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Inverse Gaussian process models for degradation analysis: A Bayesian perspective

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  • Peng, Weiwen
  • Li, Yan-Feng
  • Yang, Yuan-Jian
  • Huang, Hong-Zhong
  • Zuo, Ming J.

Abstract

This paper conducts a Bayesian analysis of inverse Gaussian process models for degradation modeling and inference. Novel features of the Bayesian analysis are the natural manners for incorporating subjective information, pooling of random effects information among product population, and a straightforward way of coping with evolving data sets for on-line prediction. A general Bayesian framework is proposed for degradation analysis with inverse Gaussian process models. A simple inverse Gaussian process model and three inverse Gaussian process models with random effects are investigated using Bayesian method. In addition, a comprehensive sensitivity analysis of prior distributions and sample sizes is carried out through simulation. Finally, a classic example is presented to demonstrate the applicability of the Bayesian method for degradation analysis with the inverse Gaussian process models.

Suggested Citation

  • Peng, Weiwen & Li, Yan-Feng & Yang, Yuan-Jian & Huang, Hong-Zhong & Zuo, Ming J., 2014. "Inverse Gaussian process models for degradation analysis: A Bayesian perspective," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 175-189.
    • Handle: RePEc:eee:reensy:v:130:y:2014:i:c:p:175-189
    DOI: 10.1016/j.ress.2014.06.005
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    References listed on IDEAS

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    1. Santanu Chakraborty & Nagi Gebraeel & Mark Lawley & Hong Wan, 2009. "Residual-life estimation for components with non-symmetric priors," IISE Transactions, Taylor & Francis Journals, vol. 41(4), pages 372-387.
    2. Wang, Lizhi & Pan, Rong & Li, Xiaoyang & Jiang, Tongmin, 2013. "A Bayesian reliability evaluation method with integrated accelerated degradation testing and field information," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 38-47.
    3. Valen Johnson, 2004. "A Bayesian Chi-Squared Test for Goodness of Fit," The University of Michigan Department of Biostatistics Working Paper Series 1000, Berkeley Electronic Press.
    4. Bae, Suk Joo & Kuo, Way & Kvam, Paul H., 2007. "Degradation models and implied lifetime distributions," Reliability Engineering and System Safety, Elsevier, vol. 92(5), pages 601-608.
    5. Guida, M. & Pulcini, G., 2013. "The inverse Gamma process: A family of continuous stochastic models for describing state-dependent deterioration phenomena," Reliability Engineering and System Safety, Elsevier, vol. 120(C), pages 72-79.
    6. Haitao Liao & Elsayed A. Elsayed, 2006. "Reliability inference for field conditions from accelerated degradation testing," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(6), pages 576-587, September.
    7. Pan, Zhengqiang & Balakrishnan, Narayanaswamy, 2011. "Reliability modeling of degradation of products with multiple performance characteristics based on gamma processes," Reliability Engineering and System Safety, Elsevier, vol. 96(8), pages 949-957.
    8. Wang, Wenbin, 2012. "A simulation-based multivariate Bayesian control chart for real time condition-based maintenance of complex systems," European Journal of Operational Research, Elsevier, vol. 218(3), pages 726-734.
    9. Mohammadian, S. Hossein & Aït-Kadi, Daoud & Routhier, François, 2010. "Quantitative accelerated degradation testing: Practical approaches," Reliability Engineering and System Safety, Elsevier, vol. 95(2), pages 149-159.
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