Bayesian reliability assessment of gear lifetime under fuzzy environments

This paper proposes a new method to determine the membership function of the estimates of the reliability function of multi-parameter lifetime distributions. An artificial neural network is used to approximate the calculation process of parameter estimation and reliability prediction. The genetic algorithm is used to find the boundary values of the membership function of the estimate of interest at any cut level. The effectiveness of the proposed method is illustrated with the gear lifetime that follows the lognormal distribution.