Evaluation of proactive maintenance policies on a stochastically dependent hidden multi-component system using DBNs

Basit Öğe Kaydı
dc.authorid0000-0002-7414-2330
dc.authorid0000-0002-3835-7684
dc.contributor.authorÖzgür Ünlüakın, Demeten_US
dc.contributor.authorTürkali, Busenuren_US
dc.date.accessioned2021-03-29T08:32:27Z
dc.date.available2021-03-29T08:32:27Z
dc.date.issued2021-07
dc.departmentIşık Üniversitesi, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.departmentIşık University, Faculty of Engineering, Department of Industrial Engineeringen_US
dc.descriptionThis research is supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under grant: 117M587.en_US
dc.description.abstractIn complex systems with stochastically dependent components which are not observed directly, determining an effective maintenance policy is a difficult task. In this paper, a dynamic Bayesian network based maintenance decision framework is proposed to evaluate proactive maintenance policies for such systems. Two preventive and one predictive maintenance strategies from a cost perspective are designed for multi-component dependable systems which aim to reduce maintenance cost while increasing system reliability at the same time. Tabu procedure is employed to avoid repetitive similar actions. The performances of the policies are compared with a reactive maintenance strategy and also with each other using different strategy parameters on a real life system confronted in thermal power plants for six different scenarios. The scenarios are designed considering different structures of system dependability and reactive cost. The results show that the threshold based maintenance which is the predictive strategy gives the minimum cost and maintenance number in almost all scenarios.en_US
dc.description.sponsorshipTürkiye Bilimsel ve Teknolojik Arastırma Kurumu (TÜBİTAK)en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationÖzgür Ünlüakın, D. & Türkali, B. (2021). Evaluation of proactive maintenance policies on a stochastically dependent hidden multi-component system using DBNs. Reliability Engineering and System Safety, 211, 1-14. doi:10.1016/j.ress.2021.107559en_US
dc.identifier.doi10.1016/j.ress.2021.107559
dc.identifier.endpage14
dc.identifier.issn0951-8320
dc.identifier.issn1879-0836
dc.identifier.scopus2-s2.0-85102866969
dc.identifier.scopusqualityQ1
dc.identifier.startpage1
dc.identifier.urihttps://hdl.handle.net/11729/3105
dc.identifier.urihttp://dx.doi.org/10.1016/j.ress.2021.107559
dc.identifier.volume211
dc.identifier.wosWOS:000663909700008
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakScience Citation Index Expanded (SCI-EXPANDED)en_US
dc.institutionauthorÖzgür Ünlüakın, Demeten_US
dc.institutionauthorTürkali, Busenuren_US
dc.institutionauthorid0000-0002-7414-2330
dc.institutionauthorid0000-0002-3835-7684
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherElsevier Ltden_US
dc.relation.ispartofReliability Engineering and System Safetyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDynamic Bayesian networksen_US
dc.subjectMulti-component hidden systemsen_US
dc.subjectProactive maintenanceen_US
dc.subjectStochastic dependencyen_US
dc.subjectTabu procedureen_US
dc.subjectCostsen_US
dc.subjectPreventive maintenanceen_US
dc.subjectStochastic systemsen_US
dc.subjectTabu searchen_US
dc.subjectThermoelectric power plantsen_US
dc.subjectMaintenance decisionsen_US
dc.subjectMaintenance policyen_US
dc.subjectMaintenance strategiesen_US
dc.subjectMulti-component hidden systemen_US
dc.subjectMulti-component systemsen_US
dc.subjectNetwork-baseden_US
dc.subjectStochastic dependenciesen_US
dc.subjectBayesian networksen_US
dc.subjectOpportunistic maintenanceen_US
dc.subjectPredictive maintenanceen_US
dc.subjectControl charten_US
dc.subjectOptimizationen_US
dc.subjectStrategiesen_US
dc.subjectComponentsen_US
dc.subjectFailureen_US
dc.subjectModelen_US
dc.titleEvaluation of proactive maintenance policies on a stochastically dependent hidden multi-component system using DBNsen_US
dc.typeArticleen_US
dspace.entity.typePublication

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim Yok
İsim:
3105.pdf
Boyut:
3.23 MB
Biçim:
Adobe Portable Document Format
Açıklama:
Publisher's Version
İndir
Lisans paketi
Listeleniyor 1 - 1 / 1
Küçük Resim Yok
İsim:
license.txt
Boyut:
1.44 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama:
İndir

Koleksiyon

Makale Koleksiyonu | Endüstri Mühendisliği Bölümü
Scopus İndeksli Yayınlar Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu