Abstract
This work presents a state-of-the-art predictive maintenance (PdM) framework, which is tailored to demanding cases, where information is dynamic and partial, and non-supervised solutions should be applied. Moreover, it discusses and aims to demonstrate the application of this framework to the Navarchos Fleet Management System (FMS).
The research is funded under the programme of social cohesion “THALIA 2021–2027" co-funded by the European Union, through Research and Innovation Foundation.
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Giannoulidis, A., Michailidou, AV., Toliopoulos, T., Constantinou, I., Gounaris, A. (2024). Predictive Maintenance in a Fleet Management System: The Navarchos Case. In: Islam, S., Sturm, A. (eds) Intelligent Information Systems. CAiSE 2024. Lecture Notes in Business Information Processing, vol 520. Springer, Cham. https://doi.org/10.1007/978-3-031-61000-4_13
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DOI: https://doi.org/10.1007/978-3-031-61000-4_13
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