Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Searching for Gas Turbine Maintenance Schedules
RISE - Research Institutes of Sweden, ICT, SICS.ORCID iD: 0000-0003-1597-6738
RISE, Swedish ICT, SICS.
RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.ORCID iD: 0000-0002-9331-0352
RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.ORCID iD: 0000-0002-5893-7774
Show others and affiliations
2010 (English)In: AI Magazine, Vol. 31, no 1, p. 21-36Article in journal (Refereed) Published
Abstract [en]

Preventive maintenance schedules occurring in industry are often suboptimal with regard to maintenance coal-location, loss-of-production costs and availability. We describe the implementation and deployment of a software decision support tool for the maintenance planning of gas turbines, with the goal of reducing the direct maintenance costs and the often costly production losses during maintenance downtime. The optimization problem is formally defined, and we argue that the feasibility version is NP-complete. We outline a heuristic algorithm that can quickly solve the problem for practical purposes and validate the approach on a real-world scenario based on an oil production facility. We also compare the performance of our algorithm with results from using integer programming, and discuss the deployment of the application. The experimental results indicate that downtime reductions up to 65% can be achieved, compared to traditional preventive maintenance. In addition, the use of our tool is expected to improve availability with up to 1% and reduce the number of planned maintenance days by 12%. Compared to a integer programming approach, our algorithm is not optimal, but is much faster and produces results which are useful in practice. Our test results and SIT AB’s estimates based< on operational use both indicate that significant savings can be achieved by using our software tool, compared to maintenance plans with fixed intervals.

Place, publisher, year, edition, pages
aaai.org , 2010, 6. Vol. 31, no 1, p. 21-36
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:ri:diva-23743OAI: oai:DiVA.org:ri-23743DiVA, id: diva2:1042820
Available from: 2016-10-31 Created: 2016-10-31 Last updated: 2018-01-14Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

http

Search in DiVA

By author/editor
Bohlin, MarkusKreuger, PerSteinert, Rebecca
By organisation
SICSSICSDecisions, Networks and Analytics lab
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 11 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
v. 2.34.0