000010661 001__ 10661
000010661 005__ 20241024114714.0
000010661 0247_ $$2doi$$a10.24868/10661
000010661 245__ $$aSmart Maintenance for Modern Naval Ships
000010661 269__ $$a2022-07-26
000010661 336__ $$aConference Proceedings
000010661 520__ $$aThe 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.
000010661 542__ $$fCC-BY-NC
000010661 6531_ $$aSmart Maintenance
000010661 6531_ $$aPredictive Maintenance
000010661 6531_ $$aCondition Based Maintenance
000010661 6531_ $$aOrganisational Transition
000010661 6531_ $$aRoyal Netherlands Navy
000010661 7001_ $$aTiddens, W$$uRoyal Netherlands Navy
000010661 7001_ $$aPollmann, B$$uRoyal Netherlands Navy
000010661 7001_ $$aCuvers, D$$uRoyal Netherlands Navy
000010661 7001_ $$aTeunisse, M$$uRoyal Netherlands Navy
000010661 7001_ $$aShanez Saz, S$$uRoyal Netherlands Navy
000010661 7001_ $$aZegers, J$$uRoyal Netherlands Navy
000010661 773__ $$tConference Proceedings of INEC
000010661 773__ $$jINEC 2022
000010661 8564_ $$9d185c09b-f05a-4ebf-9e6a-eeccc6880f01$$s5502883$$uhttps://library.imarest.org/record/10661/files/INEC_2022_paper_21.pdf
000010661 980__ $$aConference Proceedings