Imagine using real-time analytics to optimize warehouse operations or anticipating supply chain disruptions before they occur. Does that sound futuristic? No more. 

This is becoming a reality because of digital twins in supply chain management.

Here’s a surprising fact: Global supply networks experienced a 38% increase in interruptions in 2024, with factors ranging from labor strikes and factory fires to economic uncertainty and changes in leadership.. 

Thus,  firms are under tremendous pressure to increase productivity, lower risks, and make better decisions. 

So, the digital twin supply chain creates virtual versions of manufacturing lines, warehouses, and logistics networks.

The possibilities are endless, ranging from digital twin logistics that optimize fleet mobility to warehouse digital twin solutions that enhance inventory management. 

However, how precisely does digital twin technology operate, and why is it becoming so popular?

Let us get started!

A virtual representation of your supply chain operations is called a "digital twin in supply chain." It replicates every facet of your supply chain. This includes digital twins in the logistics market, distribution, manufacturing, and warehousing. 

An exact and flexible replica of the supply chain is produced by combining real-time data from sensors, IoT devices, and business systems.

Digital twin platforms continuously gather and evaluate data from different supply chain locations. The digital model is updated in real-time by the data it receives.

Here's how digital twins in the supply chain work:

• Data collection

Sensors and Internet of Things devices monitor ambient circumstances, machinery operation, inventory levels, and transportation progress.

• Integration and Syncing 

Integrating this data into the digital twin model correctly reflects the physical supply chain's present status.

• Simulation and Analysis

The digital twin uses this information to run multiple scenarios, forecast possible hiccups, and assess how different elements may affect the supply chain.

• Decision-Making and Optimization

These simulations provide insights that aid in decision-making for process optimization, cost reduction, and performance enhancement.

Please Read: How to Manage Supply Chain Risks With Digital Twin. Here

1. Enhancing Visibility and Transparency

Imagine seeing every step of your supply chain in real-time, from the procurement of raw materials to the delivery of the finished product. This is not an impossible dream; with a digital twin, it is a reality. 

A digital twin uses data from sensors, IoT devices, and other digital tools to provide ongoing, real-time supply chain monitoring. This monitoring allows you to identify anomalies or delays as soon as they occur. 

For example, consider digital twins in the manufacturing industry. The Digital Twin can notify you in advance of a production line machine's breakdown if it begins to exhibit signs of damage. This enables you to plan maintenance proactively. 

Similarly, in the event of a shipping delay, you can pinpoint the exact location of the bottleneck and move quickly to lessen its effects. Thus, supply chain management becomes a proactive rather than reactive process with real-time monitoring. 

You can prevent issues from arising rather than rushing to solve them after they occur. This will keep your business operations in top shape and increase productivity and efficiency.

Please read: Digital twin software for business 

2. Streamlining Logistics and Inventory Management

Two essential supply chain elements that significantly affect pricing and productivity are inventory management and logistics. Better scheduling and execution are made possible by the entire perspective of these processes that digital twins offer.

Consider the multinational logistics giant DHL. DHL is improving its operations by implementing digital twins in logistics. By generating a digital twin logistics network, DHL can test various routing alternatives, optimize delivery timetables, and anticipate future delays. Delivery times have improved significantly, and transportation expenses have decreased by 25% as a result.

Procter & Gamble (P&G) is yet another outstanding example. Warehouse digital twin helps P&G manage its inventory across several warehouses. By employing predictive analytics and constant inventory level monitoring, P&G can more precisely forecast demands and prevent shortages. It also avoids surplus and scarcity of stocks. 

Digital twins in warehouses help in optimizing the operations. For example, Amazon uses digital twin technology to optimize warehousing operations. By modeling various picking and packing techniques, Amazon can reduce order fulfillment time and maximize warehouse worker efficiency, resulting in lower labor costs and quicker delivery times.

3. Optimizing Operations and Productivity 

Improving productivity and streamlining processes can be difficult tasks when managing complicated supply chains. However, this picture is changing because digital twins offer real-time insights and predictive power that older approaches just cannot match.

Digital twins excel at predictive maintenance, cutting delays, and dramatically increasing output. By constantly examining data from sensors and Internet of Things devices, they can anticipate equipment issues before they occur and enable prompt repairs.

For instance, Siemens uses Digital Twin technology to track its machinery and forecast maintenance requirements throughout its manufacturing sites. Due to this proactive approach, production lines operate smoothly and effectively, and unexpected downtime has decreased by 20%. Using real-time data, Siemens can maintain uninterrupted, high-performance operations by planning maintenance tasks.

Similarly, digital twins give businesses an in-depth, real-time picture of the complete supply chain, facilitating activity optimization and streamlining. Taking a comprehensive approach makes it possible to spot errors and bottlenecks and take quick corrective steps.

Boeing, for instance, uses digital twin technology to streamline their intricate global supply chain, which includes many suppliers and manufacturing facilities. Boeing can discover the most productive processes by simulating several situations and producing a virtual representation of their supply chain. Due to the increased cooperation among suppliers and increased assembly line efficiency, lead times have decreased, and total productivity has increased.

4. Sustainability 

Any supply chain leader should prioritize eliminating waste, and digital twins provide a cutting-edge answer to this enduring issue. By simulating various scenarios and building an imitation of your supply chain, you can uncover places where resources are wasted or misused. Digital twins and sustainability are therefore interconnected. 

Take the multinational consumer products corporation Unilever, for instance. To optimize manufacturing procedures, Unilever has effectively integrated digital twins into its supply chain. By simulating several production scenarios, they achieved a 15% reduction in energy use and a 10% reduction in trash. This was accomplished by using data from their Digital Twin to discover production line inefficiencies and make real-time modifications.

GE Aviation also uses digital twins to track and improve jet engine performance. They can save waste and increase the total effectiveness of their activities by predicting maintenance needs and avoiding needless overhauls by evaluating data from sensors on each engine.

Please Read: 7 Best Digital Twin Companies To Look For In 2024. Here

5. Improved Tracking and Traceability Of Products and Components

Tracking goods and parts across the supply chain has always been challenging. Keeping an accurate picture when using traditional approaches is challenging since they frequently lead to information shortages and delays. Digital twins provide unmatched traceability and tracking, which completely changes the game.

Your supply chain's products and components can all be fitted with sensors that constantly provide data to the Digital Twin. This creates a detailed, current map of where things are at all times. 

The digital twin instantly gives you all the details you require, whether you need to know if a component satisfies the criteria for quality or need to verify the status of a shipment while it's in transportation.

This degree of traceability is significant for sectors like medicines and food and beverages with strict regulatory requirements. Ensuring compliance and quality control involves tracking a product's path from beginning to end. This allows you to quickly identify the cause of a recall or a quality problem and take the necessary action.

Additionally, better traceability and tracking raise consumer satisfaction. Today's consumers desire insight into where their items are coming from and what time they will arrive, and they also expect openness. You can gain your client's trust and loyalty by providing precise, constant communication with a digital twin. Thus, digital twins enhance customer experience. 

For example, consider digital twins in clinical trials. Altis Labs has established a global alliance with AstraZeneca and Bayer Pharmaceuticals to develop and apply digital twins in clinical trials.

Digital twins are simulations designed to help clinicians and drug developers better understand how a therapy or patient would behave in real-world scenarios. Altis, a company that creates AI-enabled computational imaging to expedite clinical trials, will donate its Nota imaging platform. This platform uses prognostic AI models to manage and analyze imaging data from ongoing and completed clinical studies.

6. Quality and Compliance 

The pharmaceutical sector is subject to strict regulations to ensure quality and compliance. Pharmaceutical businesses can uphold these standards using digital twins in medicine, which offer comprehensive analytics and real-time production process monitoring.

Pfizer incorporated Digital Twin technology into its pharmaceutical manufacturing processes. By generating a digital image of its manufacturing operations, Pfizer can monitor real-time production. This enables them to quickly identify any deviations from the recommended parameters, guaranteeing that each batch of medication satisfies the necessary quality requirements. By implementing real-time quality control, the danger of non-compliance is minimized, and only safe and effective products are released onto the market.

7. Resilience and Risk Management

Natural disasters, economic changes, or abrupt variations in demand can all cause significant problems for supply chain management. 

Digital twins address these issues, letting businesses model various situations so they can foresee and prepare for them. 

Businesses can use a digital twin to test "what-if" scenarios for risks like raw material shortages, transportation problems, or supplier delays and create backup plans for each. 

For instance, businesses might model other routes or suppliers in real-time to maintain operations if a disruption is predicted in one area of the supply chain. 

By strengthening resilience, this proactive strategy enables businesses to react swiftly to emergencies with little disruption to their supply chain. 

Digital twins are ultimately vital for creating an efficient and flexible supply chain, strengthening the company's resilience to unforeseen circumstances.

8. Saving Money and Increasing Efficiency

Digital twins present significant cost-saving opportunities in supply chain management. 

They allow companies to improve resource allocation, cut waste, and anticipate asset and equipment maintenance requirements. 

For example, businesses might improve processes by analyzing the flow of commodities within the digital twin to find inefficiencies like bottlenecks, underutilized equipment, or overstocked inventory. 

Another vital feature is predictive maintenance, which guarantees that equipment is maintained before malfunctions happen, cutting down on repair expenses and downtime. 

Additionally, by constantly monitoring manufacturing and logistical operations, digital twins can assist firms in optimizing their use of energy and raw materials, reducing costs and supporting environmental goals. 

This degree of understanding makes smarter, data-driven decisions that promote operational efficiencies possible. 

These savings increase over time, strengthening the supply chain's financial stability and enabling the business to invest in expansion and innovation.

Please read: Digital Twins Use Cases 

Although digital twins have a lot to offer supply chain managers, there are also drawbacks and things to keep in mind.

1. Data Security and Privacy

When using Digital Twins, it is crucial to ensure that valuable supply chain data is protected. These systems may become popular targets for cyberattacks due to the massive volumes of data they gather from numerous sources. Thus, following the best practices for digital twin security is a must.

For instance, as part of its Digital Twin strategy, the multinational pharmaceutical giant Merck has put strict data protection safeguards in place. They have effectively protected their supply chain data from possible intrusions by utilizing multi-factor authentication and advanced encryption, guaranteeing the confidentiality and integrity of critical data.

Key Considerations:

• Data encryption

• Access controls

• Regular audits 

2. Integration with Existing Systems

Integrating Digital Twins with current legacy systems might be difficult and complex. Since many businesses have made significant investments in their existing facilities, it is essential to guarantee an effortless transition without interfering with business as usual.

Boeing encountered numerous difficulties when incorporating Digital Twin technology with its legacy systems. By utilizing proprietary APIs and middleware, Boeing accomplished smooth compatibility and allowed real-time data interchange between its new Digital Twin system and its current infrastructure. This strategy guaranteed a seamless changeover while reducing operational difficulties.

Key Considerations:

• Compatibility

• Interoperability

• Incremental Implementation

3. Cost and Implementation

Implementing digital twins can revolutionize your supply chain. However, to guarantee a favorable return on investment (ROI), you must have a strategic plan and a comprehensive grasp of the expenses involved.

When selecting whether to use digital twins, ROI analysis and financial factors are crucial. Digital twins help in maximizing ROI, although the technology has several advantages, there can be a significant upfront cost. You must, therefore, have enough understanding and idea about digital twin implementation cost before you start with it.

Siemens, for instance, carried out a thorough ROI analysis before implementing digital twin technology. They compared the estimated cost savings from decreased downtime, increased productivity, and better predictive maintenance to the initial expenditure. Their choice was supported by the strong return on investment, and the execution produced notable operational gains.

Key Considerations:

• Initial Investment

• Ongoing Maintenance

• ROI Analysis

Suggested Read: How Toobler Helps Companies Become Digital Twin Ready? Here

The use of digital twins in supply chain management has a promising future. 

As technology develops, we may anticipate even more advanced capabilities, like improved AI-driven analytics, deeper IoT and blockchain integration, and broader digital twin applications across other industries.

Digital Twins enable firms to anticipate and minimize risks, make educated decisions, and promote continuous development by offering a dynamic, real-time view of operations. The capacity to model situations, forecast results, and enhance procedures using up-to-date information can revolutionize any sector. 

This ranges from manufacturing and healthcare to logistics and retail. Thus, you must connect with the best digital twin development company. 

At Toobler, we're experts in cutting-edge Digital Twin services that help companies reach their objectives and maximize productivity. Our team of professionals uses the newest tools and methods to create Digital Twins that replicate your physical assets or systems. We also offer insightful information on their behavior and performance. 

So, what are you looking for?

Come and join us to gain more insights on digital twin development. 

1. Can digital twins optimize inventory management?

Yes, digital twins are a powerful tool for supply chain managers, significantly boosting inventory control. By creating real-time virtual inventory models, digital twins provide a wealth of insights into supply chain efficiency, demand patterns, and stock levels, empowering managers to make informed decisions.

With the help of predictive analytics, digital twins can forecast demand and adjust inventory levels accordingly, ensuring optimal resource utilization. This proactive approach not only prevents stockouts but also reduces surplus inventory, providing a sense of security and reassurance to supply chain managers.

More operational efficiency is achieved by streamlining inventory management, cutting expenses, and improving overall supply chain performance.

2. How does a digital twin improve supply chain visibility?

A digital twin improves supply chain visibility by offering a virtual, real-time model of the complete supply chain, from manufacturing to distribution. Businesses can use this model to monitor commodity flows and inventory levels and evaluate real-time equipment performance, such as machine uptime and production rates.

Digital twins provide proactive modifications by forecasting demand, optimizing routes, and identifying possible disturbances such as traffic jams or equipment breakdowns. Businesses can make data-driven decisions, reduce delays, and guarantee more seamless, effective supply chain operations with increased visibility.

3. What are the critical challenges in implementing digital twins in supply chains?

• Data Integration: Integrating data from many systems and sources can be difficult and time-consuming.

• Huge Implementation Costs: Creating and managing digital twins requires significant financial and human effort.

• Data security and privacy: It's crucial to guarantee safe data transfer and shield private data from intrusions.

• Scalability: Because of infrastructural and connection constraints, scaling digital twins across international supply chains can be difficult.

• The complexity of Modeling: Precisely representing dynamic supply chain connections and operations can be complex and resource-intensive.

4. What is a digital twin in the supply chain?

A digital twin supply chain is a virtual representation of the assets, activities, and processes. Logistics, inventory, production, and distribution are all simulated, tracked, and optimized through real-time data, IoT, and AI. 

Digital twins help firms increase productivity, cut expenses, and lower risks by offering real-time visibility and predictive insights. 

They enable businesses to test various scenarios, foresee interruptions, and improve decision-making, resulting in a more resilient and agile supply chain.

5. What technologies are used to create digital twins in supply chains?

Supply chain digital twins use a variety of cutting-edge technology, such as:

• The Internet of Things, or IoT, gathers real-time data from sensors and linked devices.

• AI and machine learning make pattern analysis, disruption prediction, and operational optimization possible.

• Large amounts of supply chain data are processed and stored by cloud computing.

• Big Data Analytics: Supports scenario analysis and in-the-moment decision-making.

• Blockchain: Provides security and transparency to supply chain transactions.

• 3D modeling and simulation: produces digital depictions of tangible items and logistical procedures.

These technologies improve performance, lower risks, and increase supply chain efficiency.

6. How can digital twins help in risk management?

Digital twins aid risk management by offering scenario evaluation, real-time visibility, and predictive insights throughout the supply chain. 

How to do it:

• Real-time monitoring: Keeps tabs on resources, operations, and logistics to identify possible problems early.

• Predictive analytics uses artificial intelligence (AI) and machine learning to forecast interruptions such as equipment failures or supply shortages.

• Before being used in actual operations, scenario simulation tests various risk-reduction tactics.

• Identifying inefficiencies, cutting expenses, and enhancing supply chain resilience are all part of operational efficiency.

• Disaster Preparedness: Enables organizations to create backup plans by simulating possible emergencies, such as natural catastrophes or market swings.