Faculty Publications
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Item Failure rate and reliability of the KOMATSU hydraulic excavator in surface limestone mine(American Institute of Physics Inc. subs@aip.org, 2018) N. S., N.S.; Choudhary, R.P.; Murthy, C.S.N.The model with failure rate function of bathtub-shaped is helpful in reliability analysis of any system and particularly in reliability associated privative maintenance. The usual Weibull distribution is, however, not capable to model the complete lifecycle of the any with a bathtub-shaped failure rate function. In this paper, failure rate and reliability analysis of the KOMATSU hydraulic excavator/shovel in surface mine is presented and also to improve the reliability and decrease the failure rate of each subsystem of the shovel based on the preventive maintenance. The model of the bathtub-shaped for shovel can also be seen as a simplification of the Weibull distribution. © 2018 Author(s).Item This paper deals with the cost analysis of a two-unit repairable system subject to on-line preventive maintenance (on-line PM) and/or repair. The policy adopted here is that the on-line PM work of the operating unit is undertaken first on its completion, the repair work of the failed unit, if any, is subsequently carried out. All the random variables that arise in the analysis are assumed to be independently and arbitrarily distributed. An expression for the expected total cost incurred by the system in a specified time interval is obtained by considering the expected busy period of the server spent on various actions. The analysis is carried out using the regeneration point technique. © 1992.(Cost analysis of a two-unit repairable system subject to on-line preventive maintenance and/or repair) Gopalan, M.N.; Bhanu, K.S.; Murulidhar, N.N.1992Item Worldwide, increasingly stringent regulations are coming into force, limiting the exposure of workers to industrial noise. Industrial noise and its consequences is thus growing in importance to employers, local and central government officials, trade unions, occupational hygienists and physicians and insurers. India is not an exception for this. The mining industry in India is facing serious problem of noise due to increasing demand for minerals for which large capacity machines are being deployed producing high noise levels. To know the status and to control the noise, the S&T Department of the Ministry of Coal, Government of India sponsored a research project in the area of noise pollution and its control for opencast projects. To start with, a detailed literature survey was carried out in the area of noise pollution and its control in the mining industry, embracing equipment like from Heavy Earth Moving Machinery (HEMM), compressors, workshops, pneumatic drills, processing plants etc., to know the quantum of work done in India and worldwide. The various aspects studied in this project were the daily noise dose and/or noise exposure level of the operators of various types of heavy earth moving machinery and its assessment, noise characteristics at different operating conditions of the machine, analysis of noise coming out from different parts of the machine, analysis of noise at different distances from the machine for different frequency components and the most important one i e, impact of periodic maintenance on the noise characteristics of machines and to find out with which maintenance schedule there is maximum fluctuation in the noise level and to evolve a technique for attenuating the noise generated from these machines as well as to reduce the operator's exposure to high noise levels. This paper highlights the results of this research project.(Multi-Science Publishing Co. Ltd, Noise analysis of heavy earth moving machinery deployed in opencast mines and development of suitable maintenance guidelines for its attenuation - Part 1) Vardhan, H.; Rao, Y.V.; Karmakar, N.C.2004Item An experimental investigation of the sound level produced by bulldozers with various maintenance schedules(Inderscience Publishers, 2008) Vardhan, H.; Raj, M.G.This study was made to understand and evaluate the effect of maintenance on noise production from bulldozers through experimental measurements of sound levels in a large open cast mine. Assessment of sound pressure levels at each periodic maintenance interval revealed that maximum sound level reduction was achieved at 1000 h maintenance schedule. For other periodic maintenance intervals, reduction in A-weighted sound pressure level was below 1.0 dB. The study revealed that primarily, the major noise-generating systems in Heavy Earth Moving Machinery (HEMM) are air, exhaust, cooling and fuel systems. However, maintenance of lubricant, transmission and hydraulic systems yielded no significant improvements in sound levels. Results also indicated sound level emissions from various systems to lie in different frequency ranges. © 2008, Inderscience Publishers.Item 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 Application ANN Tool for Validation of LHD Machine Performance Characteristics(Springer, 2020) Balaraju, B.; Raj, G.R.; Murthy, C.S.Survival of industries has become more critical in the present global competitive business environment unless they produce their projected production levels. The accomplishment of this can be possible only by maintaining the men and machinery in an efficient and effective manner. Hence, it is more essential to estimate the performance of utilized equipment for reaching/achieving future goals. The present study focuses on the estimation of underground mining machinery such as the load–haul–dump machine performance characteristics using ‘Isograph Reliability Workbench 13.0’ software. The allocation of best-fit/goodness-of-fit distribution was made by utilizing the Kolmogorov–Smirnov test (K–S) test. The parameters were recorded based on the best-fitted results using the maximum likelihood estimate test. Further, a feed-forward-back-propagation artificial neural network (ANN) tool has been used to develop the models of reliability, availability and preventive maintenance time intervals. The number of neurons was selected with the Levenberg–Marquardt learning algorithm in the hidden layer as the optimal value. The output responses were predicted corresponding to the optimal values. Further, an attempt has been made to validate the computed results with ANN predicted responses. The recommendations are suggested to the industry based on the results for the improvement of system performance. © 2020, The Institution of Engineers (India).Item Reliability, availability and maintainability (RAM) investigation of Load Haul Dumpers (LHDs): a case study(Springer, 2022) Balaraju, B.; Raj, G.R.; Murthy, S.M.Load Haul Dumpers (LHDs) are prominent equipment employed for transportation operations in many of the underground mines. This equipment often suffers from frequent breakdowns due to a variety of technical and managerial practices resulting in increased maintenance costs and loss of production and productivity. Reliability, Availability and Maintainability (RAM) analysis deal with the optimal functioning of equipment, maintenance scheduling, controlling cost, and improvement of availability and performance. Keeping this in view, the current study focused on the estimation of the performance of the equipment using RAM investigation. The required failure and repair data of LHDs were collected from field investigations. Graphical analyses using Trend and serial correlation tests and analytical analysis using Statistic-U test were conducted to validate the Independent and Identical Distribution (IID) nature of the data sets. Based on the above tests, the Renewal Process was adopted to carry out the RAM analysis. The best-fit approximation of datasets was selected by performing the Kolmogorov–Smirnov (K–S) test. In addition to that, the reliability-based Preventive Maintenance time intervals were estimated to improve the percentage of reliability. © 2021, The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden.