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dc.contributor.authorSpuntrup, F Schulze
dc.contributor.authorDalle Ave, G
dc.contributor.authorImsland, Lars Struen
dc.contributor.authorHarjunkoski, Iiro
dc.identifier.citationFrontiers in Applied Mathematics and Statistics. 2020, 6 1-12.en_US
dc.description.abstractDecision-making for maintenance of engineering assets is a common challenge in the process industry due to ongoing degradation. With an increasing company-size, this problem becomes more complex from an operational and computational point of view. This paper introduces a case study to the academic community that represents the problem of optimal decision-making in the context of large asset fleets. The case study poses a large fleet of offshore compressors for gas production with a specific network structure. Two exemplary discrete-time mixed integer linear programming models following the Resource Task Network framework are presented. They address asset deterioration due to effects such as fouling by suggesting specific maintenance actions as a set of different countermeasures. Novel enumerator formulations are a computationally efficient and extendable way to model the various degradation types. Results show the benefit of optimal maintenance in the application to asset fleets. The decision-support that is delivered by the scheduling and planning approach helps to determine which maintenance type should be conducted and at what time. The paper demonstrates the benefits of optimal (long-term) schedules for maintenance, but indicate at the same time the need for efficient algorithms in the context of large asset fleets, in contrast to common industrial case studies that are rather small-scale.en_US
dc.publisherFrontiers Mediaen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.titleOptimal Maintenance for Degrading Assets in the Context of Asset Fleets-A Case Studyen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.source.journalFrontiers in Applied Mathematics and Statisticsen_US
dc.description.localcodeCopyright © 2020 Schulze Spüntrup, Dalle Ave, Imsland and Harjunkoski. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.en_US

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