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

Asadi Saeid, Panahi Hanieh, Anwar Sadia, Lone Showkat Ahmad

Eksploatacja i Niezawodność

2023

Vol. 25, no. 2

art. no. 163054

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 SSRemodel based on the Burr III distribution under the improved adaptive progressive type-II censoring scheme (IAPrgCS-II). Estimation methods of the SSReparameters 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 tostudy 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.

Estimation procedures for partially accelerated life test model based on unified hybrid censored sample from the Gompertz distribution

Lone Showkat Ahmad, Panahi Hanieh

Eksploatacja i Niezawodność

2022

Vol. 24, no. 3

427--436

The accelerated life testing is the key methodology of evaluating product reliability rapidly. This paper presents statistical inference of Gompertz distribution based on unified hybrid censored data under constant-stress partially accelerated life test (CSPALT) model. We apply the stochastic expectation-maximization algorithm to estimate the CSPALT parameters and to reduce computational complexity. It is shown that the maximum likelihood estimates exist uniquely. Asymptotic confidence intervals and confidence intervals using bootstrap-p and bootstrap-t methods are constructed. Moreover the maximum product of spacing (MPS) and maximum a posteriori (MAP) estimates of the model parameters and accelerated factor are discussed. The performances of the various estimators of the CSPALT parameters are compared through the simulation study. In summary, the MAP estimates perform superior than MLEs (or MPSs) with respect to the smallest MSE values.