Author:
Werner Andreas,Mendez-Rial Roi,Salvo Pablo,Charisi Vasiliki,Piccini Joaquín,Mousavi Alireza,Civardi Claudio,Monios Nikos,Espinosa Diego Bartolomé,Hildebrand Marlène,Zimmermann Nikolas,Aguirre Irati Vizcarguenaga,Cassina Jacopo,Avendano Diego Nieves,Oliveira Helder,Caljouw Daniel,Fazziani Matteo,de la Maza Silvia
Publisher
Springer International Publishing
Reference18 articles.
1. Mikat, H.: Hybride Fehlerprognose zur Unterstützung prädiktiver Instandhaltungskonzepte in der Luftfahrt. Technische Universität Darmstadt, Institut für Flugsysteme und Regelungstechnik, Dissertation (2015)
2. Werner, A., Zimmermann, N., Lentes, J.: Approach for a holistic predictive maintenance strategy by incorporating a digital twin. Procedia Manuf. 39, 1743–1751 (2019). https://doi.org/10.1016/j.promfg.2020.01.265
3. Roland Berger GmbH: Predicitve Maintenance: Service der Zukunft—und wo er wirklich steht. Munich (2017)
4. Cubillo, A., Perinpanayagam, S., Esperon-Miguez, M.: A review of physics-based models in prognostics: application to gears and bearings of rotating machinery. Adv. Mech. Eng. 8(8), 1–21 (2016). https://doi.org/10.1177/1687814016664660
5. Wang, Q., Bu, S., He, Z.: Achieving predictive and proactive maintenance for high-speed railway power equipment with LSTM-RNN. IEEE Trans. Ind. Inf. 16(10), 6509–6517 (2020). https://doi.org/10.1109/TII.2020.2966033
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