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DC poleHodnotaJazyk
dc.contributor.authorPoór, Peter
dc.contributor.authorBasl, Josef
dc.date.accessioned2020-03-02T11:00:26Z-
dc.date.available2020-03-02T11:00:26Z-
dc.date.issued2019
dc.identifier.citationPOÓR, P., BASL, J. Predictive maintenance as an intelligent service in Industry 4.0. Journal of Systems Integration, 2019, roč. 10, č. 1, s. 3-10. ISSN 1804-2724.en
dc.identifier.issn1804-2724
dc.identifier.urihttp://hdl.handle.net/11025/36566
dc.format8 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherCzech Society of Systems Integrationen
dc.relation.ispartofseriesJournal of Systems Integrationen
dc.rights© Czech Society of Systems Integrationen
dc.titlePredictive maintenance as an intelligent service in Industry 4.0en
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedCurrent trend of digitization offers a whole new approach to providing maintenance services. From sensors to cloud, production data is a unique opportunity to declare a real added value for maintenance work. Predictive maintenance is one of the key elements of the Industry 4.0 concept associated with the emerging digitalization of industry. The purpose of predictive maintenance is to predict the status of production equipment and detect potential failure. Practical implementations of predictive maintenance are already found in a number of industrial companies, either in the partial form of maintenance according to technical condition, or in diagnostic maintenance, and in the form of actual equipment wear prediction and planned maintenance. Predictive maintenance extends routine health monitoring to look into the future of machines, offering options to increase efficiency and reduce overall operating costs. First part of this article presents the term of maintenance, its definition and role in the company. Also, various types of machinery maintenance types are presented. Next part of the article focuses on predictive maintenance.en
dc.subject.translatedpredictive maintenance, Industry 4.0, services, intelligent, CMMSen
dc.identifier.doi10.20470/jsi.v10i1.364
dc.type.statusPeer-revieweden
dc.identifier.obd43926935
dc.project.IDSGS-2018-031/Optimalizace parametrů udržitelného výrobního systémucs
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