engleski

A review of artificial intelligence applications in ship structures

Through both shipbuilding periods, the design phase and operational life, data was collected mostly for validation of contracts between shipbuilders and shipowners and compliance rules from classification societies and international institutions. Rapid development of computer science and information technology has created a fair amount of new approaches and possibilities to collect, sort, analyse and what’s most important, use a vast amount of data intelligently. Thus, it has paved the way for new concept and approaches like internet of things (IoT), digital twin, artificial intelligence (AI), machine learning(ML) to enter in shipbuilding and industry in general. AI and ML methods can be used for numerous applications in different shipbuilding areas: design optimization, sea state and loads prediction, corrosion prediction, collision avoidance, route optimization, collision avoidance, autonomous transport, corrosion prediction, maintenance planning, energy efficiency etc. The purpose of this paper is to present and analyse available state of the art solutions and implementations of AI and ML methods in different areas of maritime industry that are immediately or mediately affecting the design, safety or life expectancy of the ship structure. A short overview of artificial intelligence and machine learning methods is presented. These approaches are then classified and discussed within the framework of their application area in the field of maritime industry. Also, a most significant application area of these approaches is outlined. Finally, recommendations regarding new possible implementations are given together with the further steps within this research project.

artificial inteligence ; ship structures

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