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

Jianing Man, Qiang Zhou

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)480-489
Number of pages10
JournalComputers and Industrial Engineering
Volume125
DOIs
StatePublished - Nov 2018

Keywords

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

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

Fingerprint

Dive into the research topics of 'Prediction of hard failures with stochastic degradation signals using Wiener process and proportional hazards model'. Together they form a unique fingerprint.

Cite this