Digital twin – application examples for the customs world

From Janine Lampprecht | 23. June 2021 | Reading time: 5 Minutes
Mann halt Hände gegeneinander, als würde er einen Ball halten. Zwischen dne Händen sind zahlreiche Bilder und Icons.

Before a t-shirt ends up in our closet, it has come a long way. What if I design my t-shirt on the computer and send it off for a test run? Let’s imagine that my digital t-shirt is a data cloud to which additional attributes are assigned and data are assigned at each station in its life cycle. In the course of the entire supply chain, information on material, size and weight, brand, EAN, customs tariff number, etc. is added to the data cloud, the digital twin of the T-shirt. Some of these datasets would be freely available to everyone; thus everyone could benefit from someone else’s digital twin.

Digital twin – more than just a model

The digital twin is the exact virtual representation of a product or system that exactly describes the individual properties of the real counterpart. So there is a 1: 1 relationship between the digital and physical world. The digital twin behaves in the virtual environment in the same way as the physical counterpart in reality. As a virtual image, with real data included, the digital twin enables all “what-if” questions to be answered. By simulating optimization approaches, the digital twin makes change effects visible as a whole.


The digital twin is already being used in the following areas:

Industrial manufacturing of technical products

Production and order control

Transport industry



Digital twins in the world of customs

Digital twins offer unmatched capabilities for tracking, monitoring, and diagnosing objects. You can transform supply chains in a number of ways to enable data-driven decision making, streamlined processes, and new business models.


Digital supply chain – platforms – goods tracking

Research projects from Bosch Connected Industry and the BMW Group are working on a digital twin for the supply chain. The Bosch project includes, for example, the seamless control of goods in multinational supply chains. Sensors on package level send status-relevant data to a gateway in real time. Together with position data, they are sent to the cloud and can therefore be used across companies. The package reports autonomously at defined points in the supply chain and the data is automatically transferred. BMW is researching a global supplier network with various logistics service providers. A program based on artificial intelligence ensures complete transparency in the supply chain. The position data of a good is updated every 15 minutes in order to identify possible delivery delays in good time. In logistics, digital twins can be used in a variety of applications along the entire value chain, for example in management of container fleets, monitoring of transports or design of logistics systems. For example, IoT sensors on individual containers indicate their location and monitor them for damage and contamination. This data flows into a digital twin of the container network, which uses machine learning to ensure that the containers are used as efficiently as possible. Digital twins not only can be used for individual objects, but also for entire networks and ecosystems such as warehouses by linking a 3D model of a facility with inventory and operational data. This means that the system can not only provide an overview, showing the machines’ condition and the availability of products, but also make predictions and autonomous decisions about stocks or transport activities.

For mechanical and plant engineering, greater transparency and connectivity of the supply chain offers potential for increasing efficiency. For example, capacity bottlenecks at suppliers’ or delays in customs clearance can be identified in good time and their effects on the completion of a machine or system can be assessed.

Ports, for example in France, are expanding their digital platforms to exchange information, with their partners in the port area, in order to make processing of goods more efficient. With the help of common standards, it should be possible to transfer ship movements in order to accelerate processing in the next port. In addition, a platform with blockchain technology will establish / develop further transport routes. This would enable the flow of goods to be recorded and transport to be optimized. However, data is not only fed into platforms manually, but increasingly also automatically. In addition, truck and rail traffic are to be integrated. Tracking boxes, which are linked to a sensor, can be used to confirm the integrity of the containers and thus speed up customs clearance.


Challenges for the use of digital twins

Internet-based platforms and IT security

Cross-manufacturer, global exchange of information takes place in the Internet of Things (IoT). The IOT contains a multitude of technologies for global information society infrastructure, which makes it possible to link physical and virtual objects with one another. Using digital twins, the industry 4.0 platform provides the basis for manufacturer-independent, global exchange of information. It sets the standards for communication, spoken across industries. Common standards regarding regulations for legal security, a European cloud infrastructure and 5G network infrastructures are not yet fully developed.

Questions regarding data protection, both internal and external, have to be organized in complex IT structures; on top, there is the additional work involved in obtaining consent.

Due to the lack of legal regulations on data sovereignty, ambiguities in ownership and usage rights must be clarified individually with the help of contracts. Furthermore, the organization of access authorizations and releases for the data must be stored so that sensitive and internal information does not become public.

Data quality as a success factor

The success or failure of the digital twin depends to a large extent on the data quality that the digital twin and the associated simulation access. The creation of a digital twin begins with the digitization of all data sources. Various forms of certification already exist to ensure uniform accuracy of all data from the digital twin.


Variety of technologies

Digital twins are not an isolated technology, but rather the intelligent combination of powerful digital trends such as AI, IoT, Big Data or 5G. Strategic design of digital twin usage requires a variety of technologies, which must be checked for availability, compatibility and maturity.



The digital twin is a great help and offers optimization possibilities in all areas of industry and in the service sector, for example in product design, where it helps the technology to meet new requirements and to solve existing problems faster and more cost-effectively. Predicting and eliminating hazards through simulations, assessing risks, improving quality assurance – all these buzzwords represent the potential of this technology in all areas of life.

On the other hand, digital twins can make an existing process unnecessarily complex. Because not all projects need a digital twin.

Furthermore, many technology providers are not yet ready to support the concept of digital twins. The full potential of a digital twin only unfolds when it is implemented across the board. Until then, it is advisable to tackle this major topic in small steps, e.g. in the form of internal projects.


Earth as a digital twin

With the “destination earth” initiative, the European Union (EU) wants to create a highly precise data twin of the world, within the European data strategy. Using concentrated research and industrial competence, data will be collected and processes modelled, to finally create a virtual glass globe representing our planet. Natural occurances and human influence will be visualised, watched and forecast. The earth’s twin is planned to be brought to life from 2021, to help drive sustainable development strategies.