Decision Support Framework using Knowledge Based Digital Twin for Sustainable Product Development and End of Life
Year: 2023
Editor: Kevin Otto, Boris Eisenbart, Claudia Eckert, Benoit Eynard, Dieter Krause, Josef Oehmen, Nadège Troussier
Author: Mouflih, Chorouk (1); Gaha, Raoudha (1); Durupt, Alexandre (1); Bosch-Mauchand, Magali (1); Martinsen, Kristian (2); Eynard, Benoit (1)
Series: ICED
Institution: 1: Université de Technologie de Compiègne; 2: Norwegian University of Science and Technology
Section: Design Methods
Page(s): 1157-1166
DOI number: https://doi.org/10.1017/pds.2023.116
ISBN: -
ISSN: -
Abstract
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 management, digital twin, Sustainability, Decision making, Design engineering