• DocumentCode
    3576555
  • Title

    A Bayesian accelerated degradation studies on nitrile rubber O-ring

  • Author

    Wang, L.Z. ; Wang, X.H. ; Li, Y.X. ; Fan, W.H.

  • Author_Institution
    Beihang Univ., Beijing, China
  • fYear
    2014
  • Firstpage
    292
  • Lastpage
    296
  • Abstract
    To research nitrile rubber O-rings´ lifetime with less time and resources, and to reach a more convincing and statistic result, an accelerated degradation testing (ADT) is designed, which consists of a 90C pre-test and a step-stress test with 70 °C, 80 °C, 90 °C and 100 °C. Compression sets obtained from ADT are analyzed as degradation data, and degradation models were fitted to data using Bayesian method which easily accommodated uncertainties in the test. Then a relationship model between degradation model and temperature was built with support vector machines (SVM), so the step-stress data can be converted to data at 25 °C and the O-rings´ 25 °C degradation models were obtained. Finally, with these models, nitrile rubber O-rings´ lifetimes were studied by Bayesian method, and the lifetime´s distribution was obtained, which predicted that the nitrile rubber O-ring will reach 60% compression set by 6.2 years at 25°C based on 97.5% confidence bands.
  • Keywords
    belief networks; life testing; production engineering computing; rubber; support vector machines; ADT; Bayesian accelerated degradation study; Bayesian method; SVM; accelerated degradation testing; compression set; confidence band; degradation data; degradation model; lifetime distribution; nitrile rubber O-ring lifetime; pre-test; step-stress data; step-stress test; support vector machines; temperature 100 degC; temperature 25 degC; temperature 70 degC; temperature 80 degC; temperature 90 degC; Analytical models; Bayes methods; Data models; Degradation; Rubber; Structural rings; Trajectory; Bayesian method; Nitrile rubber O-ring; accelerated degradation testing; degradation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management (IEEM), 2014 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/IEEM.2014.7058646
  • Filename
    7058646