Prediction of the failure interval with maximum power based on the remaining useful life distribution

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

7 Scopus Citations
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Author(s)

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

Detail(s)

Original languageEnglish
Pages (from-to)1072-1087
Journal / PublicationIIE Transactions (Institute of Industrial Engineers)
Volume47
Issue number10
Online published18 May 2015
Publication statusPublished - 2015

Abstract

Prognosis of the Remaining Useful Life (RUL) of a unit or system plays an important role in system reliability analysis and maintenance decision making. One key aspect of the RUL prognosis is the construction of the best prediction interval for failure occurrence. The interval should have a reasonable length and yield the best prediction power. In current practice, the center-based interval and traditional confidence interval are widely used. Although both are easy to construct, they do not provide the best prediction performance. In this article, we propose a new scheme, the Maximum Power Interval (MPI), for estimating the interval with maximum prediction power. The MPI guarantees the best prediction power under a given interval length. Some technical challenges involved in the MPI method were resolved using the maximum entropy principle and truncation method. A numerical simulation study confirmed that the MPI has better prediction power than other prediction intervals. A case study using a real industry data set was conducted to illustrate the capability of the MPI method.

Research Area(s)

  • interval prediction, maximum entropy, prediction power, Remaining useful life

Citation Format(s)