How much can we improve hull performance using real hull data?
Our team of experts recently got together thought about the importance of Big Data in the shipping industry. The last decade has seen a rising interest in the applications of Big Data – the act gathering and processing large of data from specific sources and turning them into easy-to-read reports – and the Shipping industry is no exception.
In order to truly understand why processing large amounts of hull data captured during surveys, inspections and maintenance operations, Notilo Plus studied the impact of detailed reports and proactive actions on ship hulls on cost- and time-saving results. The following paragraphs are an abstract of our full whitepaper, which is available for download by submitting the form at the end of this article.
Fleet Performance has witnessed major optimizations in the last decades. One of the aims of these algorithms is to estimate the fuel performance loss due to hull fouling, and thus decide when it is time for hull cleaning. However, these methods are largely reactive and tend to postpone cleaning until no doubt remains of its need. The authors open the discussion on how much could be saved by feeding these fleet performance algorithms with the actual state of the hull, and how it could help to reach CII and green shipping targets more easily. Notilo Plus uses Artificial Intelligence to create reproducible data out of ship hull inspections. Here, we share preliminary work and thoughts on how some machine learning and digitization techniques could be used to assist in hull performance review and performance prediction. Digitalizing the hull thus opens a new world of opportunities to move from reactive hull cleaning to predictive maintenance.