HD Hyundai, SK Shipping join forces on AI-based LNG cargo solution

HD Hyundai's three units are joining forces with SK Shipping to install an artificial intelligence-based LNG cargo operation solution on the latter's 174,000-cbm LNG carrier.

South Korea’s HD Korea Shipbuilding & Offshore Engineering, HD Hyundai Heavy Industries, and HD Hyundai Marine Solution recently held a signing ceremony with compatriot SK Shipping at HD Hyundai Heavy Industries’ Ulsan yard to jointly work on the next-generation AI cargo handling solution (AI-CHS).

HD KSOE developed the AI-CHS cargo operation solution.

The shipbuilder stated that the solution predicts the amount of boil-off gas (BOG) naturally generated during the operation and berthing of LNG carriers. It assists in decision-making to appropriately distribute this gas to key equipment, such as reliquefaction facilities, generators, and main engines.

Liquefied natural gas in the LNG carrier cargo hold is transported at cryogenic temperatures, while bout 0.1 percent of evaporation gas is generated every day due to sloshing and heat inflows during transportation.

In order to maintain proper pressure in the cargo hold, the vessel’s main or auxiliary engines use this boil-off gas as fuel.

Previously, this series of decision-making processes was based on the experiences of skilled sailors, but AI-CHS provides solutions by comprehensively judging operating conditions and cargo operation conditions to support stable LNG cargo operations even for beginner sailors, according to HD KSOE.

Moreover, HD Hyundai will install the AI-CHS solution on SK Shipping’s LNG carrier, which joined the fleet in June this year.

After collecting and analyzing operational cargo management data, it will conduct demonstrations on cargo operation fuel efficiency evaluation, fuel usage optimization guidance, and simplification of crew tasks.

HD Hyundai and SK Shipping anticipate that this project will “significantly” enhance vessel and fleet operational efficiency through stable LNG cargo transportation, establish a data-based fuel efficiency evaluation system, maximize vessel fuel efficiency, and reduce crew workload.

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