Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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

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    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).
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    Reliability Analysis of LHD Machine - A Case Study
    (Springer Nature, 2020) BalaRaju, J.; Govinda Raj, M.; Murthy, C.S.N.
    In the present global scenario, survival of the industry is more critical unless it produces their intended targets. Accomplishment of expected rate of production levels are depends on the performance of equipment. Hence, it is very important to predict the maintenance schedules for replacement or repair actions of the defective parts. Keeping in view, every industry is constantly looking for enhancement equipment life. Reliability analysis is one of the well appropriated techniques used to estimate the life of the equipment. In this paper, performance of Load-Haul-Dumper (LHD) has been analyzed. Renewal process approach has been utilized for reliability investigation. 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 Maximum Likelihood Estimate (MLE) method. Reliability of each individual sub-system has been computed according to the best fit distribution. In addition to that, reliability based preventive maintenance (PM) time schedules were calculated for the expected 90% reliability level. The possible recommendations were suggested for improvement of reliability level. © 2020, Springer Nature Switzerland AG.