Vessel monitoring and design in industry 4.0: A data driven perspective
| Autor: | Andrea Coraddu, Toine Cleophas, Davide Anguita, Luca Oneto, Katerina Xepapa |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Decision support system
Engineering Industry 4.0 Computer Networks and Communications business.industry Condition-based maintenance Biomedical Engineering Energy Engineering and Power Technology Instrumentation Computer Science Applications1707 Computer Vision and Pattern Recognition Human Factors and Ergonomics 020101 civil engineering 02 engineering and technology Process automation system Automation 0201 civil engineering Data-driven Data modeling 0202 electrical engineering electronic engineering information engineering Systems engineering 020201 artificial intelligence & image processing State (computer science) business Simulation |
| Zdroj: | RTSI |
| DOI: | 10.1109/rtsi.2016.7740594 |
| Popis: | The main purpose of this work is to build a data driven model to create realistic operating profiles in order to assess and compare different design solutions. The proposed approach takes advantage on the new generation of automation systems which allow gathering a large amount of data from on-board machinery. A data driven modeling of the operational profiles of the vessel (and in general of the fleet) could provide a tool both to diagnose and predict the vessel's state (e.g. for condition based maintenance purposes), for improving the performance and the efficiency of the vessel, and for improving design solutions. The diagnosis and prognosis of the ship's performance can be used as decision support in determining when actions to improve performance should be taken. The developed model will be tested on a real DAMEN vessel where on-board sensors data acquisitions are available from the automation system. |
| Databáze: | OpenAIRE |
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