Truck Selection with the Fuzzy-WSM Method in Transportation Systems of Open Pit Mines

Open pit mines gain width and become more complicated as they are deeper today, and it is inevitable to carry the produced material with a truck transportation system. Therefore, in large-scale businesses, truck selection has great importance for the transportation costs to be sustainable. This study investigates the main factors and corresponding criteria influential in selection of trucks, which are the most frequent used means of transportation in open pit mines. Analytic hierarchy process and fuzzy weighted sum model are employed to solve the selection problem. Six different truck types and 20 selection criteria are considered. As a result of technical analysis, most suitable trucks are found

Evolution, Monitoring and Predicting Models of Rockburst: Precursor Information for Rock Failure

Load/unload response ratio predicting of rockburst; Three-dimensional reconstruction of fissured rock; Nonlinear dynamics evolution pattern of rock cracks; Bayesian model for predicting rockburs

Development of fractal-fuzzy evaluation methodology and its application for seismic hazards assessment using microseismic monitoring in coal mining

Seismic hazards have become one of the common risks in underground coal mining and their assessment is an important component of the safety management. In this study, a methodology, involving nine fractal dimension-based indices and a fuzzy comprehensive evaluation model, has been developed based on the processed real time microseismic data from an underground coal mine, which allows for a better and quantitative evaluation of the likelihood for the seismic hazards. In the fuzzy model, the membership function was built using a Gaussian shape and the weight of each index was determined using the performance metric F score derived from the confusion matrix. The assessment results were initially characterised as a probability belonging to each of four risk levels (none, weak, moderate and strong). The comprehensive result was then evaluated by integrating the maximum membership degree principle (MMDP) and the variable fuzzy pattern recognition (VFPR). The model parameters of this methodology were first calibrated using historical microseismic data over a period of seven months at Coal Mine Velenje in Slovenia, and then applied to analyse more recent microseismic monitoring data. The results indicate that the calibrated model was able to assess seismic hazards in the mine

Computational intelligent impact force modeling and monitoring in HISLO conditions for maximizing surface mining efficiency, safety, and health

Shovel-truck systems are the most widely employed excavation and material handling systems for surface mining operations. During this process, a high-impact shovel loading operation (HISLO) produces large forces that cause extreme whole body vibrations (WBV) that can severely affect the safety and health of haul truck operators. Previously developed solutions have failed to produce satisfactory results as the vibrations at the truck operator seat still exceed the “Extremely Uncomfortable Limits”. This study was a novel effort in developing deep learning-based solution to the HISLO problem. This research study developed a rigorous mathematical model and a 3D virtual simulation model to capture the dynamic impact force for a multi-pass shovel loading operation. The research further involved the application of artificial intelligence and machine learning for implementing the impact force detection in real time. Experimental results showed the impact force magnitudes of 571 kN and 422 kN, for the first and second shovel pass, respectively, through an accurate representation of HISLO with continuous flow modelling using FEA-DEM coupled methodology. The novel ‘DeepImpact’ model, showed an exceptional performance, giving an R2, RMSE, and MAE values of 0.9948, 10.750, and 6.33, respectively, during the model validation. This research was a pioneering effort for advancing knowledge and frontiers in addressing the WBV challenges in deploying heavy mining machinery in safe and healthy large surface mining environments. The smart and intelligent real-time monitoring system from this study, along with process optimization, minimizes the impact force on truck surface, which in turn reduces the level of vibration on the operator, thus leading to a safer and healthier working mining environments --Abstract, page iii

Advances in mining safety theory, technology, and equipment

Mineral resources are an important pillar of human social development. With the gradual depletion of shallow resources, deep mining is an inevitable choice for ensuring energy security in various countries in the future. The complex and harsh environment in deep mining areas has led to frequent occurrences of hazardous events such as rockburst, coal and gas outburst, and mine fires. Mining safety science and engineering issues are receiving increasing attention. In August 2023, the 6th International Symposium on Mine Safety Science and Engineering was held in Harbin to promote innovative development of mining safety, and foster international collaborations among scholars in the field of mining safety. It served as a platform for the exchange of the most recent advancements in mining safety scientific theories, technologies, and equipment by bringing together global talent. Over 400 delegates representing 9 countries, including Australia, Russia, United State, Kazakhstan, and Canada, engaged in academic discussions and knowledge sharing on new theories, technologies, equipment, and methods in mining safety science and engineering. The latest research results are of great significance in enhancing the practices of preventing mine disaster and ensuring the safety of mining operations.Document Type: EditorialCited as: He, S., He, X., Mitri, H., Meng, S., Wu, Q., Ren, T., Liu, S. Advances in mining safety theory, technology, and equipment. Advances in Geo-Energy Research, 2023, 10(2): 71-76. https://doi.org/10.46690/ager.2023.11.0

Life Cycle-based Environmental Performance Indicator for the Coal-to-energy Supply Chain: A Chinese Case Application

Coal consumption and energy production (CCEP) has received increasing attention since coal-fired power plants play a dominant role in the power sector worldwide. In China, coal is expected to retain its primary energy position over the next few decades. However, a large share of CO2 emissions and other environmental hazards, such as SO2 and NOx, are attributed to coal consumption. Therefore, understanding the environmental implications of the life cycle of coal from its production in coal mines to its consumption at coal-fired power plants is an essential task. Evaluation of such environmental burdens can be conducted using the life cycle assessment (LCA) tool. The main issues with the traditional LCA results are the lack of a numerical magnitude associated with the performance level of the obtained environmental burden values and the inherent uncertainty associated with the output results. This issue was addressed in this research by integrating the traditional LCA methodology with a weighted fuzzy inference system model, which is applied to a Chinese coal-to-energy supply chain system to demonstrate its applicability and effectiveness. Regarding the coal-to-energy supply chain under investigation, the CCEP environmental performance has been determined as “medium performance”, with an indicator score of 39.15%. Accordingly, the decision makers suggested additional scenarios (redesign, equipment replacement, etc.) to improve the performance. A scenario-based analysis was designed to identify alternative paths to mitigate the environmental impact of the coal-to-energy supply chain. Finally, limitations and possible future work are discussed, and the conclusions are presented

Study on coal mine macro, meso and micro safety management system

SummaryIn recent years, the coal mine safety production situation in our country improved year by year, but severe accidents still occurred; the accidents caused great economic loss to the national economy. According to statistical analysis, almost all of the coal mine accidents will expose the hidden danger in before, most of the accidents caused due to safety management not reaching the designated position and the hidden danger management does not take any decision in time. Based on the coal mine safety management holes in our country, the coal mine macro, meso and micro safety management system was established in this paper, which includes meaning and conception of the theories of the macro, meso and micro safety management, and also includes the matching hardware equipment, in order to achieve the hidden danger's closed-loop control and dynamic early warning in the process of coal mine production

Qualitative and Quantitative Approaches for Evaluation of Safety Risks in Coal Mines

The safety in underground coal mines continues to be a major problem in the Indian mining industry. Despite significant measures taken by the Directorate General of Mines Safety (DGMS) to reduce the number of mining accidents in underground coal mines, the number remains high. To improve the safety conditions, it has become a prerequisite to performing risk assessment for various operations in Indian mines. It is noted that many research studies conducted in the past are limited to either statistical analysis of accidents or study of single equipment or operation using qualitative and quantitative techniques. Limited work has been done to identify, analyse, and evaluate the safety risks of a complete underground coal mine in India. The present study attempts to determine the appropriate qualitative and quantitative risk assessment approaches for the evaluation of safety risks in Indian underground coal mines. This thesis addresses several important objectives as (i) to identify the type of safety risk analysis techniques suitable for evaluating various mining scenarios (ii) to identify and analyse the hazard factors and hazardous events that affects the safety in underground coal using the qualitative and quantitative approaches (iii) to evaluate the risk level (RL) of the hazardous factors/groups, hazardous events, and the overall mine using the proposed methodology. In this research work, the qualitative techniques, i.e. Failure Mode and Effects Analysis (FMEA), Workplace Risk Assessment and Control (WRAC), and the quantitative techniques, i.e. Fault Tree Analysis (FTA) and Event Tree Analysis (ETA) were applied in an underground coal mine to identify and analyse the hazard factors and hazard events. The analysis of FMEA and WRAC results concluded that the qualitative risk assessment is easy to execute and practical as they are not dependent on the historical data; rather they need experience and close examination. On the other hand, they may yield subjective results due to instinctive human assessment. The analysis of the FTA and ETA results concluded that the quantitative risk assessment could not be performed in Indian underground coal mines due to lack of probability, exposure, and consequence data. To overcome the mentioned problems in qualitative and quantitative techniques, a methodology was proposed for evaluation of the safety risks of hazard events, hazard groups, and overall mine. The proposed methodology is the unification of fuzzy logic, VIKOR (In Serbia: VIseKriterijumska Optimizacija I Kompromisno Resenje, that means: Multi-criteria Optimization and Compromise Solution), and Analytic Hierarchy Process (AHP) techniques. Because of the imprecise nature of the information available in the mining industry, fuzzy logic was employed to evaluate the risk of each hazardous event in terms of consequence, exposure, and probability. VIKOR as was used to rank the evaluated risk of hazardous events. AHP technique helps to determine the relative importance of the risk factors. Therefore, AHP technique was integrated into the risk model so that the risk evaluation can progress from hazardous event level to hazard factor level and finally to overall mine level. To reduce the calculation time significantly and to increase the speed of the proposed risk assessment process, a user-friendly Graphical User Interface (TRAM) was developed using the C# language through Microsoft Visual Studio 2015 and .Net libraries. The proposed methodology developed in this thesis was applied to six underground coal mines. The results presented the risk level of hazard events, hazards groups and overall mine of six mines. The mine-5 has the highest risk level among the evaluated mines. The ranking order of the mines observed based on the overall risk level is mine-5> mine-1 > mine-2 > mine-3 > mine-6 > mine-4. The results of the proposed methodology were compared with DGMS proposed rapid ranking method. This is observed that the proposed methodology presents better evaluation than other approaches. This study could help the mine management to prepare safety measures based on the risk rankings obtained. It may also aid to evaluate accurate risk levels with identified hazards while preparing risk management plans

ODABIR NAJPRIKLADNIJE METODE EKSPLOATACIJE U IRANSKOME RUDNIKU ZLATA KODAKAN

The selection of mining methods is a challenging and complicated concept in mining engineering. It depends on various and different factors such as geotechnical, geological and economic properties and characteristics. Kodakan Gold Mine in Iran is currently mined using the open pit method. However, due to the special conditions of this mine and the increase in waste removal costs, it is inevitable to decide to select an underground mining method in the future. The purpose of this research is to select the most proper underground mining method for this mine. The shape, dip, and depth of the deposit, the thickness of the ore, grade distribution, recovery, skilled manpower, output per worker, and strength specifications of the ore, hanging-wall, and footwall are considered as the main decision attributes. Since there are different parameters in selecting the appropriate mining method using the multi-attribute decision making approach, therefore hybrid multi-attribute decision-making method was employed in this paper to enhance the strength of the decision model and eliminate the weaknesses of the classical methods. Regarding the results of this study, rock quality designation of the hanging-wall and deposit shape have the highest weight value in selecting the underground mining method. Moreover, the shrinkage mining method is proposed as the most appropriate method.Odabir eksploatacijske metode izazovan je i složen proces u rudarskome inženjerstvu. Ovisi o raznim čimbenicima kao što su geotehnička, geološka i ekonomska svojstva i karakteristike. U iranskome rudniku zlata Kodakan trenutačno se eksploatira površinskim kopom. Međutim, zbog posebnih uvjeta i povećanja troškova uklanjanja otkrivke neizbježno je u budućnosti odabrati određenu metodu podzemne eksploatacije. Cilj je istraživanja odabir najprikladnije metode podzemne eksploatacije za ovaj rudnik. Oblik, nagib i dubina ležišta, debljina rude, distribucija kvalitete rude, iskorištenje, kvalificirana radna snaga, učinak po radniku, čvrstoća rude, krovine i podine smatraju se glavnim parametrima za odluku. Zbog različitih čimbenika u odabiru odgovarajuće metode eksploatacije pri pristupu odlučivanja s više parametara korištena je hibridna metoda odlučivanja kako bi se povećala uspješnost modela odlučivanja i otklonili nedostatci klasičnih metoda. Rezultati istraživanja pokazali su da najveću težinsku vrijednost pri odabiru metode podzemne eksploatacije imaju indeks kvalitete jezgre krovine i oblik ležišta. Pored toga, natkopna metoda predložena je kao najprikladnija metoda podzemne eksploatacije