Japanese shipping firm Mitsui OSK Lines (MOL) has developed a vessel allocation and cargo loading plan for car carriers in collaboration with its group company MOL Information Systems and Osaka University.
The plan utilises mathematical optimisation that is a fundamental artificial intelligence (AI) technology.
Go deeper with GlobalData
The technology is expected to enable MOL’s personnel to allocate vessels and prepare loading plans faster.
MOL runs a fleet of approximately 100 car carriers. Each ship is capable of handling about 5,000 standard passenger cars.
Operating the vessel in its peak productivity while meeting diversifying demands of automakers has become essential. This can be achieved through efficient vessel allocation and cargo loading.
When a ship has to sail towards various ports to load and unload the cargo, the deck and hold for cargo loading can considerably affect the safety of cargo operations and efficiency.
During the voyage, it is essential to consider the loading / unloading and hull balance. As a result, developing a loading plan takes more time than usual.
Two teams in collaboration with associate professor Shunji Umetani from Graduate School of Information Science and Technology in Osaka University developed an algorithm that creates a proposed plan, leveraging mathematical optimisation.
It is specifically effective when transport volumes or the order of port calls changes suddenly and the ship has to plan within a short period of time to meet customers’ demand.
MOL will evaluate the potential for practical use of the technology.
Recently, MOL and SenseTime Japan released an AI-powered vessel image recognition and recording system to support automated ship monitoring.
In June, Hong Kong LNG Terminal signed a charter contract with MOL to supply a floating storage and regasification unit (FSRU) for an offshore terminal project.
