Models and methods to make decisions while mining production scheduling

Purpose is to develop a new approach to the design of mining operations basing upon models and methods of decision making. Methods. The paper has applied a complex approach involving approaches of decision-making theory. Analysis of the pro-duction development scenarios is proposed for strategic activity planning; criteria to make decisions under the uncertainty conditions as well as decision-making trees for day-to-day management are proposed to determine balanced production level. Findings. It has been identified that mining production design is of the determined character demonstrating changes in “state of the nature” depending upon the made decisions. The idea of mining production is to reduce uncertainty gradually by means of analysis of production scenarios, and elimination of unfavourable alternatives. Operative management is implemented while constructing decision trees, and optimizing operation parameters. Representation of sets of rational equipment types as well as development scenarios, and their comparison in terms of decision-making parameters makes it possible to determine adequate capacity of a working area, and to reduce expenditures connected with the equipment purchase and maintenance. In this context, limiting factors, effecting anticipatory mining out-put, are taken into consideration. Successive comparison of the alternatives helps identify decision-making area for different scenarios of the production development. Originality. To manage mining production, approaches of decision-making theory have been proposed which involve the use of decision trees, decision-making criteria, and analysis of scenarios basing upon representation of operating procedures in the form of a network model within which the shortest route corresponds to optimum decision. Practical implications. Decision-making system has been developed making it possible to optimize operation parameters, to reduce prime cost of mining, and to select a structure of engineering connections with the specified production level. The described approaches may be applied at the stage of a stope design as well as in the process of a field development. Specific attention has been paid to a software development to implement the approaches.Мета. Розробити новий підхід до проектування гірничого виробництва, який базується на моделях та методах теорії прийняття рішень. Методика. В роботі застосовано комплексний метод, який включає підходи теорії прийняття рішень. Для стратегічного планування діяльності запропоновано досліджувати сценарії розвитку виробництва, для визначення раціонального рівня виробництва – критерії прийняття рішень в умовах невизначеності, а також дерева прийняття рішень для поточного управління. Результати. Виявлено, що процес проектування гірничого виробництва має детермінований характер, який демонструє зміну “станів природи” залежно від прийнятих рішень. Суть проектування гірничого виробництва зводиться до послідовного зменшення невизначеності шляхом дослідження сценаріїв виробництва та виключення несприятливих альтернатив. Оперативне управління здійснюється шляхом побудови дерев рішень та оптимізації параметрів експлуатації. Представлення множин раціональних типів обладнання, сценаріїв розвитку подій та порівняння їх за критеріями прийняття рішень дозволяє визначити раціональний рівень видобутку виймальної дільниці і знизити витрати на придбання та обслуговування обладнання, при цьому враховуються обмежувальні фактори, які впливають на величину очікуваного видобутку. Послідовне порівняння альтернатив дозволяє встановити поле прийнятних рішень для різних сценаріїв розвитку виробництва. Наукова новизна. Для управління гірничим виробництвом запропоновано підходи теорії прийняття рішень, які включають застосування дерев рішень, критеріїв прийняття рішень та аналіз сценаріїв, котрі базуються на представленні технологічного процесу у вигляді мережевої моделі, в якій найкоротший маршрут відповідає оптимальному рішенню. Практична значимість. Розроблена система прийняття рішень, дозволяє оптимізувати параметри експлуатації, знизити собівартість видобутку, вибрати структуру технологічних зв’язків з заданим рівнем продуктивності. Описані в роботі підходи можуть бути використані як на стадії проектування очисного забою так і в процесі експлуатації родовища корисних копалин. Особливу увагу приділено розробці програмного забезпечення для впровадження описаних підходів у виробництво.Цель. Разработать новый подход к проектированию горного производства, который базируется на моделях и методах теории принятия решений. Методика. В работе использован комплексный метод, который включает подходы теории принятия решений. Для стратегического планирования деятельности предложено исследовать сценарии развития производства, для определения рационального уровня производства – критерии принятия решений в условиях неопределенности, а также деревья принятия решений для текущего управления. Результаты. Установлено, что процесс проектирования горного производства носит детерминированный характер, который отражает изменение “состояний природы” в зависимости от принятых решений. Суть проектирования сводится к последовательному уменьшению неопределенности путем исследования сценариев производства и исключения неблагоприятных альтернатив. Оперативное управление осуществляется посредством построения деревьев решений и оптимизации параметров эксплуатации. Представление множества рациональных типов оборудования, сценариев развития событий та сравнение их по критериям принятия решений позволяет определить рациональный уровень добычи очистного участка и снизить затраты на приобретение и обслуживание оборудования, при этом учитываются ограничивающие факторы, которые влияют на величину ожидаемой прибыли. Последовательное сравнение альтернатив позволяет установить поле приемлемых решений для разных сценариев развития производства. Научная новизна. Для управления горным производством предложены подходы теории принятия решений, которые включают применения деревьев, критериев принятия решений и анализ сценариев, основанных на представлении технологического процесса в виде сетевой модели, где кратчайший маршрут соответствует оптимальному решению. Практическая значимость. Разработана система поддержки принятия решений, которая позволит оптимизировать параметры эксплуатации, снизить себестоимость добычи, выбрать структуру технологических взаимосвязей с заданным уровнем производительности. Описанные в работе подходы могут быть использованы как на стадии проектирования очистного забоя, так и в процессе эксплуатации месторождения полезных ископаемых. Особое внимание уделено разработке программного обеспечения для внедрения описанных подходов в горное дело.The study has been carried out within the framework of research project of the National Academy Sciences of Ukraine for young scientists “Resource-saving techniques to support mine workings under the complex hydrogeological conditions”; Agreement #29-04/06-2019; official registration #0119U102370

Methane concentration forward prediction using machine learning from measurements in underground mines

Unmanaged gases inside the mine airways are hazards to health and explosions, mainly methane (CH4) in coal mines. Temperature rise caused by heat release from the strata and machinery is another factor that may harm the health and safety of workers in underground mines. Control of methane and other gas components and the high temperature near a working face require overall localized ventilation management and adequate mine cooling systems. Continuously monitoring the in-situ atmospheric conditions and the number of contaminant gases, especially methane, are important factors for predicting the necessary actions for keeping the mine a safe and healthy place for workers. Studies are reported for predicting methane concentration variations inside underground mines using a long-short-term memory (LSTM) artificial recurrent neural network. Results will be compared to a simple time-series regression predictor (time-series filter). Different combinations of the variables and techniques are tested in the LSTM model to find the best results for accuracy and applicability. Forward time step variations are tested to explore the best prediction outcome. The results show that the LSTM model is limited to one-step-ahead prediction for reasonable accuracy. Furthermore, increasing the number of variables or the training window size does not seem to increase the accuracy of the LSTM predictions. Comparing the results using artificial data and the measured data from the mine, it is observed that the LSTM performs better if the data has a specific pattern and is as smooth as possible

Applications of Advanced Computational Modelling for Principal Underground Mining Hazards Management and Control

Underground coal mining is facing increased threats from the hazards of spontaneous combustion and heating of coal, abnormal mine gas emissions, and harmful dust concentrations in underground workings, due to increased production outputs and extraction depth of cover. To control and mitigate these engineering problems, there is a need to gain critical knowledge of spontaneous heating in the longwall (LW) goaf, gas migration patterns onto the LW face, and ventilation dynamics and dust dispersion in complex underground environments. Advanced Computational Fluid Dynamics (CFD) modelling can be used to simulate various scenarios portraying these hazards that may occur in underground LWs and provide much-needed knowledge and fundamental science that can be used to develop robust and effective control and mitigation strategies against these hazards. A comprehensive literature review has been conducted to understand these principal mining hazards (PMH), with a particular emphasis on the applications of CFD modelling in the prevention management and control of those PMH arising during coal extraction process. The insufficiencies and gaps in research on spontaneous combustion in active LW goaf, gas migration onto the LW face, and dust dispersion and transport in the development heading were identified. In addition, several field studies were carried out in underground coal mines in Australia to gain a better understanding of these mining issues and collate essential data for the CFD modelling studies. In recent years, goaf heating and spontaneous combustion incidents have been reported in several Australian underground coal mines during normal production cycles. The onset of these heating incidents was dictated by many operational and environmental parameters. Based on the site-specific conditions of an underground coal mine, where the coal seam gas is of approximately 80% carbon dioxide (CO2) and 20% methane (CH4) with a gas emission rate of 2000 l/s, CFD models were developed and validated with field gas monitoring data collected from the Tube Bundle System. The CFD models incorporated a user defined function (UDF) of gas emission and permeability variations in a three-dimensional (3D) space of computational domain representing the LW panels and goaf areas. Simulation results indicated that better goaf inertisation could be achieved when nitrogen (N2) was injected via cut-throughs (C/T) at about 250 m behind the LW face on the maingate (MG) side and surface boreholes at 100 m and 700 m on the tailgate (TG) side, with a total injection rate greater than 1750 l/s. The oxygen concentration on the MG and TG side dropped below 5% at distances of 120 m and 75 m behind the LW face, with a confined oxidation zone area of 35375 m2, which was approximately one-third of the oxidation zone area without inert gas injection. The impact of geological variations (i.e., coal seam orientations and goaf gas composition) on spontaneous combustion prevention and management was further studied using CFD models. The influence of ventilation design and operational parameters (e.g., tightness of the goaf seals) on spontaneous combustion control was also investigated by additional CFD models based on field data. During LW sealing-off, the ventilation flow dynamics change within the goaf, which considerably increases the risk of spontaneous combustion and gas explosion. To prevent these hazards, CFD models were developed and calibrated with field gas monitoring data to simulate a range of operational scenarios of different ventilation arrangements. The modelling studies indicated that at least six gas sensors should be employed and positioned appropriately to ensure effective goaf atmosphere monitoring for risk management during the LW sealing-off process. Extensive CFD-DPM (Discrete phase model) coupling modelling studies were conducted to investigate dust-related issues in LW gateroad development panels. Based on site-specific conditions, a CFD model incorporating a Continuous Miner (CM), Shuttle Car (SC) and exhausting ventilation tube was established and validated with onsite dust monitoring data. Three scenarios of CM cutting at the middle, floor and roof positions were considered and simulated. In all cases, the simulation results indicated that high levels of dust exposure would occur to left-hand-side (LHS) operators and consequently they should be equipped with high-quality personal protective equipment and stay behind the ventilation duct inlet during coal cutting process, while miners standing at the right-hands-side (RHS) of the CM for roof and/or rib bolting and machine operation should stay immediately behind the bolting rig where dust concentration was relatively low. The studies conducted in this thesis provided new insights into the current goaf inertisation practices to effectively manage and control spontaneous heating in LW goaf by considering geological variations and mining design. Furthermore, the CFD modelling study of gas flow dynamics during the panel sealing-off process provides new knowledge of ventilation and goaf gas dynamics, which is critical to the positioning of gas monitoring sensors to reliably measure goaf atmosphere changes, thus minimizing spontaneous heating and gas explosion risks with much-improved mine safety. The research work also shed light on the dust and ventilation behaviour in gateroad development panels, and provided several recommendations for operators’ locations and dust mitigation strategies to improve the health and safety of miners. The research outcomes from this study contribute to the improvement of current practices and guidance for PMH management and control in underground mines and tunnelling projects

Mining Safety and Sustainability I

Safety and sustainability are becoming ever bigger challenges for the mining industry with the increasing depth of mining. It is of great significance to reduce the disaster risk of mining accidents, enhance the safety of mining operations, and improve the efficiency and sustainability of development of mineral resource. This book provides a platform to present new research and recent advances in the safety and sustainability of mining. More specifically, Mining Safety and Sustainability presents recent theoretical and experimental studies with a focus on safety mining, green mining, intelligent mining and mines, sustainable development, risk management of mines, ecological restoration of mines, mining methods and technologies, and damage monitoring and prediction. It will be further helpful to provide theoretical support and technical support for guiding the normative, green, safe, and sustainable development of the mining industry

ODABIR NAJPRIKLADNIJEGA NAČINA BUŠENJA I MINIRANJA UPOTREBOM MADM METODA (STUDIJA SLUČAJA: RUDNIK ŽELJEZA SANGAN, IRAN)

Drilling is the first stage of open pit mining that has a considerable effect on the other stages of mining, including blasting, loading, hauling and crushing. An unsuitable drilling pattern may lead to undesirable results such as poor fragmentation, back break and fly rock that not only results in technical and safety issues but also increases the operating cost of the mine. Multi-Attribute Decision-Making (MADM) methods can be useful approaches to select the appropriate drilling pattern among various alternatives, performed previously. This paper aims to select the most proper drilling and blasting pattern for Sangan Iron Mine, Iran. To achieve this, in the first step, rock fragmentation, back break, fly rock, specific charge and specific drilling were considered as the decision criteria and their degree of importance was calculated using the AHP method under a fuzzy environment. Then, TOPSIS and PROMETHEE methods were used to select the most proper alternative. The results of this study show that the drilling pattern with a spacing of 5 m, burden 4 m, hole depth 10 m, and hole diameter 15 cm is the most suitable one. The stemming length and powder factor of the suggested pattern are 2.3 m and 2.6 gr/cm3, respectively.Bušenje je prva faza površinske eksploatacije koja ima znatan utjecaj na ostale faze rudarenja, uključujući miniranje, utovar, transport i drobljenje. Neprimjeren način bušenja može dovesti do nepoželjnih rezultata poput loše fragmentacije, povratnoga loma i odbacivanja stijena, što ne samo da rezultira tehničkim i sigurnosnim problemima, već i povećava operativne troškove rudnika. Metode donošenja odluka s više atributa (MADM) mogu biti korisne za odabir odgovarajućega načina bušenja među raznim prethodno izvedenim alternativama. Cilj je ovoga rada odabrati najpogodniji način bušenja i miniranja za rudnik željeza Sangan, Iran. Da bi se to postiglo, u prvome koraku kao kriteriji za odlučivanje razmatrani su fragmentacija stijena, povratno lomljenje, odbacivanje stijena, specifično punjenje i specifično bušenje, a njihova važnost izračunana je korištenjem AHP metode u neizrazitome okruženju. Zatim su korištene metode TOPSIS i PROMETHEE za odabir najprikladnije alternative. Rezultati ove studije pokazuju da je najprikladniji način bušenja s razmakom od 5 m, opterećenjem od 4 m, dubinom rupe od 10 m i promjerom rupe od 15 cm. Duljina čepa bušotine i specifična potrošnja eksploziva predloženoga uzorka iznose 2,3 m, odnosno 2,6 g/cm3

Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes

The book documents 25 papers collected from the Special Issue “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”, highlighting recent research trends in complex industrial processes. The book aims to stimulate the research field and be of benefit to readers from both academic institutes and industrial sectors

Mining Technologies Innovative Development

The present book covers the main challenges, important for future prospects of subsoils extraction as a public effective and profitable business, as well as technologically advanced industry. In the near future, the mining industry must overcome the problems of structural changes in raw materials demand and raise the productivity up to the level of high-tech industries to maintain the profits. This means the formation of a comprehensive and integral response to such challenges as the need for innovative modernization of mining equipment and an increase in its reliability, the widespread introduction of Industry 4.0 technologies in the activities of mining enterprises, the transition to "green mining" and the improvement of labor safety and avoidance of man-made accidents. The answer to these challenges is impossible without involving a wide range of scientific community in the publication of research results and exchange of views and ideas. To solve the problem, this book combines the works of researchers from the world's leading centers of mining science on the development of mining machines and mechanical systems, surface and underground geotechnology, mineral processing, digital systems in mining, mine ventilation and labor protection, and geo-ecology. A special place among them is given to post-mining technologies research

Volume II: Mining Innovation

Contemporary exploitation of natural raw materials by borehole, opencast, underground, seabed, and anthropogenic deposits is closely related to, among others, geomechanics, automation, computer science, and numerical methods. More and more often, individual fields of science coexist and complement each other, contributing to lowering exploitation costs, increasing production, and reduction of the time needed to prepare and exploit the deposit. The continuous development of national economies is related to the increasing demand for energy, metal, rock, and chemical resources. Very often, exploitation is carried out in complex geological and mining conditions, which are accompanied by natural hazards such as rock bursts, methane, coal dust explosion, spontaneous combustion, water, gas, and temperature. In order to conduct a safe and economically justified operation, modern construction materials are being used more and more often in mining to support excavations, both under static and dynamic loads. The individual production stages are supported by specialized computer programs for cutting the deposit as well as for modeling the behavior of the rock mass after excavation in it. Currently, the automation and monitoring of the mining works play a very important role, which will significantly contribute to the improvement of safety conditions. In this Special Issue of Energies, we focus on innovative laboratory, numerical, and industrial research that has a positive impact on the development of safety and exploitation in mining