Abstract

The sequential hard and soft failure mode, a typical failure phenomenon, involves degradation that starts after an initiation period. According to this situation, a random initiation effect is introduced to the normal degradation stage. Intuitively, a lifetime delayed degradation process (LDDP) provides a general framework for this typical complex failure mode. In the present study, general reliability inference approaches involving the joint likelihood function are developed for the LDDP with repeated measurements, according to the expectation maximization (EM) and stochastic EM algorithms, along with numerical simulations and practical application based on real data. Additionally, statistical inferences were obtained using a bootstrap method on the basis of parameter estimations. The proposed method was compared with the traditional two-step strategy under different sample sizes and inspection frequencies and exhibited enhanced performance.

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