Please use this identifier to cite or link to this item: https://idr.l1.nitk.ac.in/jspui/handle/123456789/11275
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dc.contributor.authorN., S., H.K.
dc.contributor.authorChoudhary, R.P.
dc.contributor.authorMurthy, C.S.N.
dc.date.accessioned2020-03-31T08:31:02Z-
dc.date.available2020-03-31T08:31:02Z-
dc.date.issued2019
dc.identifier.citationInternational Journal of Innovative Technology and Exploring Engineering, 2019, Vol.8, 5, pp.1025-1030en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/11275-
dc.description.abstractTo develop a nonparametric bathtub curve model for a shovel and dumper in an opencast limestone mine, the historical failure data such as time between failure (TBF) and failure frequency of a shovel and dumper were collected from the mine. Based on the collected TBF and failure frequency, Weibull parameters i.e., shape parameter (?), scale parameter (?)?and location parameter (?) were calculated under the K-S test (Kolmogorov Smirnov). A Weibull distribution model has been developed to obtain the probability distribution function (PDF) and the bathtub-shaped failure rate curve for a shovel-dumper system using Reliability Isograph Workbench (RWB). Also, the Artificial Neural Network (ANN) model has been developed to predict the PDF and failure rate for the same shovel-dumper system and compared with the obtained values of Reliability Isograph Workbench. It was found that the values of RMSE and R 2 were 5.96E-5 & 0.999 for PDF and 9.23E-8 & 0.9993 for failure rate respectively. BEIESP.en_US
dc.titleFailure rate analysis of shovel and dumper in opencast limestone mine using RWB and ANNen_US
dc.typeArticleen_US
Appears in Collections:1. Journal Articles

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