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Holistic System-Analytics as an Alternative to Isolated Sensor Technology: A Condition Monitoring Use Case

Martin, Dominik; Kühl, Niklas

Sensor technology has become increasingly important (e.g., Industry 4.0, IoT). Large numbers of machines and products are equipped with sensors to constantly monitor their condition. Usually, the condition of an entire system is inferred through sensors in parts of the system by means of a multiplicity of methods and techniques. This so-called condition monitoring can thus reduce the downtime costs of a machine through improved maintenance scheduling. However, for small components as well as relatively inexpensive or immutable parts of a machine, sometimes it is not possible or uneconomical to embed sensors. We propose a system-oriented concept of how to monitor individual components of a complex technical system without including additional sensor technology. By using already existing sensors from the environment combined with machine learning techniques, we are able to infer the condition of a system component, without actually observing it. In consequence condition monitoring or additional services based on the component’s behavior can be developed without overcoming the challenges of sensor implementation.

DOI: 10.24251/HICSS.2019.124
Zitationen: 4
Zugehörige Institution(en) am KIT Karlsruhe Service Research Institute (KSRI)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2019
Sprache Englisch
Identifikator ISBN: 978-0-9981331-2-6
ISSN: 1530-1605
KITopen-ID: 1000085832
Erschienen in Proceedings of the 52nd Annual Hawaii International Conference on System Sciences : January 8-11, 2019, Maui, Hawaii. Ed.: Tung X. Bui
Veranstaltung 52nd Hawaii International Conference on System Sciences (HICSS 2019), Wailea, HI, USA, 08.01.2019 – 11.01.2019
Verlag University of Hawaii at Manoa, Hamilton Library, ScholarSpace
Seiten 1005-1012
Nachgewiesen in Scopus
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