Journal Articles
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Item Estimating rock properties using sound levels produced during drilling(Elsevier BV, 2009) Vardhan, H.; Adhikari, G.R.; Govinda Raj, M.An attempt has been made in this paper to experimentally investigate the estimation of rock properties like compressive strength and abrasivity using sound levels produced during drilling. The investigation was carried out on a laboratory scale using small portable pneumatic drilling equipment used in hard rock drilling. For this purpose, a pneumatic drill setup was fabricated for drilling vertical holes. The compressive strength and the abrasivity of various rock samples collected from the field were determined in the laboratory. A set of test conditions were defined for measurement of sound level of the pneumatic drill. Also, with the help of the experimental setup, vertical drilling was carried out on the rock samples for varying thrust and air pressure values and the corresponding A-weighted equivalent continuous sound levels were measured. Results of this study indicate that sound level can be a promising tool in estimating rock properties during drilling. © 2008 Elsevier Ltd. All rights reserved.Item Fuzzy-FMEA risk evaluation approach for LHD machine-A case study(Central Mining Institute in Katowice gzyl@gig.katowice.pl, 2019) Balaraju, J.; Govinda Raj, M.; Murthy, C.S.Improvement of productivity has become an important goal for mining industries in order to meet the expected targets of production and increased price competitiveness. Productivity can be improved in different ways. The effective utilization of men and machinery is one such way. Equipment is prone to numerous unexpected potential failures during its operation. Failure Mode and Effect Analysis (FMEA) is one of the suitable techniques of reliability modeling used to investigate the failure behavior of a complex system. In conventional FMEA, the risk level of failures, a ranking of failures and prioritization of necessary actions is made on the basis of estimated Risk Priority Number (RPN). While this approach is easy and uncomplicated, there are a few flaws in acquiring the best approximation of the failure. The estimation of RPN is made by multiplying the Severity (S), Occurrence (O) and Detection (D) alone and irrespective of the degree of importance of each input. Hence, a new risk management approach known as the Fuzzy rule base interface system was proposed in this research in order to mitigate the failures. Fuzzy FMEA is designed in order to acquire the highest Fuzzy RPN value which will be used as the focus of enhancements to reduce the probability of occurrence of some kind of failure for a second time. This study focused on the Root Cause Analysis (RCA) of underground mining machinery such as Load-Haul-Dumper (LHD). 16 potential risks of various sub-system breakdowns were identified in Fuzzy FMEA. The highest value of RPN 168 (for potential failure mode-F9) was obtained for the electrical subsystem (SSE), as was the highest FRPN 117 (F9). There is a difference between the RPN and FRPN values. The FRPN value is obtained from Fuzzy field generation with consideration of the degree of importance of the given input data. In addition, the recommendations were made based on the analysis to reduce the uneven occurrence of failures. © 2019 Central Mining InstituteItem Maintenance management of load haul dumper using reliability analysis(Emerald Group Holdings Ltd., 2020) Balaraju, B.; Govinda Raj, M.; Ch.S.N, M.Purpose: Load haul dumper (LHD) is one of the main ore transporting machineries used in underground mining industry. Reliability of LHD is very significant to achieve the expected targets of production. The performance of the equipment should be maintained at its highest level to fulfill the targets. This can be accomplished only by reducing the sudden breakdowns of component/subsystems in a complex system. The identification of defective component/subsystems can be possible by performing the downtime analysis. Hence, it is very important to develop the proper maintenance strategies for replacement or repair actions of the defective ones. Suitable maintenance management actions improve the performance of the equipment. This paper aims to discuss this issue. Design/methodology/approach: Reliability analysis (renewal approach) has been used to analyze the performance of LHD machine. Allocations of best-fit distribution of data sets were made by the utilization of Kolmogorov–Smirnov (K–S) test. Parametric estimation of theoretical probability distributions was made by utilizing the maximum likelihood estimate (MLE) method. Findings: Independent and identical distribution (IID) assumption of data sets was validated through trend and serial correlation tests. On the basis of test results, the data sets are in accordance with IID assumption. Therefore, renewal process approach has been utilized for further investigation. Allocations of best-fit distribution of data sets were made by the utilization of Kolmogorov–Smirnov (K–S) test. Parametric estimation of theoretical probability distributions was made by utilizing the MLE method. Reliability of each individual subsystem has been computed according to the best-fit distribution. In respect of obtained reliability results, the reliability-based preventive maintenance (PM) time schedules were calculated for the expected 90 percent reliability level. Research limitations/implications: As the reliability analysis is one of the complex techniques, it requires strategic decision making knowledge for the selection of methodology to be used. As the present case study was from a public sector company, operating under financial constraints the conclusions/findings may not be universally applicable. Originality/value: The present study throws light on this equipment that need a tailored maintenance schedule, partly due to the peculiar mining conditions, under which they operate. This study mainly focuses on estimating the performance of four numbers of well-mechanized LHD systems with reliability, availability and maintainability (RAM) modeling. Based on the drawn results, reasons for performance drop of each machine were identified. Suitable recommendations were suggested for the enhancement of performance of capital intensive production equipment. As the maintenance management is only the means for performance improvement of the machinery, PM time intervals were estimated with respect to the expected rate of reliability level. © 2019, Emerald Publishing Limited.Item Performance Evaluation of Underground Mining Machinery: A Case Study(Springer, 2020) BalaRaju, J.; Govinda Raj, M.; Murthy, C.S.N.Unexpected occurrence of uneven breakdowns and their consequences have a significant influence on the equipment life. Hence, there is a need to discover the motives for the happening of critical potential failures and required repair or replacement action to control. Reliability analysis is utilized to approximate the performance of the equipment. In this study, the performance of the underground mining machinery known as load haul dumper (LHD) has been estimated with reliability analysis. The best-fit distribution of the data sets was selected by testing the numerous statistical distributions using the Kolmogorov–Smirnov (K-S) test. The percentage of reliability of each subsystem of the LHD machine was computed based on the best-fit approximation. The overall system reliability of the equipment was estimated using a series configuration-based reliability block diagram (RBD) approach. The reliability-based preventive maintenance (PM) time intervals were also computed for estimated 90.00% reliability. To accomplish the desired level of reliability, a review on maintenance programs should be made. Possible recommendations were made to the maintenance department in the industry for improvement in equipment. © 2020, ASM International.Item Screening performance of coal of different size fractions with variation in design and operational flexibilities of the new screening machine(Taylor and Francis Ltd., 2023) Shanmugam, B.K.; Vardhan, H.; Govinda Raj, M.; Kaza, M.; Sah, R.; Hanumanthappa, H.Coal separation was usually carried out using the wet coal beneficiation technique. The waste generated by this technique pollutes the environment. So, in this work, a new mechanism of screening machine for dry coal beneficiation was developed. Dry coal screening removes ash impurities from the coal and improves its energy productivity. Hence, a new screening machine was developed with flexibility in changing the screen mesh, screen angle, and frequency of vibration. In this work, coal feed of less than 6 mm were divided into three groups of −6 + 4 mm, −4 + 2 mm, and −2 + 0.5 mm size fractions. Each size fraction was screened individually in the new screening machine by changing the screen mesh to the required perforation. The screening efficiency was determined for each size fraction by varying operational variables such as screen angle and frequency of vibration. This new screening machine provides maximum screening efficiency of 87.36%, 80.52%, and 66.42% for screening coal feed of 6 + 4 mm, −4 + 2 mm, and −2 + 0.5 mm size fractions, respectively. Highly efficient screening and higher removal of ash from coal were obtained due to the design and operational flexibilities of the screening machine. © 2019 Taylor & Francis Group, LLC.Item Evaluation of the Parametric Effects of Separation of Coal in Vibration Separator Using Plackett–Burman Design of Experiments(Springer, 2023) Shanmugam, B.K.S.; Vardhan, H.; Govinda Raj, M.; Kaza, M.; Sah, R.; Hanumanthappa, H.Plackett–Burman’s design of experiment (DOE) technique provides a mathematical interrelationship between the output parameter and influential input parameters. The vibration separator performance was evaluated by considering three input variables: moisture, inclination, and frequency. Plackett–Burman DOE consists of a minimum number of 12 experimental trials for obtaining the most influential input parameter of the vibration separator. The output parameter of the vibration separator obtained for each experimental trial was separation efficiency. So, the present work provides the most influential input parameter, which highly controls the separation efficiency of the vibration separator for the separation of coal. The model was validated using the residual analysis. Further, the revalidation of the Plackett–Burman DOE mathematical model for the separation of coal was carried out by comparing the closeness of the experimental cube plot and predicted cube plot. Furthermore, the Pareto chart, normal plot, and ANOVA table were utilized to determine the significant input parameter for obtaining higher efficiency of vibration separator. The main effect plot, interactive plots, and optimization results provide the most optimized input parameter for obtaining higher efficiency of coal separation. So, the present work will provide the most influential parameters using Plackett–Burman DOE for separation of coal in the vibration separator. © 2022, The Indian Institute of Metals - IIM.