The use of ARIMA models for reliability forecasting and analysis

Siu Lau Ho, M. Xie

Research output: Journal article publicationJournal articleAcademic researchpeer-review

168 Citations (Scopus)

Abstract

This paper investigates the approach to repairable system reliability forecasting based on the Autoregressive Integrated Moving Average (ARIMA) models. This time series technique makes very few assumptions and is very flexible. It is theoretically and statistically sound in its foundation and no a priori postulation of models is required when analysing failure data. An illustrative example on a mechanical system failures is presented. Comparison is also made with the traditional Duane model. It is concluded that ARIMA model is a viable alternative that gives satisfactory results in terms of its predictive performance.
Original languageEnglish
Pages (from-to)213-216
Number of pages4
JournalComputers and Industrial Engineering
Volume35
Issue number1-2
Publication statusPublished - 1 Jan 1998
Externally publishedYes

Keywords

  • ARIMA models
  • Duane model
  • Forecasting
  • MAD
  • Repairable system
  • Time series

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Information Systems and Management
  • Industrial and Manufacturing Engineering
  • Applied Mathematics

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