Journal Articles

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/19884

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Author: search.filters.author.Murthy, C.S.N.Subject: search.filters.subject.Maintenance

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    Reliability analysis and failure rate evaluation of load haul dump machines using Weibull distribution analysis
    (International Information and Engineering Technology Association info@iieta.org, 2018) Balaraju, R.J.; Govinda, R.M.; Murthy, C.S.N.
    Improvement of multifaceted system quality requires a group of complex design modifications. An expanding complexity of system is potentially prone to increase in the failure frequency. Continuous and random occurrence of failures in a system could be the main cause for performance drop of machinery. Theoritical probability distribution is one of the techniques used to estimate the lifetime of a system and its sub-systems with several failure considerations. One of the most extensively used statistical approaches for reliability estimation is a Weibull distribution. In the present paper a three-parameter Weibull distribution approach was adopted to analyze the data sets of Load-Haul-Dumper (LHD) in underground mines using 'Isograph Reliability Workbench 13.0' software package. The parameters were evaluated using best fit distributions and Weibull likelihood plots. Percentage reliability of each individual subsystem of LHD was estimated. Further, an attempt has been made to identify the preventive maintenance (PM) time intervals for enhancing the expected rate of reliability. © 2017 IIETA.
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    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.