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DECISION SUPPORT FRAMEWORK USING KNOWLEDGE BASED DIGITAL TWIN FOR SUSTAINABLE PRODUCT DEVELOPMENT AND END OF LIFE

Published online by Cambridge University Press:  19 June 2023

Chorouk Mouflih ,
Raoudha Gaha ,
Alexandre Durupt ,
Magali Bosch-Mauchand ,
Kristian Martinsen  and
Benoit Eynard
Chorouk Mouflih*
Affiliation:
1 Université de Technologie de Compiègne;
Raoudha Gaha
Affiliation:
1 Université de Technologie de Compiègne;
Alexandre Durupt
Affiliation:
1 Université de Technologie de Compiègne;
Magali Bosch-Mauchand
Affiliation:
1 Université de Technologie de Compiègne;
Kristian Martinsen
Affiliation:
2 Norwegian University of Science and Technology
Benoit Eynard
Affiliation:
1 Université de Technologie de Compiègne;
*
Mouflih, Chorouk, Laboratoire Roberval, France, [email protected]

Abstract

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In order to have a sustainable disassembly process, a successful decision-making based on reliable and up-to-date information should be made while taking into consideration sustainability indicators. In this context, The aim of this paper is to introduce a decision support system based on knowledge based and digital twin in order to help stakeholders to choose the most sustainable disassembly scenario .In this research, firstly, we presented the state of art of disassembly process, digital twin, knowledge based system and the merging of knowledge based system and digital twin for disassembly. Secondly, we presented the knowledge based digital twin (KBDTw) system framework for a sustainable disassembly process. Thirdly, a case study is presented about the use of KBDTw in the end-of-life of internet boxes. Finally, a conclusion and future work are conducted.

Keywords

Knowledge managementdigital twinSustainabilityDecision makingDesign engineering
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 1157 - 1166
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

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