Tampered random variable modeling for multiple step-stress life test

Sultana, Farha; Dewanji, Anup

doi:10.1080/03610926.2021.2008440

Cited by 7 publications

(5 citation statements)

References 25 publications

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“…Consequently, we observed the fact that the optimal stress change point choices are not sensitive to misspecification of the model parameters as long as they are not far deviated from their true values. We can generalize this idea for multiple step‐stress TRV modeling as proposed by Sultana and Dewanji 7 …”

Section: Discussionmentioning

confidence: 99%

“…The third approach, known as Tampered Random Variable (TRV) modeling, scales down the remaining lifetime at successive stress levels. See Goel, 5 DeGroot and Goel, 6 Sultana and Dewanji, 7 and Koley et al 8 for more details. Recently, Sultana and Dewanji 7 have shown the relationship between the TRV model and the other two models, namely, CE and TFR, under the multiple step-stress framework.…”

Section: Introductionmentioning

confidence: 99%

“…See Goel, 5 DeGroot and Goel, 6 Sultana and Dewanji, 7 and Koley et al 8 for more details. Recently, Sultana and Dewanji 7 have shown the relationship between the TRV model and the other two models, namely, CE and TFR, under the multiple step-stress framework. Also, the authors mentioned that TRV modeling is equivalent to CEM and TFR if and only if the baseline lifetime is exponential and the marginal distributions of each stress level follow a scale parametric family, respectively.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Step‐stress life‐testing under tampered random variable modeling for Weibull distribution in presence of competing risk data

Sultana,

Çetinkaya,

Kundu

2023

Quality & Reliability Eng

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In this paper, we have considered the classical and Bayesian inference of the unknown parameters of the lifetime distribution based on the observations obtained from a simple step‐stress life‐testing (SSLT) experiment and when more than one cause of failures are observed. We have used the Tampered Random Variable (TRV) approach. The main advantage of the TRV approach is that it can be easily extended to a multiple step‐stress model as well as for different lifetime distributions. In this paper, it is assumed that the lifetime of the experimental units at each stress level follows Weibull distribution with the same shape parameter and different scale parameters. Further, we have introduced different tempering co‐efficient for different causes of failures. The maximum likelihood estimators and the associated asymptotic confidence intervals are obtained based on Type‐II censored observations. Further, we have considered the Bayesian inference of the unknown model parameters based on a fairly general class prior distributions. An extensive simulation study is performed to examine the performances of the proposed method, and the analysis of a real data set has been provided to show how the method can be used in practice. We have compared the TRV model with some of the other existing models, and the TRV model provides a better fit in terms of information theoretic criteria. We have also provided some optimality criteria, to determine the optimal stress change time and some sensitivity analyses have been performed. Most of the methods can be extended for other lifetime distributions also.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Step‐stress life‐testing under tampered random variable modeling for Weibull distribution in presence of competing risk data

Sultana,

Çetinkaya,

Kundu

2023

Quality & Reliability Eng

Self Cite

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“…Additionally, Sultana and Dewanji [11] explored the relationships between the TRV model and the two other models, TFR and CE, within a multi-step stress environment. They noted that TRV modeling aligns with CE and TFR when the fundamental lifetime distribution is exponential and the distributions at each stress level adhere to a scale-based parametric family.…”

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confidence: 99%

Tampered Random Variable Analysis in Step-Stress Testing: Modeling, Inference, and Applications

Ahmad,

Ramadan,

Almetwally

2024

Mathematics

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This study explores a new dimension of accelerated life testing by analyzing competing risk data through Tampered Random Variable (TRV) modeling, a method that has not been extensively studied. This method is applied to simple step-stress life testing (SSLT), and it considers multiple causes of failure. The lifetime of test units under changeable stress levels is modeled using Power Rayleigh distribution with distinct scale parameters and a constant shape parameter. The research introduces unique tampering coefficients for different failure causes in step-stress data modeling through TRV. Using SSLT data, we calculate maximum likelihood estimates for the parameters of our model along with the tampering coefficients and establish three types of confidence intervals under the Type-II censoring scheme. Additionally, we delve into Bayesian inference for these parameters, supported by suitable prior distributions. Our method’s validity is demonstrated through extensive simulations and real data application in the medical and electrical engineering fields. We also propose an optimal stress change time criterion and conduct a thorough sensitivity analysis.

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Inference and expected total test time for step-stress life test in the presence of complementary risks and incomplete data

Tian

Gui

2023

Comput Stat

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Tampered random variable modeling for multiple step-stress life test

Cited by 7 publications

References 25 publications

Step‐stress life‐testing under tampered random variable modeling for Weibull distribution in presence of competing risk data

Step‐stress life‐testing under tampered random variable modeling for Weibull distribution in presence of competing risk data

Tampered Random Variable Analysis in Step-Stress Testing: Modeling, Inference, and Applications

Inference and expected total test time for step-stress life test in the presence of complementary risks and incomplete data

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