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.
The world’s largest classification society on a gross ton
basis, ClassNK is dedicated to ensuring the safe development of the
international maritime industry and the protection of the marine environment.
This research project is one of more than 100 R&D projects currently being
carried out as part of ClassNK’s “Practical R&D for Industry” program,
which unites partners from both within and out the maritime community to
develop new solutions to the challenges faced by the shipping and shipbuilding
industries.
IHIMU, which will soon merge with Universal Shipbuilding
under the name Japan Marine United to become Japan’s largest shipbuilder, will
use the data and expertise developed as part of this project to improve the
ship support service of its lifecycle business, which will be one of the
company’s key market segments following the merger.