Smart Design for Ships in a Smart Product Through-Life and Industry 4.0 Environment (original) (raw)

Hock, Joo, Goh, Cindy ORCID logoORCID: https://orcid.org/0000-0001-6735-9972 and Li, Yun ORCID logoORCID: https://orcid.org/0000-0002-6575-1839(2016) Smart Design for Ships in a Smart Product Through-Life and Industry 4.0 Environment. In: 2016 IEEE Congress on Evolutionary Computation (CEC), Vancouver, BC, Canada, 24-29 Jul 2016, pp. 5301-5308. ISBN 9781509006236(doi: 10.1109/CEC.2016.7748364)

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Abstract

As the world becomes more connected and customer’s ‘needs and wants’ lean more towards bespoke products, the way they are designed and manufactured must adapt. Recognised as the main driver for the future of the manufacturing value chain, Industry 4.0 (i4) is rapidly gaining momentum worldwide. One of the key enablers of the i4 design model to achieve mass customisation manufactured at a mass production cost is the computational intelligence based Computer-Automated Design (CAutoD). This paper demonstrates how CAutoD realises the i4 concept for smart design of future ships and smart ships through-life. Following an overview of the i4 and CAutoD interface, a smart ship design technique is introduced to form an automated closed-loop approach to the entire ship design process. Then, key challenges and future directions on this roadmap are discussed. Lastly, a framework in which the concepts of morphing and free-form deformation are embedded into an evolutionary algorithm is developed to automate the design and optimisation process of the hull form.

Item Type: Conference Proceedings
Additional Information: This research is funded by Economic Development Board (EDB) of Singapore and Sembcorp Marine Ltd. under Industrial Postgraduate Programme (IPP) grant no: COY-15-IPP/140002.
Status: Published
Refereed: Yes
Glasgow Author(s) Enlighten ID: Goh, Professor Cindy Sf and Li, Professor Yun
Authors: Hock, J., Goh, C., and Li, Y.
College/School: College of Science and Engineering > School of EngineeringCollege of Science and Engineering > School of Engineering > Systems Power and Energy
ISBN: 9781509006236
Copyright Holders: Copyright © 2016 IEEE
First Published: First published in 2016 IEEE Congress on Evolutionary Computation (CEC): 5301-5308
Publisher Policy: Reproduced in accordance with the publisher copyright policy
Related URLs: Organisation

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Deposit and Record Details

ID Code: 118544
Depositing User: Mr Gavin Merrifield
Datestamp: 29 Apr 2016 11:49
Last Modified: 22 Sep 2021 18:37
Date of acceptance: 16 March 2016
Date of first online publication: 21 November 2016
Date Deposited: 29 April 2016
Data Availability Statement: No