Vessel monitoring and design in industry 4.0

A data driven perspective

Conference Paper (2016)
Author(s)

Luca Oneto (Università degli Studi di Genova)

Davide Anguita (Università degli Studi di Genova)

Andrea Coraddu (DAMEN Shipyards Singapore)

Toine Cleophas (DAMEN Shipyards Singapore)

Katerina Xepapa (DAMEN Shipyards Singapore)

Affiliation
External organisation
DOI related publication
https://doi.org/10.1109/RTSI.2016.7740594
More Info
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Publication Year
2016
Language
English
Affiliation
External organisation
ISBN (electronic)
9781509011315

Abstract

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.

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