TY - GEN
T1 - IIoT-based fatigue life indication using augmented reality
AU - Khalil, Mohamed
AU - Bergs, Christoph
AU - Papadopoulos, Theodoros
AU - Wuchner, Roland
AU - Bletzinger, Kai Uwe
AU - Heizmann, Michael
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - Online condition monitoring services and predictive maintenance are becoming more and more a key for system operators to extend the system lifetime and detect faults in early stages. Therefore, system manufactures need to efficiently provide system operators so-called digital twins which can be executed during operation and give the system operator an impression of the health state of the system. Industrial Internet of Things (IIoT) platforms are enablers for such services and provide new possibilities to interact with the system running in the field. Furthermore, the traditional dashboard are becoming obsolete as user interface and are replaced by novel solutions that let the system operator experience the system health state. For example, health estimation and condition monitoring of electric motors is a topic of high interest nowadays. This article addresses an application which acquires machine data, processes it on an IIoT platform to get the system health and visualizes the results online in an augmented reality user interface.
AB - Online condition monitoring services and predictive maintenance are becoming more and more a key for system operators to extend the system lifetime and detect faults in early stages. Therefore, system manufactures need to efficiently provide system operators so-called digital twins which can be executed during operation and give the system operator an impression of the health state of the system. Industrial Internet of Things (IIoT) platforms are enablers for such services and provide new possibilities to interact with the system running in the field. Furthermore, the traditional dashboard are becoming obsolete as user interface and are replaced by novel solutions that let the system operator experience the system health state. For example, health estimation and condition monitoring of electric motors is a topic of high interest nowadays. This article addresses an application which acquires machine data, processes it on an IIoT platform to get the system health and visualizes the results online in an augmented reality user interface.
KW - Augmented reality
KW - Fatigue life
KW - Health indication
KW - IIoT
KW - Predictive maintenance
KW - Simulation in operation
UR - http://www.scopus.com/inward/record.url?scp=85079058966&partnerID=8YFLogxK
U2 - 10.1109/INDIN41052.2019.8972114
DO - 10.1109/INDIN41052.2019.8972114
M3 - Conference contribution
AN - SCOPUS:85079058966
T3 - IEEE International Conference on Industrial Informatics (INDIN)
SP - 746
EP - 751
BT - Proceedings - 2019 IEEE 17th International Conference on Industrial Informatics, INDIN 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th IEEE International Conference on Industrial Informatics, INDIN 2019
Y2 - 22 July 2019 through 25 July 2019
ER -