Reliability Estimation in Load-Sharing System Model with Application to Real Data

Pundir, Pramendra Singh; Gupta, Puneet Kumar

doi:10.1007/s40745-017-0120-5

Cited by 6 publications

(3 citation statements)

References 34 publications

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“…After doing the contour constraint check for β =0 and β = 1 [20], [21]. We examine the results for the following scenario: So, when β =0 in equation ( 7) and ( 8).…”

Section: Particular Circumstances At What Time β=0 Furthermore β=1mentioning

confidence: 99%

Reliability and Mean Time to System Failure of a Parallel System' by Using One or Two Decimal Random Data Points

Kaur,

Sharma

2024

ICST Transactions on Scalable Information Systems

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Focusing on Weibull failure rules, which govern the stopping of components, this work evaluates reliability metrics such as stability and the mean time to system failure (MTSF) of a structure that is parallel. These metrics' behaviour has been seen for one or two decimal random values of component failure rates, operation times, form parameters, and the total quantity of components used in the parallel structure. In order to analyze the variation in the ethics of reliability as well as MTSF, the particular case of the Weibull distribution has also been taken up.

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“…After doing the contour constraint check for β =0 and β = 1 [20], [21]. We examine the results for the following scenario: So, when β =0 in equation ( 7) and ( 8).…”

Section: Particular Circumstances At What Time β=0 Furthermore β=1mentioning

confidence: 99%

Reliability and Mean Time to System Failure of a Parallel System' by Using One or Two Decimal Random Data Points

Kaur,

Sharma

2024

ICST Transactions on Scalable Information Systems

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“…Kayal et al 29 discussed estimation and prediction for unknown parameters of Chen distribution. Pundir and Gupta 30 estimated the unknown parameter and reliability characteristics of the load sharing system model under Chen distribution. Kayal et al 31 provided inferences for two unknown parameters of this bathtub‐shaped model under progressive first failure censoring scheme.…”

Section: The Baseline Modelmentioning

confidence: 99%

Reliability analysis of the dynamic system for the Chen model through sequential order statistics

Tyagi

Choudhary

Singh

2021

Quality & Reliability Eng

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Recently, the two-parameter Chen distribution has widely been used for reliability studies in various engineering fields. In this article, we have developed various statistical inferences on the composite dynamic system, assuming Chen distribution as a baseline model. In this dynamic system, failure of a component induces a higher load on the surviving components and thus increases component hazard rate through a power-trend process. The classical and Bayesian point estimates of the unknown parameters of the composite system are obtained by the method of maximum likelihood and Markov chain Monte Carlo techniques, respectively. In the Bayesian framework, we have used gamma priors to obtain Bayes estimates of unknown parameters under the squared error and generalized entropy loss functions. The interval estimates of the baseline reliability function are obtained by using the Fisher information matrix and Bayesian method. A parametric hypothesis test is presented to test whether the failed components change the hazard rate function. A compact simulation study is carried out to examine the behavior of the proposed estimation methods. Finally, one real data analysis is performed for illustrative purposes.

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“…They also used log-linear link function to model the relationship between the stress levels and component lifetimes. Pundir and Gupta (2018) obtained maximum likelihood and Bayes estimators of system reliability and hazard rate function of a multi-component load sharing system based on Chen distribution. Wang et al (2019) considered loadsharing models with recent memory.…”

Section: Introductionmentioning

confidence: 99%

On Bayesian reliability estimation of a 1-out-of-k load sharing system model of modified Burr-III distribution

Ali

Dey²,

Rehman³

et al. 2019

Int J Syst Assur Eng Manag

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This article deals with classical and Bayesian estimation of the parameters of a 1-out-of-k load-sharing parallel system model in which each component's lifetime follows modified Burr-III distribution. In the classical set up, the maximum likelihood estimates of the load-share parameters, system reliability and hazard rate functions with their bias, standard errors (SEs), average absolute bias (AABias) and width of the confidence interval along with coverage probability are obtained. Besides, two bootstrap confidence intervals for the parameters of the model are also obtained. Further, by assuming both gamma and noninformative priors for the unknown parameters, Bayes estimates of the parameters, system reliability and hazard rate functions with their bias, SEs, AABias and width of the Bayes credible interval along with coverage probability (C p ) are obtained. We have performed a simulation study in order to compare the proposed Bayes estimators with the maximum likelihood estimators. Finally, we analyze one real data set to illustrate the results derived.

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Reliability Estimation in Load-Sharing System Model with Application to Real Data

Cited by 6 publications

References 34 publications

Reliability and Mean Time to System Failure of a Parallel System' by Using One or Two Decimal Random Data Points

Reliability and Mean Time to System Failure of a Parallel System' by Using One or Two Decimal Random Data Points

Reliability analysis of the dynamic system for the Chen model through sequential order statistics

On Bayesian reliability estimation of a 1-out-of-k load sharing system model of modified Burr-III distribution

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