Prediction of hard failures with stochastic degradation signals using Wiener process and proportional hazards model

In this paper, we propose a method to predict the remaining useful life (RUL) of systems subject to hard failures, which are probabilistically linked to system degradation signals (health indictors). A joint modeling framework is adopted to incorporate both the degradation signals and time-to-event data. In the joint model, a Wiener process with drift is used to model stochastic degradation signals, and the proportional hazards (PH) model with nonparametric baseline hazard is used to model time-to-event data. With proposed joint model and Markovian property of the Wiener process, system RUL could be predicted. Extensive simulations and a case study are conducted to demonstrate the performance of the proposed method.