Browsing by Author "Akhil, A."

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    A State-of-the-Art Review on the Applications of Sensors in the Mining Industry
    (World Researchers Associations, 2025) Himanshu, M.; Akhil, A.
    As the mining industry undergoes a transformative revolution driven by technological innovation, this State-of-the-Art review meticulously charts the trajectory of sensor applications, unraveling their profound impact on every facet of mining operations. Through a comprehensive analysis of contemporary literature and cutting-edge research, this review serves as an indispensable guide, offering an in-depth exploration of the multifaceted applications, challenges and future prospects of sensors in mining. The review begins by elucidating the fundamental principles of sensor technology, providing a solid foundation for understanding the diverse sensor types employed in the mining domain. Moving beyond mere enumeration, it categorizes sensor applications into three pivotal domains: real-time equipment monitoring, environmental sensing and automated data analytics. Each domain is dissected to reveal the latest advancements, showcasing how sensors are transforming the mining landscape by enhancing safety, optimizing operational efficiency and promoting environmental sustainability. In the realm of real-time equipment monitoring, the review scrutinizes the integration of sensors for predictive maintenance, condition monitoring and performance optimization. Environmental sensing takes center stage as the review explores how sensors are instrumental in hazard detection, air quality monitoring and environmental impact assessment, fostering a safer and ecologically responsible mining ecosystem. This review includes the challenges inherent in sensor deployment, addressing issues of interoperability, data security and scalability. Practical considerations for navigating the dynamic and often harsh mining environment are discussed, providing a holistic perspective for industry practitioners. This review can provide strategic roadmap to harness the full potential of sensor technologies in steering mining operations towards a sustainable, efficient and technologically advanced operation. © 2025, World Researchers Associations. All rights reserved.
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    A State-of-the-Art Review on the Applications of Sensors in the Mining Industry
    (World Researchers Associations, 2025) Himanshu, M.; Akhil, A.
    As the mining industry undergoes a transformative revolution driven by technological innovation, this State-of-the-Art review meticulously charts the trajectory of sensor applications, unraveling their profound impact on every facet of mining operations. Through a comprehensive analysis of contemporary literature and cutting-edge research, this review serves as an indispensable guide, offering an in-depth exploration of the multifaceted applications, challenges and future prospects of sensors in mining. The review begins by elucidating the fundamental principles of sensor technology, providing a solid foundation for understanding the diverse sensor types employed in the mining domain. Moving beyond mere enumeration, it categorizes sensor applications into three pivotal domains: real-time equipment monitoring, environmental sensing and automated data analytics. Each domain is dissected to reveal the latest advancements, showcasing how sensors are transforming the mining landscape by enhancing safety, optimizing operational efficiency and promoting environmental sustainability. In the realm of real-time equipment monitoring, the review scrutinizes the integration of sensors for predictive maintenance, condition monitoring and performance optimization. Environmental sensing takes center stage as the review explores how sensors are instrumental in hazard detection, air quality monitoring and environmental impact assessment, fostering a safer and ecologically responsible mining ecosystem. This review includes the challenges inherent in sensor deployment, addressing issues of interoperability, data security and scalability. Practical considerations for navigating the dynamic and often harsh mining environment are discussed, providing a holistic perspective for industry practitioners. This review can provide strategic roadmap to harness the full potential of sensor technologies in steering mining operations towards a sustainable, efficient and technologically advanced operation. © 2025, World Researchers Associations. All rights reserved.
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    Application of Laubscher MRMR classification system in the design of open-pit chromite mines – A case study
    (World Researchers Associations, 2025) Dinesh, K.; Akhil, A.; Kunal, M.; Kumar, K.A.
    The study work was conducted at the Boula Chromite Mine site, focusing on geotechnical field observations in and around the area. The investigation aimed to comprehensively analyze surface and underground conditions, structural features, rock mass conditions and slope stability. The stereo net plot method was employed for slope stability analysis. Slope failures in rock masses were observed at the mine site at few locations, prompting us to delve into understanding the events and proposing precise recommendations for safe and efficient mining practices. The analysis of results formed the core objective of this study. To achieve the stated goal, a rational and systematic study in the field was conducted. This encompassed examining the geological and structural setup of rock formations, conducting field investigations to asses various geotechnical parameters, identifying the most influential factors affecting rock mass behavior, categorizing rock masses into groups based on similar behavior (rock mass classes), gathering structural data on slopes, classifying rock mass conditions using Laubscher’s rock mass classification and determining failure modes (planar, wedge, toppling and circular) in rock slopes through graphical analysis. The comprehensive rock mass classification and failure analysis were compiled in this work. The findings are crucial for identifying and thoroughly analyzing potential risks. This knowledge can play a pivotal role in ensuring the safety and efficiency of mining operations in and around the Boula Chromite Mine site. Moreover, the knowledge acquired from the study can be instrumental in planning and opening pit projects with similar geotechnical and mining conditions. The study thus provides valuable information for the broader field and contributes to the overall advancement of safe and effective mining practices. © 2025, World Researchers Associations. All rights reserved.
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    Application of Laubscher MRMR classification system in the design of open-pit chromite mines – A case study
    (World Researchers Associations, 2025) Dinesh, K.; Akhil, A.; Kunal, M.; Kumar, K.A.
    The study work was conducted at the Boula Chromite Mine site, focusing on geotechnical field observations in and around the area. The investigation aimed to comprehensively analyze surface and underground conditions, structural features, rock mass conditions and slope stability. The stereo net plot method was employed for slope stability analysis. Slope failures in rock masses were observed at the mine site at few locations, prompting us to delve into understanding the events and proposing precise recommendations for safe and efficient mining practices. The analysis of results formed the core objective of this study. To achieve the stated goal, a rational and systematic study in the field was conducted. This encompassed examining the geological and structural setup of rock formations, conducting field investigations to asses various geotechnical parameters, identifying the most influential factors affecting rock mass behavior, categorizing rock masses into groups based on similar behavior (rock mass classes), gathering structural data on slopes, classifying rock mass conditions using Laubscher’s rock mass classification and determining failure modes (planar, wedge, toppling and circular) in rock slopes through graphical analysis. The comprehensive rock mass classification and failure analysis were compiled in this work. The findings are crucial for identifying and thoroughly analyzing potential risks. This knowledge can play a pivotal role in ensuring the safety and efficiency of mining operations in and around the Boula Chromite Mine site. Moreover, the knowledge acquired from the study can be instrumental in planning and opening pit projects with similar geotechnical and mining conditions. The study thus provides valuable information for the broader field and contributes to the overall advancement of safe and effective mining practices. © 2025, World Researchers Associations. All rights reserved.
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    Comparison of model study with field implementation of gravity blind backfilling method to control subsidence induced disaster in abandoned underground coal mines
    (World Researchers Associations, 2023) Kumar, P.S.; Akhil, A.; Kumar, T.A.
    Blind hydraulic backfilling technique is used for subsidence control in underground coal mines. A laboratory size model of underground working was developed to understand backfilling process. Observations from model were utilized for backfilling process in one of the underground mines. This study describes the results obtained in the field investigation at an old abandoned waterlogged underground coal mine of Eastern Coalfields Limited (ECL), a subsidiary of Coal India Limited and their verification with the findings obtained in the laboratory scale model study carried out on a model of underground coal mine worked by board and pillar method. The relative influence of slurry concentration and flow rates on the areas of filling from a single inlet borehole has been discussed. The relative spread of sand in different directions has also been measured using a remotely operated underground vehicle mounted camera. The empirical relationships developed under field conditions have been found to be similar to those of laboratory model. © 2023, World Research Association. All rights reserved.
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    Human-in-the-Loop Data Analytics for Classifying Fatal Mining Accident Causes Using Natural Language Processing and Machine Learning Techniques
    (Springer Science and Business Media Deutschland GmbH, 2025) Sharma, A.; Kumar, A.; Vardhan, H.; Mangalpady, A.; Mandal, B.B.; Senapati, A.; Akhil, A.; Saini, S.
    Mining remains one of the most hazardous industries globally, marked by frequent fatalities resulting from complex operational risks. While accident investigation reports hold valuable insights for improving safety practices, the manual coding of fatality narratives remains labor-intensive, inconsistent, and impractical for large datasets. Although natural language processing (NLP) and machine learning (ML) techniques have gained traction for automating the analysis of safety narratives in other high-risk industries, their application to mining accident data, particularly within the Indian context, remains limited. Addressing this gap, the present study proposes a ML framework for the semi-automated classification of fatal accident causes from unstructured text narratives reported by the Directorate General of Mines Safety (DGMS) between 2016 and 2022. A total of 401 fatal accident descriptions were pre-processed and vectorized using Bag-of-Words, TF-IDF, and Word2Vec techniques, followed by model evaluation across multiple algorithms. A semi-automated classification scheme was developed to balance efficiency with expert oversight, where high-confidence predictions were assigned automatically and uncertain cases were flagged for manual review. Logistic regression combined with TF-IDF unigram features achieved the highest performance, with an F1 score of 0.78 and an accuracy of 0.81. Overall, the developed framework successfully auto-coded 68.75% of cases with 94% accuracy, 0.93 recall, and 0.91 precision. Word cloud visualizations were also employed to capture dominant words associated with different cause categories. The proposed framework offers a practical and operationally feasible solution for assigning fatality causes in the mining sector, contributing to active safety management, surveillance, and policy formulation. © Society for Mining, Metallurgy & Exploration Inc. 2025.
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    Influence of Angle of Internal Friction and Slope Face Angle on Kinematic Failures in Marble Mines: A Predictive Approach
    (Springer, 2025) Sinha, S.; Tripathi, A.K.; Akhil, A.; Kumar, M.
    This study investigates the kinematic stability of slopes in two opencast marble mines, focusing on the variation of dip angles of the slope and angles of internal friction on overall slope stability. The research draws on joint orientation data collected from the mines to perform detailed kinematic analyses, examining different slope faces at various dip directions that gave a probability of failure. A crucial part of the study involved statistical analysis by curve-fitting model to establish a relationship between the dip angle (or overall pit angle) and the angle of internal friction. The relationship was found to be nonlinear following a trend of 3rd-degree polynomial equation. Additionally, sensitivity analysis was conducted to further understand the relationship between these critical parameters. The sensitivity index was calculated by finite difference method where the parameters dip angle and angle of internal friction were taken into consideration by keeping one of the parameter constants and varying the other parameter and vice versa to find out the dependency of the varying parameter on the probability of failure. This multifaceted approach not only validates the importance of these variables, but also provides a predictive framework for assessing slope failure risks. © The Author(s), under exclusive licence to Indian Geotechnical Society 2025.
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    Influence of Stiffness Ratio and Powder Factor on Burden Rock Movement in Blasting Operations: A Case Study on Limestone Mines
    (World Researchers Associations, 2025) Channabassamma, N.; Akhil, A.; Rama, S.V.
    In opencast mining, blasting is a critical operation that significantly impacts the efficiency and costeffectiveness of material removal. This study focuses on optimizing the use of explosive energy to move the burden, thereby reducing reliance on mechanical methods. Effective blast design involves strategically utilizing energy within a blast hole, considering factors such as explosive type, quantity, detonation timing and blast hole geometry. Given the rapid nature of blasting, high-speed video cameras are employed to capture the blast progression on a millisecond scale, providing essential data for analyzing blast dynamics. This research evaluates the influence of blast design parameters, specifically the stiffness ratio (the ratio of bench height to the burden) and powder factor (the amount of explosive per unit volume of rock), on the movement of burden rock in a limestone mine. By examining these parameters, the study aims to optimize blast designs to achieve improved fragmentation, reduced fly rock and minimized ground vibrations, ultimately enhancing the efficiency and cost effectiveness of mining operations. © 2025, World Researchers Associations. All rights reserved.
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    Parametric Analysis of Mine Bench Blasting using High Speed Video Camera
    (World Researchers Associations, 2025) Channabassamma, N.; Akhil, A.; Rama, S.V.; Kumar, T.A.; Sahana, P.
    This study presents a comprehensive parametric analysis of mine bench blasting through the utilization of high-speed video camera technology. Mine bench blasting is a critical operation in the extraction of minerals and understanding its parameters is essential for optimizing safety, efficiency and environmental impact. The research employs a high-speed video camera, specifically the S-Motion Model by AOS Technologies, Switzerland, capable of recording at 1000 frames per second. Here we carried out the sensitive parametric analysis like dependency of burden rock movement on ejection of stemming gaseous, stemming ratio, stemming height and total explosive charge using Proanalyst image processing software. Through the analysis, we identified key trends and correlations that contribute to control rock movement, stemming gas ejection and optimizing explosive charge distribution. This comprehensive understanding provides valuable insights for improving the overall effectiveness and precision of future blasting operations, thereby contributing to enhanced operational outcomes and safety in mining or construction activities. © 2025, World Researchers Associations. All rights reserved.
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    Predicting Burden Rock Velocity in Limestone Mines using Artificial Neural Network Models
    (World Researchers Associations, 2025) Channabassamma, N.; Akhil, A.; Rama, S.V.; Sahas, S.V.; Ranjit, K.
    The prediction of burden rock velocity is crucial in optimizing the efficiency of mining and excavation operations. This study presents a novel approach utilizing Artificial Neural Networks (ANNs) to accurately predict the velocity of burden rocks based on various input parameters such as rock property, geological property and bench properties. A comprehensive dataset was collected from field measurements and laboratory experiments to train the ANN models. The performance of the ANN models such as Multi-layered Perceptron (MLP), Deep Neural Network (DNN), simple MLP and Backpropagation Neural Network (BPNN) was evaluated based on performance metrics R-squared (R)2, Mean Squared Error (MSE) and Mean Absolute Error (MAE). Among the developed ANN models, the BPNN model was found to be the most accurate predictive model for burden rock velocity, as evidenced by metrics R2(0.821), MSE (0.099) and MAE (0.226). The results indicate that the BPNN model effectively captures the complex relationships between the predictors and burden rock velocity. Advanced neural network algorithms such as recurrent neural networks and long short-term memory techniques can be used to improve the accuracy of presented neural network models. © 2025, World Researchers Associations. All rights reserved.
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    Prediction of the specific energy requirement of hydraulic rock breaker based on laboratory impact hammer – a case study
    (Inderscience Publishers, 2024) Pal, S.K.; Akhil, A.; Vyas, A.; Tripathi, A.K.
    The present study was conducted in a limestone mine at central Rajasthan, India for correlating the impact energy of hydraulic rock breaker with laboratory size gravitational impact rock breaker. Data generation and results were obtained mainly to correlate the specific impact energy required by the hydraulic rock breaker field (IEF) in kJ/m3 for breaking boulders in the field versus the specific impact energy required by the gravitational impact rock breaker laboratory (IEL) in kJ/m3. Laboratory investigation values for Schmidt rebound number (RN) is between 27 to 44; UCS (σc) between 96.27 to 132.25 MPa; tensile strength (σt) between 9.14 to 14.66 MPa; and point load strength (Is50) between 8.95 to 12.65 MPa. In the present research, an attempt is made to study impact energy utilised by hydraulic rock breaker in the field and comparison of specific energy requirements based on a laboratory-size impact hammer. © 2024 Inderscience Enterprises Ltd.
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    Production enhancement with dragline planning with real time topography
    (World Researchers Associations, 2025) Singh, S.M.; Akhil, A.; Kumar, K.; Chandra, P.D.; Sanjay, C.
    The seamless fusion of dragline planning with real-time topography is explored to boost production in surface mining. In coal mining, draglines play a crucial role as primary stripping tools and their uninterrupted operation is essential for cost-effective productivity. The transition from shovel to dragline mining in largescale coal mining projects, underscores the significance of these machines. The study underscores the importance of precise dragline design to ensure reliability and predictability, minimizing disruptions during repairs and component replacements. The proposed method integrates real-time topography data, introducing an innovative aspect to dragline planning. Utilizing advanced technologies such as Datamine (MineScape software), this integration enables dynamic adjustments in dragline operations based on evolving topographical conditions. The research highlights the potential of this integrated approach in enhancing production by facilitating proactive decision-making, minimizing downtime and overall improving mining efficiency. © 2025, World Researchers Associations. All rights reserved.
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    Subsidence Analysis for Old Abandoned Board and Pillar Coal Mines Using ANSYS and Monte Carlo Simulation
    (Pleiades Publishing, 2024) Akhil, A.; Pal, S.K.; Tripathi, A.K.; Kumar, G.
    Abstract: This research paper will cover the possible causes which can lead to subsidence above old abandoned board and pillar coal mines at a shallow depth. The research includes the calculation and analysis of the factor of safety for pillars using ANSYS and Monte Carlo Simulations for ascertaining subsidence. An old abandoned coal mine of South Eastern Coalfields Ltd. (SECL, a subsidiary of Coal India Limited) was considered for the study of coal pillar fatigue and eventual crushing of pillars over a long duration of time, simulation analysis of stress and strength of coal pillars over a long period, change in behavior of factor of safety as the dimension of the pillars changes. © Pleiades Publishing, Ltd. 2024.
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    Subsidence Analysis for Old Abandoned Board and Pillar Coal Mines Using ANSYS and Monte Carlo Simulation
    (Pleiades Publishing, 2023) Akhil, A.; Pal, S.K.; Tripathi, A.K.; Kumar, G.
    Abstract: Mine Subsidence is a phenomenon of lateral or vertical ground movement caused by a failure initiated at the mine level of man-made underground mines and an abandoned mine is a site where mining activities occurred but acceptable mine closure and reclamation did not take place or was incomplete. Subsidence is one of the major problems which is faced over an old abandoned mine. Presently there are limited means or methods which can predict subsidence over an old abandoned coal mine at a shallow depth efficiently and the precautionary methods that should be taken in these situations. This research paper will cover the possible causes which can lead to subsidence above an old abandoned board and pillar coal mines at a shallow depth. The research includes the calculation of the factor of safety for pillars and analysis of FoS using ANSYS and Monte Carlo Simulations for ascertaining subsidence. An old abandoned coal mine of South Eastern Coalfields Ltd. (SECL, a subsidiary of Coal India Limited), was considered for the study of coal pillar fatigue and eventual crushing of pillars over a long duration of time, simulation analysis of stress and strength of coal pillars over a long period, change in behavior of factor of safety as the dimension of the pillars changes. © Pleiades Publishing, Ltd. 2024.