Reliability estimation from lifetime testing data and degradation testing data with measurement error based on evidential variable and Wiener process

Highlights: • Evidential variable and evidence theory are introduced in Wiener process. • The measurement error is considered. • Lifetime and degradation testing data is used to estimate model parameters. • Difference of reliability degrees among the samples is considered. • The proposed method shows high accuracy in reliability prediction. Evidential variable has been applied in Wiener process based reliability estimation due to its powerful ability on parameter describing. The previously published evidential variable and stochastic process based reliability estimation methods neglect measurement error and cannot utilize lifetime testing data. However, in practical applications, lifetime testing is an important approach and measurement error is an inevitable factor. Hence, in this paper, the evidential variable and Wiener process based reliability estimation method is improved to handle the above issues. A simulation study is used to verify the effectiveness of the proposed reliability estimation method. Furthermore, an actual engineering case on piston pump is also studied to demonstrate the proposed method in engineering practice. It is concluded that utilizing lifetime testing data and considering measurement error can improve the accuracies of model parameter evaluation, degradation prediction, reliability estimation and etc., in evidential and Wiener process based reliability estimation.