A joint ship maintenance management system to help reduce ship lifecycle cost
ClassNK, IHI Marine United (IHIMU), Diesel United (DU) and IBM Japan have announced they will jointly develop a ship maintenance management system to help reduce ship lifecycle cost.
The jointly developed system, which will make use of the latest condition monitoring sensor technology and data analysis systems, will be offered by ClassNK as a cloud-based service to shipowners, managers and operators from June 2013.
As ships face dramatically changing ocean conditions, appropriate maintenance and condition monitoring of on-board machinery is essential to ensuring smooth operations. With bunker prices near historic highs, shipowners are increasingly turning their attention to maintenance management schemes utilizing on-board sensors data and diagnostic analysis tools to prevent malfunctions, ensure smooth operations, and reduce maintenance costs.
From April to July 2012, ClassNK, IHIMU and IBM Japan carried out joint research to investigate methods for the early detection of machinery abnormalities. Making use of the technical expertise and extensive ship machinery performance data provided by the IHIMU Group, ClassNK and its partners analyzed how machinery performance changed in the situations where malfunctions occurred.
This analysis was made possible by new data analysis technology developed by IBM Research – Tokyo which can automatically identify hidden dependencies between operational parameters as well identify sensor anomalies, allowing noise and false positives to be automatically removed from the sensor data. When research confirmed that the new technology can effectively analyze the data from sensors on-board machinery, ClassNK began working to adapt the system for use in the maritime industry.
ClassNK’s new ship maintenance management system will be developed using technical know-how derived from IHIMU’s ADMAX shipboard management software, which is already in use on more than 700 vessels, with IBM’s Maximo asset management software system. The IBM Maximo software platform is one of the world’s leading Enterprise Asset Management (EAM) systems and is widely used in power generation, manufacturing, real estate and other industries to manage maintenance and reduce the lifecycle costs of machinery and other capital intensive assets.
The system itself will make use of IBM’s cloud service to ensure the availability and security of maintenance information from anywhere in the world. In order to efficiently record maintenance data on-board ships even when internet access is not available, IBM will also jointly develop a mobile Enterprise Asset Management application for the new management software using its Worklight mobile application platform. IBM’s market leading mobile architecture will make it possible for maintenance data to be recorded on-board and accessed by managers or owners from anywhere in the world via mobile devices.
In order to ensure the effectiveness of the sensor data analysis technology the new system will also be verified on existing bulk carriers, oil tankers, and container carriers equipped with DU’s Lifecycle Administrator (LC-A) total support system, which also makes use of sensor data to determine the condition of diesel engines and other engine room machinery. In addition to confirming the effectiveness of the new analysis technology, the tests will also confirm the effect of real ocean conditions and differences between individual ships on the sensor data.
DU’s LC-A is a sophisticated sensor based system for condition based and preventive maintenance which includes trouble shooting functions. While LC-A requires a specialist to develop an analysis model for each vessel on an individual basis, thanks to IBM’s new technology and extensive testing on actual vessels, ClassNK’s new maintenance system is expected to minimize the need for a custom built analysis model, increasing the scope of system application and allowing it to be used immediately on almost all vessels.
By providing an integrated ship maintenance management system with sensor data analysis technology, ClassNK’s new service will help owners and managers detect machinery abnormalities at the earliest point possible and predict where malfunctions are likely to occur, thus allowing owners to prevent machinery malfunction and lengthening machinery lifespan, while also reducing lifecycle costs.
Source: ClassNK
