2. Thesis and Dissertations
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Item Investigations on Performance of Load Haul Dumpers in Underground Mines and Improvement of its Availability and Utilization Using Reliability Analysis(National Institute of Technology Karnataka, Surathkal, 2021) Jakkula, Balaraju.; Raj, M Govinda.; Murthy, Ch. S. N.Every organization in today’s competitive world intends to improve its economy by increasing their production and productivity rates. Unequivocally, the production in Indian underground mines over the years is not satisfactory, due to a variety of reasons. There are manifold of avenues for the betterment of production and one such approach is through enhanced utilization of mechanized equipment such as Load Haul Dumper (LHD). These LHDs are prone to continuous and random occurrence of numerous potential failures during the operation. Understanding of each failure mode will help to take an appropriate maintenance action, which leads to reduce the downtimes of the machinery. One approach of productivity improvement efforts is through an increase in percentage availability and utilization of these machines. The higher availability and utilization of these machines under certain operating constraints, leads to an increase in the production and productivity of these capital intensive equipment. The accomplishment of this goal can be possible only with the improvement of the reliability of equipment by reducing the occurrence of breakdowns. The purpose of the research performed for this thesis is to make an attempt to control the occurrence of uneven breakdowns, by using reliability analysis. The developed methods can be used to identify the problems/causes affecting LHD downtime, to assess suitable maintenance management strategies for repair and replacement action and to identify the economic lifetime of LHD systems. The major objective can be explained as providing quantitative forecasts of diverse performance characteristics of LHDs through reliability computations, evaluations, and forecasts. Such characteristics are Reliability, Availability, and Maintainability (RAM), downtimes, frequency of failures, and Overall Equipment Effectiveness (OEE) of the system. The estimation of these characteristics is significant for optimal decision making. To perform the reliability analysis, a fleet of LHDs deployed at both coal and non-coal mines of M/s The Singareni Coal Collieries Company Limited (SCCL), Telangana, M/s The Hutti Gold Mines Company Limited (HGML), Karnataka, and M/s The Hindustan Zinc Limited (HZL), Rajasthan were selected to carry out the field investigation for collection of failure and repair data of equipment. Before performing the reliability analysis it is necessary to perform the trend and serial correlation tests to determine whether and how the failure patterns are changing with respect to time and to validate the Independent and Identical Distribution (IID) nature of the data sets. As the data have been collected from the field investigations and if such tests are not performed, then there is a possibility of arriving at incorrect conclusions. On analysis it has been found that the time between successive failures (TBFs) of LHDs is free from the presence of trends. Statistical based analysis like statistic U-test (Chi-squared test) has been carried out to determine the method for reliability modeling. Generally, the Renewal Process (RP) method can be utilized for perfect repairs and the Non-Homogeneous Poisson Process (NHPP) method can be utilized for minimal repairs. However, most repair activities may realistically not result in such two extreme situations but are a unique combination in this range. In this study, the RP approach has been utilized to perform the reliability analysis for estimation of percentage of each sub-system (i.e., Engine, Braking, Transmission, Tyre, Hydraulic, Electrical and Mechanical) reliability and failure rate of the LHDs. Best-fit distribution of data sets have been identified by the utilization of Kolmogorov-Smirnov (K-S) test. Maximum Likelihood Estimate (MLE) method has been used to estimate the theoretical probability distribution parameters (η, β, and γ) of best-fit curves. Reliability of each individual sub-system has been computed according to the best fit distribution. In addition to the operational procedures and technical expertise, maintenance efficiency is also a significant factor that needs to be considered for assessment of system performance or effectiveness. Improvement of performance of the equipment mainly depends upon the adoption of suitable maintenance management actions (repair/replacement). Keeping this in view, in this analysis maintainability percentages has been estimated for the LHDs after successful identification of best-fit probability distribution function. Further, the reliability-based Preventive Maintenance (PM) time intervals were forecasted for the enhancement of equipment reliability. vi vii vii vii In this research work, the most appropriate methods of reliability modeling and optimization such as Failure Mode Effect Analysis (FMEA), Reliability Block Diagram (RBD) and Fault Tree Analysis (FTA) are presented to estimate the percentage of reliability, availability, and maintainability (RAM). The FMEA approach has been utilized in this research study to investigate the failure behavior of the LHDs. FMEA identifies the reasons for occurrence of potential failure modes and provides the necessary recommendations or corrective actions to reduce the uneven occurrence of failures. The risk-based numerical assessment was made with prioritization of critical failure modes through the Risk Priority Number (RPN) calculation. A new risk management approach known as “MATLAB Fuzzy rule based interface system” was utilized to validate the calculated RPN values. The series and the parallel configuration systems are the two important approaches in RBD approach and are widely used to estimate the overall system reliability of the LHDs. In this study, all the connections of the components in a machine have been identified in series configuration system. Hence, the overall system reliability of the LHDs were estimated using series configuration system calculation. In addition to that, the reliable life (TR) of the equipments were also calculated to forecast the duration (threshold time) for occurenance of next subsequent failure. In this study, FTA was carried out to identify the percentage of unavailability of the system and to know the influence of each component/ cut set/ critical part on the system failure. Further, the computed values of reliability, availability and maintainability were validated with MATLAB based Artificial Neural Network (ANN) results for identification of percentage error value. In addition to this, an attempt has been made for the improvement of performance of the equipment through evaluation of Overall Equipment Effectiveness (OEE). The OEE percentage of each LHD has been computed in terms of percentage availability, performance and quality. This thesis provides a scientific base for evaluating the reasons for performance drop of the equipment and suggests the necessary remedial measures and recommendations to the mining industry for the improvement of performance on the basis of RAM analysis and OEE calculations.Item Prediction of Rock Properties and Specific Energy using Sound Levels Produced during Diamond Drilling(National Institute of Technology Karnataka, Surathkal, 2021) Kumar, Ch Vijaya.; Murthy, Ch. S. N.; Vardhan, Harsha.Drilling is widely used in many engineering applications such as mining, geotechnical and petroleum industries. Drilling operations produce sound that can be used to estimate rock properties and specific energy. The conventional method of determining of rock properties and specific energy is expensive and time-consuming. In this study, a new technique was developed to estimate rock properties and specific energy (SE) using dominant frequencies and A-weighted equivalent sound pressure levels generated during diamond drilling operations. First, sound pressure level was recorded while performing rock drilling experiments on seven different types of rock samples using computer numerical control (CNC) drilling machine BMV 45 T20 and sound signals of these sound frequencies were analyzed using Fast Fourier transform (FFT). Using simple linear, multiple regression analysis and artificial neural networks, mathematical equations were developed for various rock properties, i.e. uniaxial compressive strength, Brazilian tensile strength, density, abrasivity, impact strength index using dominant frequencies of sound pressure levels. This study also reports the methods for prediction of SE, effect of physico-mechanical rock properties on SE and effect of operational variables on SE using A - weighted equivalent sound levels produced during diamond drilling operations. Initially SE was determined for all selected rock types and a correlation was developed between SE and physico-mechanical rock properties (PMRP) and operating variables. The developed prediction models were validated using determination coefficients (R2), t-test, F-test and performance predictions i.e. values account for (VAF), root mean square error (RMSE) and mean absolute percentage error (MAPE). For SE, the R2 values obtained a range from 75.58 % to 78.76 %, RMSE values obtained a range from 0.074411 to 0.578601, VAF values obtained a range from 72.826808 to 84.155813 and MAPE values obtained a range from 0.061218 to 2.321007 for selected rock samples and t and F values also obtained below the tabulated values (2.44). Concerning SE’s relation to PMRP, it was observed that SE increased with increasing uniaxial compressive strength, Brazilian tensile strength and dry density and decreased with increasing abrasivity. For PMRP, the R2 values obtained from 92.25 %, 90.99 %, 47.15 %, 93.39 %, corresponded to uniaxial compressive strength, Brazilian tensile strength, density and abrasivity. Similarly, regarding SE’s relation with operational variables, it was found that SE decreased with increasing drill bit diameter, penetration rate and drill bit speed. The developed models can be used to predict rock properties and specific energy at early stage of planning and design.Item Experimental Investigation on Assessment and Prediction of Specific Energy in Rock Cutting(National Institute of Technology Karnataka, Surathkal, 2021) Raghavan, Vijaya.; Murthy, Ch. S. N.The rock cutting machine was fabricated to measure the cutting rate and specific energy (SE). The variable parameters include attack angle, pick angle, RPM, cutting force, and torque to determine the cutting parameters. For measuring the cutting force and torque, a cutting tool dynamometer is used. Experimental investigations were also carried out to determine physico-mechanical properties of the rocks, namely density, uniaxial compressive strength (UCS), Brazilian Tensile strength (BTS), abrasivity and brittleness of the rocks were determined as per ISRM standards. During the cutting process, the RPM is varied from 225, 300,325 and 350 and the cutting force is measured at each RPM. The cutting process was carried using point attack picks of 45°, 50°, 55° and 65° pick angles and 45°, 55° and 65° attack angles. During the cutting process, the cutting force was varied using a hydraulic pressure valve. In this research, for each RPM and thrust combination, cutting is done for 60 seconds and cutting depth is measured using a digital vernier calliper. The rock cuttings are collected and weighed using a digital weighing machine. Then, the SE (J/m3) is calculated by cutting force multiplied by the depth of cut and divided by volume collected during the cutting process. The increase in RPM, torque, and cutting force observations reveals that the increase in the parameters increases the cutting rate with a corresponding decrease in SE. With cutting rate, the minimum and maximum variation irrespective of the rock type are found to be 0.3 to 4.8% for pick angles, 0.2 to 32% for attack angles, 0.05 to 4.08% for RPM, 0.05 to 3.2% for torque and 0.05 to 3.2% for cutting force. With specific energy, the minimum and maximum variations irrespective of the rock type are found to be 0.023 to 4.41% for pick angles, 21.91 to 51.26% for attack angles, 0.03 to 4.41% for RPM, 0.03 to 7.8% for torque and 0.18 to 7.36% for cutting force. Hence, attack angle has more influence on cutting rate and specific energy. The cutting rates and specific energy values were determined for the pick tool subjected to wear of 5mm at an 45° attack angle. a comparison of the same was made. A decrease in cutting rate is observed with a proportional increase in specific energy. The minimum vi and maximum variations irrespective of the rock type are 24.5 to 33.36% for pick angles, 24.5 to 30.36% for RPM, 21.56 to 35.16% for torque and 20.05 to 32.61% with cutting force for cutting rate. For specific energy, the minimum and maximum variations irrespective of the rock type are 21.86 to 35.81% for pick angles, 21.80 to 32.66% for RPM, 21.89 to 36.20% for RPM torque and 21.98 to 36.64% for cutting force. A property correlation with specific energy was also plotted as a line graph It was observed that, with the increase in density, UCS, BTS, abrasivity, and brittleness of the rock, SE increases linearly. This is because, with the increase in the strength of rock, the cutting resistance increases linearly. The regression models shown in Equations 6.1, 6.2 and 6.3 were developed and can be used to estimate the SE during rock cutting as they can be used as guidance in practical applications. The developed regression model results showed that the SE's significant operating variables were attack angle, type of pick followed by other cutting parameters, such as the rock's mechanical properties. The results showed that input parameters were significant, and the model possesses an R-Square value of 99.55%. The respective variance account for (VAF), root mean square error RMSE and mean absolute percentage error (MAPE) indices for predicting SE are VAF of 99.17, RMSE of 12.08 and MAPE of 0.032535, respectively, from the multiple regression model (testing). The result of the current study provides opportunities to evaluate the cuttability of rocks before involving complicated experimental procedures. Error graphs also resulted in the goodness of fits of a statistical model. Artificial Neural Network (ANN), was developed to predict the SE. the input parameters include cutting force, pick angle, attack angle, depth of cut, volume broken and rock properties like density, UCS, BTS, abrasivity and brittleness. The ANN results showed that the model's predictive performance for VAF, RMSE and MAPE indices are VAF of 99.98289, RMSE of 9.47741, MAPE of 0.0000158 for training and VAF, RMSE and MAPE for validation were VAF of 99.97602, RMSE of 11.85352, MAPE of 0.0000666. Error graphs also resulted in the goodness of fits of a statistical model. vii A numerical model using Finite Element Method (FEM) analysis was constructed to determine the depth of cut for all pick-rock combinations considered using the cutting force values from experimental rock cutting tests (up to loading cycle only). Then the depth of penetration obtained in FEM analysis of all pick-rock combinations was compared with the respective depth of cut obtained with experimental results. The depth of penetration obtained during experiments is lesser than FEM analysis for all pick-rock combinations considered and ranges from 1 to 8% (except a few). Further, the results indicated that displacement decreases from the loading axes towards the boundary in all directions. The stress analysis was carried using Ansys workbench for all the pick-rocks combinations considered along X, Y and Z - directions. The results showed that the maximum compressive stress generated is at the tip of the cut zone. In this research, a new concept is proposed: Rock Cutting Resistance (RCR), i.e., the resistance offered by the rock against the cutting force required to achieve a unit depth of cut, and is expressed as N/mm. The results of the RCR (Experimental and FEM) can be used to predict the depth of cut during rock cutting. Hence, RCR can be used for the efficient design of the rock cutting parameters and the machine.Item Improvement of Shovel and Dumper Availability in Indian Surface Mines using Reliability Analysis(National Institute of Technology Karnataka, Surathkal, 2021) S, Harish Kumar N.; Murthy, Ch. S. N.; Choudhary, R P.Reliability, Availability and Maintainability (RAM) analysis of mining equipment is essential to reduce breakdown hours, operational cost and capital cost and enhance mineral production. The expenditure on mining equipment and expertise increases with the size and complexity of the equipment. A survey of the literature showed that no studies are available on reliability approaches based on subsystems using Markov and RBD model and studies that included mining factors, although a lot of studies exist on shovel and dumper. Consequently, the literature throws little light on the comparison of different reliability approaches between different mines, which is necessary to understand different mine factors. Therefore, the present study attempted to develop mathematical models based on reliability for shoveldumper system for different surface mines (surface coal mine, surface iron ore mine and surface limestone mine) and determine the life of subsystem. The study aims to overcome the major challenges in the mining engineering equipment of breakdown, complexity, size, competition, cost and safety of equipment as well as increased use of mechanization, automation and amalgamation. The research was carried out using quantitative approach as the present study determines the reliability in mining sector. The failure data were collected over a period of one years from daily downtime reports and maintenance records from SCCL, Telengana (for coal mine), M/s. Subbarayanahalli Iron Ore mines and M/s. Mysore Minerals, Sandure (for iron ore) and Thummalapenta Limestone Mine, Telangana (for limestone). To ensure that the data are independent and identically distributed (IID), the trend and serial correlation test were conducted. The analysis of the data was performed using Isograph Reliability Workbench software and characterised by Reliability Block Modelling (RBD) and Morkov modelling. To model the failure and repair processes of subsystems, RAM analysis using time between the failure (TBF) and time to repair (TTR) were carried out. The match factor for coal mine was 1:4, while it was 1:3 for iron ore and limestone mine, which led to the selection of two shovels and eight dumpers for coal mine and two shovels and six dumpers each for iron ore and limestone mine. A total of ten subsystems were formed for the shovel and dumper system. The highest failure percentage for coal mine was 42.1% viii and 48.3% for iron ore mine and limestone mine. Further, in trend and serial correlation analysis, no trend was observed between TBF and TTR was observed and the IID assumption was proved. The Kolmogorov-Smirnov test (K-S test) yielded the probability distribution functions for different subsystems of shovel-dumper system for coal mine as shovels as 0.373 (KS1) and 0.285 (KS2) and dumpers have 0.356 (BD3), 0.269 (BD4), 0.347 (BD5), 0.334 (BD6), 0.332 (KD7), 0.275 (KD8) 0.268 (KD9) and 0.291 (KD10); for iron ore mine as shovels have 0.312 (KS11) and 0.275 (KS12) reliability and dumpers have 0.359 (BD13), 0.342 (BD14), 0.332 (BD15), 0.409 (KD16), 0.393 (KD17) and 0.394 (KD18) and for limestone mine as shovels, 0.343 (KS19) and 0.348 (KS20) reliability and dumpers, 0.325 (BD21), 0.292 (BD22), 0.329 (BD23), 0.362 (KD24), 0.334 (KD25) and 0.304 (KD26). To improve obtained reliability of each system, the preventive maintenance is needed for each system i.e., shovel and dumper. The time interval for each subsystem of shovel and dumper were determined for the 90%, 80% and 70% of reliability of system. The different shovel-dumper systems considered in the study showed ‘infant mortality’ failure indicating manufacturing flaws during the early usage of equipment; however, it improved over time. RBD was used to develop mathematical models for series and series-parallel connection of the systems; whereas, Markov modelling was used for simultaneously-active and continuous-time. The mathematical model for series-parallel connection of the shovel and dumpers were developed based on their match factor and best fit distribution to improve the reliability. As well as Markov model also developed for same shovel and dumper for different mines by considering both failure rate and repair rate. The findings of the study revealed that the method of RAM analysis adopted in the study was highly effective in determining the time-to-failure of the shovel-dumper system that indicated the need for better maintenance plan and design modifications to improve the reliability of the system. The findings showed the necessity of standardizing the maintenance records to include causes and results of failure and delay time condition and providing training to staff on standardization. Creation of a web-based maintenance platform, real-time policies for maintenance, optimization of spare parts, crew members and inspection periods and long-term maintenance plans were also suggested.Item Development of Thermal Efficient Non Fired Bricks using Iron Ore Tailings and Perlite(National Institute of Technology Karnataka, Surathkal, 2021) Rao, P Shubhananda.; Chandar, K Ram.Brick is the most basic artifact and plays a very important role in the construction of buildings. The construction industry is in need of easily available, economically feasible and green materials, as there is a scarcity of naturally available river sand. A lot of research is going on to improve mechanical properties of bricks and also to make more environmentally friendly and economical. A systematic study is taken up by manufacturing bricks using iron ore tailings and additives like perlite. The physical and chemical properties of the materials used in the bricks were determined as per Indian Standard (IS) codes. Use of iron ore tailings (IOT) found to be very beneficial in this research, and the addition of perlite as an admixture to improve its thermal properties is given scope for the development of non-fired thermal efficient bricks. These are non-burnt bricks manufactured in a nontraditional method, which creates a cleaner and greener environment. Bricks were made using different proportions, by replacing sand with Iron Ore Tailings from 30 to 60 percent at 10 percent interval, cement from 10 to 20 percent at 5 percent interval, and Perlite at 2 and 5 percent, of 230mmX112.5mmX75mm dimensions. The study on ecofriendly bricks aims to assess the suitability of IOT in construction in terms of strength, durability, percentage of water absorption and thermal conductivity. Based on laboratory experiments, the optimum percentage of mix to make bricks consisting of iron ore tailings, sand, cement, and perlite was found to be 50%, 25%, 20%, and 5% respectively. The optimum mix gave a compressive strength 3.89MPa, water absorption 14.82% and thermal conductivity 0.920 W/mk which are well within IS codes. Based on the positive laboratory results, further a pilot-scale study is taken up with IOTperlite bricks. In order to assess the effectiveness of IOT-perlite bricks, the pilot-scale study also planned with locally available conventional bricks (fired bricks). Two model rooms, one with IOT – perlite bricks and the other with conventional bricks are constructed to assess the effectiveness of thermal conductivity. It is assessed by measuring the temperature on all sides of the walls at different timings of the day. The results revealed that heat transferred from the outside surface to the inside surface of the bricks in the walls of the model room constructed with IOT-Perlite bricks was less compared with the room constructed with ordinary bricks. Lower thermal conductivity of IOT-Perlite bricks will tend to have less room temperature ii compared to the ordinary brick room. The reduction in the temperature of the IOT-Perlite brick room will consume less electricity and it was estimated in terms of energy savings will be around 8 percentage. The study proved that eco-friendly bricks by using IOT will have lower thermal conductivity, better strength and lightweight in structure. Regression models are developed to predict strength and durability properties like density, compressive strength and thermal conductivity. The regression fit between actual and predicted values in all cases showed a very good correlation.Item Evaluation of Human Body Vibration in Indian Surface Coal Mines and Prediction of Health Risk based on Health Guidance Caution Zone (HGCZ)(National Institute of Technology Karnataka, Surathkal, 2021) Kumar, Jeripotula Sandeep.; Aruna, M.The use of Heavy Earth Moving Machinery (HEMM) to perform various surface mining activities is very common in surface mining Industry. Exposure to whole body vibration from HEMM, such as Dumper, Dozer, Loader, Grader etc., has been associated with low back pain and also with the degeneration of intervertebral disc. The weight of evidence in the literature suggests that no reported studies are available with regard to evaluation of HEMM operators based on seat-back measurements, job cycle and postural variability. Further, prediction of health risks of HEMM operators due to exposure to WBV based on ISO 2631-1:1997 Standards are limited and published literature was not found regarding prediction with respect to European Union (EU) Directive 2002 in Indian surface coal mines. Therefore, the objectives of this study are to evaluate the whole body vibration exposure levels during the operation of different types of HEMM and to assess health risks of operators based on ISO 2631-1:1997 Standard and EU Directive 2002. This study was conducted at two mechanized Indian surface coal mines. HEMM operator’s exposure to vibration was measured according to the procedures stipulated in ISO 2631-1:1997 Standard. A tri-axial seat pad accelerometer was used to measure the vibration exposure levels at the operator’s seat-surface and seat-back. For cyclic operations the measurements were taken for the entire cycle of operation, whereas for non-cyclic operation the minimum measurement duration was 20 minutes. The obtained results were analyzed in accordance to frequency-weighted root mean square (RMS), vibration dose value (VDV), and crest factor (CF) as suggested in ISO 2631-1:1997 Standard. The literature survey carried out infers that there lacks reported studies on WBV evaluation of HEMM operator’s with regard to seat-back measurements, job cycle, postural variability and prevalence of Musculoskeletal disorders (MSDs) among dozers operators. Further, studies were not reported pertaining to ergonomic assessment of surface coal miners. In this regard, two mechanized surface coal mines were considered (which are designated as Mine-I and Mine-II in this report) so as to study the WBV of HEMM operators with regard to - seat-back as well as seat-surface measurements, job cycle of dumper and dozer operators, MSDs and postural variability of dozer operators, and ergonomic assessment of surface coal miners. vi Hence, this study is categorized into four objectives. To evaluate WBV of HEMM operators with regard to seat-back measurements, the study was performed on seventeen types of machinery (i.e dragline-1 no., shovel-4 no., front end loader-2 no., drill-3 no., spreader-1 no., crane-1 no., grader-3 no., water sprinkler-2 no.). The obtained results show that among all the machinery under consideration, the measured WBV of grader operators with regard to seat-back was exceeding Exposure Limit Value (ELV) as per EU Directive 2002. Hence, there should be prompt health surveillance especially for grader operators. For both seat-surface and seat-back measurements, z-axis (i.e. vertical direction) was found to be a prominent axis for most of the HEMM. To study the influence of WBV on dumper operators based on seat-surface and seat-back measurements, six dumpers (i.e. 60T-3nos. and 100T-3nos.) were taken as sample size. The measurements were taken for the entire cycle duration (i.e. loading, loaded travel, unloading and empty travel). The results obtained illustrated that haulage (loaded travel and empty travel) was the chief contributor to vibration exposure for both seat-surface and seat-back measurements. Maximum RMS of 1.12 m/s2 was reported during empty travel for seat-surface measurements and 1.09 m/s2 was reported as highest RMS during empty travel task for seat-back measurements. This high exposure to WBV during haulage would be minimized by regular maintenance of roadways and by regulating speed limits. For seat-surface measurements based on RMS, z-axis was dominant axis of vibration for all the dumpers during haulage task, whereas for seat-back measurement the dominant axis varies between x and y. Similarly, the study was conducted on dozer operators to evaluate the prominence of job cycle on WBV based on seat-surface and seat-back measurements. In this regard, eight dozers were considered and the measurements were taken at every phase of job cycle i.e., forward motion (such as cutting and drifting) and return motion (such as dozer travelling in the reverse direction). The study revealed that all the dozer operators were in severe zone (i.e. above HGCZ) with respect to measured RMS value, during forward motion and return motion, irrespective of type of measurements (i.e., seat-surface and seat-back). To evaluate the effect of WVB on dozer operators based on postural variability. Measurements were taken for three different sitting postures of the operators i.e. lean forward inclination with a trunk flexion of 15°, vertically erect posture and lean backward inclination with a trunk flexion of 15°. Among these three postures lean backward inclination with a trunk flexion of 15° was found as a favorable sitting posture for the dozer operators, as in this posture operators are exposed to minimum vibration. To study the effect of WBV on MSDs of dozer operators, subjective assessment was carried out using Standardized Nordic Questionnaire, for which sample size of forty two dozer operators were selected as exposed group. Out of this exposed group, 35 of them (i.e. 83.33%) reported severe lower back pain. Lastly, an ergonomic study of MSDs was conducted on 500 mine workers. The study demonstrated that the largest number of low-back injuries among miners is influenced by design of workplace and the way the work is organized. Hence, there is a need for intervention to mitigate the WMSDs among miners by better design of workplace and appropriate planning of job cycle, particularly in Indian surface coal mines. The thesis consists of nine chapters. The first chapter includes the general introduction followed by the origin and the objectives of the work. The second chapter gives the brief literature review. The third chapter gives the information about instrumentation and methodology. Chapter four comprehends the evaluation of whole-body vibration exposure of various HEMM operators. Chapter five discusses evaluation of WBV exposure of dumper operators based on the job cycle, followed by chapter six which discusses evaluation of WBV exposure of dozer operators based on job cycle and postural variability. Chapter seven discusses assessment of musculoskeletal disorders among dozer operators exposed to WBV. Chapter eight summarizes ergonomic assessment of musculoskeletal disorders among Indian surface coal mine workers. Chapter nine encapsulates conclusions and scope for future work in this research field.Item Experimental Investigations on Assessment and Prediction of Temperature during Rotary Drilling(National Institute of Technology Karnataka, Surathkal, 2020) S, Vijay Kumar.; Kunar, B M.; Murthy, Ch S N.Drilling is one of the most energy consuming technology processes in conducting exploration works in mining industries. Heat is generated during rock drilling due to friction between rock and bit, which leads to the thermal stress and is subjected to rock failure. Nearly 80% of the energy supplied to the bit is used for heat release, 1.5 % to 10 % for the residual changes of the bit and 8 to 10 % for destruction of rocks (Dreus et al. 2016). Overall, the major cause of the wear of the bit is abrasion wear because the drill bit is most abraded against the rock formation, it is mainly consists of the silica content in the rock samples (Abbas, K. 2018). Hence, selection of drilling parameters and choosing the most appropriate type of drill bit for a certain rock sample will prolong the bit life and reduce the drilling costs. Experimental investigations were carried out on five types of rock samples to measure the temperature at bit-rock interface using newly fabricated K-type grounded thermocouple during rotary drilling in a Computer Numerical Control (CNC) vertical machining centre. The temperature at bit-rock interface was measured by using digital temperature indicator and embedded thermocouple technique. The observations were made using different operational parameters, namely, drill bit diameter (6, 8, 10, 12 and 16 mm), spindle speed (250, 300, 350, 400 and 450 rpm), penetration rate (2, 4, 6, 8 and 10 mm/min) and at different depth (6, 14, 22 and 30 mm). The experimental results show that the tungsten carbide masonry drill bit for all bit rock combinations considered generates an average maximum temperature at bit-rock interface of 91C, 128C, 236C, 124C and 147C for medium grained sandstone, fine grained sandstone (grey), fine grained sandstone (pink), limestone and shale respectively. It was found that the temperature at bit-rock interface increased significantly from 48.48C to 74.53C, 43.81C to 84.68C, 55.73C to 147.82C, 50.34C and 44.29C to 89.57C for MG, FG, FGP, limestone and shale with the increase in depth of drill, drill bit diameter, spindle speed and penetration rate.vi Wear rate of the tungsten carbide (WC) drill bit was measured using weight loss method. Wear rate of tungsten carbide (WC) drill bit and the interrelationship between temperature at the bit-rock interface and wear rate during rotary drilling operations was investigated. Under the test conditions at constant drill bit diameter (16mm) and spindle speed (450rpm) by varying penetration rate of 2, 4, 6, 8 and 10 mm/min respectively, wear rate coefficients (k) were calculated using Archard model and found to be 0.05916, 0.0705, 0.07924, 0.05423 and 0.0596 mg/Nm for medium grained sandstone, fine grained sandstone (grey), fine-grained sandstone (pink), limestone and shale respectively. The SEM and EDS analyses clearly showed that medium grained (MG) sandstone and limestone have less SiO2 contents of 7.85 (wt.%) and 5.76 (wt. %), which gave less wear rate coefficient and bit-rock interface temperature of 0.1423, 0.1594 mg/Nm and 74C, 83C respectively. Similarly fine grained sandstone (grey), fine grained sandstone (pink) and shale which contain 16.45 (wt. %), 30.22 (wt. %) and 25.54 (wt. %) gave wear rate coefficients and temperatures at bit-rock interface of 0.2072, 0.2803, 0.1781 mg/Nm and 84C, 147C, 89C respectively. A study of rock drilling was systematically carried out using full factorial method to determine the effect of operational parameters such as drill bit diameter, spindle speed, penetration rate, thrust and torque on the temperature at bit-rock interface and to find out the wear rate of the tungsten carbide masonry drill bit. ANOVA analysis was applied to investigate the effect of the operational parameters (drill bit diameter, spindle speed, penetration rate, thrust and torque) and rock properties (uniaxial compressive strength, Brazilian tensile strength, Los Angeles abrasion and density) on temperature at bit-rock interface in rotary drilling. The statistically significant parameters i.e., operational parameters and rock properties were identified. Furthermore, multiple linear regression analysis and artificial neural network (ANN) technique were utilized to develop empirical models for predicting the temperature at bit-rock interface and wear rate of the tungsten carbide drill bit. The developed models showed good predictive capability with acceptable accuracy. Artificial neural network models showed optimum neuron with best algorithm and transfer function for the prediction of temperature at bit-rock interface.Item Utilization of Iron Ore Waste and Tailings in Concrete Pavements(National Institute of Technology Karnataka, Surathkal, 2020) B C, Gayana.; Chandar, K Ram.With the augmenting infrastructure, the need for construction materials is increasing in various applications viz., buildings, bridges and pavements. The quantity of materials required for pavement construction is huge. At present scenario, in a few states within India, sand mining is banned due to which it is affecting the construction industry. So, many research works are being focussed on utilization of indusial waste in pavements. A systematic research study is taken up to utilize iron ore mine waste and iron ore tailings in concrete pavements. The main objective of this research study is to evaluate the properties of concrete mixes with marginal materials derived from mine waste i.e., iron ore waste rock (WR) and iron ore tailings (IOT) as coarse and fine aggregates with suitable admixtures for M40 grade concrete based on requirement. The fresh and hardened properties of concrete determined were workability, compressive, splitting tensile and flexural strength. Rapid Chloride Permeability Test (RCPT) was conducted to determine its durability property. Experimental investigations were carried out for three different material compositions. Firstly, two different mixes were considered, one set of concrete mixes with WR as coarse aggregates and other set of concrete mixes with IOT as fine aggregates were replaced partially by 10%, 20%, 30%, 40% and 50% for 3, 7 and 28 curing days with varying water-cement (w/c) for each composition by 0.35, 0.40 and 0.45. Around 162 cubes, 54 cylinders and 54 beams were casted for each mix composition and tested for their strength properties. Optimum strength was obtained at 40%, 30% and 20% replacement of WR in concrete and at 30%, 20% and 10% for IOT concrete for 28days cured specimens, for 0.35, 0.40 and 0.45 w/c. Concrete mix with IOT was workable with higher w/c compared to 0.35 and 0.40 w/c; this is due to the high specific gravity of IOT. In case of WR concrete, workability was found to satisfy the design criteria. Flexural strength observed for IOT and WR concrete mixes ranged between 4.50 to 5.10 MPa. Similar trend was observed in case of compressive and splitting tensile strength.ii To enhance the strength properties of concrete mixes with WR and IOT replacement, alccofine was used as a binder replacement by 10%. Similar to the first case, two different mixes with WR and IOT as coarse and fine aggregates respectively in concrete were considered with 10% alccofine at 10%, 20%, 30%, 40% and 50% for 3, 7, 28 and 56 days curing. Water-cement (w/c) ratio varied for each composition by 0.35, 0.40 and 0.45. Around 216 cubes, 108 cylinders and 108 beams were casted for each mix composition and tested for their strength properties. Similar to WR and IOT concrete mixes, optimum strength obtained for 0.35, 0.40 and 0.45 w/c were at 50%, 40% and 30% replacement of WR-alccofine concrete and in case of IOT-alccofine concrete, optimum strength obtained were at 40%, 30% and 20% respectively. Here, compressive strength ranged between 55 to 75 MPa, splitting tensile strength ranged between 3.8 to 5.0 MPa and flexural strength ranged between 5.80 to 7.30 MPa for WR-alccofine and IOT-alccofine concrete mixes. In this case, density of concrete increased due to the high specific gravity of WR and IOT aggregates. To reduce the density of WR-alccofine and IOT-alccofine concrete respectively and make it a light weight concrete, expanded perlite (EP) was added as partial replacement for fine aggregate by 0%, 2.5%, 5.0%, 7.5% and 10.0% for 3, 7, 28 and 56 days curing with varying w/c of 0.35, 0.40 and 0.45. In this case, control concrete mix with optimum percentage obtained from WR-alccofine and IOT-alccofine were considered for their respective w/c and later EP was replaced as fine aggregates for varying percentages. Based on the results obtained for EP-concrete, density reduced drastically and ranged between 2,600 Kg/m3 to 2,300 Kg/m3 making it a light weight concrete. Due to addition of EP in WR-IOT-alccofine concrete, strength also reduced due to its fineness and porous nature which absorbs water. However, the strength achieved from 5% EP concrete are still higher than the target strength requirement as per IS codes. Compressive strength varied between 58 MPa to 49 MPa. Similar results were obtained in the case of splitting tensile and flexural strength of concrete. Based on all the above experimental investigations, it can be concluded that, for light weight concrete the optimum mix is with 5% replacement of EP concrete for all the w/c considered. For 0.35, 0.40 and 0.45 w/c the optimum percentage of mix consistsiii of WR-IOT-alccofine-EP of 50-40-10-5 percent and 40-30-10-5 percent and 30-20- 10-5 respectively. Whereas, for high dense concrete applications, the optimum percentage of WR-alccofine for 0.35, 0.40 and 0.45 w/c is at 50%, 40% and 30% respectively. Similarly for IOT-alccofine concrete, the optimum percentage was found to be for 0.35, 0.40 and 0.45 w/c is at 40%, 30% and 20% respectively. A statistically fitted multiple regression analysis was performed for all the mechanical properties to evaluate the significant level of concrete containing WR-alccofine, IOTalccofine and EP-concrete mixes. These prediction models developed have high accuracy and low bias. The validation process presented that the equations can perform in a better way in predicting the WR-alccofine, IOT-alccofine and EP concrete properties.Item Investigations on Performance of a Diesel Engine Operated with Raw Cardanol and Kerosene Blends(National Institute of Technology Karnataka, Surathkal, 2019) Ravindra; Aruna, M.; Vardhan, HarshaWorldwide diesel engines are the main source of power for heavy duty equipments in mines and other applications. Since the world crude oil reserves are depleting very fast, there is a need for alternative source. The biodiesel originated from animal fats or vegetable oils are the easier alternatives for diesel fuel, which can be utilised without much engine alterations. However, increased cost of the biodiesel due to the esterification process involved in the production of biodiesel is a limiting factor for vast usage of this alternative. In this research work, raw Cardanol extracted from cashew nut shell is tested as a diesel engine fuel without esterification. To reduce the viscosity of Cardanol, it was blended with kerosene. Experiments were carried out in a 3.5 kW four stroke single cylinder diesel engine using different blends of Cardanol and kerosene, such as BK10 (10% kerosene and 90% Cardanol), BK20% (20% kerosene and 80% Cardanol), BK30 (30% kerosene and 70% Cardanol), BK40% (40% kerosene and 60% Cardanol) as a fuel. Performance parameters such as brake thermal efficiency, brake specific fuel consumption, exhaust gas temperature and the exhaust emissions of unburned hydrocarbon, carbon monoxide, oxides of nitrogen and smoke were measured and compared with diesel fuel. Effect of the engine operating parameters like, compression ratio, injection pressure and injection timing on the engine performance are also investigated. Using the taguchi method, the experimental results were optimised and BK30 blend proved as the most favourable blend for optimum engine performance with minimum emissions, under the following operating conditions: compression ratio - 18:1; injection pressure - 220 bar; injection timing - 24.5°BTDC; load - 12 kg. A fuel cost reduction by about 22% could be observed upon using BK30 biofuel blend as a replacement to diesel fuel in mine machineries. Invention of this novel biofuel blend increases the effective utilisation of Cardanol as a biofuel.Item Studies on Seismic Energy of Ground Vibrations due to Blasting based on Signal Processing and Electrical Energy generation(National Institute of Technology Karnataka, Surathkal, 2019) Garimella, Raghu Chandra.; Sastry, V. R.Blasting may be considered as the most crucial process in opencast mines. It is, therefore, important for mining engineers to understand the effect of blast design parameters on the results of blasting. Blasting operations in mines and quarries always result in ground vibrations, which are of major environmental concern. In general, a meager percentage of total explosive energy is utilized in rock fragmentation process, while the rest is wasted. Wasted explosive energy manifests in the form of various environmental effects such as ground vibrations, air over pressure and fly rock (Dowding, 1985). Ground vibrations caused by blasting cannot be totally eliminated, yet they can be minimized through a suitable blasting methodology. Substantial amount of research associated with identification of ground vibrations and assessing the blast performance in terms of intensity of ground vibrations has been carried out, so far. Nonetheless, very little research has gone into seismic energy and utilizing this energy in understanding the performance of blasts. Modern tools like high speed videography and seismic energy analysis reveal many aspects of fragmentation process, which otherwise are difficult to visualize and understand (Sastry, 2015). In the current research study, an attempt was made for the assessment and estimation of seismic energy dissipated into the ground due to blast induced ground vibrations at different distances from blast site. Studies were carried out in three mines having hard limestone formation, one soft limestone mine formation, one underground coal mine formation, two sandstone formations, and five quarries of hard granite rock formation. Initial studies were carried out by determining the geotechnical parameters influencing the propagation of ground vibrations in the laboratory, using the samples collected from mines and quarries of respective formations. Later, altogether 116 ground vibration events in hard limestone formation, 37 ground vibration events in soft limestone formation, 86 ground vibration events in an underground coal formation, 43 ground vibration events in sandstone formation, and 94 vibration events in granite formation were recorded resulting from various blast rounds using ground vibration monitors. Further, digital signal processing computation was done using Advanced Blastware and DADiSP software for all ground vibration waveforms. Mostof the blasts studied were recorded using High Speed Video Camera of 1000fps capacity for analyzing the blast dynamics. Multiple regression analysis was carried out for assessing the influence of Maximum Charge/Delay, Scaled Distance, Distance, and PPV on seismic energy. Also, ANOVA analysis was carried out for estimation of seismic energy with given blast design parameters using MATLAB. An attempt was made to tap electrical energy from blast induced ground vibrations using the Piezo-Generator (Piezo-Gen) circuit. Validation of Piezo-Gen circuit was done by comparing its output (generated voltage) with the vibration data obtained from geophones. It was evident from the results that the working of developed PiezoGen circuit is appropriate and analogous with vibration monitors. The developed Piezo-Gen circuits were placed adjacent to the seismographs at different short to long range distances to tap electrical energy from ground vibrations. In total, electrical energy was tapped from 66 blast induced ground vibrations in limestone formation, 36 in coal formation, 41 in sandstone formation and 94 in granite formation. Electrical voltage tapped from the blast induced ground vibrations during studies was used for running low powered VLSI systems as ambient power source. The tapped electrical energy was correlated with the PPV and seismic energy. Additionally, numerical modelling was carried out as a parametric study for predicting the seismic energy component resulting from a given blast. Altogether, 98 models were developed using SIMULIA Abaqus / CAE interface. Among them, 28 models are in limestone formation, 14 models are in coal formation, 15 models are in sandstone formation and 41 models are in granitic rock formation. Typical size of each developed model after running the job was upto 3.71GB in limestone formation, 461MB in underground coal formation, 6.02GB in sandstone formation and 5.47GB in granite formation. Each model job run took upto 8-27hrs for completion, in different rock formations. SIMULIA Abaqus based Finite Element Analysis (FEA), with both Python Scripting and Graphic User Interface (GUI) was used to estimate the magnitude of ground vibration intensity (PPV) resulting from a given blast. Additional parameter observed during a blast in the simulated models of four formations was stress components at integral points. Validation of results obtainedfrom developed models was done by comparing with the field results by carrying out three dimensional regression analysis. A proper correlation (>75%) between seismic energy and scaled distance was observed in all four rock formations. Also, from the regression analysis made, an excellent correlation (>90%) between seismic energy and electrical energy was observed in all formations. It indicated the possibility of assessing seismic energy dissipated by ground vibrations with the electrical energy generated by the developed Piezo-Gen circuit. From the numerical modelling analysis, higher stress values were observed at lower distances from blast location indicating dissipation of greater seismic energy. Also, PPV was found to increase in proportional to the distance in all four formations. From the three dimensional curve fitting analysis made among PPVs resulting from modelling study, PPVs obtained in field investigations, and electrical voltages obtained from Piezo-Gen circuit, a very good correlation between the modelling results and seismic data generated from vibration monitoring and electrical data generated from piezo electric generator was observed. Study indicated that the working of Piezo-Gen circuit in tapping ground vibrations is as accurate as traditional ground vibration monitors.
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