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dc.contributor.authorSchulze Spüntrup, Frederik
dc.contributor.authorLondono, Juan G.
dc.contributor.authorSkourup, Charlotte
dc.contributor.authorThornhill, Nina F.
dc.contributor.authorImsland, Lars Struen
dc.date.accessioned2019-03-13T15:05:23Z
dc.date.available2019-03-13T15:05:23Z
dc.date.created2019-01-10T12:52:41Z
dc.date.issued2018
dc.identifier.issn2405-8963
dc.identifier.urihttp://hdl.handle.net/11250/2589899
dc.description.abstractPhysical assets of the process industries include compressors, pumps, heat exchangers, batch reactors and many more. A large company that operates over many sites typically manages such assets in a coordinated way as an asset fleet. Strategic planning of maintenance and scheduling requires information about reliability, availability and maintainability of the assets in an asset fleet. The work presented in this paper assesses the reliability of centrifugal compressors based on the data collected in OREDA (Offshore and onshore REliability DAta project). The fault tree (a top-down approach to illustrate all subsystems in a system) has been modeled by focusing on the six main subsystems of the compressor (power transmission, compressor, control and monitoring, lubrication system, shaft seal system, and miscellaneous). All the maintainable items described in ISO 14224 are considered. Based on the failure rates collected in OREDA, the most prevalent failures have been identified via a Pareto analysis. The article gives recommendations which subsystems should be prioritized for maintenance and which types of faults are likely to occur. The main contribution of this paper is an industry-based statistical analysis of the failure mechanisms in centrifugal compressor systems. It is expected to improve the reliability of centrifugal compressor systems and can be implemented in industrial settings with a similar documentation system like OREDA.nb_NO
dc.language.isoengnb_NO
dc.publisherIFAC Papers Onlinenb_NO
dc.titleReliability improvement of compressors based on asset fleet reliability datanb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.pagenumber8nb_NO
dc.identifier.doihttps://doi.org/10.1016/j.ifacol.2018.06.380
dc.identifier.cristin1654057
dc.description.localcode2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.nb_NO
cristin.unitcode194,63,25,0
cristin.unitnameInstitutt for teknisk kybernetikk
cristin.ispublishedtrue
cristin.fulltextpostprint


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