AN INNOVATIVE MACHINE LEARNING SYSTEM FOR REAL TIME CONDITION MONITORING OF SHIP MACHINERY

von Oikonomou, S.
Veröffentlicht in Smart ship technology (Veranstaltung : 2020 : Online) International Conference Smart Ship Technology 2020 (2020)

Investigating ship system performance degradation and failure criticality using FMECA and Artificial Neural Networks

von Daya, A. A.
Veröffentlicht in MARTECH (6. : 2022 : Lissabon) Trends in maritime technology and engineering ; Volume 2 (2022)

Dynamic reliability analysis tool for ship machinery maintenance

von Dikis, K.
Veröffentlicht in International Maritime Association of the Mediterranean Towards green marine technology and transport : proceedings of the 16th International Congress of the International Maritime Association of the Mediterranean (IMAM 2015), Pula, Croatia, 21-24 September 2015 (2015)

An innovative machinery data management system for ships using a catalogue data model

von Taheri, A.
Veröffentlicht in International Maritime Association of the Mediterranean Towards green marine technology and transport : proceedings of the 16th International Congress of the International Maritime Association of the Mediterranean (IMAM 2015), Pula, Croatia, 21-24 September 2015 (2015)

Inspection capabilities for enhanced ship safety

von Lazakis, I.
Veröffentlicht in International Maritime Association of the Mediterranean Towards green marine technology and transport : proceedings of the 16th International Congress of the International Maritime Association of the Mediterranean (IMAM 2015), Pula, Croatia, 21-24 September 2015 (2015)

Application of photogrammetry techniques for the visual assessment of vessels’ cargo hold

von Kolyvas, E.
Veröffentlicht in International Maritime Association of the Mediterranean Towards green marine technology and transport : proceedings of the 16th International Congress of the International Maritime Association of the Mediterranean (IMAM 2015), Pula, Croatia, 21-24 September 2015 (2015)