Journal Articles
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/19884
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Item Miners’ return to work following injuries in coal mines; Powrót do pracy górników poszkodowanych w wypadkach w kopalni w?gla(Nofer Institute of Occupational Medicine ul. sw. Teresy od Dzieciatka Jezus 8 Lodz 91-348, 2016) Bhattacherjee, A.; Kunar, B.M.Background: The occupational injuries in mines are common and result in severe socio-economical consequences. Earlier studies have revealed the role of multiple factors such as demographic factors, behavioral factors, health-related factors, working environment, and working conditions for mine injuries. However, there is a dearth of information about the role of some of these factors in delayed return to work (RTW) following a miner’s injury. These factors may likely include personal characteristics of injured persons and his or her family, the injured person’s social and economic status, and job characteristics. This study was conducted to assess the role of some of these factors for the return to work following coal miners’ injuries. Material and Methods: A study was conducted for 109 injured workers from an underground coal mine in the years 2000-2009. A questionnaire, which was completed by the personnel interviews, included among others age, height, weight, seniority, alcohol consumption, sleeping duration, presence of diseases, job stress, job satisfaction, and injury type. The data was analyzed using the Kaplan-Meier estimates and the Cox proportional hazard model. Results: According to Kaplan-Meier estimate it was revealed that a lower number of dependents, longer sleep duration, no job stress, no disease, no alcohol addiction, and higher monthly income have a great impact on early return to work after injury. The Cox regression analysis revealed that the significant risk factors which influenced miners’ return to work included presence of disease, job satisfaction and injury type. Conclusions: The mine management should pay attention to significant risk factors for injuries in order to develop effective preventive measures. © 2016, Nofer Institute of Occupational Medicine. All rights reserved.Item Experimental investigation and statistical analysis of operational parameters on temperature rise in rock drilling(International Information and Engineering Technology Association info@iieta.org, 2018) Vijay Kumar, V.K.; Kunar, B.M.; Murthy, C.S.Heat generated during rock drilling, due to friction at the bit-rock interface. Due to which temperature increases, which can influence the thermal stress and subsequent rock failure. In this paper, an attempt is made to present results related to the temperature assessment during rotary drilling of rocks on medium-grained sandstone under controlled laboratory conditions. The experiments were conducted by using embedded thermocouple technique, the thermocouple was placed at a distance of 0.5mm (horizontal) from the bit-rock interface. The influence of operational parameters, i.e., the diameter of the drill bit, spindle speed and rate of penetration of rise in temperature was studied using multiple regression and data analysis was carried out using analysis of variance (ANOVA). The temperature was measured by using embedded thermocouple technique at a depth of 6mm, 14mm, 22mm and 30mm respectively. Regression models were developed for the prediction of temperature at the bit-rock interface. It was observed that the increase in temperature for medium-grained sandstone was from 49 0 C to 74 0 C (51.08%) with an increase in the diameter of the drill bit, spindle speed and rate of penetration. © 2018 International Information and Engineering Technology Association.Item ANN model for prediction of bit–rock interface temperature during rotary drilling of limestone using embedded thermocouple technique(Springer Science and Business Media B.V., 2020) Vijay Kumar, V.K.; Kunar, B.M.; Murthy, C.S.N.In the present work, an artificial neural network (ANN) model has been developed to predict the bit–rock interface temperature using a newly fabricated grounded K-type thermocouple (range 0–1250 °C) during rotary drilling in a CNC vertical machining center. The data have been taken from experimental observation using an embedded thermocouple technique in the laboratory at room temperature (28 °C) using a masonry drill bit. The observations were made using four different operational conditions, namely drill bit diameter (6, 8, 10, 12 and 16 mm), spindle speed (250, 300, 350, 400 and 450 rpm), rate of penetration (2, 4, 6, 8 and 10 mm min?1) and depth (6, 14, 22 and 30 mm). The ANN has been developed based on the multi layer perceptron neural network (MLPNN) with four different input parameters. A Levenberg–Marquardt (LM) algorithm with feed-forward and backward propagation has been used in this model. The predicted value of the bit–rock interface temperature with the highest R2 value provides a satisfactory result with the experimental data. The training value of RMSE is 1.2127, MAPE is 0.0196 and R2 is 0.9960, while the testing value of RMSE is 1.2770, MAPE is 0.0170 and R2 is 0.9978. The ANN model shows that the proposed MLPNN model successfully predicts the bit–rock interface temperature during the rotary drilling of limestone. © 2019, Akadémiai Kiadó, Budapest, Hungary.Item Measurement of bit-rock interface temperature and wear rate of the tungsten carbide drill bit during rotary drilling(Tsinghua University Press wyl-dhh@tsinghua.edu.cn, 2020) Vijay Kumar, V.K.; Kunar, B.M.; Murthy, C.S.; Ramesh, M.R.Rock drilling is an essential operation in mining industries. Temperature at the bit-rock interface plays a major role in the wear rate of the drill bit. This paper primarily focuses on the wear rate of tungsten carbide (WC) drill bit and the interrelationship between temperature and wear rate during rotary drilling operations conducted using a computer numerical control (CNC) machine. The interrelationship between the temperature and wear rate was studied with regard to three types of rock samples, i.e., fine-grained sandstone (FG) of uniaxial compressive strength (UCS) that is 17.83 MPa, medium-grained sandstone (MG) of UCS that is 13.70 MPa, and fine-grained sandstone pink (FGP) of UCS that is 51.67 MPa. Wear rate of the drill bit has been measured using controlled parameters, i.e., drill bit diameter (6, 8, 10, 12, and 16 mm), spindle speed (250, 300, 350, 400, and 450 rpm), and penetration rate (2, 4, 6, 8, and 10 mm/min), respectively. Further, a fully instrumented laboratory drilling set-up was utilized. The weight of each bit was measured after the bit reached 30 mm depth in each type of the rock sample. Furthermore, effects of the bit-rock interface temperature and operational parameters on wear rate of the drill bits were examined. The results show that the wear rate of drill bits increased with an increase in temperature for all the bit-rock combinations considered. This is due to the silica content of the rock sample, which leads to an increase in the frictional heat between the bit-rock interfaces. However, in case of medium-grained sandstone, the weight percentage (wt%) of SiO2 is around 7.23 wt%, which presents a very low wear rate coefficient of 6.33×10?2 mg/(N·m). Moreover, the temperature rise during drilling is also minimum, i.e., around 74 °C, in comparison to that of fine-grained sandstone and fine-grained sandstone pink. In addition, this paper develops the relationship between temperature and wear rate characteristics by employing simple linear regression analysis. © 2019, The Author(s).Item Postural analysis of dumper operators and construction workers – a case study(Books and Journals Private Ltd., 2021) Kunar, B.M.; Mangalpady, M.; Kar, M.B.This case study aims at assessing and understanding the level of ergonomics in manual material handling tasks (loading, granite cutting, concrete mixing, brickwork, and plastering) of civil construction workers and dump truck drivers working in Indian opencast mines. The study involves the determination of the level of musculoskeletal disorder and predicting the most affected body parts due to incorrect working posture. The comprehensive methodology involved in this study includes rapid upper limb assessment (RULA) and rapid entire body assessment (REBA) techniques to find the risk involved in the working posture of the construction workers and dump truck drivers. The study showed that posture adopted in civil construction work and dump truck operators (loading and unloading task) are ergonomically incorrect and may cause musculoskeletal disorder (MSD) related problems in the future. This study also showed that the trunk and wrist are the most affected parts of the body in construction workers and the neck and wrist in case of the dumper operator while performing different tasks. © 2021, Books and Journals Private Ltd.. All rights reserved.Item Fuzzy Logic-Based Rapid Upper Limb Assessment: A Novel Approach to Evaluate the Postural Risk of Dumper Operators(Springer, 2023) Kar, M.B.; Mangalpady, M.; Kunar, B.M.It is proved that the accuracy of the standard Rapid Upper Limb Assessment (RULA) method for evaluating the risk of work-related musculoskeletal disorders (WRMSDs) is often poor. In this paper, a fuzzy logic-based RULA system was developed to address this issue using the MATLAB software package. To evaluate the developed system, 15 dumper operators working in the surface iron ore mine were randomly selected. Video footage of their driving postures was recorded while they were performing different job cycles, such as loading, full-load travel, unloading, and empty travel. The video footage was examined to identify the most frequent driving postures. From this posture, the range of motion of both the axial and appendicular body parts was measured. The measured data were used as input parameter for the fuzzy model to calculate the fuzzy RULA score. The result revealed that 20% of the driving postures adopted by the dumper operators correspond to the medium risk of WRMSDs. Furthermore, the interquartile range of the fuzzy RULA score during dynamic operations was found to be small. This indicates that the fuzzy RULA score remained consistent throughout the dynamic operations. In contrast, the interquartile range exhibited large magnitude in the static operations, thus indicating a greater level of variation in fuzzy RULA score. The correlation test and Bland–Altman analysis were performed to compare the standard and fuzzy RULA scores. This analysis proved that the fuzzy logic-based method is a reliable alternative to the standard method for assessing RULA scores among dumper operators. © 2023, The Institution of Engineers (India).Item Risk factors associated with work-related musculoskeletal disorders among dumper operators: A machine learning approach(Elsevier B.V., 2023) Kar, M.B.; Mangalpady, M.; Kunar, B.M.Aims: This study aimed to determine the risk factors associated with work-related musculoskeletal disorders (WRMSDs) among dumper operators working in Indian iron ore mines. Methods: A total of 246 dumper truck operators meeting inclusion and exclusion criteria were chosen for data collection. A self-report custom and the standard Nordic questionnaire were used for collecting data about risk factors and WRMSDs. The data were pre-processed and analyzed using machine learning (ML) algorithms (such as logistic regression ( LR), support vector machines (SVM), decision trees (DT), gradient boosting machine (GBM) and random forest (RF)). Results: RF model was found to outperform the other algorithms with high accuracy (0.71), precision (0.75), recall (0.78), F1 score (0.76), and area under the receiver operating characteristic curve (0.82). The mean rank of the risk factors showed that age is the most critical parameter, followed by awkward posture, experience in mines, job demand, alcohol consumption, smoking cigarettes, work design, and marriage status. Conclusion: Overall, the study provides valuable insights into the risk factors associated with WRMSDs among dumper operators and suggests that measures should be taken to address these risk factors to prevent WRMSDs in the dumper operator population. © 2023 The Author(s)Item Structural equation modelling of work related musculoskeletal disorders among dumper operators(Nature Research, 2023) Kar, M.B.; Mangalpady, M.; Kunar, B.M.The aim of this study is to investigate the impact of personal factors, habitual factors, and work-related factors on work-related musculoskeletal disorders (WRMSDs) among dumper operators. In total, 248 dumper operators working in an iron ore mine were considered for this study. A questionnaire was developed and administered to collect dumper operators' personal, habitual, and work-related data. The reliability of the questionnaire was cross-checked by Cronbach alpha and the test–retest method. The values of Cronbach alpha for all latent variables were above 0.7, and the correlation coefficient of the questionnaire items at Time 1 and Time 2 was above 0.82. After verifying the validity (i.e., convergent and divergent) of the questionnaire data, the relationship between the factors under consideration was examined by structural equation modeling (SEM). The SEM demonstrated a moderate fit, with χ2df value of 1.386, comparative fit index (CFI) of 0.86, goodness-of-fit index (GFI) of 0.72, adjusted goodness-of-fit index (AGFI) of 0.69, Tucker-Lewis Index (TLI) of 0.83, normed fit index (NFI) of 0.71 and root mean square error of approximation (RMSEA) of 0.051. The SEM analysis revealed a positive relationship between WRMSDs and personal factors (with path coefficient = 0.313 and p < 0.05) as well as work-related factors (with path coefficient = 0.296 and p < 0.05). However, the relationship between WRMSDs and habitual factors was not statistically significant (with path coefficient = 0.142 and p > 0.05). Overall, this study provides valuable insights into the factors that influence the prevalence of WRMSDs among dumper operators. The findings highlight the significance of personal and work-related factors by which one can make a positive decision to prevent and reduce the incidence of WRMSDs among dumper operators. © 2023, Springer Nature Limited.Item An adaptive modeling for bifacial solar module levelized cost and performance analysis for mining application(John Wiley and Sons Ltd, 2024) Shiva Kumar, B.S.; Kunar, B.M.; Murthy, C.S.N.Power density and efficiency typically dominate design approaches for power electronics. However, cost optimality is in no way guaranteed by these strategies. A design framework that minimizes the (i) levelized cost of electricity (LCOE), (ii) collection of light, and (iii) irradiance of the generation system is proposed as a solution to this flaw. From an improvement of the swarm behavior optimization model to get a minimum LCOE of solar panel, we design to optimize height, tilt angle, azimuth angle, and some parameters to solve the objective function and LCOE improvement problem to obtain the optimal design problem. In adaptive salp swarm optimization (ASSO), this change's proposed model producer swarm behavior is regarded as an adaptive process that keeps the algorithm from prematurely converging during exploration. The proposed algorithm's performance was confirmed using benchmark test functions, and the results were compared with those of the salp swarm optimization (SSO) and other efficient optimization algorithms. LCOE condition as far as “land-related cost” and “module-related cost” demonstrates that the optimal design of bifacial farms is determined by the interaction of these parameters. This proposed model can be used to evaluate visibility on building surfaces that are suitable for mining applications like crushing. Experimentation results show Minimum LCOE AS 0.05 (€/Kw)minimum irradiance and collection light as 336.23(w/m2) and 83.02%n proposed framework model. The swarm optimization method is contrasted with the optimal parameters derived from a conventional solver. © 2023 John Wiley & Sons Ltd.Item An analytical hierarchy approach for studying the impact of human error, environmental factors, and equipment failure on mine accidents: a case study in India(Springer, 2024) Kar, M.B.; Mangalpady, M.; Kunar, B.M.This paper presents a study using the Analytical Hierarchy Process (AHP) to understand and prioritize the accidents that have occurred in the Indian mining industry. The data for the study was collected from accident reports submitted to the Directorate General of Mines Safety from 2011 to 2020. The accident information was divided into six categories (i.e., accidents due to ground movement, transport machinery, machinery other than transport, explosives, electricity shock, and fall-of-person). These accidents were considered alternatives in the AHP analysis. Three risk factors (i.e., environment, equipment fault, and human error) that caused the accident were considered as criteria in the AHP analysis. The safety expert carefully examined the pattern of accidents and ranked the relative importance of the alternatives with respect to each criterion. This rank was used to build the AHP model using the R programming language and the AHP library (version 0.2.8). The results revealed that the highest number of accidents occurred due to the transport machinery (0.306), followed by accidents due to ground movement (0.232), falls of individuals (0.206), machinery other than transportation (0.122), electricity (0.082), and explosives (0.048). In order to identify the contributing risk factors for each type of mining accident, the weight and the rank of the criteria were determined. The result showed that the most accidents in the six accident categories are due to human error (0.26), followed by environmental (0.25) and equipment faults. The finding of the study provides valuable insights for the mining industry to develop effective strategies to mitigate mine accidents. © The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2024.