‘K’ Line and Kawasaki to create AI condition monitoring system

Japanese shipping company ‘K’ Line and Kawasaki Heavy Industries (KHI) have concluded a co-development contract to create an AI-based Marine Machinery Operation Support System, to support failure prediction and CBM (Condition-Based Maintenance) based on analysis of machinery operations data.

The project will feed the artificial intelligence system with ‘K’ Line’s data on vessel operations, using data collected from Kawasaki-Integrated Marine Solutions during management and maintenance of onboard machinery, and combine that with KHI’s technology and expertise in building ships and propulsion plants.

Rather than focus on specific single pieces of equipment, the new technology will be designed to regard marine machinery onboard as a whole ecosystem, including the 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,” ‘K’ Line says.

“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 an effective maintenance schedule and advises optimum engine operation based on the condition of plants, ultimately to improve fuel consumption and to contribute to greenhouse gas reduction.”

Fellow Japanese company Preferred Networks, a specialist in deep-learning and machine-learning technologies, will participate in developing the ‘Marine AI’ at the core of the system, which will be responsible for failure prediction and operational condition diagnostics.

The Marine AI will be implemented both on board and in the cloud, with the onboard system learning the vessel’s operational patterns and using that information to diagnose issues on a real-time basis. The cloud system will periodically collect the data accumulated on each vessel and collate it centrally for further learning, to become ‘smarter’.

In related news, ‘K’ Line and IBM have also announced that they have begun work on a field trial utilising Internet of Things (IoT) devices and artificial intelligence (AI) to improve safety management in cargo handling on car carriers.

The technology systems were used to collect and analyse information on how vehicles are driven during operations in cargo holds, as well as to study the position of vehicles and workers.

In cooperation with a stevedoring company, positional information beacons, surveillance cameras, and speed measurement equipment was installed on the cargo deck to collect data. AI-based image recognition technology was employed to distinguish between vehicles and workers based on camera images to determine their proximity.

In addition, heart rate data were obtained from workers’ wearable devices and analysed to examine trends in driver stress.

IBM Japan deployed its Maximo Monito remote monitoring system on the IBM Cloud to provide real-time visualisation of the data collected, using a configurable dashboard. The company’s data scientists also played a role in support tasks such as IoT application design and data analysis.

‘K’ Line says it will analyse the diverse and complex data set to visualise the number and severity of speed violations and near-miss incidents on the vessel to improve safety management procedures in the future.

Share this story

About the Author

Picture of Rob O'Dwyer
Rob O'Dwyer

Rob is Chief Network Officer and one of the founders of Smart Maritime Network. He also serves as Chairman of the Smart Maritime Council. Rob has worked in the maritime technology sector since 2005, managing editorial for a range of leading publications in the transport and logistics sector. Get in touch by email by clicking here, or on LinkedIn by clicking here.

Further Reading

News Archive