Maintenance optimization for degrading systems under installation constraints

Zhaojun Li, Murad Hamada, Haitao Liao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

To maintain a degrading system, many groups focusing on different tasks may be involved. It is often expected to allocate limited resources (e.g., the budget for technical training) among those maintenance groups to achieve the highest system performance. However, to allocate the resources and implement the maintenance tasks, the sequence of maintenance activities constrained by the system structure has to be considered. This paper provides a model for the maintenance of degrading systems under installation constraints. Based on this model, a nonlinear programming (NLP) model is presented in optimizing the allocation of maintenance resources. In particular, the failure replacement (FR) policy and opportunistic maintenance (OM) policy are considered for a two-module series system. The associated steady-state availabilities of the system are derived for the two cases. To demonstrate the approach in practical use, a numerical example for the FR maintenance policy is provided, and a significance analysis is conducted to provide more insight into the resource allocation issue.

Original languageEnglish (US)
Title of host publicationProceedings - 13th ISSAT International Conference on Reliability and Quality in Design
Pages285-289
Number of pages5
StatePublished - 2007
Externally publishedYes
Event13th ISSAT International Conference on Reliability and Quality in Design - Seattle, WA, United States
Duration: Aug 2 2007Aug 4 2007

Publication series

NameProceedings - 13th ISSAT International Conference on Reliability and Quality in Design

Other

Other13th ISSAT International Conference on Reliability and Quality in Design
Country/TerritoryUnited States
CitySeattle, WA
Period8/2/078/4/07

Keywords

  • Installation constraints
  • Resources allocation optimization
  • System availability

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality

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