Supply chain 4.0 and the digital twin approach: a framework for improving supply chain visibility
| dc.contributor.author | Sani, Shehu | |
| dc.contributor.author | Zarifnia, Alireza | |
| dc.contributor.author | Salonitis, Konstantinos | |
| dc.contributor.author | Milisavljevic-Syed, Jelena | |
| dc.date.accessioned | 2024-10-22T13:00:16Z | |
| dc.date.available | 2024-10-22T13:00:16Z | |
| dc.date.freetoread | 2024-10-22 | |
| dc.date.issued | 2024-10-15 | |
| dc.date.pubOnline | 2024-10-15 | |
| dc.description.abstract | The emergence of Industry 4.0 has led to an increased level of complexity in supply chain operations. As a result, innovative approaches are required to improve visibility. Conventional approaches such as optimisation and simulation are no longer adequate for ensuring visibility across the entire supply chain. The aim of this study is to explore the potential of digital twins (DT) within the domain of supply chain management. A comprehensive DT framework is formulated utilising the Genetic Algorithm (GA). The results emphasise the potential of DT in promoting data-driven decision-making, improving visibility, and optimising SC operations. This study attempts to fill the current gaps in knowledge, offering significant insights for stakeholders in the supply chain. | |
| dc.description.conferencename | 34th CIRP Design Conference 2024 | |
| dc.description.journalName | Procedia CIRP | |
| dc.format.extent | pp. 321-326 | |
| dc.identifier.citation | Sani S, Zarifnia A, Salonitis K, Milisavljevic-Syed J. (2024) Supply chain 4.0 and the digital twin approach: a framework for improving supply chain visibility. Procedia CIRP, Volume 128, October 2024, pp. 321-326. 34th CIRP Design Conference, 3-5 June 2024, Cranfield University, UK | en_UK |
| dc.identifier.elementsID | 555063 | |
| dc.identifier.issn | 2212-8271 | |
| dc.identifier.uri | https://doi.org/10.1016/j.procir.2024.03.014 | |
| dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/23088 | |
| dc.identifier.volumeNo | 128 | |
| dc.language | English | |
| dc.language.iso | en | |
| dc.publisher | Elsevier | en_UK |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | 4014 Manufacturing engineering | |
| dc.subject | Digital twin | en_UK |
| dc.subject | Industry 4.0 | en_UK |
| dc.subject | Supply chain management | en_UK |
| dc.subject | Visibility | en_UK |
| dc.subject | Genetic Algorithm | en_UK |
| dc.subject | Resilience | en_UK |
| dc.title | Supply chain 4.0 and the digital twin approach: a framework for improving supply chain visibility | en_UK |
| dc.type | Article | |
| dcterms.coverage | Cranfield, UK | |
| dcterms.dateAccepted | 2024 | |
| dcterms.temporal.endDate | 05-Jun-2024 | |
| dcterms.temporal.startDate | 03-Jun-2024 |