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Estimation of multicomponent stress-strength reliability following Weibull distribution based on upper record values

Content Provider	Scilit
Author	Hassan, Amal S. Nagy, Heba F. Muhammed, Hiba Z. Saad, Mohammed S.
Copyright Year	2020
Description	Stress-strength models are of special importance in reliability literature and engineering applications. This paper deals with the estimation problem of a stress-strength model incorporating multi-component system. The system is regarded as alive only if at least $S out ofk(S<k) strength components exceed the stress. The reliability of such system is obtained when strength and stress variables have Weibull distributions. Maximum likelihood estimator ofRS,k and asymptotic confidence intervals are obtained based on upper record values. Bayesian estimator under squared error and linear exponential loss functions using gamma prior distributions and the corresponding credible intervals are obtained. Due to the lack of explicit forms for the Bayes estimates, the Markov Chain Monte Carlo (MCMC) method is employed. A simulation study is implemented to assess the performance of estimates. A real-life example is presented to show how the proposed model may be utilized in breaking strength of jute fibre data.$
Related Links	https://www.tandfonline.com/doi/pdf/10.1080/16583655.2020.1721751?needAccess=true
Ending Page	253
Page Count	10
Starting Page	244
ISSN	16583655
e-ISSN	16583655
DOI	10.1080/16583655.2020.1721751
Journal	Journal of Taibah University for Science
Issue Number	1
Volume Number	14
Language	English
Publisher	Informa UK Limited
Publisher Date	2020-01-01
Access Restriction	Open
Subject Keyword	Composite Materials Mechanics Weibull Distribution Multicomponent Stress–strength Reliability Upper Record Values Asymptotic Confidence Interval Markov Chain Monte Carlo
Content Type	Text
Resource Type	Article
Subject	Earth and Planetary Sciences Chemistry Physics and Astronomy Biochemistry, Genetics and Molecular Biology Mathematics Environmental Science Agricultural and Biological Sciences

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