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Optimal design of multiple stresses accelerated life test plan based on transforming the multiple stresses to single stress
Chinese Journal of Mechanical Engineering volume 27, pages 1125–1132 (2014)
Abstract
For planning optimum multiple stresses accelerated life test plans, a commonly followed guiding principle is that all parameters of the life-stress relationship should be estimated, and the number of the stress level combinations must be no less than the number of parameters of the life-stress relationship. However, the general objective of an accelerated life test(ALT) is to assess the p-th quantile of the product life distribution under normal stress. For this objective, estimating all model parameters is not necessary, and this will increase the cost of test. Based on the theoretical conclusion that the stress level combinations of the optimum multiple stresses ALT plan locate on a straight line through the origin of coordinate, it is proposed that a design idea of planning the optimum multiple stresses ALT plan through transforming the problem of designing an optimum multiple stresses ALT plan to designing an optimum single stress ALT plan. Moreover, a method of planning the optimum multiple stresses ALT plan which can avoid estimating all model parameters is established. An example shows that, the proposed plan which only has two stress level combinations could achieve an accuracy no less than the traditional plan, and save the test time and cost on one stress level combination at least; when the actual product life is less than the design value, even the deviation of the model initial parameters value is up to 20%, the variance of the estimation of the p-th quantile of the proposed plan is still smaller than the traditional plans approximately 25%. A design method is provided for planning the optimum multiple stresses ALT which uses the statistical optimum degenerate test plan as the optimum multiple stresses accelerated life test plan.
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Supported by National Natural Science Foundation of China(Grant Nos. 50935002, 51075370, 51105341, 51275480, 51305402), Zhejiang Provincial Natural Science Foundation of China(Grant No. Y1100777), Zhejiang Provincial Key Science and Technology Innovation Team(Grant No. 2010R50005), and Key Program of Science and Technology of Sichuan Provincial Education Department, China(Grant No. 14ZA0005)
GAO Liang, born in 1981, is a docent at College of Mechanical and Electrical Engineering, Sichuan Agricultural University, China. He received his PhD degree from Zhejiang University, China, in 2012. His research interests include modeling and statistical analyzing of accelerated life testing, design of testing plans, and reliability estimate.
CHEN Wenhua, born in 1963, is currently a professor at Zhejiang University and Zhejiang Sci-Tech University, and the director of Zhejiang Province’s Key Laboratory for Reliability Technology of Mechanical & Electrical Products, Zhejiang Sci-Tech University, China. He received his PhD degree in mechanical manufacture from Zhejiang University, China, in 1997. He is mainly engaged in the research of reliability design, test, and statistical analysis.
QIAN Ping, born in 1983, is an associate professor at School of Mechanical and Automatic Control, Zhejiang Sci-Tech University, China. She received her PhD degree from Zhejiang University, China, in 2010. Her research interests include modeling and statistical analyzing of accelerated life testing, design of testing plans, and reliability estimate.
PAN Jun, born in 1974, is a professor at School of Mechanical and Automatic Control, Zhejiang Sci-Tech University, China. He received his PhD degree from Zhejiang Sci-Tech University, China, in 2011. His research interests include modeling and statistical analyzing of accelerated degradation testing, design of testing plans, and reliability estimate.
HE Qingchuan, born in 1984, is a docent at School of Mechanical and Automatic Control, Zhejiang Sci-Tech University, China. He received his PhD degree from Zhejiang Sci-Tech University, China, in 2013. He is mainly engaged in the research of reliability design and test, and system reliability.
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Gao, L., Chen, W., Qian, P. et al. Optimal design of multiple stresses accelerated life test plan based on transforming the multiple stresses to single stress. Chin. J. Mech. Eng. 27, 1125–1132 (2014). https://doi.org/10.3901/CJME.2014.0826.141
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DOI: https://doi.org/10.3901/CJME.2014.0826.141