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Titel:

Failure Mode Classification for Control Valves for Supporting Data-Driven Fault Detection

Dokumenttyp:
Konferenzbeitrag
Autor(en):
Trunzer, Emanuel; Kirchen, Iris; Folmer, Jens; Schrüfer, Carolin; Vogel-Heuser, Birgit; Erben, Stefan; Unland, Stefan; Vermum, Christian
Abstract:
Significant losses of production due to unplanned downtimes are a major problem caused by technical failures of equipment. Existing approaches like failure mode and effect analysis try to identify possible equipment breakdowns, their causes and effects in order to quantify the reliability of the system. Yet, they are not used for the detection of faults. On the other hand, Industrie 4.0 and data mining aim to improve the total operating time of automated production systems. However, due to the c...     »
Kongress- / Buchtitel:
IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)
Verlagsort:
Singapur, Singapur
Jahr:
2017
Seiten:
5
Nachgewiesen in:
Scopus; Web of Science
Reviewed:
ja
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