Digital Twins Will Revolutionize Modern Logistics. Here’s How
As of 2022, the global market for digital twins was valued at $11.12 billion — and experts estimate an impressive annual growth rate of 37.5% from 2023 to 2030.
Digital twins help connect the physical and virtual worlds, allowing workers to timely identify when things need fixing, work more efficiently, and create less waste. So, embracing the potential of digital twins is a crucial move as the logistics sector steps into the new Industry 5.0 era.
What benefits can this technology bring to the logistics and supply chain industry?
Let’s take a closer look at them in this article.
What Is Digital Twin Technology?
Digital twins are virtual replicas of real objects. For example, if there is a need to make changes in a supply chain, supply chain managers can test things virtually without disrupting actual operations by using a digital twin.
Digital twins combine IoT, Big Data, AI, and ML to construct virtual environments. Sensors on physical objects collect real-time and historical data, which is then used in the digital twin.
AI and ML simulate real-world conditions, behaviors, and interactions within this digital realm. So, with digital twins, teams can create exact virtual replicas, explore different scenarios, and predict problems before they happen in reality.
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In manufacturing, digital twins are used to model production lines accurately, helping operators identify bottlenecks, enhance efficiency, and minimize downtime. They can even simulate how new components interact with existing systems before physical implementation.
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In logistics, digital twins can simulate entire supply chains, offering valuable insights into areas like warehouse operations, inventory management, and transportation efficiency. By pinpointing potential disruptions, companies can develop stronger, more resilient, and efficient logistics networks.
This innovation has the potential to boost revenue by up to 10% and improve product quality by as much as 25%.
How Does It Work?
It all starts with a group of experts, including data scientists, ML engineers, and analysts, who research the data and physical characteristics of a real-world object or system. They use this knowledge to build a detailed digital copy of the real thing.
Then, developers create virtual models that constantly receive real-time data from the physical object through sensors. With the help of these models, the digital twin can replicate events in real-time.
Digital twins can be as simple or complex as the objective requires, and the quality of the virtual model depends on the data they receive. Companies can use this technology during product development to provide feedback or as a standalone prototype to predict what might happen once changes are applied to the physical version.
What Are the Use Cases of Digital Twin in Logistics?
Warehouse Management
A digital twin model provides up-to-the-minute insights into all activities within the warehouse. It’s like having a map that directs workers to the best spots for inventory organization, helps them to monitor supplies, and figure out the quickest paths for the company’s busy loaders. It also lets warehouse managers assess how layout and process changes might affect operations before they actually implement those changes. As a result, warehouse managers can make the most efficient use of their space and resources.
For example, IBM offers a system that uses sensor data and point-of-sale information to create a virtual inventory replica. Their digital twin can forecast demand, streamline the supply chain, and add automation to warehouse inventory.
Supply Chain Management
Digital twins provide a comprehensive view of supply chain management, incorporating production, inventory, demand, and procurement data with real-time insights for informed decision-making.
By using advanced analytics and AI, digital twins optimize resource utilization, planning, and risk reduction. In addition, the technology identifies vulnerabilities in supply chains and warns supply chain managers to take proactive measures, while a consistent flow of real-time data enables timely issue resolution and ensures high customer satisfaction.
Transportation Management
With real-time data on location, condition, and status, businesses can identify and resolve potential issues with packages or cargo. Digital twins also help with selecting the quickest routes based on real-time traffic data from various options. Essentially, they work as an improved and personalized GPS that finds the fastest path, ensuring efficient deliveries and reduced fuel consumption.
With a digital twin, even vehicles can provide valuable, exclusive data about surroundings and performance, allowing logistics service providers to make informed decisions about their fleet management. For example, FedEx uses digital twins to map out the best routes for their trucks and monitor shipments around the clock.
How to Get the Best Results from Digital Twins
Creating digital twins is a complex task. To get started with this technology, business leaders should first focus on the specific areas that match their goals. The technology is based on making accurate digital models of complicated things that match the real-world product and its real-time changes. Also, as any product that involves AI/ML, the performance of a digital twin depends on the data it receives. So, if you put good data in, you’ll get good results.
As of 2022, the global market for digital twins was valued at $11.12 billion — and experts estimate an impressive annual growth rate of 37.5% from 2023 to 2030.
Digital twins help connect the physical and virtual worlds, allowing workers to timely identify when things need fixing, work more efficiently, and create less waste. So, embracing the potential of digital twins is a crucial move as the logistics sector steps into the new Industry 5.0 era.
What benefits can this technology bring to the logistics and supply chain industry?
Let’s take a closer look at them in this article.
What Is Digital Twin Technology?
Digital twins are virtual replicas of real objects. For example, if there is a need to make changes in a supply chain, supply chain managers can test things virtually without disrupting actual operations by using a digital twin.
Digital twins combine IoT, Big Data, AI, and ML to construct virtual environments. Sensors on physical objects collect real-time and historical data, which is then used in the digital twin.
AI and ML simulate real-world conditions, behaviors, and interactions within this digital realm. So, with digital twins, teams can create exact virtual replicas, explore different scenarios, and predict problems before they happen in reality.
-
In manufacturing, digital twins are used to model production lines accurately, helping operators identify bottlenecks, enhance efficiency, and minimize downtime. They can even simulate how new components interact with existing systems before physical implementation.
-
In logistics, digital twins can simulate entire supply chains, offering valuable insights into areas like warehouse operations, inventory management, and transportation efficiency. By pinpointing potential disruptions, companies can develop stronger, more resilient, and efficient logistics networks.
This innovation has the potential to boost revenue by up to 10% and improve product quality by as much as 25%.
How Does It Work?
It all starts with a group of experts, including data scientists, ML engineers, and analysts, who research the data and physical characteristics of a real-world object or system. They use this knowledge to build a detailed digital copy of the real thing.
Then, developers create virtual models that constantly receive real-time data from the physical object through sensors. With the help of these models, the digital twin can replicate events in real-time.
Digital twins can be as simple or complex as the objective requires, and the quality of the virtual model depends on the data they receive. Companies can use this technology during product development to provide feedback or as a standalone prototype to predict what might happen once changes are applied to the physical version.
What Are the Use Cases of Digital Twin in Logistics?
Warehouse Management
A digital twin model provides up-to-the-minute insights into all activities within the warehouse. It’s like having a map that directs workers to the best spots for inventory organization, helps them to monitor supplies, and figure out the quickest paths for the company’s busy loaders. It also lets warehouse managers assess how layout and process changes might affect operations before they actually implement those changes. As a result, warehouse managers can make the most efficient use of their space and resources.
For example, IBM offers a system that uses sensor data and point-of-sale information to create a virtual inventory replica. Their digital twin can forecast demand, streamline the supply chain, and add automation to warehouse inventory.
Supply Chain Management
Digital twins provide a comprehensive view of supply chain management, incorporating production, inventory, demand, and procurement data with real-time insights for informed decision-making.
By using advanced analytics and AI, digital twins optimize resource utilization, planning, and risk reduction. In addition, the technology identifies vulnerabilities in supply chains and warns supply chain managers to take proactive measures, while a consistent flow of real-time data enables timely issue resolution and ensures high customer satisfaction.
Transportation Management
With real-time data on location, condition, and status, businesses can identify and resolve potential issues with packages or cargo. Digital twins also help with selecting the quickest routes based on real-time traffic data from various options. Essentially, they work as an improved and personalized GPS that finds the fastest path, ensuring efficient deliveries and reduced fuel consumption.
With a digital twin, even vehicles can provide valuable, exclusive data about surroundings and performance, allowing logistics service providers to make informed decisions about their fleet management. For example, FedEx uses digital twins to map out the best routes for their trucks and monitor shipments around the clock.
How to Get the Best Results from Digital Twins
Creating digital twins is a complex task. To get started with this technology, business leaders should first focus on the specific areas that match their goals. The technology is based on making accurate digital models of complicated things that match the real-world product and its real-time changes. Also, as any product that involves AI/ML, the performance of a digital twin depends on the data it receives. So, if you put good data in, you’ll get good results.
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