What if you could test and refine your strategies without risking a single actual resource? That’s the true power of the digital twin supply chain.
Curious if your supply chain can handle a 25% spike in demand? Fire up a virtual replica to find out. Unsure if your inventory levels can handle unexpected disruptions? Simulate various scenarios and adjust before problems arise. Wondering how a supplier shutdown in China could ripple through your supply chain? Model it before it happens.
Digital twin technology lets you create real-time replicas of your entire supply chain network for scenario testing. It offers end-to-end visibility into your supply chain, making it easier to understand bottlenecks, analyze operational risks, and uncover optimization opportunities.
What is Digital Twin Technology?
A digital twin is a virtual replica of a physical object or system that mirrors its real-world behaviors, characteristics, processes, and performance. It connects to every aspect of your system and uses real-time data and simulation techniques to create a dynamic replica for scenario planning and decision-making.
In a responsive supply chain, digital twin technology is most helpful in logistics optimization and risk mitigation. It bridges the gap between theoretical forecasting and real-world variability, enabling continuous adaptation to shifting market conditions.
Benefits of Digital Twin Technology in Supply Chain Management
Several competing forces are exerting pressure on the supply chain:
- Rising wages for manufacturing, warehouse, and delivery employees.
- Consumer demand for low-priced products delivered by fast free shipping.
- Murky visibility into future macroeconomic disruptions.
Under these circumstances, organizations that don’t recalibrate their supply chain operations risk falling behind. Digital supply chain twins can help with the recalibration.
Real-Time Visibility
With so many interconnected moving parts and constantly changing market conditions, monitoring supply chains can be complicated. Using real-time data, a replica of your supply chain lets you see every facet of your operations:
- Your processes at any level
- Risk and bottlenecks
- Demand
- Inventory levels
- Supplier and sales data
With a supply chain twin, you can run any number of “what if” scenarios without real-life risks to gather actionable insights for achieving your goals.
Predictive Capabilities
Combined with modern predictive AI, a supply chain twin can be predictive and prescriptive. It collects and analyzes data from systems that manage inventory, demand, logistics, and production to help you anticipate future scenarios and optimize operations before issues arise. You can forecast demand fluctuations and adjust inventory levels accordingly. You can also analyze supplier performance, weather patterns, and geopolitical risks to foresee supply chain bottlenecks.
Improved Decision-Making
Customer-centric supply chains and their ecosystems are extremely complex. Without a way to simulate scenarios, you have to make a lot of judgment calls. Supply chain digital twins let you evaluate different choices and vet many scenarios to help you make faster, more informed operational decisions. The simulation assesses what’s happening now in your supply chain and what will happen if you make specific changes.
Key Components of Digital Twin Technology
A digital twin system involves several components that allow data flow between physical and digital domains to create an accurate, real-time representation of supply chain operations. Here are the three main systems in a virtual replica:
Data Integration
Digital twins aggregate data from various supply chain resources, such as IoT devices, enterprise systems, sensors, and external data streams. The integration includes:
- Real-time data
- Historical data
- Operational data
- Environmental data
You want to ensure continuous integration of real-time and historic data so your digital twin provides a comprehensive and accurate representation of your supply chain.
Simulations and Modeling
Once data is integrated, simulation tools create virtual versions of physical systems and processes. These models mimic real-world behaviors of physical assets, allowing you to test your system under various conditions and see how they respond. Advanced simulation powered by AI and machine learning can even predict the outcomes to help you make better decisions before changes happen in the real world.
Analytics and Insights
Analytics and insights are critical components of the digital twin because they help you understand and interact with your replica by transforming raw data into actionable information. Advanced analytics uncovers patterns and trends, providing valuable insights. These insights drive predictive maintenance, demand forecasting, process optimization, and other strategies that enhance supply chain efficiency and resilience.
Difference Between Digital Twins and Traditional Simulations
While digital twins and traditional simulations both use virtual model-based simulation, they are not the same. Digital twins are dynamic, real-time virtual replicas that continuously receive live data from sensors and other sources. They evolve with their physical counterparts.
On the other hand, traditional simulations are static models that analyze predefined scenarios using historical or estimated data. Once created, they don’t update in real time and require manual adjustments to reflect new conditions.
Challenges in Implementing Digital Twin Technology
While 86% of business leaders report that digital twin technology is applicable to their organization, many struggle with unexpected obstacles. Here are some common challenges you can expect:
Data Integration and Interoperability:
Integrating data from diverse sources across the supply chain is complex and requires consistent data quality and standardized governance practices.
Scalability and Performance
Managing large-scale, real-time integrations of digital twins demands substantial computing power and efficient data processing capabilities.
Security and Privacy Concerns
Continuous data exchange in digital twin systems increases the risk of cyber threats and unauthorized access. You need to deploy robust security measures to protect sensitive information.
Industries Utilizing Digital Twin Technology
Digital twin technology is transforming various industries. Here are some key sectors leveraging digital twins:
Manufacturing
Manufacturers use digital twins to optimize product lines, predict equipment failure, and improve product design.
Supply Chain and Logistics
Digital twins provide end-to-end visibility into supply chains, allowing businesses to anticipate disruptions, optimize inventory levels, and streamline logistics operations.
Healthcare
Hospital and medical researchers use digital twins to simulate patient conditions, enhance personalized treatments, and improve medical device performance before real-world applications.
The Future of Supply Chain Management With Digital Twins
Leading companies are already turning to digital twins to ensure their supply chains are flexible, agile, and responsive enough to overcome unexpected disruptions. As the technology evolves, its role in supply chain transformation management will continue to expand in various key areas. At Surgere, we combine industry expertise and cutting-edge IoT technology to help you create a digital twin that improves supply chain management. Our solutions provide seamless data integration, end-to-end visibility, and insight to help you get the most out of your digital twin. Contact us today to learn how our systems can help you optimize your supply chain and improve operational efficiency.
