A digital twin is a virtual representation of a physical object, process or process system. It is based on real-time data and enables in-depth analysis and predictions. In the context of logistics, a digital twin is a virtual representation of a real supply chain. Using a digital twin makes it possible to carry out comprehensive, data-driven optimisation processes that encompass all levels of value creation. The concept is much more than a static imitation of a logistics system — it uses real-time data to make sure any changes are instantly reflected in the model, acting as a true-to-life digital representation.
A digital twin can help companies to really make the most of their smart supply chains. However, companies cannot truly tap into the full potential for value creation offered by a digitalised supply chain until their systems, machines and products have been integrated into this system through the use of digital twins.
Advantages of a smart supply chain
Process optimisation, efficiency and cost savings — optimising supply chains to achieve maximum productivity with maximum efficiency has always been a balancing act. But the pressure to implement optimisations using smart technology has never been as acute as in recent years. Supply chains have faced many challenges in recent years, not least due to a global pandemic and multiple political crises. Many companies turned to the support of smart systems for solutions to these complex problems. According to the latest supply chain report by reichelt elektronik, which surveyed 500 industrial companies in Germany about their supply chain management (SCM), 41 percent have switched to a smart SCM system in the last 2 years. A further 22 percent plan to take this step over the next 12 months. Thanks to the growing range of compatible products such as smart glasses, smart gloves and scanners worn on the back of the hand as well as pioneering software technology for real-time evaluation, the barrier for entry for businesses is getting lower and lower. At the same time, process reliability is improving. This makes investment in these systems attractive to a wide range of companies.
Real-time monitoring
One of the greatest strengths of a smart supply chain monitoring solution is the ability to monitor the status of products, inventory and transport equipment in real time. “With the help of sensors, transponders and QR codes linked to NFC tags, all logistics processes can be monitored and combined into a single model”, explains Tobias Wölk, Product Manager for Automation Technology & Active Components at reichelt elektronik. “This makes it possible to monitor targets, immediately detect any potentially undesirable developments and issue alerts. This shortens the reaction time in the event of congestion, bottlenecks, unusual weather conditions, personnel shortages or technical failures. As a result, downtime costs can be avoided”. Real-time monitoring therefore plays an important role in ad-hoc troubleshooting and ensures your processes run smoothly.
While it is still possible to manually detect and correct malfunctions in small warehouses and logistics centres, this approach reaches its limits when applied to larger operations and storage capacities. Especially in large and complex warehouses, events requiring action can quickly exceed the capacity of the employees. For example, DHL has created a digital twin of its food processing warehouse in Southeast Asia. The AI-supported system contains 120,000 storage units in more than 2500 facilities. All incoming and outgoing goods are recorded by cameras and sensors and this data is fed into the digital twin in real time. It is easy to check which kinds of goods are in the warehouse and where there is storage space for new goods at any time. This ensures that easily perishable foodstuffs are transported to a suitable storage location within 30 minutes. These automated processes make the work of management personnel considerably simpler, while improving quality at the same time, as fewer goods are spoiled due to incorrect storage or long waiting times.
Inventory management
Real-time monitoring also helps users to keep an eye on their inventory at all times. This more precise inventory management prevents bottlenecks and excess stock. Furthermore, integrated systems can automatically update the inventory whenever products enter or leave the warehouse. This minimises the need for manual interventions and therefore prevents human error during inventory management.
“Automated alerts are issued as soon as the stock levels of a particular product fall below a pre-defined threshold, allowing supply chain managers to improve efficiency and respond to inventory problems at an early stage”, advises Tobias Wölk.
Smart solutions also enable the integration of supplier management. This allows companies to both accurately locate products in their own warehouse and keep an eye on ordered goods throughout the entire transport process. Supply chain managers are therefore able to determine the exact storage location of the goods as well as estimate when they will arrive.
Proactive problem solving and improved forecasting
All of the data collected during monitoring and optimisation can also be evaluated to provide medium- and long-term support for process optimisation. The goal is to find solutions and improvements by identifying patterns in everyday operations. Artificial intelligence and machine learning can be used to analyse enormous amounts of data automatically. They help predict problems and even proactively suggest solutions.
However, one of the challenges companies still face is supplying the automated systems with sufficient high-quality data. As soon as companies implement processes that automatically pass data from monitoring systems to analysis systems, they are able to implement both short-term actions and long-term optimisations. For example, depending on the economic circumstances, the threshold values for certain critical components may need to be adjusted.
Increased transparency
Constant monitoring creates more transparency. In the EU, suppliers are obliged to provide their customers with information about delivery dates. The more accurate the insights suppliers have into the status of certain goods, the easier it is for them to comply with this requirement and to provide customers with precise delivery dates.
Furthermore, when suppliers have an overview of their logistics processes, they are better able to calculate the associated costs. It is usually difficult to determine the total cost of a supply chain. The usual logistics costs, recorded using traditional cost centre accounting, generally do not match up exactly with the actual total costs of the supply chain. Potential savings along the supply chain can be more accurately identified if the costs are calculated more transparently and in a less general manner. Companies can use supply chain monitoring to improve the availability of their data and thus report their costs more transparently.
Sustainability
Last but not least, optimising the supply chain also contributes to better environmental protection. By optimising routes and using resources more efficiently, companies not only save money, but also reduce their CO2 emissions automatically. Furthermore, AI-based tools are able to provide targeted suggestions for reducing waste and CO2 emissions as well as increasing the sustainability of your operations by evaluating all operational data.
Why digital twins are indispensable for smart supply chains
Automation is an essential part of smart supply chains. Using technologies such as robots, autonomous vehicles and automated warehouses can help companies to increase their efficiency. However, companies can only tap into the full potential of a digital supply chain when the machines, systems and robots they use are also represented in a digital model—a digital twin—and integrated into supply chain management.
Digital twins — how can they help you?
A digital twin is a model of a machine, a system or a product that is more than just a 3D model. It also contains information about the functionalities and operation of the system. In the automotive industry, for example, this means that the digital twin of an engine enables virtual tests and simulations to be carried out to check the engine’s performance, efficiency and response to various environmental conditions before the physical product is even manufactured.
“A large number of companies in the manufacturing industry are already using digital twins in their systems to monitor the status of the machines in real time”, explains Tobias Wölk. “By analysing operational data, they can predict potential malfunctions and outages and avoid the need to carry out preventive maintenance. This prevents costly unplanned production downtime”. In addition, engineers can simulate different production processes in the model to maximise their efficiency, identify bottlenecks and optimise production capacity.
Digital twins and supply chains go hand in hand
While the benefits of digital twins described above ultimately contribute to the efficiency of the supply chain, they are more likely to be driven by production. However, digital twins can also be expanded to bring significant benefits to the supply chain. In addition to the functionalities of a product, the manufacturing process can also be part of a digital twin. This includes, for example, selecting the appropriate production machines and tools, material tests and the selection of suppliers. This allows planning to be more precise and costs to estimated even more accurately. This step is also particularly important when it comes to meeting sustainability targets. More and more companies are taking the entire lifecycle of new products into account during the development phase. This also applies to the development process itself and the suppliers involved. This step in particular also makes it easier to compile the documentation required for supply chain due diligence obligations.
What’s more, the use of a digital twin at this early stage of development reduces resource consumption — and costs too, since the first prototypes are purely digital objects. It is only at a later stage of development when the product is more sophisticated that the first physical version is created, meaning that fewer materials are used overall. If new machines need to be purchased and integrated into the production process, creating a digital model for virtual commissioning is advantageous, as this allows the interoperability to be tested and the interaction of the machines to be refined before the physical machine is installed.
Agile responses to goods availability
An additional advantage is that different scenarios regarding the availability of goods and various supply situations can be simulated as soon as a new product is created. In this way, it is possible to build a resilience to goods shortages into the design. For example, a product can be designed so that certain parts that are often affected by supply bottlenecks can be easily replaced with alternative components without affecting the functionality of the product. Even with existing products, a digital twin can be useful for testing the functionality and compatibility of an alternative component in a simulated model first, before any goods shortages occur. And even if goods shortages occur, a digital twin helps to keep track of whether the alternative component exhibits different behaviour to the planned behaviour of the original component. Accurate monitoring of data allows deviations to be detected quickly and corrected if necessary. This means that the best product quality is always guaranteed, even when there are supply chain challenges.
Conclusion
The integration of a digital twin into a smart supply chain offers numerous advantages. This virtual image of physical objects, processes and systems not only enables comprehensive, data-driven optimisation, but also establishes a direct link between digital representation and the real product. However, in order to take full advantage of the benefits of a digital supply chain, it is essential to integrate all of the systems, machines and products.
There are many advantages to a smart supply chain, especially supply chain monitoring and digital twins. Real-time monitoring, automated alerts and accurate inventory management help to increase efficiency. Proactive problem solving and advanced forecasting enable users to not only respond to current challenges, but also to implement long-term optimisation. Constant monitoring increases transparency for customers and simplifies cost tracking.
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