Scientists

Simon Mewes (geb. Burmester) M. Sc.
Changqing Jiang M. Eng.
Dr.-Ing. Udo Lantermann
Dr.-Ing. Jens Neugebauer
Prof. Dr.-Ing. Bettar Ould el Moctar

Project Description

Due to the rapidly advancing automation onboard ships, operators have an extensive database at hand which may be used to assess ships operations. An evaluation of the data offers considerable potential for more efficient, safe and environmentally friendly operation. In addition, new tools have been developed to monitor the on-board equipment, to determine maintenance intervals, and to improve ship safety. This data can also play an important role in the design of new ships and on-board installations. The main objectives of the project are:

1. to collect spatially and temporally high-resolution ship operation data (e.g., propulsion and manoeuvring relevant data) as well as environmental conditions with different systems: on board, via satellites and ashore, their processing and provision via a cloud-based IT infrastructure (distributed Big Data Management).
2. development of knowledge-based filtering methods (artificial intelligence - AI) and sound validation methods: from Big Data to Smart Data, considering inherent uncertainties.
3. developing recommendations for measures to reduce the energy consumption during ship operation based on operating data evaluation and an allocation of additional energy consumption occurring.
4. determination of load spectra based on long-term measurements of propeller forces.
5. determination of representative operation scenarios of ships for "retrofit" and newbuilding projects, evaluation of energy saving potentials.

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Figure 1: In the DigitShip project, data of the MSC Bari (ship owner CPO) are collected and processed to achieve the goals named. Source: https://www.marinetraffic.com