Reliability Assessment and Remaining Useful Life Prediction Based on the Inverse Gaussian Step-Stress Accelerated Degradation Data

An inverse Gaussian step-stress accelerated degradation test model was put forward, in which the drift and shape parameters are functions of the stress levels. The confidence intervals of the model parameters and some reliability measures, such as the mean lifetime, the reliability function, and the p th percentile under the rated usage stress, are presented. The online and offline remaining useful life prediction intervals under the rated usage stress level are also acquired. Simulation technologies are used to examine the effect of the presented interval estimation approaches. Simulation results manifest that the presented interval estimation method performs well in all cases. Finally, a case study is provided to illustrate our inference approaches.