Application of degradation growth model in the estimation of Bayesian system reliability

References

• Abedin, Z., and M. Karson. 1993. Classical and Bayesian estimation of exponential reliability under time censoring with replacement: Classical and Bayesian estimation. Communications in Statistics - Simulation and Computation 22 (2):471–96. doi:10.1080/03610919308813104.
   Web of Science ®Google Scholar
• Al-Haj, E. M., O. Eidous, and G. Kmail. 2009. Estimating percentiles of time-to-failure distribution obtained from a linear degradation model using kernel density method. Communications in Statistics - Simulation and Computation 38 (9):1811–22. doi:10.1080/03610910903145130.
   Web of Science ®Google Scholar
• Bae, S. J., and P. H. Kvam. 2010. Degradation models. Encyclopedia of Statistics in Quality and Reliability.
   Google Scholar
• Bhuyan, P., and A. Dewanji. 2017. Reliability computation under dynamic stress–strength modeling with cumulative stress and strength degradation. Communications in Statistics - Simulation and Computation 46 (4):2701–13. doi:10.1080/03610918.2015.1057288.
   Web of Science ®Google Scholar
• Chiao, C., and M. Hamada. 1995. Experiments with degradation data for improving reliability and for achieving robust reliability. IIQP Research Report.
   Google Scholar
• Chiao, C., and M. Hamada. 1996. Using degradation data from an experiment to achieve robust reliability for light emitting diodes. Quality and Reliability Engineering International 12 (2):89–94. doi:10.1002/(SICI)1099-1638(199603)12:2<89::AID-QRE997>3.0.CO;2-D.
   Web of Science ®Google Scholar
• Efron, B., and R. J. Tibshirani. 1993. “The jackknife” An introduction to the bootstrap. US: Springer 141–52.
   Google Scholar
• Freitas, M. A., E. A. Colosimo, T. R. d Santos, and M. C. Pires. 2010. Reliability assessment using degradation models: Bayesian and classical approaches. Pesquisa Operacional 30 (1):194–219. doi:10.1590/S0101-74382010000100010.
   Google Scholar
• Freitas, M. A., M. L. G. de Toledo, E. A. Colosimo, and M. C. Pires. 2009. Using degradation data to assess reliability: A case study on train wheel degradation. Quality and Reliability Engineering International 25 (5):607–29. doi:10.1002/qre.995.
   Web of Science ®Google Scholar
• Freitas, M. A., T. R. dos Santos, M. C. Pires, and E. A. Colosimo. 2010. A closer look at degradation models: Classical and Bayesian approaches. Advances in Degradation Modeling, 2721–39. Springer.
   Google Scholar
• Gebraeel, N. Z., M. A. Lawley, R. Li, and J. K. Ryan. 2005. Residual-life distributions from component degradation signals: A Bayesian approach. IIE Transactions 37 (6):543–57. doi:10.1080/07408170590929018.
   Web of Science ®Google Scholar
• Gorjian, N., L. Ma, M. Mittinty, P. Yarlagadda, and Y. Sun. 2010. A review on degradation models in reliability analysis. In Engineering Asset Lifecycle Management, 369–84. London: Springer.
   Google Scholar
• Hamada, M. 2005. Using degradation data to assess reliability. Quality Engineering 17 (4):615–20. doi:10.1080/08982110500225489.
   Google Scholar
• Kumar, M., and P. N. Bajeel. 2017. Introduction to system reliability evaluation through Bayesian approach. Mathematical concepts and application in mechanical engineering and machatronics, 130–53. IGI Global.
   Google Scholar
• Lawless, J., and M. Crowder. 2004. Covariates and random effects in a gamma process model with application to degradation and failure. Lifetime Data Analysis 10 (3):213–27. doi:10.1023/B:LIDA.0000036389.14073.dd.
   PubMed Web of Science ®Google Scholar
• Lu, C. J., and W. O. Meeker. 1993. Using degradation measures to estimate a time-to-failure distribution. Technometrics 35 (2):161–74. doi:10.1080/00401706.1993.10485038.
   Web of Science ®Google Scholar
• Lin, J., M. Asplund, and A. Parida. 2014. Reliability analysis for degradation of locomotive wheels using parametric Bayesian approach. Quality and Reliability Engineering International 30 (5):657–67. doi:10.1002/qre.1518.
   Web of Science ®Google Scholar
• Murray, W. P. 1993. Archival life expectancy of 3M magneto-optic media. Journal of the Magnetics Society of Japan 17 (S_1_MORIS_92):S1_309–314. doi:10.3379/jmsjmag.17.S1_309.
   Google Scholar
• Meeker, W. Q., L. A. Escobar, and Y. Hong. 2009. Using accelerated life tests results to predict product field reliability. Technometrics 51 (2):146–61. doi:10.1198/TECH.2009.0016.
   Web of Science ®Google Scholar
• Nakagawa, T. 2007. Shock and damage models in reliability theory. London: Springer Science & Business Media.
   Google Scholar
• Nikulin, M. S., N. Limnios, N. Balakrishnan, W. Kahle, and C. Huber-Carol. 2010. Advances in degradation modeling. Boston: Birhuser.
   Google Scholar
• Park, C., and W. J. Padgett. 2005. Accelerated degradation models for failure based on geometric Brownian motion and gamma processes. Lifetime Data Analysis 11 (4):511–27. doi:10.1007/s10985-005-5237-8.
   PubMed Web of Science ®Google Scholar
• Tseng, S., M. Hamada, and C. Chiao. 1995. Using degradation data to improve fluorescent lamp reliability. Journal of Quality Technology 27 (4):363–9. doi:10.1080/00224065.1995.11979618.
   Web of Science ®Google Scholar
• Wu, S., and J. Shao. 1999. Reliability analysis using the least squares method in nonlinear mixed-effect degradation models. Statistica Sinica :855–77.
   Web of Science ®Google Scholar
• Wu, S., and T. Tsai. 2000. Estimation of time-to-failure distribution derived from a degradation model using fuzzy clustering. Quality and Reliability Engineering International 16 (4):261–7. doi:10.1002/1099-1638(200007/08)16:4<261::AID-QRE333>3.0.CO;2-3.
   Web of Science ®Google Scholar
• Yacout, A. M., S. Salvatores, and Y. Orechwa. 1996. Degradation analysis estimates of the time-to-failure distribution of irradiated fuel elements. Nuclear Technology 113 (2):177–89. doi:10.13182/NT96-A35187.
   Web of Science ®Google Scholar