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Yili Hong, Haiming Ma, W. Meeker (2010)
A Tool for Evaluating Time-Varying-Stress Accelerated Life Test Plans With Log-Location-Scale DistributionsIEEE Transactions on Reliability, 59
Ying Shi, Luis Escobar, W. Meeker (2009)
Accelerated Destructive Degradation Test PlanningTechnometrics, 51
W. Nelson (1998)
Statistical Methods for Reliability Data
I Vaca‐Trigo, WQ Meeker (2009)
Service Life Prediction of Polymeric Materials
Chih-Chun Tsai, S. Tseng, Narayanaswamy Balakrishnan, Chien-Tai Lin (2013)
Optimal Design for Accelerated Destructive Degradation TestsQuality Technology & Quantitative Management, 10
Iliana Vaca-Trigo, W. Meeker (2009)
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The authors are to be commended for their important contributions to the area of reliability test planning. The planning of repeated measures accelerated degradation test (RMADT) is usually more challenging than the planning of accelerated life test (ALT) (e.g., , and ) and accelerated destructive degradation test (ADDT) (e.g., ). Different from ALT and ADDT models, for most RMADT models, one usually cannot obtain a closed‐form expression for the CDF of the induced time to failure T . Without closed‐form expressions, the test planning could be challenging. Based on linear models assumption (or models that can be transformed into linear models), the authors have done a great job in obtaining closed‐form expressions for the asymptotic variance of the estimator of the p quantile, t p , which is a key step in the test planning. We would like to discuss some ideas that leverage on numerical methods and modern computing power and how such ideas may be used to extend the current work to more general models. In general, the degradation‐path model can be nonlinear (e.g., the degradation model used in ) so that there is no closed‐form expressions for the CDF of T . Let D (
Applied Stochastic Models in Business and Industry – Wiley
Published: Jan 1, 2014
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