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

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

2 Scopus Citations
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Original languageEnglish
Pages (from-to)480-489
Journal / PublicationComputers & Industrial Engineering
Online published6 Sep 2018
Publication statusPublished - Nov 2018


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.

Research Area(s)

  • Hard failure, Proportional hazards (PH), Remaining useful life (RUL) prediction, Wiener process