Advanced condition-based maintenance for autonomous ships

26/03/2020

The NYK Group has concluded a joint research agreement for developing advanced condition-based maintenance (CBM), a new maintenance and management process for ship machineries, and has started verification during actual ship operation.

Machinery plant 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 will use this data and real-time monitoring to develop an advanced CBM method to realise manned autonomous vessels.

Time-based maintenance (TBM) is usually practised in the shipping industry, 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 utilised these advancements 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 an advanced CBM method.

In addition to a ship information management system developed by NYK and MTI and allowing data sharing among workplaces on land and sea in real time (SIMS2), equipment and a new sensor will be installed in two different types of main engine and mainsteam turbine and detailed operational data such as the levels of vibration and the temperature of the bearing will be collected. The condition of the engine will then be shared and constantly monitored by the classification society and engine manufacturers.

The projects will also work to make failure predictions and calculate the remaining useful life (RUL) of 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.

The NYK Group says it will improve the accuracy of failure predictions and remaining useful life RUL calculations. In the future, the Group will develop a more advanced CBM method that enables continuous monitoring of the condition through artificial intelligence (AI) and then realisation of further optimal maintenance by combining information such as operational schedules.

Establishing an advanced CBM system is a step towards a highly automated vessel and, thus, an autonomous one. An innovative method that can greatly benefit the realisation of a manned autonomous vessel is the Group’s target.

In accordance with the NYK Group’s medium-term management plan, ‘Staying ahead 2022 with digitalisation and green’, the Group is promoting digitalisation initiatives and strives to enhance innovation in the shipping industry, with various partners making use of operational big data.

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