Estimation of reliability in a multicomponent stress–strength system for the exponentiated moment-based exponential distribution

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dc.contributor.authorRao, Srinivasa G.
dc.contributor.authorBhatti, Fiaz Ahmad
dc.contributor.authorAslam, Muhammad
dc.contributor.authorAlbassam, Mohammed
dc.date.accessioned2020-11-24T07:56:22Z
dc.date.available2020-11-24T07:56:22Z
dc.date.issued2019
dc.descriptionFull text article. Also available at https://doi.org/10.3390/a12120246en_US
dc.description.abstractA multicomponent system of k components with independent and identically distributed random strengths X 1, X 2 , … X k , with each component undergoing random stress, is in working condition if and only if at least s out of k strengths exceed the subjected stress. Reliability is measured while strength and stress are obtained through a process following an exponentiated moment-based exponential distribution with different shape parameters. Reliability is gauged from the samples using maximum likelihood (ML) on the computed distributions of strength and stress. Asymptotic estimates of reliability are compared using Monte Carlo simulation. Application to forest data and to breaking strengths of jute fiber shows the usefulness of the model.en_US
dc.identifier.citationRao, G. S., Bhatti, F. A., Aslam, M., & Albassam, M. (2019). Estimation of reliability in a multicomponent stress–strength system for the exponentiated moment-based exponential distribution, 12(12), 246.en_US
dc.identifier.otherDOI: 10.3390/a12120246
dc.identifier.urihttp://hdl.handle.net/20.500.12661/2501
dc.language.isoenen_US
dc.publisherMultidisciplinary Digital Publishing Instituteen_US
dc.subjectExponentiated moment-baseden_US
dc.subjectReliabilityen_US
dc.subjectMonte Carlo simulationen_US
dc.subjectExponential distributionen_US
dc.subjectMaximum likelihooden_US
dc.subjectMulticomponent systemen_US
dc.subjectStrengthen_US
dc.subjectStressen_US
dc.titleEstimation of reliability in a multicomponent stress–strength system for the exponentiated moment-based exponential distributionen_US
dc.typeArticleen_US
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