A Sustainable Supply Chain Design for Personalized Customization in Industry 5.0 Era - Université de Lille
Article Dans Une Revue IEEE Transactions on Industrial Informatics Année : 2024

A Sustainable Supply Chain Design for Personalized Customization in Industry 5.0 Era

Résumé

Purpose: This research aims to present a distributed localized manufacturing (DLM)-based personalized customization Supply Chain (PCSC) model with facility siting, with the objective of enhancing the sustainability level of PCSCs within the context of Industry 5.0. Design/ methodology/approach: To accomplish the objectives, a DLM-based PCSC model is constructed, and the supply chain is optimized using a P-Median model with genetic algorithm. Furthermore, a hybrid simulation model, combining agent-based modeling and discrete event simulation, is employed to analyze and gather data on sustainable metrics. Findings: The implementation of the DLM-based PCSC model yields improvements in supply chain efficiency through cost reduction, risk mitigation, and enhanced responsiveness. By leveraging the decentralized manufacturing approach of DLM, organizations can minimize transportation distances, optimize resource utilization, and strengthen coordination among geographically dispersed facilities. Consequently, sustainability and overall performance within the supply chain are enhanced. Practical implications: This study offers valuable recommendations for stakeholders and managers, including the adoption of distributed local manufacturing, optimization of facility locations, and the integration of sustainability metrics analysis into decision-making processes. These measures contribute to the improvement of supply chain sustainability and performance. Originality/value: This article makes a significant contribution to the field by proposing a DLM-based PCSC model that incorporates facility siting. The employment of a hybrid simulation model presents an integrated approach to assessing supply chains. In addition, it expands the measurement of sustainability metrics and provides insights to enhance the sustainability and efficiency of PCSCs.
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Dates et versions

hal-04694277 , version 1 (11-09-2024)

Identifiants

Citer

Xingyuan Wang, Yufei Xue, Jie Zhang, Yan Hong, Song Guo, et al.. A Sustainable Supply Chain Design for Personalized Customization in Industry 5.0 Era. IEEE Transactions on Industrial Informatics, 2024, IEEE Trans. Ind. Inform., -, ⟨10.1109/TII.2024.3367038⟩. ⟨hal-04694277⟩

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