of a metalliferous deposit. A working open-pit copper mining complex from India has beenused to validate the model. In this study, the optimum COG for the Malanjkhand copper deposit has been found tobe (0.33%, 0.23%, 0.52%, 0.26%, 0.27%, 0.22%, 0.24%) with a maximum NPV of ₹ (12204, 14653, 16948, 14609,21454, 26717, 38821) million corresponding to various scenarios. The findings also show that the present valuegradually hits zero after the project’s life cycle, confirming the typical pattern of other mining firms.

Applied Machine Learning for Geometallurgical Throughput Prediction—A Case Study Using Production Data at the Tropicana Gold Mining Complex

With the increased use of digital technologies in the mining industry, the amount of centrally stored production data is continuously growing. However, datasets in mines and processing plants are not fully utilized to build links between extracted materials and metallurgical plant performances. This article shows a case study at the Tropicana Gold mining complex that utilizes penetration rates from blasthole drilling and measurements of the comminution circuit to construct a data-driven, geometallurgical throughput prediction model of the ball mill. Several improvements over a previous publication are shown. First, the recorded power draw, feed particle and product particle size are newly considered. Second, a machine learning model in the form of a neural network is used and compared to a linear model. The article also shows that hardness proportions perform 6.3% better than averages of penetration rates for throughput prediction, underlining the importance of compositional approaches for non-additive geometallurgical variables. When adding ball mill power and product particle size, the prediction error (RMSE) decreases by another 10.6%. This result can only be achieved with the neural network, whereas the linear regression shows improvements of 4.2%. Finally, it is discussed how the throughput prediction model can be integrated into production scheduling.

EXTRACTION MECHANIZATION OF SOFT SOILS

The state economic development is largely determined by the effectiveness of its individual structural elements. Among them, a special place is occupied by trends in the mineral sector, which dictates the requirements and mechanisms for the development of natural resources, creating the basis for a national strategy. However in this area there are a number of unsolved problems, which include: a low level of rational use of machine-technological mining systems from under the water with minimal man-made impact. The authors consider existing and alternative extraction methods of peat raw materials. The tasks facing the mineral resource sector can be solved through technological priority developments of aggregated extraction complexes for the peat raw materials and the equipment modernization for mining complexes. The analysis is carried out and recommendations are made for the working equipment modernization of the aggregated mining complex. Variants of the excavator excavation bucket for the extraction of peat raw materials from under water have been proposed. The results of studies on primary dehydration, combining mining and dewatering cycles in a bucket, are presented; the work gives the recommendations on the bucket use and the expediency of operating the mining machine's extraction body when extracting peat raw materials.

SUSTAINABLE DEVELOPMENT OF THE MINING COMPLEX OF THE MURMANSK REGION: MINIMIZATION OF MAN-MADE IMPACTS ON THE ENVIRONMENT

The Murmansk region is a region with the largest enterprises of the mining complex of the Russian Federation: KF JSC “Apatit”, JSC “Kola MMC”, JSC “Olkon”, JSC” Kovdorsky GOK”, JSC” North-West Phosphorus Company”, LLC”Lovozersky GOK”. They provide the majority of the country’s demand for phosphate ores, zirconium raw materials (baddeleyite), niobium, tantalum, and rare earth metals. In addition, the mining and processing of copper-nickel, iron and chrome ores, nepheline and ceramic raw materials, facing stone and building materials is carried out. At the same time, the activities of enterprises have a very negative impact on the environment. The issues of environmental safety in the extraction and processing of minerals, storage of mining waste in the Arctic zone of the Russian Federation are of particular relevance. The definition of sustainable development in relation to the mining industry is given. The concepts of available best technologies, circular economy, and “green growth” are considered from the point of view of their contribution to sustainable development. It is shown that the sustainable development of enterprises at the present stage is impossible without improving the environmental friendliness of production. The article analyzes the legislation of the Russian Federation and the practice of its application to identify mechanisms that promote sustainable development and eliminate barriers to the implementation of this concept in the mining industry. New technological solutions have been developed for mining enterprises of the Murmansk region, aimed at reducing aero-technogenic emissions, cleaning waste (mine) water, processing tailings of enrichment as man-made deposits, which allows both to minimize man-made environmental impacts and to increase the full use of mineral raw materials. Thus, the expediency of using the principles of “green growth” for the development of economic development policies in the Arctic is justified.

Integrating Production Planning with Truck-Dispatching Decisions through Reinforcement Learning While Managing Uncertainty

This paper presents a new truck dispatching policy approach that is adaptive given different mining complex configurations in order to deliver supply material extracted by the shovels to the processors. The method aims to improve adherence to the operational plan and fleet utilization in a mining complex context. Several sources of operational uncertainty arising from the loading, hauling and dumping activities can influence the dispatching strategy. Given a fixed sequence of extraction of the mining blocks provided by the short-term plan, a discrete event simulator model emulates the interaction arising from these mining operations. The continuous repetition of this simulator and a reward function, associating a score value to each dispatching decision, generate sample experiences to train a deep Q-learning reinforcement learning model. The model learns from past dispatching experience, such that when a new task is required, a well-informed decision can be quickly taken. The approach is tested at a copper–gold mining complex, characterized by uncertainties in equipment performance and geological attributes, and the results show improvements in terms of production targets, metal production, and fleet management.

COAL MINING COMPLEX IN THE BAIKAL-AMUR RAILWAY AREA: STATE AND PROSPECTS FOR DEVELOPMENT

The analysis of the state, prospects and problems for the development of the coal mining complex in the area of the Baikal-Amur railway is carried out. The information on the developed and planned for the development of coal deposits in the region is presented. The market requirements for the quality of solid fuel are considered. It is shown that the current documents of the federal and regional levels, which determine the strategy of the enterprises that carry out or plan their work in the field of mining, enrichment and supply of coal to consumers, require additional approval and clarification. The systematic approach used allows us to identify such inconsistencies and consider the possibilities of correction. Measures are proposed to improve the efficiency of the coal complex enterprises. The problem of improving the efficiency and competitiveness of coal supply chains is considered. The role and place of quality management of coal products in order to achieve planned goals are indicated.