With the sophistication of shipboard systems, maintenance is becoming more time-consuming and skill-dependant. Precise and timely planning, which can be achieved through Condition
Based Maintenance, is key in overcoming these challenges, as well as ensuring the longevity and efficiency of assets. The rapid growth of ship monitoring systems means that failures and
performance shifts can be linked to variations in measured parameters. This knowledge can be used to limit performance losses, through the identification of undesirable trends. The current
project seeks to predict the health status of the hull and the propeller, through the combination of performance modelling approaches from two distinct schools, first-principle techniques
and data-driven methods, with the data collection capabilities of modern vessels. Reductions of the vessel’s performance at a certain operational and environmental setting, when compared to a
reference ’clean vessel state’ can be traced to the extent of fouling of the hull & propeller, whose condition can be determined separately. A hybrid methodology, combining the accuracy, speed,
and flexibility of data-driven methods with the physical knowledge of first-principle models is considered the ideal candidate for the above tasks. The main aim of the research project is to develop a set of real-time fault detection, which can be used to supplement a maintenance strategy, reducing maintenance loads and crew requirements. The developed novel hybrid prediction models utilise both data-driven and first-principle approaches, which has not been previously applied to the problem of evaluating the vessel performance shift due to biofouling. Finally, a case study is employed to demonstrate the numerical tool’s ability to identify shifts in ship capability.
Due to the generous collaboration of DAMEN Shipyards and The Royal Netherlands Navy, the developed methodology is validated and tested on real-world data.
| Date of Award | 29 May 2025 |
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| Original language | English |
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| Awarding Institution | - University Of Strathclyde
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| Sponsors | University of Strathclyde |
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| Supervisor | Maurizio Collu (Supervisor) & Andrea Coraddu (Supervisor) |
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