Abstract
With the boom of E-commerce in recent years, the third-party logistics (3PL) gains much favor for its large scope of service provided and economy of scale. Meanwhile, in the face of oceans of parcels to deliver, it casts requests on the efficiency of warehouse management to meet the need of customers. However, most companies conduct warehousing operations still relying on the paper for guiding and recording, and information is rarely shared even in the same company. Besides, few big companies are pursuing an automatic system to replace manpower, but in effect, the system is too mass and complicated to be stable and robust in usage. In this study, an IoT-enabled cyber-physical system assisted with wearable devices and wireless communication technologies, like RFID and Bluetooth, has been developed to cooperate with kinds of stakeholders to achieve higher operational efficiency. It has been deployed in a 3PL automotive-parts company at the Great Bay Area in China as a case study. Their nationally distributed warehouses realized real-time synchronizations of operations and information sharing within the company. Moreover, it not only highlighted the sustainability by nearly removing the paper in operations but also enhanced visibility and traceability throughout the whole process. The framework of the system and workflow proposed here can be duplicated or adjusted by other enterprises who share similar features. The success of this practice may motivate more 3PL companies to adopt cutting-edge technologies to create effective solutions for warehouse management.
Original language | English |
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Pages (from-to) | 16-23 |
Number of pages | 8 |
Journal | Procedia Manufacturing |
Volume | 49 |
DOIs | |
Publication status | Published - Oct 2019 |
Externally published | Yes |
Event | 8th International Conference on Through-Life Engineering Services, TESConf 2019 - Cleveland, United States Duration: 27 Oct 2019 → 29 Oct 2019 |
Keywords
- Case Study
- Internet of Things (IoT)
- Logistics System
- Real-time
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Artificial Intelligence