Conference Papers

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

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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 Using Bayesian Belief Network on Drone System: A Case Study
    (Institute of Electrical and Electronics Engineers Inc., 2024) Das, M.; Mohan, B.R.; Ram Mohana Reddy, G.; Chhaparwal, E.; Krishna Kumar, K.; Chowdhury, S.; Sharma, S.
    Ensuring the reliability of software components is of paramount importance in safety-critical systems. Grave consequences might occur if software failures in such systems. Hence, predicting software reliability is important in these systems. This research uses Bayesian Belief Network(BBN) and leverages historical failure data to find fault interdependencies, giving much more insights than methodologies like Fault Tree Analysis (FTA) and Reliability Block Diagrams (RBD). By comparing BBNs with these traditional methods, the research shows the dynamic capabilities of BBNs. BBN also shows the capability of using real-time data and machine learning together to increase the software reliability of the software components, making this system much safer. © 2024 IEEE.