| Abstract (ENG): |
Firms rely on their supply chain networks to ensure the supply and distribution of products. While modern ERP systems help firms to manage their standard business processes such as plan, source, make, deliver, and return, more sophisticated and complex situations arise in case of occurring risks, especially in the supply phase between own production plants and suppliers. Firms manage occurring risks with dedicated teams from different departments such as logistics, supply chain management (SCM), quality, or procurement. However, the given transparency using modern ERP systems is quite low, and the employees need additional information to take informed decisions. We have developed a supply chain network generator as the base for the first worldwide digital supply chain twin (DSCT). The DSCT includes all nodes from the network, such as harbors, ships, planes, production locations, routes, etc. In addition, different layers enhance users’ ability to visualize the world map with various information. For example, one layer visualizes environmental aspects such as flooding, tsunamis, and general weather conditions. Other layers include transport information of roads, the sea, or rivers. Furthermore, the DSCT enhances firms to integrate the Sustainable Development Goals of the United Nations and allows them to ensure compliance with the European Corporate Sustainability Due Diligence Directive (CSDDD) for supply chains. In addition, the visualization allows firms to analyze their supply chain networks, e.g., events occurring in the supply network such as the status of their shipment or tornadoes. Hence, the technology network generator serves as the base for all information about the supply chain network, while modern AR/VR technology visualizes the supply chain elements. We evaluated the DSCT in the lab and proofed its capability of visualizing the complete supply chain network in real-time, while we need to evaluate its capabilities with industry partners. |
| Citation: |
Cenk, Gökhan and Andersson, Jonas and Engel, Tobias
(2024)
Digital supply chain twin.
In: (Proceedings of the) International Conference on Applied Management Advances in the 21st Century 2024 (AMA21), December, 11-12, 2024, Virtual, pp. 33-38.
ISBN 9789898704634
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