Reliability Assessment from Performance Degradation Data Based on Time Series Model
To evaluate reliability and predict lifetime for products from performance degradation data, a new method based on degradation measure distribution is proposed. Assume that the degradation measure follows the same distribution family but its parameters may change with time, dynamic data of time-dependent parameters can be modeled by autoregressive integrated moving average (ARIMA), and the corresponding reliability functions are then developed. The method has the advantages of strong selfadjustment with time series model for stochastic process and high precision for prediction, and effectively overcomes human factors influences caused by the hypothesis of time-dependent parameter distributions, so the method has better robustness. An example of reliability assessment is given at last, which can illustrate the validity and feasibility of the presented method.
Degradation Measure Distribution Time-Dependent Parameters Time Series Model Reliability Assessment
YOU Qi MA Xiaobing ZHAO Yu
Department of System Engineering of Engineering Technology, Beijing University of Aeronautics and Astronautics, Beijing, P.R.China, 100083
国际会议
2008年国际应用统计学术研讨会(2008 International Institute of Applied Statistics Studies)
烟台
英文
1-5
2008-08-14（万方平台首次上网日期，不代表论文的发表时间）