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Data Management Architectures for the Improvement of the Availability and Maintainability of a Fleet of Complex Transportation Systems: A State-of-the-Art Review

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 762))

Abstract

This paper deals with the way constructors of a fleet of complex systems, and especially, in the field of transportation, aim to improve the availability and the maintainability of their fleet during their use, fleet operated by a public operator or a private company. More precisely, the focus is set on the architecture of the data management system that supports this aim. In this context, this paper presents a literature review on the main existing approaches that address the architecting of the data management of fleet or a set of transportation systems with the target to improve directly or indirectly their availability or maintainability. For that purpose, a positioning typology is suggested, which enables to identify, characterize and evaluate the state-of-the-art from the point of view of an industrialist working in the transportation sector. A set of future research challenges are finally suggested.

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Acknowledgements

This work is done in the context of the joint research Lab, “Surferlab” (http://www.surferlab.fr/en/home), founded by Bombardier Transport, Prosyst and the University of Valenciennes and Hainaut-Cambrésis. SurferLab is scientifically supported by the CNRS and is partially funded by ERDF (European Regional Development Fund). The authors would like to thank the CNRS, the European Union and the Hauts-de-France region for their support.

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Correspondence to Damien Trentesaux .

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Trentesaux, D., Branger, G. (2018). Data Management Architectures for the Improvement of the Availability and Maintainability of a Fleet of Complex Transportation Systems: A State-of-the-Art Review. In: Borangiu, T., Trentesaux, D., Thomas, A., Cardin, O. (eds) Service Orientation in Holonic and Multi-Agent Manufacturing. Studies in Computational Intelligence, vol 762. Springer, Cham. https://doi.org/10.1007/978-3-319-73751-5_8

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  • DOI: https://doi.org/10.1007/978-3-319-73751-5_8

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