Shipping has never recorded more about what happens onboard its ships. Maintenance histories, machinery data, inspection findings, and fault reports can now follow a vessel through years of its working life. Yet, when a problem reappears, the person dealing with it may still be encountering it for the first time.
The gap between recording a ship’s past and actually learning from it is becoming increasingly important as AI, digital twins, and condition-monitoring systems move deeper into vessel operations. A ship might remain in service for 25 or 30 years, but its crews will not. So, for example, an unusual machinery fault may have been encountered and solved years earlier, but how readily can the engineer facing it today discover what happened, why a particular repair was chosen, and whether the same symptoms have appeared before?
The information may already exist. The challenge is turning it into usable knowledge.
Until recently, retrieving that history largely depended on someone knowing what to look for and where to find it. Maintenance systems might hold one part of the story, sensor data another, and reports or inspection records yet another. Some of the most valuable context may never have made it into a structured database at all.
AI potentially changes that equation. The significance is not simply its ability to predict when a component might fail. Increasingly capable systems can interrogate large volumes of historical information together, potentially allowing an engineer to ask not only what is happening now?, but has anything like this happened before?
That could make a vessel’s accumulated experience far more useful to successive crews. It also raises the possibility of going further. If a recurring problem can be identified from the history of one ship, could experience across sister vessels or an entire fleet reveal patterns that no individual engineer would ever encounter often enough to recognise?
There is an important limitation. Ships generate data; seafarers generate knowledge. Why an engineer rejected one solution, what they noticed before a failure, or which apparently minor detail proved important, may exist only in conversations and professional memory. AI cannot retrieve knowledge that was never captured, and poor or incomplete records can produce misleading conclusions.
That makes this as much a knowledge-management challenge as a technology one. As shipping invests in increasingly sophisticated systems for collecting information, it also needs to consider what experience is worth preserving, how it is recorded, and who should have access to it as crews, managers, and owners change.
The opportunity is therefore not to give ships a memory. They already have one, scattered across decades of records, systems, and people. It is to make that memory usable, so that the next person confronting the problem does not have to learn a lesson the ship has already learned.
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Words by Robert Platt, Head of Content, Intent Communications Photo Credit: Pixabay.com
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