Supporting group maintenance through prognostics-enhanced dynamic dependability prediction

J. I. Aizpurua, V. M. Catterson, Y. Papadopoulos, F. Chiacchio, D. D'Urso

Research output: Contribution to journalSpecial issue

12 Citations (Scopus)

Abstract

Condition-based maintenance strategies adapt maintenance planning through the integration of online condition monitoring of assets. The accuracy and cost-effectiveness of these strategies can be improved by integrating prognostics predictions and grouping maintenance actions respectively. In complex industrial systems, however, effective condition-based maintenance is intricate. Such systems are comprised of repairable assets which can fail in different ways, with various effects, and typically governed by dynamics which include time-dependent and conditional events. In this context, system reliability prediction is complex and effective maintenance planning is virtually impossible prior to system deployment and hard even in the case of condition-based maintenance. Addressing these issues, this paper presents an online system maintenance method that takes into account the system dynamics. The method employs an online predictive diagnosis algorithm to distinguish between critical and non-critical assets. A prognostics-updated method for predicting the system health is then employed to yield well-informed, more accurate, condition-based suggestions for the maintenance of critical assets and for the group-based reactive repair of non-critical assets. The cost-effectiveness of the approach is discussed in a case study from the power industry.
LanguageEnglish
Pages171-188
Number of pages18
JournalReliability Engineering and System Safety
Volume168
Early online date21 Apr 2017
DOIs
Publication statusPublished - 31 Dec 2017

Fingerprint

Cost effectiveness
Planning
Online systems
Condition monitoring
Dynamical systems
Repair
Health
Industry

Keywords

  • prognostics
  • predictive maintenance
  • diagnostics
  • dynamic dependability
  • maintenance grouping

Cite this

Aizpurua, J. I. ; Catterson, V. M. ; Papadopoulos, Y. ; Chiacchio, F. ; D'Urso, D. / Supporting group maintenance through prognostics-enhanced dynamic dependability prediction. In: Reliability Engineering and System Safety. 2017 ; Vol. 168. pp. 171-188.
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Supporting group maintenance through prognostics-enhanced dynamic dependability prediction. / Aizpurua, J. I.; Catterson, V. M.; Papadopoulos, Y.; Chiacchio, F.; D'Urso, D.

In: Reliability Engineering and System Safety, Vol. 168, 31.12.2017, p. 171-188.

Research output: Contribution to journalSpecial issue

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T1 - Supporting group maintenance through prognostics-enhanced dynamic dependability prediction

AU - Aizpurua, J. I.

AU - Catterson, V. M.

AU - Papadopoulos, Y.

AU - Chiacchio, F.

AU - D'Urso, D.

PY - 2017/12/31

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