Automation technologies in ship systems maintenance: problems and ways to improve through cross-sector experience

Abstract

The cross-sector borrowing of advanced automation technologies from the aviation, railway, automotive, energy, aerospace, and logistics sectors is considered to improve the reliability, safety, and efficiency of maritime transport maintenance. This study emphasizes the importance of transitioning from traditional scheduled maintenance to approaches based on actual technical condition and failure prediction. Based on a review of successful solutions in other industries, the article analyzes the possibilities of adapting the following innovations in the maritime industry: the introduction of equipment remote monitoring, digital twins, internet of things (IoT) sensors, diagnostic systems and machine learning for technical condition analysis, the use of drones and autonomous robots for inspection and emergency work, as well as the development of comprehensive digital maintenance management platforms. The article demonstrates that such technologies have already proven their efficiency in related sectors - reducing the number of accidents by 30–70%, reducing repair costs by up to 40%, and reducing downtime by 20–50%. At the same time, the maritime industry implements these approaches slowly, due to the lack of open databases for training forecasting models and the absence of unified standards for exchanging technical information. The paper emphasizes the need for a systematic approach to integrating predictive maintenance into water transport, creating a regulatory framework, developing a digital fleet infrastructure, and training personnel to work with new monitoring and analysis tools. The paper provides examples of already implemented initiatives, including remote monitoring of ships' engines, the use of certified drones for tank inspections, and analytical platforms for fleet maintenance management. It also describes potential future developments, such as repairing drones, autonomous firefighting modules, and digital ship health passports. The study's results indicate that implementing predictive maintenance can become a key direction in the digital transformation of the maritime industry. This will not only increase the reliability of vessels and the safety of crews but also significantly reduce operating costs, minimize environmental risks, and ensure a higher level of fleet readiness for modern challenges