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Digital twin technology within the supply chain – simulation and optimization in real time

by Editorial Office

Advancing digitization has profoundly changed the logistics industry by opening up new opportunities for greater transparency and efficiency: Modern technologies enable seamless networking and data integration along the entire supply chain. This allows companies to optimize their operational processes and react quickly to dynamic market conditions. As a virtual representation of physical supply chain processes, the AI-based digital twin is also playing an increasingly important role in the management of complex supply chains. We discuss how a digital twin works, what advantages the approach offers and how it can be implemented in practice.

Digital twin – the advantages for companies

As a virtual replica of a physical system or process, the digital twin offers companies the opportunity to simulate, analyze and optimize processes along the supply chain. It is based on real-time data collected via the Internet of Things. The approach creates a dynamic model that can be used to run simulations of various scenarios in order to predict future conditions – without having to intervene directly in the actual operational processes. The digital twin maps all elements of the supply chain, from procurement and production through to distribution and delivery to the end customer.

This is how companies benefit from a digital twin:

  • Increased transparency: The virtual copy makes the entire supply chain more transparent. Companies can track where their goods are located and how processes are running. This transparency is crucial for quickly identifying and eliminating inefficiencies.
  • Proactive risk management: By simulating various scenarios, managers can develop strategies in advance to minimize risks and potential disruptions. In this way, preventive measures can be taken before actual problems occur.
  • Optimized operations: The ability to test possible operations in a simulated environment before implementing them in the real world reduces the risk of wrong decisions and promotes a more efficient supply chain design.
  • Reduced costs: By optimizing processes and identifying errors at an early stage, companies can significantly reduce their financial outlay. Key benefits that contribute to the reduction of costs are less waste, an improved asset utilization and seamlessly coordinated logistics processes.
  • More sustainability: Companies also benefit from a digital twin of their supply chain when it comes to meeting sustainability criteria. By analyzing end-to-end data, low-energy and low-emission supply models can be calculated and developed that reduce the ecological footprint without having to intervene in ongoing processes on a trial basis. By precisely monitoring and evaluating all information, inefficient transport routes can be identified, suppliers with lower emission profiles may be preferred and more sustainable packaging solutions can be sought.

Implementation of a digital twin and best practices

The implementation of the digital twin requires careful integration of real-time data provided via a collaborative network. This data needs to be embedded in a precise, dynamic model of the physical supply chain that reflects both the physical and operational aspects. The challenge lies in creating a seamless connection between the virtual replica and existing IT systems, such as SCM and ERP software, in order to ensure a continuous data synchronization and analysis. It is also necessary to constantly evaluate and adapt the model in order to maintain and further optimize the accuracy and relevance of the twin.

Modern digital twins integrate ML algorithms (machine learning) to recognize patterns in the data and develop self-learning models. These can adapt to changing conditions and continuously improve. By linking to blockchain, a secure and unalterable record of transactions and movements within the supply chain is guaranteed. With the help of advanced visualization tools, the complex data collected is displayed in such a way that users can intuitively understand and interpret it. 3D visualizations and interactive dashboards support rapid decision-making and facilitate collaboration between different departments and stakeholders.

After the successful implementation and linking, companies are offered a comprehensive range of application options that go far beyond simple visualizations:

  1. Optimization of the transport route: A digital twin enables globally active companies to adapt transport routes in real time. By integrating traffic data, weather information and vehicle condition monitoring, the system can suggest more efficient routes in the event of sudden traffic disruptions, reroute the fleet, thereby shortening delivery times and reducing fuel costs. By analyzing historical data, the digital twin recognizes patterns and reports which routes are likely to experience disruptions at certain times. These predictive components make it possible to proactively consider alternative transportation routes and schedules. By simulating different transportation scenarios under varying conditions, the most efficient method can be determined.

 

  1. More efficient warehousing: By simulating different inventory strategies, companies are able to reduce their storage costs in the long term. The digital twin does not only model the physical warehouse conditions, but also delivery times, demand forecasts and supplier performance data. For example, it can automatically trigger repeat orders if the stock falls below a certain threshold. In turn, the arrangement of goods can be optimized by visualizing the warehouse layout. This holistic view enables a precise prediction of the optimum stock quantity and reduces the risk of overstocking or stock-outs.

However, as the results of the 19th Hermes Barometer show, many companies are still faced with the task of mapping their supply chain processes transparently: Only one in five logistics managers surveyed (20 percent) agree that they already have a digital real-time supply chain.

Conclusion and outlook: The digital twin as a driver of innovation in the supply chain

The digital twin is a transformative technology that has the potential to fundamentally improve the responsiveness, sustainability and efficiency of supply chains. By precisely mapping and simulating actual processes, workflows can be analyzed and optimized in real time. The implementation of a virtual copy increases the transparency of the supply chain. It therefore helps those responsible to manage risks in an agile manner and make data-based decisions. The technology of the digital twin is constantly evolving: Future improvements could include the enhanced modeling and faster processing of information, which in turn enables an even more accurate and timely response to changes in the supply chain.

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