Stress–strength reliability estimation of a consecutive <i>k</i>-out-of-<i>n</i> system based on proportional hazard rate family

Demiray, Duygu; Kızılaslan, Fatih

doi:10.1080/00949655.2021.1935947

Cited by 13 publications

(7 citation statements)

References 22 publications

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“…Bai et al (2019) evaluated the model parameters under progressive interval censored sample. Demiray and Kizilaslan (2022) proposed the reliability parameters estimation of a consecutive k-out-of-n model under proportional hazard distributions. Asadi and Panahi (2022) studied the point and interval estimators using classical and Bayesian and presented its application for coating processes.…”

Section: Introductionmentioning

confidence: 99%

Inference of reliability model with burr type XII distribution under two sample balanced progressive censored samples

Lone,

Panahi,

Anwar

et al. 2024

Phys. Scr.

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The balanced joint progressive censoring scheme gives guidelines for researchers in reducing the expense and period of the experiment with modified efficiency. In this paper, the stress-strength reliability model are considered and investigated, in which two independent samples are generated from Burr Type XII distributions under balanced joint progressive censoring scheme. In the classical analysis, the maximum likelihood estimate of the reliability parameter is derived, then the relevant confidence interval is provided based on the Fisher matrix. Under the Bayesian framework, the Lindley’s technique and hybrid Gibbs within Metropolis-Hastings algorithm are applied to acquire the estimates of the parameters, and the corresponding highest posterior density credible interval of the reliability model is also constructed. The reliability inference is realized by numerical simulation, and the validity of the inference method is analyzed based on the splashing data of silicone oil droplets impact (SSODI) under two surfaces wettability conditions.

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Section: Introductionmentioning

confidence: 99%

Inference of reliability model with burr type XII distribution under two sample balanced progressive censored samples

Lone,

Panahi,

Anwar

et al. 2024

Phys. Scr.

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“…For computational ease, Kızılaslan 13 , Jha et al 15 , and Mahto et al, 16 have also considered the case when both the stress and strength variables follow different distributions with a common scale parameter. Demiray and Kızılaslan 17 developed the stress-strength reliability estimation procedures for a consecutive k-out-of-n system based on proportional hazard rate family.…”

Section: Introductionmentioning

confidence: 99%

Efficient estimation of the reliability functions in a multicomponent stress‐strength set‐up for a generalized family of distributions under progressive type II censoring

Kumari,

Pathak

2024

Quality & Reliability Eng

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In this paper, we have introduced the concept of a new multicomponent reliability function Estimation procedures are developed for under progressive type II censoring scheme, which is subsequently used to develop the estimation procedures for the multicomponent stress‐strength reliability function . Herein, we consider a system having k statistically independent and identically distributed strength components, , say, which are exposed to a common random stress Y. Both strength and stress variables are independent and follow different scaled proportional hazard rate family of distributions with common scale parameter. The reliability functions and are estimated by using maximum likelihood and Bayesian methods of estimation. The performances of these estimators are studied on the basis of their mean squared errors through Monte Carlo simulation technique. Finally, the utility of the proposed estimators is examined and explained through two different real data sets.

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“…This reliability system is introduced by Church and Harris [9], and since then statistical inference of SSRe model has been continuing to be studied under different assumptions. For some recent studies about this topic, one can see, Bhattacharyya [6], Rao et al [22], Akgul and Senoglu [1], Bai et al [5], Asadi and Panahi [2], De La Cruz [11] and Demiray and Kizilaslan [12]. Also, one of the important applications of this reliability model is to evaluate the strength of coated microlayers on the surfaces of mechanical devices.…”

Section: Introductionmentioning

confidence: 99%

Reliability Estimation of Burr Type III Distribution under Improved Adaptive Progressive Censoring with Application to Surface Coating

Asadi¹,

Panahi²,

Anwar³

et al. 2023

Eksploatacja i Niezawodność – Maintenance and Reliability

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The stress-strength reliability (SSRe) model is widely investigated in reliability engineering to determine the probability of the strength component overcomes the stress imposed on it. In this paper, we studied the estimation of SSRe model based on the Burr III distribution under the improved adaptive progressive type-II censoring scheme (IAPrgCS-II). Estimation methods of the SSRe parameters are developed using frequentist and Bayesian approaches. The point and interval estimations using the maximum likelihood are considered to estimate the parameters. Two approximations are applied to compute the Bayes estimates. A simulation study is conducted for the comparison of the methods of estimation. Also, parallel to the development of reliability studies, it is necessary to study its application in different sciences such as engineering. Therefore, the droplet splashing (DrS) data under two wettabilities are proposed as an application of the considered SSRe model and methods. The results show us that the reliability model can be used to amend the quality of coatings.

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Stress–strength reliability estimation of a consecutive k-out-of-n system based on proportional hazard rate family

Cited by 13 publications

References 22 publications

Inference of reliability model with burr type XII distribution under two sample balanced progressive censored samples

Inference of reliability model with burr type XII distribution under two sample balanced progressive censored samples

Efficient estimation of the reliability functions in a multicomponent stress‐strength set‐up for a generalized family of distributions under progressive type II censoring

Reliability Estimation of Burr Type III Distribution under Improved Adaptive Progressive Censoring with Application to Surface Coating

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