Digital Twin for Intelligent Parcel Sorting: Advancing Real-Time Management and Optimization in Logistics Networks
Parcel distribution centers (PDCs), as the pivotal nodes in logistic networks, facilitate parcel sorting, consolidation, and distribution. In the past decades, the rapid growth of e-commerce and steadily increasing parcel volumes have imposed big challenges on the efficiency and reliability of PDCs. Though recent studies have focused on using simulation-based approaches for decision-making at PDCs, the dynamic and complex nature of logistics networks is yet to be thoroughly captured due to the commonly used simplified simulation models with idealized assumptions. Our work aims to establish a parcel-sorting digital twin system (PSDTS) under practical settings, with real-time responses, sufficient fidelity, and high real-world applicability. This paper presents the detailed design and implementation of the PSDTS in PDCs, which is the first industrial digital twin system deployed in logistics. Specifically, we first establish a standardized Industrial Internet of Things (IIoT) framework that ensures seamless integration of heterogeneous sorting devices, enabling standardized data transmission and processing. Then, based on the standardized IIoT framework, the PSDTS is capable of real-time interaction, precise validation, and intelligent management, achieving a new level of operational transparency and system optimization. Validation across various PDCs with real-world sorting data demonstrates the exceptional accuracy of the PSDTS, providing a robust foundation for intelligent operations, optimization, and real-time decision-making. This work represents a significant step forward in intelligent logistics management and operational optimization, setting a cornerstone for the continued evolution of logistics networks driven by Digital Twin technology.
Authors
- Wei Zhang (ORCID: https://orcid.org/0000-0001-6563-2322)
- Renming Liu
- Li Ran (ORCID: https://orcid.org/0000-0002-9626-6799)
- Chuan Huang (ORCID: https://orcid.org/0000-0001-5965-0823)
- Liang Liao (ORCID: https://orcid.org/0009-0005-0022-9678)
- Yuanming Tian (ORCID: https://orcid.org/0000-0003-3211-7820)
Institutions
- Chinese University of Hong Kong (HK)
- Chinese University of Hong Kong, Shenzhen (CN)
Publication Details
- Published
- 2025-03-26
- DOI
- https://doi.org/10.1109/icit63637.2025.10965291
- Primary Topic
- Advanced Manufacturing and Logistics Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00