Abstract
Degradation modeling might be an alternative to the conventional life test in reliability assessment for high quality products. This paper develops a Bayesian approach to the step-stress accelerated degradation test. Reliability inference of the population is made based on the posterior distribution of the underlying parameters with the aid of Markov chain Monte Carlo method. Further sequential reliability inference on individual product under normal condition is also proposed. Simulation study and an illustrative example are presented to show the appropriateness of the proposed method.
Original language | English |
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Pages (from-to) | 1417-1424 |
Number of pages | 8 |
Journal | Quality and Reliability Engineering International |
Volume | 33 |
Issue number | 7 |
DOIs | |
State | Published - Nov 2017 |
Keywords
- Bayesian reliability inference
- MCMC
- gamma process
- step-stress accelerated degradation test