Journal
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY
Volume 28, Issue 10, Pages 3937-3946Publisher
KOREAN SOC MECHANICAL ENGINEERS
DOI: 10.1007/s12206-014-0904-x
Keywords
Bayesian approach; Degradation tests; Inverse Gaussian process; Optimal design; Prior distribution
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Funding
- National Natural Science Foundation of China [11272082]
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The inverse Gaussian process is recently introduced as an attractive and flexible stochastic process for degradation modeling. This process has been demonstrated as a valuable complement for models that are developed on the basis of the Wiener and gamma processes. We investigate the optimal design of the degradation tests on the basis of the inverse Gaussian process. In addition to an optimal design with pre-estimated planning values of model parameters, we also address the issue of uncertainty in the planning values by using the Bayesian method. An average pre-posterior variance of reliability is used as the optimization criterion. A trade-off between sample size and number of degradation observations is investigated in the degradation test planning. The effects of priors on the optimal designs and on the value of prior information are also investigated and quantified. The degradation test planning of a GaAs Laser device is performed to demonstrate the proposed method.
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