Reliability assessment using accelerated degradation data based on time series model

A new method was proposed to evaluate reliability and predict lifetime using accelerated degradation data for high-reliability and long-life products. A general modeling approach based on time series for degradation path was analyzed. By introducing accelerated equations into analysis of accelerated degradation data, the calculation formula for reliability index and the evaluation algorithm for model parameters based on integral inference were presented. And taking the log-normal and Weibull distribution for example, the reliability confidence interval was given by fiducial inference. With the effective use of degradation data in different states as well as the advantages of strong self-adjustment with time series model, the robustness of product reliability assessment and lifespan prediction is improved. Moreover, based on accelerated degradation data, a novel technical way is provided to valuate reliability and predict lifetime. Finally, an example was presented to show the validity of this method.