NYK project to study advanced CBM

Malcolm Latarche

Malcolm Latarche · 25 November 2019

ShipInsight


Japan-based ship operator NYK along with several partners including ClassNk, Japan Engine Corporation (J-ENG), Mitsubishi Heavy Industries has concluded a joint research agreement for developing advanced condition-based maintenance (CBM) and has started verification during actual ship operation.

Machinery data from many sensors will be shared and monitored with the classification society and engine manufacturers in real time, thus advancing maintenance management. In the future, the NYK Group plan to use this data and real-time monitoring to develop an advanced CBM sufficient to realise manned autonomous vessels.

In the shipping industry, time-based maintenance (TBM) is usually practiced, but TBM requires a vessel to halt operations for a few weeks of inspections every two or three years even if no fatigue or breakdown of the engine is observed. Moreover, unexpected failures can occur during voyages and cause long delays.

In accordance with recent developments in information and communication technology, large amounts of data can be transmitted between ship and shore. The NYK Group has utilszed these advances to focus on CBM and conduct research on optimal maintenance. NYK has now decided to boost its research by partnering with other companies to develop advanced CBM.

In addition to SIMS2, (the data sharing and ship information management system developed by NYK and MTI) a new sensor and equipment is installed in two different types of main engine and main steam turbine, and detailed operational data such as vibration and bearing temperature is to be collected. The condition of the engine will then be shared and constantly monitored by the classification society (ClassNK) and J-ENG.

The projects will also work to make failure predictions and remaining useful life for the engine by taking advantage of manufacturer expertise to create optimal CBM guidelines and then verify them on actual ships. These results will be shared with the classification society to establish a new classification survey scheme based on CBM. In the future, the project partners will develop a more advanced CBM that enables continuous monitoring of the condition through AI (artificial intelligence), and then realisation of further optimal maintenance by combining information such as operational schedules. Establishing an advanced CBM system is a step toward a highly automated vessel, and thus an autonomous one. An innovative method that can greatly benefit the realisation of manned autonomous vessel is the NYK Group’s target.

For its part, J-ENG has said its aims are improving main engine safety and optimisation of maintenance timing/interval. As well as the data from sensors being used on the UE main engines in the project, J-ENG is using a digital twin to reproduce main engine’s running condition virtually based on the actual running data together with introducing IoT and AI technology actively to contribute to maritime industries’ innovation.

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