Abstract
Accelerated Degradation Test (ADT) provides effective information for reliability assessment of performance characteristic of long-life and high-reliability products. Existing typical models and analysis usually assume that the products under test are of high consistency level during the manufacturing process, which implies that the individual differences of the initial performance of the products can be ignored. However, this may not be the case, and the initial performance of the test units may have great impact on the subsequent degradation rate. Both positively related and negatively related are possible. This phenomenon can be observed in many different examples, such as the performance of inkjet printer heads. It means that reliability-related information can be obtained before accelerated degradation test. The study considers the impact of initial performance on the reliability assessment. Based on the existing typical accelerated degradation test model and analysis process, this paper introduces the initial information of the products to carry out reliability assessment and test plan. The asymptotic variance of a lifetime quantile at normal use conditions is considered to obtain the optimum test plan. Results show that the initial performance of the test units can be made use of to improve the accuracy of estimators. The impact of fisher information has been taken into account.
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Chow, S.C.: Advanced Linear Models: Theory and Applications. Routledge, New York (2018)
Kiefer, J.: Optimum experimental designs. J. Roy. Stat. Soc.: Ser. B (Methodol.) 21(2), 272–304 (1959)
Klein, A., Mélard, G., Zahaf, T.: Construction of the exact fisher information matrix of gaussian time series models by means of matrix differential rules. Linear Algebra Appl. 321(1), 209–232 (2000)
Li, L.: Design of accelerated degradation test. The university of Chinese Academy of Sciences (2013)
Lu, J.: Degradation processes and related reliability models. McGill University Montreal, Canada (1995)
Lu, J.C., Park, J., Yang, Q.: Statistical inference of a time-to-failure distribution derived from linear degradation data. Technometrics 39(4), 391–400 (1997)
Marseguerra, M., Zio, E., Cipollone, M.: Designing optimal degradation tests via multi-objective genetic algorithms. Reliab. Eng. Syst. Saf. 79(1), 87–94 (2003)
Meeker, W.Q., Escobar, L.A.: Statistical Methods for Reliability Data. Wiley, New York (2014)
Sheng-Tsaing, T., Hong-Fwu, Y.: A termination rule for degradation experiments. IEEE Trans. Reliab. 46(1), 130–133 (1997)
Wang, X., Xu, D.: An inverse gaussian process model for degradation data. Technometrics 52(2), 188–197 (2010)
Weaver, B.P., Meeker, W.Q., Escobar, L.A., Wendelberger, J.: Methods for planning repeated measures degradation studies. Technometrics 55(2), 122–134 (2013)
Whitmore, G.A.: Estimation of wiener diffusion parameters using process measurements subject to error. In: Jewell, N.P., Kimber, A.C., Lee, M.L.T., Whitmore, G.A. (eds.) Lifetime Data: Models in Reliability and Survival Analysis, pp. 363–369. Springer, Heidelberg (1996). https://doi.org/10.1007/978-1-4757-5654-8_47
Wu, S.J., Shao, J.: Reliability analysis using the least squares method in nonlinear mixed-effect degradation models. Stat. Sin. 9(3), 855–877 (1999)
Ye, Z.S., Hu, Q., Yu, D.: Strategic allocation of test units in an accelerated degradation test plan. J. Qual. Technol. 51(1), 64–80 (2019)
Yu, H.F., Tseng, S.T.: Designing a degradation experiment. Naval Res. Logistics (NRL) 46(6), 689–706 (1999)
Acknowledgements
The authors are honored to get invitation for contributing a book chapter to celebrate the 80th birthday of Professor Jinhua Cao. The authors are also thankful for the reviewers’ comments and suggestions.
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Wang, C., Hu, Q., Yu, D. (2019). Assessment of Reliability in Accelerated Degradation Testing with Initial Status Incorporated. In: Li, QL., Wang, J., Yu, HB. (eds) Stochastic Models in Reliability, Network Security and System Safety. JHC80 2019. Communications in Computer and Information Science, vol 1102. Springer, Singapore. https://doi.org/10.1007/978-981-15-0864-6_10
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DOI: https://doi.org/10.1007/978-981-15-0864-6_10
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