~ For the Future with Maritime Autonomous Surface Ships ~

Kawasaki Kisen Kaisha, Ltd. (“K” Line) and Kawasaki Heavy Industries, Ltd. (KHI) announced that they have concluded a co-development contract for “AI (Artificial Intelligence)-based Marine Machinery Operation Support System” (hereinafter referred to as “the System”) that is expected to be part of the core technology to achieve autonomous vessel operation in the future.  The System will have such functions as failure prediction/ diagnostics, CBM (Condition-Based Maintenance), and optimum operation support, based on the data analytics of marine machinery operation data using AI. 

In view of safer operations at sea, improvement of working environment for seafarers, and higher pressure for industrial competitiveness, the expectations for autonomous operations for ships is increasingly growing these days. Through this co-development project, they aim to complete the System by combining “K” Line’s extensive data on vessel operation and marine machinery operation collected from Kawasaki-Integrated Marine Solutions*1 and its years of experiences in operation and maintenance of onboard machinery, and KHI’s technology and expertise in building ships and propulsion plants, and by having AI learn these data and knowledge.

The System manages not only a specific piece of equipment but marine machinery onboard as a whole, including main engine and power generator.  In developing the System, we will first target those vessels with diesel propulsion plants, and then those with various types of propulsion systems such as steam turbines and electronic propulsion systems in the next phase.  The System will be beneficial for crew onboard as well as ship management personnel on land, providing useful information on failure predictions and failure diagnostics. This not only enables users to prevent major engine troubles from occurring but also assists planning effective maintenance schedule and advises optimum engine operation based on the condition of plants, ultimately to improve fuel consumption and to contribute to the greenhouse gas reduction.

Preferred Networks, Inc.*2 known for their cutting-edge technologies on deep-learning and machine-learning, is joining us in developing the “Marine AI,” the core of the System that executes failure prediction and operation condition diagnostics.

The Marine AI will be implemented both onboard and in the cloud system. The one onboard learns the vessel’s operation data and uses them to diagnose on a real-time basis. The one in the cloud system periodically collects the data accumulated on each vessel, and centrally uses them for further learning, allowing itself to become smarter and offer failure prediction and diagnostics as well as optimum operation support for any type of vessels.  A proof-of-concept has been established for the core technology of the Marine AI for failure prediction and diagnostics.  With abundant data collected from various ships via Kawasaki-Integrated Marine Solutions, as well as such data obtained from the latest sensors that were not available before, “K” Line and KHI will further proceed on developing the Marine AI that is versatile enough to be applied for any types of vessels. 

Both “K” Line and KHI are innovators, fully utilizing their expertise in maritime transport and shipbuilding, collaborating with entities from other industries with their special knowledge and technologies to accelerate system development so that they will achieve autonomous vessel operation for the future. “K” Line and KHI will contribute to accomplish safer operations at sea, improved working environment for seafarers, and higher competitiveness in the marine industry.

Notes

*1. Kawasaki-Integrated Marine Solutions is an ICT system for vessels that allows ship operation management, condition monitoring, performance analysis, and others from management office on land, using ship-land communication network.

Released on June 28, 2016: Joint development project of “K-IMS”; Integrated vessel operation and performance management system

https://www.kline.co.jp/en/news/other/other3295047094663452046.html

Released on December 4, 2019: Completed Additional Development (Phase-2) of “Kawasaki Integrated Maritime Solutions”

https://www.kline.co.jp/en/news/other/20191204EN/main/0/link/20191204EN.pdf

*2. Preferred Networks, Inc. was founded in March 2014, and has been making progressive advancement to achieve the application of machine learning and deep learning to industry in collaboration with leading companies of many different fields, including transportation system, manufacturing industries, and bio-healthcare since then.  As part of the areas of machine learning/ deep learning application, Preferred Networks has been employing their cutting-edge technology for failure prediction of industrial equipment based on anomaly detection using time-series data and operation optimization of factory plants. 

Kawasaki Kisen Kaisha, Ltd. (“K” LINE) and IBM Japan, Ltd. (IBM Japan) have conducted a field trial with the objective of improving work quality by strengthening the safety management of cargo handling. Internet of Things (IoT) devices and artificial intelligence (AI) were utilized to collect and analyze information on driving of vehicles during operation in cargo holds, positional information of vehicles and workers, and vital information of workers.

The field trial verified the restriction of driving speed of vehicles, prevention of contact between vehicles and workers, prevention of collisions of vehicles, and collection of vital information of workers. Specifically, with the cooperation of a stevedoring company, beacons (positional information sensors), surveillance cameras, and speed measurement equipment were installed on the cargo deck to collect data. Furthermore, AI-based image recognition technology (Note*) was used to separate vehicles and workers based on camera images to determine the status of their proximity. In addition, heart rates data were obtained from wearable devices (Note*) and based on analyzed data by algorithm to ascertain trends in driver stress. The aim is to improve work quality by strengthening the safety management of cargo handling by analyzing this diverse and complex data and visualizing the number and condition of speed violations and near-miss incidents in the vessel.

IBM Cloud, which is secure and has a track record in many companies as a data platform, was used for data analysis. IBM Japan created IBM®︎ Maximo Monito, a solution for remote monitoring, on IBM Cloud to provide real-time visualization of large data sets, AI-based anomaly detection, and a configurable dashboard. This solution enabled the collection, management, and analysis of sensor information, and data scientists played a central role in supporting tasks such as IoT application design and data analysis.

“K” LINE will conduct further verification aimed at practical implementation based on the results of this field trial.

“K” LINE aims to establish a world-leading safe operation system, with contribution to people living well and prosperously under its corporate philosophy as an integrated logistics group. In order to further strengthen safety management in the car carrier business, “K” LINE believes it is important to further utilize digital technologies such as IoT and AI.

“K” LINE has also been engaged in strengthening communication infrastructure. The “CENTURY HIGHWAY GREEN,” a next-generation environmentally friendly car carrier, was delivered to “K” LINE in March 2021, equipped with significantly improved facilities for communication within the vessel and between the vessel and land. By adopting a variety of environmental measures and digital technologies, “K” LINE will remain committed to the improvement of safety, the environment, and quality as a key issue it faces.

Reference

March 12, 2021 release: Delivery of Next-generation Environmentally Friendly Car Carrier Fueled by LNG “CENTURY HIGHWAY GREEN” https://www.kline.co.jp/en/news/car/car753727087818379669/main/0/link/210312EN1.pdf

Kawasaki Kisen Kaisha, Ltd. (“K” LINE), together with ITOCHU Corporation, NS United Kaiun Kaisha, Ltd., Nihon Shipyard Co., Ltd. and Mitsui E&S Machinery Co., Ltd. have jointly applied for and been selected for the “Green Innovation Fund Project / Development Project for Next-Generation Ships / Development of Ammonia-Fueled Ships,” a project publicly announced by the New Energy and Industrial Technology Development Organization (NEDO).

In order to achieve the International Maritime Organization’s strategy to reduce greenhouse gas (GHG) emissions, this project will use ammonia as marine-fuel, which is attracting attention from various fields as a candidate for alternative fuels, to develop, own and operate propulsion systems and hulls ahead of other countries, with the aim of implementing ammonia-fueled ships in society under Japan’s leadership as early as possible by 2028, so that Japan’s maritime industry can maintain its long-term advantage in the field of zero-emission ships.

Role of each company

Through the “Joint Study” framework for studying ammonia as an alternative marine fuel (Note 1) established in June this year, “K” LINE has been studying the use of ammonia as marine-fuel. Together with the four companies involved in this joint project, “K” LINE will continue to work toward the social implementation of ammonia, a promising zero-emission fuel, as a marine-fuel in society.

~Captured CO2 has Purity greater than 99.9%, Demonstrating performance in line with Plan~

Kawasaki Kisen Kaisha, Ltd. (“K” LINE) has successfully separated and captured carbon dioxide (CO2) from the exhaust gas emitted from the vessel, coal carrier “CORONA UTILITY”(operated by “K” LINE for Tohoku Electric Power Co., Inc.), which has been installed the “CC-OCEAN” project for the verification of CO2 capture plant onboard as part of the “Research and Development for advancing marine resources technologies” (Note 1), in cooperation with Mitsubishi shipbuilding Co., Ltd. (“Mitsubishi Shipbuilding”) and Nippon Kaiji Kyokai (“Class NK”).

As a result of demonstration, the captured CO2 had a purity (Note 2) of more than 99.9%, which is in line with the planned performance.

In early August 2021, after installation of a small-scale CO2 capture plant (Note 1), experts from Mitsubishi Shipbuilding were onboard the vessel to operate, maintain the plant, and instruct the ship’s crew how to operate, as well as measured, analyzed the captured CO2 and evaluated the system performance.

From mid-September, the ship’s crew has been conducting the operation, measurement and maintaining the plant, and will continue to evaluate the safety and operability of the CO2 capture plant in order to sort out the issues to be considered and conduct research and development for future commercialization.

Based on the “K” LINE Environmental Vision 2050 (Note 3), we will continue to research, develop, and introduce various environmental load reduction technologies, including the “CC-OCEAN” project, and contribute to activities aimed at achieving GHG reduction targets.

(Note 1)

Announced on 31-Aug 2020: “CC-Ocean” (Carbon Capture on the Ocean) project

https://www.kline.co.jp/en/news/csr/csr-5587043701830807195/main/0/link/200831EN%20.pdf

Announced on 5-Aug 2021: Launch of the “CC-OCEAN” project demonstration

https://www.kline.co.jp/en/news/csr/csr7601431474845700352/main/0/link/210805EN.pdf

(Note 2) The purity of the CO₂ captured by the CO₂ capture plant. When a terrestrial plant captures CO₂ with a purity of more than 99.9%, the captured CO₂ can be used in a wide range of applications, including chemical processes to enhance production of fertilizer or methanol, general use such as dry ice for cooling, and enhanced oil recovery (EOR) to increase crude oil production.

(Note 3) “K” LINE Environmental Vision 2050, Blue Seas for the Future, which is formulated in 2015.

Based on the revision in June 2020, our milestone target is set to [improve CO2 emission efficiency by 50% over 2008], which is surpassing the IMO target of a 40% improvement.

https://www.kline.co.jp/en/csr/environment/management.html#002