Bootstrapping Analysis of Lifetime Data with Subsampling

Wu, Guodong; Niu, Zhanwen; Lv, Shanshan; Qu, Liang; He, Zhen

doi:10.1002/qre.1925

Cited by 16 publications

(8 citation statements)

References 22 publications

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“…The proposed technique runs on a spread-sheet. By the same token, the proposed method could also assist the robustness status of factorial experiments in accelerated tests that undergo subsampling (Wang et al , 2016) since our method is applicable regardless the distribution identity of the examined dataset and no simulations are necessitated to check parameter bias.…”

Section: Discussionmentioning

confidence: 99%

QUALITY PAPERA new rapid and robust multi-factorial screening for low-percentile use-rate accelerated reliability analysis

Besseris

Tsarouhas

2021

IJQRM

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PurposeThe study aims to provide a quick-and-robust multifactorial screening technique for early detection of statistically significant effects that could influence a product's life-time performance.Design/methodology/approachThe proposed method takes advantage of saturated fractional factorial designs for organizing the lifetime dataset collection process. Small censored lifetime data are fitted to the Kaplan–Meier model. Low-percentile lifetime behavior that is derived from the fitted model is used to screen for strong effects. A robust surrogate profiler is employed to furnish the predictions.FindingsThe methodology is tested on a difficult published case study that involves the eleven-factor screening of an industrial-grade thermostat. The tested thermostat units are use-rate accelerated to expedite the information collection process. The solution that is provided by this new method suggests as many as two active effects at the first decile of the data which improves over a solution provided from more classical methods.Research limitations/implicationsTo benchmark the predicted solution with other competing approaches, the results showcase the critical first decile part of the dataset. Moreover, prediction capability is demonstrated for the use-rate acceleration condition.Practical implicationsThe technique might be applicable to projects where the early reliability improvement is studied for complex industrial products.Originality/valueThe proposed methodology offers a range of features that aim to make the product reliability profiling process faster and more robust while managing to be less susceptible to assumptions often encountered in classical multi-parameter treatments.

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Section: Discussionmentioning

confidence: 99%

QUALITY PAPERA new rapid and robust multi-factorial screening for low-percentile use-rate accelerated reliability analysis

Besseris

Tsarouhas

2021

IJQRM

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“…Freeman and Vining [17] presented two-stage method to deal with subsampling. Wang et al [18] extended Freeman and Vining's method such that it can compute confidence interval of low percentile, but their research assumes that the shape parameter is constant. The clear future work is to analyze reliability data with subsampling under shape and scale parameters that are varied.…”

Section: Discussionmentioning

confidence: 99%

Accelerated Lifetime Data Analysis with a Nonconstant Shape Parameter

Niu

2015

Mathematical Problems in Engineering

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Accelerated life test is commonly used for the estimation of high-reliability product. In this paper, we present a simple and efficient approach to estimate the coefficients of acceleration models. Assuming that both scale and shape parameters of Weibull lifetime distribution vary with stress factors, we estimate the parameters of Weibull distribution using maximum likelihood method and reduce the bias of shape parameter estimator. Considering the heteroscedasticity, we compute the estimates of the coefficients of acceleration models through weighted least square method. Additionally, we obtain the confidence interval of low percentile via bootstrapping. We compare the proposed method with other methods using a real lifetime example. Finally, we study the performance of the proposed method by simulation. The simulation results show that our proposed method is effective.

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“…They applied a two-stage method that was previously used by Vining et al 55 to integrate the random effects into the analysis (the contribution of the newer paper is the bias correction for the shape parameter). Wang et al 63 propose an improved method of Freeman and Vining's two-stage approach to further reduce bias on estimates and calculate confidence intervals of low percentiles by bootstrapping.…”

Section: Application Of Doe On Alts: Examples and Challengesmentioning

confidence: 99%

Review on accelerated life testing plan to develop predictive reliability models for electronic components based on design‐of‐experiments

Indmeskine

Saintis

Kobi

2023

Quality & Reliability Eng

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Accelerated testing has been commonly used for the assessment of reliability of products or systems. In particular, it has been used to produce models for predicting the reliability of electronic components as a function of design and environmental parameters, or to qualify reliability. Extensive literature exists on different aspects ranging from defining type of stresses and type of censoring data, to optimizing test plans for efficient and relevant testing. On the other hand, design of experiments methodology is commonly used for studying the robustness of systems and for quality applications. This being said, combining both approaches, taking into account the system's physics of failure, is scarcely put into practice in a context of reliability prediction. Yet, this could significantly improve reliability prediction, especially in the case of electronic components which constantly go through technological progress with new parameters or properties to consider. After first presenting existing predictive reliability guides, models and parameters related to accelerated life testing, the purpose of this article is to provide a review of what has been done concerning the combination of such approaches.

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Bootstrapping Analysis of Lifetime Data with Subsampling

Cited by 16 publications

References 22 publications

QUALITY PAPERA new rapid and robust multi-factorial screening for low-percentile use-rate accelerated reliability analysis

QUALITY PAPERA new rapid and robust multi-factorial screening for low-percentile use-rate accelerated reliability analysis

Accelerated Lifetime Data Analysis with a Nonconstant Shape Parameter

Review on accelerated life testing plan to develop predictive reliability models for electronic components based on design‐of‐experiments

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