Japan’s Mitsui O.S.K. Lines (MOL) is set to implement an AI-based system developed by an Israeli startup company, to enhance fire safety on its car-carrying ships. Fires at sea are well-known as one of the leading causes of accidents. This […]
Japan’s Mitsui O.S.K. Lines (MOL) is set to implement an AI-based system developed by an Israeli startup company, to enhance fire safety on its car-carrying ships. Fires at sea are well-known as one of the leading causes of accidents. This industry is in search of new solutions to address the fire hazards, particularly those that can be caused by electric vehicles (EVs) and lithium-ion batteries.
All MOL ships that transport automobiles are currently equipped with fire alarm systems, predominantly based on smoke detectors. Despite measures taken to enhance fire safety, catastrophic losses still occur. MOL experienced such a loss in February 2022 when their ship, “Felicity Ace,” caught fire about 90 nautical miles southwest of the Azorean island of Faial in the central part of the Atlantic. The ship had to be evacuated, and the fire burned for days before the ship sank. The vessel was loaded with around 4,000 cars, including Lamborghinis, Audis, and Volkswagens, with estimated financial losses exceeding $400 million.
Although the cause of the fire was never determined, electric vehicle manufacturers claim that their vehicles do not pose a greater risk. However, battery fires present special challenges as they burn at higher temperatures and quickly become uncontrollable. Weeks after the fire on another ship, the “Fremantle Highway,” a car saved from the vessel continued to heat up when exposed to water used to extinguish the fire.
MOL has announced its plan to install the AI system developed by the Israeli company “Captain’s Eye” on 10 new LNG-powered ships. These vessels will be put into service in 2024, and the possibility of installing this system on existing ships is also being considered. MOL’s March 2023 report shows the company currently owns 96 car-carrying ships, with plans to increase the number to as many as 120 ships in this segment.
The company conducted demonstration tests with “Captain’s Eye” to assess the system’s smoke detection capabilities. The AI system developed by this company is already used to detect anomalies in the engine room and on the deck, and it has been implemented on merchant ships and other vessels worldwide.
On the “Onyx Ace,” a car carrier built in 2012 with a capacity of 18,500 tons and the ability to transport around 6,500 cars, MOL collaborated with “Captain’s Eye” to enhance the system’s functionality through numerous tests and confirmed its efficiency, including successfully detecting small amounts of smoke.
The system will analyze images collected by cameras positioned around the vehicles on board. When the system detects irregularities in the images, it sends alerts to the ship’s crew, as well as to the onshore management team. MOL believes that this system will enable faster smoke detection, and the images will help both the ship’s crew and the onshore team to react more swiftly and effectively manage fire hazards.
Allianz, a major insurance giant, stated in a market report released earlier this year that fires are a constant hazard for the maritime industry and insurers. They also highlighted that the battery market is expected to grow at a rate of over 30% annually over the next decade. According to their data, over 200 fires were reported in 2022, the highest number in the last ten years. The proportion of fires in numerous incidents increased by 17% in 2022, making them the third most common cause of incidents worldwide. In the past five years, as many as 64 ships have been completely destroyed due to fires.
The MOL Group has stated that they will continue to improve fire prevention measures in the cargo holds of their car-carrying ships. They believe that the AI system they are implementing will provide an additional capability for early detection of potential hazards and enable the ship’s crew to react quickly before incidents develop into potentially catastrophic losses.