@article{Maintenance:10661,
      recid = {10661},
      author = {Tiddens, W and Pollmann, B and Cuvers, D and Teunisse, M  and Shanez Saz, S and Zegers, J},
      title = {Smart Maintenance for Modern Naval Ships},
      journal = {Conference Proceedings of INEC},
      address = {2022-07-26},
      abstract = {The Royal Netherlands Navy (RNLN) aims to bring into  service new platforms across its force structure, including  a combat support ship, anti-submarine warfare frigates,  submarines, and various auxiliary vessels. A constant  pressure on reducing ships' crews and an increasing  complexity of systems aboard naval ships creates pressure  on the maintenance of these future naval ships.
The  increase in the number of sensors on board and the  emergence of learning algorithms offer an opportunity to  identify failures at an earlier stage, better plan  maintenance and reduce the (corrective) workload aboard  ships with the help of data analysis. The RNLN therefore  works on a transition from planned periodic maintenance  towards condition-based maintenance and predictive  maintenance based on advanced condition monitoring and data  analysis techniques, which necessitates the development of  improved shore support.
The RNLN developed the smart  maintenance roadmap to guide this transition towards a data  driven maintenance organisation. This roadmap covers the  process of collecting raw operational ship data to the  change in the RNLN’s asset management process and consists  of five strategy lines: data acquisition, data  infrastructure, data governance, data analysis and asset  management. The activities described in this paper have  been developed in close collaboration with academic  partners and industry. This paper presents the smart  maintenance roadmap and gives practical examples of  developments and challenges within each of the five  strategy lines. This paper concludes with future directions  that are envisioned for the development of smart  maintenance within the RNLN and reflects on the social  aspects of implementing smart maintenance within the  maintenance organisation of the RNLN.},
      url = {http://library.imarest.org/record/10661},
      doi = {https://doi.org/10.24868/10661},
}