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Remote maintenance support with the aid of cyber-physical systems and cloud technology
VTT Tech Res Ctr Finland Ltd, Finland.
Mondragon Univ, Spain.
Mondragon Univ, Spain.
Polytech Inst Porto, Portugal.
Vise andre og tillknytning
2018 (engelsk)Inngår i: Proceedings of the Institution of mechanical engineers. Part I, journal of systems and control engineering, ISSN 0959-6518, E-ISSN 2041-3041, Vol. 232, nr 6, s. 784-794Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

This article discusses how a business model based on traditional maintenance can evolve to generate servitization strategies, with the help of remote maintenance support. The application of cyber-physical systems and cloud technologies play a key role for such maintenance purposes. In fact, the utilization of large quantities of data collected on machines and their processing by means of advanced techniques such as machine learning enable novel techniques for condition-based maintenance. New sensor solutions that could be used in maintenance and interaction with cyber-physical systems are also presented. Here, data models are an important part of these techniques because of the huge amounts of data that are produced and should be processed. These data models have been used in a real case, supported by the Machinery Information Management Open System Alliance Open System Architecture for Condition-Based Maintenance standard architecture, for streamlining the modeling of collected data. In this context, an industrial use case is described, to enlighten the application of the presented concepts in a working pilot. Finally, current and future directions for application of cyber-physical systems and cloud technologies to maintenance are discussed.

sted, utgiver, år, opplag, sider
Sage Publications, 2018. Vol. 232, nr 6, s. 784-794
Emneord [en]
Cyber-physical systems, Internet of things, microelectromechanical systems, Machinery Information Management Open System Alliance, Open System Architecture for Condition-Based Maintenance
HSV kategori
Forskningsprogram
Data- och informationsvetenskap, Informatik
Identifikatorer
URN: urn:nbn:se:lnu:diva-77402DOI: 10.1177/0959651818772939ISI: 000439608900013Scopus ID: 2-s2.0-85047389495OAI: oai:DiVA.org:lnu-77402DiVA, id: diva2:1242863
Tilgjengelig fra: 2018-08-29 Laget: 2018-08-29 Sist oppdatert: 2019-08-29bibliografisk kontrollert

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