2025/01/08 by Hai-nan Huang, Ting Qu, Xiao-hui Qiu +4 · 5 citations
Business, Management and Accounting · Engineering · #Business #Collaboration in agile enterprises #Computer science #Control reconfiguration #Distributed computing #Embedded system #Flexible and Reconfigurable Manufacturing Systems #Information sharing #Process management #Risk analysis (engineering) #Supply Chain Resilience and Risk Management #Supply chain #The Internet
paper · open access · doi:10.1080/00207543.2024.2448284
published in International Journal of Production Research 63(12), 4328-4350 (Taylor & Francis)
openalex publication_date 2025/01/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Disruptive environments, characterised by frequent contingencies, significantly challenge supply chain operations, particularly assembly supply chains with complex structures and decentralised decision-making. Failure to promptly reconfigure chains during disruptions may ripple adverse effects through the network, causing substantial losses. Consequently, decentralised dynamic reconfiguration of assembly supply chains under contingencies warrants attention. However, existing research on this topic is limited, necessitating further exploration utilising emerging technologies. Isolated information systems, such as MES and ERP, are widely deployed across firms and increasingly integrated into industry-level Industrial Internet Platforms (IIPs) to enhance information sharing and utilisation. Nevertheless, limited research explores the integration of real-time IIP data with reconfiguration mechanisms for resilient, flexible, and decentralised chain reconfiguration. Thus, this paper proposes an IIP-driven synchronised reconfiguration of supply chains (SyncRSC) solution inspired by the concepts of synchronisation and reconfigurable supply chains. SyncRSC employs the IIP architecture for real-time information support, a three-state mechanism as the qualitative method, and improved graph neural networks alongside augmented lagrangian coordination as quantitative methods. A case study of an air-conditioning supply chain verifies the superiority of the proposed methods and analyzes SyncRSC's performance under different disruption levels.