• DocumentCode
    3438383
  • Title

    Notice of Retraction
    A study on Bayesian design of degradation tests with the inverse Gaussian processes

  • Author

    Weiwen Peng ; Hong-Zhong Huang ; Zhonglai Wang ; Yu Liu ; Shun-Peng Zhu

  • Author_Institution
    Sch. of Mech., Electron., & Ind. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • fYear
    2013
  • fDate
    15-18 July 2013
  • Firstpage
    870
  • Lastpage
    872
  • Abstract
    Notice of Retraction

    After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

    We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

    The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

    Besides the Wiener and Gamma processes, the inverse Gaussian (IG) process is recently proposed as an attractive yet flexible family for degradation modeling. Since degradation test depends heavily on the degradation model chosen for a product´s degradation process, we discuss the optimal design for degradation tests specifically based on the IG process. Other than an optimal design with pre-estimated planning values of model parameters, we handle the situation with uncertainty in the planning values using the Bayesian method. The inspection frequency and measurement numbers are included as design variables. The average pre-posterior variance of reliability is defined as the optimization criterion. An application to the degradation test planning of a GaAs Laser device is used to demonstrate the proposed method.
  • Keywords
    Bayes methods; Gaussian processes; gamma distribution; inspection; life testing; planning; reliability; Bayesian design; Bayesian method; IG process; Wiener process; degradation modeling; degradation test planning; degradation tests; gallium arsenide laser device; gamma process; inspection frequency; inverse Gaussian processes; measurement numbers; model parameters; optimal design; optimization criterion; preestimated planning values; preposterior variance; product degradation process; reliability; Bayes methods; Degradation; Gallium arsenide; Gaussian processes; Planning; Reliability engineering; Bayesian method; degradation test; inverse Gaussian process; optimal design;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE), 2013 International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4799-1014-4
  • Type

    conf

  • DOI
    10.1109/QR2MSE.2013.6625707
  • Filename
    6625707