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dc.contributor.authorAdams, J
dc.contributor.authorSrinivasan, R
dc.contributor.authorParlikad, AKN
dc.contributor.authorDiaz, V
dc.contributor.authorCrespo Marquez, A
dc.date.accessioned2017-01-09T11:12:31Z
dc.date.available2017-01-09T11:12:31Z
dc.date.issued2016-12-16
dc.identifier.issn2405-8963
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/261774
dc.description.abstractAn asset’s risk is a useful indicator for determining optimal time of repair/replacement for assets in order to yield minimal operational cost of maintenance. For a successful asset management practice, asset-intensive organisations must understand the risk profile associated with their asset portfolio and how this will change over time. Unfortunately, in many risk-based asset management approaches, the only thing that is known to change in the risk profile of the asset is the likelihood (or probability) of failure. The criticality (or consequences of failure) of asset is assumed to be fixed and has considered as more or less a static quantity that is not updated with sufficient frequency as the operating environment changes. This paper proposes a dynamic criticality-based maintenance approach where asset criticality is modeled as a dynamic quantity and changes in asset’s criticality is used to optimize maintenance plans (e.g. determining the optimal repair time/replacement age for an asset over it life cycle period) to have a better risk management and cost savings. An illustrative example is used to demonstrate the effect of implementing dynamic criticality in determining the optimal time of repair for a bridge infrastructure. It is shown that capturing changes in the criticality of the bridge over time and using this understanding in the risk analysis of the bridge provided the opportunity for better maintenance planning resulting to reduction of the total risk.
dc.language.isoen
dc.publisherElsevier
dc.subjectdynamic criticality
dc.subjectasset management
dc.subjectasset risk profile
dc.subjectreplacement age
dc.subjectmaintenance plan
dc.titleTowards Dynamic Criticality-Based Maintenance Strategy for Industrial Assets
dc.typeConference Object
prism.endingPage107
prism.issueIdentifier28
prism.publicationDate2016
prism.publicationName3rd IFAC Workshop on Advanced Maintenance Engineering, Services and Technology AMEST 2016 - Biarritz, France, 19-21 October 2016
prism.startingPage103
prism.volume49
dc.identifier.doi10.17863/CAM.6988
dcterms.dateAccepted2016-06-29
rioxxterms.versionofrecord10.1016/j.ifacol.2016.11.018
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2016-12-16
dc.contributor.orcidParlikad, Ajith [0000-0001-6214-1739]
dc.identifier.eissn2405-8963
rioxxterms.typeConference Paper/Proceeding/Abstract
pubs.funder-project-idEuropean Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (645733)
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/K000314/1)
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/L010917/1)
pubs.conference-name3rd IFAC Workshop on Advanced Maintenance Engineering, Service and Technology
pubs.conference-start-date2016-10-19
cam.orpheus.successThu Nov 05 11:56:36 GMT 2020 - The item has an open VoR version.
pubs.conference-finish-date2016-10-21
rioxxterms.freetoread.startdate2100-01-01


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