Estimation of Reliability in a Multicomponent Stress- Strength Model Based on Generalized Linear Failure Rate Distribution

Abstract

In this paper, we consider the problem of estimation reliability in multicomponent stress-strength model, when the system consists of kcomponents have strength are given by independently and identically distributed random variables X1, ..., X k each component experiencing a random stress governed by a random variable Y . The reliability such system is obtained when strength and stress variables are given by a generalized linear failure rate distribution. The system is regarded as alive only if at least s out of k (s < k) strength exceed the stress. The multicomponent reliability of the system is given by R s,k = P [ at least s of X1, ..., X k exceed Y ]. The maximum likelihood estimator (M LE) and Bayes estimator of R s,k are obtained. A simulation study is performed to compare the different estimators of R s,k . Real data is used as a practical application of the proposed procedure.

Bayesian Estimation of Reliability for Multicomponent Stress-Strength Model Based on Topp-Leone Distribution

“…Nadar and Kizilaslan in 2015 [15,16], Karam and Jani in 2016 [17]. Hassan and Alohali in 2018 [18]. And in the same year, too.2018, Ali et al [19] estimated the reliability function of the same system when the stress and strength are non-independent components and follow the Weibull and BurrIII distribution.…”

Reliability Inference for the Multicomponent System Based on Progressively Type II Censored Samples from Generalized Pareto Distributions

“…Various researchers have studied the inference of δ s,k for the MSS system using different distributions. For example, Rao [5] studied δ s,k for the generalized exponential distribution; Rao et al [6] investigated δ s,k for the Burr-XII distribution; Hassan and Alohali [7] studied δ s,k for the generalized linear failure rate distribution; and Pak et al [8] investigated δ s,k for the power Lindley model. Readers can refer Kotz, et al [9] for a comprehensive review of the MSS.…”