Remaining useful life prediction of individual units subject to hard failure

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

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Author(s)

  • Qiang Zhou
  • Junbo Son
  • Shiyu Zhou
  • Xiaofeng Mao
  • Mutasim Salman

Detail(s)

Original languageEnglish
Pages (from-to)1017-1030
Journal / PublicationIIE Transactions (Institute of Industrial Engineers)
Volume46
Issue number10
Online published27 Jun 2014
Publication statusPublished - 2014

Abstract

To develop a cost-effective condition-based maintenance strategy, accurate prediction of the Remaining Useful Life (RUL) is the key. It is known that many failure mechanisms in engineering can be traced back to some underlying degradation processes. This article proposes a two-stage prognostic framework for individual units subject to hard failure, based on joint modeling of degradation signals and time-to-event data. The proposed algorithm features a low computational load, online prediction, and dynamic updating. Its application to automotive battery RUL prediction is discussed in this article as an example. The effectiveness of the proposed method is demonstrated through a simulation study and real data. © 2014 Copyright © "IIE".

Research Area(s)

  • hard failure, joint model, Remaining useful life prediction

Citation Format(s)

Remaining useful life prediction of individual units subject to hard failure. / Zhou, Qiang; Son, Junbo; Zhou, Shiyu; Mao, Xiaofeng; Salman, Mutasim.

In: IIE Transactions (Institute of Industrial Engineers), Vol. 46, No. 10, 2014, p. 1017-1030.

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