SwePub
Sök i LIBRIS databas

  Extended search

onr:"swepub:oai:DiVA.org:ri-23632"
 

Search: onr:"swepub:oai:DiVA.org:ri-23632" > A Tool for Gas Turb...

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

A Tool for Gas Turbine Maintenance Scheduling

Bohlin, Markus (author)
RISE,SICS,Swedish Institute of Computer Science, SICS
Doganay, Kivanc (author)
RISE,SICS,Swedish Institute of Computer Science, SICS
Kreuger, Per (author)
RISE,Decisions, Networks and Analytics lab,Swedish Institute of Computer Science, SICS
show more...
Steinert, Rebecca (author)
RISE,Decisions, Networks and Analytics lab,Swedish Institute of Computer Science, SICS
Wärja, Mathias (author)
Siemens Industrial Turbomachinery AB
show less...
 (creator_code:org_t)
20
IEEE Computer Society, 2009
2009
English.
In: Proceedings of the Twenty-First Conference on Innovative Applications of Artificial Intelligence (IAAI'09). - : IEEE Computer Society. - 9781577354239
  • Conference paper (peer-reviewed)
Abstract Subject headings
Close  
  • We describe the implementation and deployment of a software decision support tool for the maintenance planning of gas turbines. The tool is used to plan the maintenance for turbines manufactured and maintained by Siemens Industrial Turbomachinery AB (SIT AB) with the goal to reduce the direct maintenance costs and the often very costly production losses during maintenance downtime. The optimization problem is formally defined, and we argue that feasibility in it 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 mixed integer linear 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, using our tool is expected to improve availability with up to 1% and reduce the number of planned maintenance days with 12%. Compared to a mixed integer programming approach, our algorithm not optimal, but is orders of magnitude 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.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences (hsv//eng)

Publication and Content Type

ref (subject category)
kon (subject category)

Find in a library

To the university's database

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

Find more in SwePub

By the author/editor
Bohlin, Markus
Doganay, Kivanc
Kreuger, Per
Steinert, Rebecc ...
Wärja, Mathias
About the subject
NATURAL SCIENCES
NATURAL SCIENCES
and Computer and Inf ...
Articles in the publication
Proceedings of t ...
By the university
RISE
Mälardalen University

Search outside SwePub

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Close

Copy and save the link in order to return to this view