Faculty Publications

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    Improvement of overall equipment performance of underground mining machines- a case study
    (AMSE Press 16 Avenue Grauge Blanche Tassin-la-Demi-Lune 69160, 2018) Balaraju, B.; Raj, G.; Chivukula, M.S.
    Production and productivity of any industry mainly depends on effective utilization of men and machinery. Underground mine production for the last few decades in India is not in satisfactory level, due to less mechanization. The maximum amount is expended for introducing the large scale mechanized equipment. Hence, mechanization in loading system has made advantageous towards production. In spite of this Load Haul Dumper (LHD) is one and used as loading and hauling machine for intermediate of operation. During the operation of the equipment, possible major breakdowns are occurred in some aspects. Therefore, these lead to reduce the percentage availability and utilization of the machines. As a result of this, it is very essential to analyze the performance of LHD machines, to reduce the cost during the operations. The higher availability of machine gives an optimum utilization, which increase the production and productivity of these principal intensive items. Keeping this in view, this paper focuses on improvement of overall equipment performance (OEP) by calculating the percentage availability and capacity utilization of LHDs in underground mines. Further an attempt is also emphasized to identify the contributing factors of performance improvement. © 2018 AMSE Press. All Rights Reserved.
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    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.
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    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).
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    Reliability block diagram (RBD) and fault tree analysis (FTA) approaches for estimation of system reliability and availability – a case study
    (Emerald Group Holdings Ltd., 2021) Balaraju, B.; Raj, G.R.; Ch.S.N, M.
    Purpose: In the present worldwide situation, the survival of a business is a major crucial aspect. The business cannot be succeeded unless it produces the anticipated production levels. Achievement of this can be possible only by maintaining the equipment into an adequate level. Load-Haul-Dumpers (LHDs), as the main workhorse and massive transporting machines, are highly utilized in underground mining operations. Despite the usage of LHDs, these are prone to the uneven and unexpected occurrence of potential failures. These are causes to minimize the production and productivity of capital intensive equipment. To get a good profitability index, it is very necessary to have the required levels of equipment reliability and availability. Estimation of reliabilities and availabilities play a critical role in the performance evaluation of equipment. Design/methodology/approach: By keeping the significance of the present research work in view in this research paper one of the well appropriate techniques such as fault tree analysis (FTA) was utilized to assess the reliability of the LHD system based on the function flow diagram. Best fit distribution of data sets were made by the utilization of Kolmogorov–Smirnov (K-S) test. Parametric estimation of theoretical probability distributions was done by utilizing the maximum likelihood estimation (MLE). Failure rate of each LHD system has computed based on the best fit results from “Isograph Reliability Workbench 13.0”. Reliability configuration of each LHD system has modeled using reliability block diagram (RBD), as well as the FTA. Findings: Independent and identical distribution (IID) assumption of data sets was validated through statistic U-test (Chi Squared test). 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 ofK-S test. Parametric estimation of theoretical probability distributions was made by utilizing maximum likelihood estimation (MLE) method. Reliability of each individual subsystem has been computed according to the best fit distribution. The deductive method called RBD was utilized to investigate the given system reliability by analyzing with graphical representations of logic system and observed highest percentage of reliability as 69.44% (LH29). FTA has been utilized to investigate the availability percentage of a system and observed highest percentage value as 79.51% (LH29). This technique also helps to identify the most critical parts/cut sets by using Fussell-Vesely (F-V) importance measure. 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 schedules, partly due to the peculiar mining conditions, under which they operate. This analysis provides the information on several aspects such as present working condition of the machines, occurrence of various potential failure modes, influence of failure modes on its performance and reliable life aspects etc. Also, these investigations asses the forecasting of necessary managerial practices or control measures like possible design modifications and replacement actions of components to ensure the required levels of availability and utilization of the equipment. Both qualitative and quantitative analysis of FTA has been performed to determine the minimal/most influencing cut sets of the system and to estimate overall system availability within the work environment. Based on the computed results reasons for performance drop of each machine was identified and suitable recommendations were suggested to improve the performance of capital intensive systems. © 2020, Emerald Publishing Limited.
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    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.
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    Effective Maintenance Planning for Improving the Reliability of Underground Mining Equipment—A Case Study
    (Acadlore Publishing Services Limited, 2025) Balaraju, B.; Raj, M.G.; Tripathi, A.K.
    The Load Haul Dumper (LHD) is essential machinery utilized for moving ore in the underground mining industry, in order to fulfil production targets. In this connection, the efficiency of the equipment should be maintained at an ideal standard, to be accomplished by reducing unexpected failure of components or subsystems in this intricate system. Downtime analysis helped identify faulty components and subsystems, which require the development of complementary maintenance plans to facilitate the replacement or fixing of parts. Proper practices of maintenance management improve the performance of the equipment. In this research, the efficiency of the LHD machine was assessed through reliability methods. Initially, the assumption of independent and identical distribution (IID) for the data sets was validated using trend and serial correlation analyses. The statistical tests indicated that the data sets adhered to the IID assumption. Therefore, a renewal process method was utilized for additional examination. The Kolmogorov-Smirnov (K-S) test was utilized to identify the most suitable distribution for the data sets. The theoretical probability distributions were estimated parametrically using the Maximum Likelihood Estimate (MLE) approach. The dependability of each separate subsystem was determined using the optimal fit distribution. Based on the reliability outcomes, preventive maintenance (PM) time plans were created to reach the targeted 90% reliability. Different maintenance strategies, in addition, were suggested to the maintenance team to extend the lifespan of the machine. © 2025 by the author(s). Licensee Acadlore Publishing Services Limited, Hong Kong.