Abstract
Current research on digital twins provides a solid foundation for asset synchronization and cross-border supply chains, but it fails to address issues such as data quality management across organizational boundaries, model uncertainty, network risks, and decision-making authority. This study constructs a trustworthy network digital twin architecture, differentiating perception and event capture, edge verification, semantic interoperability, federated twin services, and human-machine decision coordination through key findings from integrated standards and peer-reviewed research. Traceability, uncertainty management, and policy enforcement are integrated across these layers. This framework aims to promote autonomy and network coordination at the local plant level, but sensor drift, semantic heterogeneity, logistical delays, and jurisdictional limitations may restrict its portability. Further research is needed through simulation, hardware-in-the-loop experiments, and multi-site comparative field studies.
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