Abstract
The calculation of lashing forces on containerships is one of the most important aspects in terms of cargo safety, as well as slot utilization, especially for large containerships such as more than 10,000 TEU (Twenty-foot Equivalent Unit). It is a challenge for stowage planners when large containerships are in the last port of region because mostly the ship is full and the stacks on deck are very high. However, the lashing force calculation is highly dependent on the Classification society (Class) where the ship is certified; its formula is not published and it is different per each Class (e.g., Lloyd, DNVGL, ABS, BV, and so on). Therefore, the lashing result calculation can only be verified by the Class certified by the Onboard Stability Program (OSP). To ensure that the lashing result is compiled in the stowage plan submitted, stowage planners in office must rely on the same copy of OSP. This study introduces the model to extract the features and to predict the lashing forces with machine learning without explicit calculation of lashing force. The multimodal deep learning with the ANN, CNN and RNN, and AutoML approach is proposed for the machine learning model. The trained model is able to predict the lashing force result and its result is close to the result from its Class.
Highlights
Instead of calculating the lashing forces by navel architecture engineering, this study proof calculating the lashing forces by navel architecture engineering, this study proposes poses multimodal deep learning with Artificial Neural Network (ANN), Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) to train machines to predict multimodal deep learning with ANN, CNN and RNN to train machines to predict the the lashing forces
Multimodal Deep Learning is applied with Artificial Neural Network (ANN), Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN)
After embedding the trained model into the Stowage Planning tool, the lashing forces result from Onboard Stability Program (OSP) and the predicted result from the trained model has been compared with the new fully loaded stowage
Summary
Stowage planning is a highly complex process with the goal to achieve cost efficiency and safety of crews and containership at the same time. This is done by ensuring that containers are loaded in the appropriate places on the containership, with consideration of the infrastructure limitation of all terminals in the round trip port rotation of the subject vessel, container composition to be loaded at each terminal, necessary segregations of the dangerous goods cargo, adherence to navigation visibility requirement, maximum number of cranes that can work concurrently, fulfilment of special stowage requirements from shippers, safety of containers and vessels, such as stability, strength, lashing, etc.
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