At Nor-Shipping 2017, NYK and DNV GL presented the first results of an ongoing maritime data center pilot project. The data center collects operational data from NYK vessels on DNV GL’s recently launched Veracity industry data platform, for monitoring vessel performance and condition-based maintenance schemes.
Over the past 18 months, four NYK container vessels have been uploading operational data to the platform. The collaboration was also supported by engine manufacturer MAN Diesel & Turbo.
An extensive amount of engine data has been collected, for use in vessel performance analysis and a condition-based maintenance and survey scheme. The pilot project has been run in several phases:
- The first phase has been to build the required components, such as data collection and data management.
- The second phase focuses on testing data quality, security, access rights and curation of data for use in various applications such as predictive maintenance and vessel performance.
- The upcoming third phase will look to pilot new digital business models.
Tadaaki Naito, President of NYK, noted that Information & Communication Technology (ICT) is growing rapidly in the maritime industry, that sees the beginning of an era to pursue ICT-enhanced technical innovations, where industry partners form organic collaborations.
“IoT (Internet of Things) data produced by ships in operation is the key to such collaborations. The promotion of data sharing brings a new opportunity for talented ICT technicians and data scientists to step into our maritime industry, resulting in a co-evolution of our industry with digital talent that allows us to reach higher. We share such open platform concept with DNV GL and MAN, and are cooperating in the pilot process of proving the validity of the concept and building a real working platform by sharing NYK ships’ operational data with MAN over DNV GL’s Veracity industry data platform.“
As part of the pilot project, a hierarchical data model is developed, creating a digital twin, which links sensor signals from equipment on board the vessels to support both simple queries and advanced analytics. Machine learning algorithms evaluate the data quality in terms of uniqueness, completeness, and a variety of other parameters. By drilling down into the data, the ship manager can see if all sensors on board the vessel are working properly and easily identify non-performing sensors which may lead to low data quality or missing data during a voyage.
“With this pilot project we are able to test a sensor-based class concept where condition-based surveys may be performed. Furthermore, the project has allowed us to test how Veracity functions in terms of data quality, security and access rights. The pilot project has also been a valuable test bed for data standardisation and data quality, including curation of the data for further use” ” says Knut Ørbeck-Nilssen, CEO DNV GL – Maritime.