J-ENG to collaborate with ClassNK in CBM and digital twin research

The deal is intended to lead to improvements in main engine safety as well as the optimisation of maintenance timing/interval for its UE low-speed engine platform.

By installing a number of additional sensors aboard an in-service vessel, the programme will improve the operational data generated by a vessel and the performance data of the main UE engine. This data will be analysed to investigate the main engine’s reliability and economy.

The programme will lead to improvements in the accuracy of engine condition diagnosis which can be used to optimise the scheduling of maintenance (Condition Based Maintenance).

J-ENG has been undertaking research into introducing digitalisation tools and CBM maintenance services into its existing Eco-Engine control system. The engine designer and manufacturer had announced plans to introduce CBM services across its wider engine portfolio at the launch of the UEC42LSH in Japan in May 2019.

Classification society ClassNK will also be given access to the results of the research programme. ClassNK plans to use the data to improve the scheduling of vessel inspections based on CBM.

J-ENG is also conducting research into digital twin technology with the aim of reproducing the main engine’s running condition virtually, based on engine operational data.

J-ENG’s research and development teams have been heavily focused on the development of Internet of Things (IoT) solutions, and this has been a focus second only to research into the new UEC42LSH engine, The Motorship understands.