Classical and Bayesian Estimation of Reliability in Multicomponent Stress-Strength Model Based on Weibull Distribution

In this study, we consider a multicomponent system which has k independent and identical strength components X1,...,Xk and each component is exposed to a common random stress Y when the underlying distributions are Weibull. The system is regarded as operating only if at least s out of k (1 ≤ s ≤ k)...

Full description

Autores:
Kizilaslan, Fatih
Nadar, Mustafa
Tipo de recurso:
Article of journal
Fecha de publicación:
2015
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/66537
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/66537
http://bdigital.unal.edu.co/67565/
Palabra clave:
51 Matemáticas / Mathematics
31 Colecciones de estadística general / Statistics
Stress-Strength Model
System Reliability
Weibull Distribution
DistribuciónWeibull
Modelo estrés-fuerza
Sistema de confiabilidad.
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
Description
Summary:In this study, we consider a multicomponent system which has k independent and identical strength components X1,...,Xk and each component is exposed to a common random stress Y when the underlying distributions are Weibull. The system is regarded as operating only if at least s out of k (1 ≤ s ≤ k) strength variables exceeds the random stress. We estimate the reliability of the system by using frequentist and Bayesian approaches. The Bayes estimate of the reliability has been developed by using Lindley's approximation and the Markov Chain Monte Carlo methods due to the lack of explicit forms. The asymptotic confidence interval and the highest probability density credible interval are constructed for the reliability. The comparison of the reliability estimators is made in terms of the estimated risks by the Monte Carlo simulations.