Vis enkel innførsel

dc.contributor.authorRødseth, Harald
dc.contributor.authorSchjølberg, Per
dc.contributor.authorEleftheriadis, Ragnhild
dc.contributor.authorMyklebust, Odd
dc.date.accessioned2019-02-21T15:10:49Z
dc.date.available2019-02-21T15:10:49Z
dc.date.created2018-12-03T15:30:57Z
dc.date.issued2018
dc.identifier.isbn9781351174657
dc.identifier.urihttp://hdl.handle.net/11250/2586859
dc.description.abstractWith the onset of Industry 4.0 several technological possibilities are offered in industry such as big data analytics, digital twin and augmented reality. The result is a more digitalised industry where faster and better decisions are possible. In long term this should provide a more reliable production with increased plant capacity and reduced downtime. To succeed with these possibilities a Cyber Physical Systems (CPS) must be established for the company. Currently, an own framework for CPS is under development and is expected to be tailored for Norwegian manufacturing. When building on the principle in Industry 4.0, big data capability with machine learning will be a fundamental model. Nevertheless, Industry 4.0 should also include other models for big data capability such as reliability modelling. The aim in this article is to present the current status of CPS framework and how it could be implemented in manufacturing industries. In particular, the article discusses and demonstrates the balance between machine learning and reliability engineering in big data analytics.nb_NO
dc.language.isoengnb_NO
dc.publisherTaylor & Francisnb_NO
dc.relation.ispartofSafety and Reliability – Safe Societies in a Changing World. Proceedings of ESREL 2018, June 17-21, 2018, Trondheim, Norway
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleReliability-based Cyber Plantnb_NO
dc.typeChapternb_NO
dc.description.versionpublishedVersionnb_NO
dc.identifier.doi10.1201/9781351174664
dc.identifier.cristin1638550
dc.description.localcodePublished by Taylor & Francis. Made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/nb_NO
cristin.unitcode194,64,92,0
cristin.unitnameInstitutt for maskinteknikk og produksjon
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


Tilhørende fil(er)

Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel

Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
Med mindre annet er angitt, så er denne innførselen lisensiert som Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal