AI-Based Automatic Generation and Evaluation of Loading Conditions for Ships and Offshore Structures

초록

The shipbuilding and ship operation industries are experiencing an increasing demand for full automation. However, considering the large-scale production and operational facilities, research and development are currently focused on achieving phased unmanned operations. To prepare for a voyage, ships are required to assess their stability and structural strength, taking into ac- count the type and quantity of cargo loaded, bunkering conditions, and other relevant factors. Such evaluations are mandated from the design stage through approval of the Trim and Stability Booklet. Also, officers rely on this infor- mation to assess whether a given loading condition allows safe sailing with re- spect to stability and longitudinal strength. In special circumstances, such as navigating in heavy weather, dedicated ballast conditions must also be exam- ined, requiring calculations and evaluations that reflect current operational data. However, in smart ships with more than a 70% reduction in crew, or in fully unmanned vessels, these tasks must be handled with limited resources either by a small number of crew or shore-based fleet operation centers, thereby necessi- tating intelligent decision-support systems. This study investigates methods for intelligently evaluating loading conditions to support rapid decision-making and examines their applicability through testing.