As C-Job continues to grow, it is increasing investment into its in-house Research & Development department. As a consequence, the company’s R&D team has been able to significantly expand its scope of work. One of the latest research subjects looks at the potential of using AIS position data from existing vessels to optimise new designs.
Automatic Identification System
Recapping about AIS, the acronym for Automatic Identification System. By regularly transmitting data regarding a vessel’s location, AIS is used to share information about identification, position, course and speed. Together with conventional radar, it is primarily used as a collision avoidance tool for ships. AIS is mandatory for vessels with a gross tonnage above 300 GT on international voyages, although in practice many more smaller vessels also use the system.
Employing the AIS data to optimise new vessel designs
C-Job R&D Engineer Matthys Dijkman explains how C-Job is employing the AIS data: “We are combining AIS position data with ship data from our own Reference Database – containing detailed information from more than 170,000 vessels – to reconstruct a vessel’s operational profile. With this knowledge we can design vessels that will better meet their operational requirements.”
The initial research has focused on Trailing Suction Hopper Dredger (TSHD) designs, and, in doing so, C-Job’s R&D team has gathered AIS data from 40 TSHDs over a period of several months. The data set is unquestionably large, due to the fact that vessels transmit information every four minutes.
“By analysing these data, we see that TSHDs have a very well-defined and repetitive operational proﬁle that consists of four principal phases. This clear picture of the operational profile of a TSHD primarily includes: dredging, sailing with hopper ﬁlled, unloading, and sailing back with an empty hopper.”
After analysing the data, the next step has been to identify how it can help to further improve the way vessels are designed. The findings can be divided into three majors areas, as Matthys shows:
– From Design Point to Design Profile
In most design processes, a vessel is designed for one specific design point of, for example, a minimum required speed with a predefined deadweight. However, in reality, a vessel operates at a range of speeds and displacements.
“This approach actually complements our work into Accelerated Concept Design, where we utilise advanced genetic algorithms to create design variations best fit for their design requirements and objectives. The two areas of research generate a broader design profile instead of a single design point, thus optimising a design towards its expected use.”
– Rethinking design requirements
This involves developing specific requirements with the vessel owner in what can be seen as a move away from initial requirements for design, and towards initial requirements of the expected operational profile.
“The results of an AIS study combined with the C-Job Reference database are used to discover relationships between type of operation and ship design. This gives a better insight into which design parameters can be best chosen to fill any gaps in an owner’s fleet, thus maximizing potential profitability.”
– Vessel rankings
The combination of AIS data and the C-Job Reference database is also used to rank vessels in terms of their performance. This approach can be used when comparing vessels within a fleet or even with the fleets of multiple competitors.
“By understanding how and why certain vessels outperform others, more informed decisions can be made about new designs. They can be adapted to better match a client’s unique operational strategy. An example from the dredging sector could be like this: one operator carries a lot of spare parts to avoid downtime while at sea. Another operator only carries minimal spare parts to save weight, but has a better logistical network to get the spare parts if needed. These two different operational demands will call for two different designs.”
Across the board
Although the initial studies have been concerned with a dredger, Matthys is quick to point out that the research can also be used to investigate – and improve upon – vessels from all maritime sectors. “Each vessel type in each branch of the industry has a specific use, and we can design better vessels by analysing AIS data and implementing this knowledge in our designs.”
As well as C-Job’s own Reference database, the AIS data can also be linked with meteorological data sets. “When designing a ferry, we know that a vessel has a similar sailing route all year round. But by looking at seasonal weather patterns and extremes, we can optimise a design for normal conditions while making it fit enough to handle the extremes.”
Offshore wind installation vessels present a similar example: “With these vessels, the sailing profile from A to B is not that important – it’s the installation process that makes the money for an operator. Therefore, it is crucial to maximise a vessel’s operational window. In this case, we would look at weather and wave data for the proposed area of operations to design a vessel that is optimised for normal conditions while still having maximum uptime in more extreme conditions.”
Proactive, not reactive
C-Job’s R&D is not only growing in scope, but also in the number of employees. “With these increased resources, we are able to have a much more proactive approach. While R&D has always contributed to our designs, this has generally been as a reaction to project requirements. Now we are able to look further ahead – creating research programmes that will result in vessels more optimised for operation.”