德勤-数字孪生在物流中的应用趋势（英文）-2019.8-39页_19mb

Summary of Digital Twins in Logistics

Core Content

Digital twins are virtual representations of physical objects or systems that are continuously updated with real-time data. They enable companies to design, visualize, monitor, manage, and maintain their assets more effectively. DHL's report highlights the growing importance of digital twins in the logistics industry, emphasizing their potential to transform traditional supply chains and improve logistics processes.

Main Points

What is a Digital Twin?

A digital twin is a virtual model that mirrors the physical object or system it represents. It captures both the physical state and behavior of the object and updates in real-time as the object changes. Digital twins are unique to a specific instance of the object and provide value through visualization, analysis, prediction, or optimization.

Underlying Technologies

The following technologies are essential in enabling digital twins:

• Internet of Things (IoT): Enables real-time data collection from physical assets.
• Cloud Computing: Provides scalable storage and processing capabilities.
• APIs and Open Standards: Facilitate data sharing and integration across systems.
• Artificial Intelligence (AI): Enhances predictive capabilities and decision-making.
• Digital Reality Technologies: Augmented, Mixed, and Virtual Reality (AR, MR, VR) are used to visualize and interact with digital twins.

How Digital Twins Create Value

Digital twins offer multiple types of value:

• Descriptive Value: Enables real-time visualization of asset status, especially for remote or dangerous assets.
• Analytical Value: Supports the analysis of internal data and performance optimization.
• Diagnostic Value: Uses data to identify root causes of issues.
• Predictive Value: Predicts future states and suggests solutions, supporting smart factory operations.

The Digital Twin Through the Product Lifecycle

Digital twins are used throughout the product lifecycle, from development to decommissioning:

• Product Development: Facilitates faster design iterations and reduces the need for physical testing.
• Production: Supports collaboration and optimization of manufacturing processes.
• Operate & Service: Enhances maintenance planning and product performance optimization.
• End-of-Life: Guides decisions on reusing, reconditioning, recycling, or scrapping assets.

Key Applications in Logistics

3.1 Packaging & Container Digital Twins

Digital twins can track and monitor the condition and performance of packaging and containers throughout their lifecycle.

3.2 Digital Twins of Shipments

These twins provide real-time tracking and insights into shipment conditions, helping to optimize logistics operations.

3.3 Digital Twins of Warehouses and Distribution Centers

They support the planning, design, and optimization of warehouse operations, improving efficiency and reducing costs.

3.4 Digital Twins of Logistics Infrastructure

These twins enable the monitoring and management of infrastructure such as roads, ports, and rail networks.

3.5 Digital Twins of Global Logistics Networks

They provide a comprehensive view of global supply chains, enabling better decision-making and strategic planning.

Logistics Implications

Implementing digital twins in logistics has several implications:

• Inbound to Manufacturing: Enhances visibility and coordination in the inbound supply chain.
• In-plant Logistics: Supports real-time monitoring and optimization of internal logistics processes.
• Aftermarket Logistics: Enables predictive maintenance and service optimization.
• Orchestrating the Supply Chain: Facilitates integration and coordination across the entire supply chain.

Challenges

Despite their potential, the adoption of digital twins faces several challenges:

• Cost: Implementing digital twins requires significant investment in technology platforms, model development, and maintenance.
• Precise Representation: Perfectly replicating the physical and operational state of complex assets is difficult and costly.
• Data Quality: Ensuring the accuracy and consistency of data from multiple sources is a critical challenge.
• Organizational Culture: A shift in mindset and collaboration practices is necessary to fully leverage digital twins.

Outlook

The report concludes that digital twins are poised to become a transformative force in the logistics industry. They will enhance the value of IoT, provide deeper insights into supply chain operations, and drive better decision-making. DHL believes that the logistics sector is at a pivotal moment to embrace digital twins and collaborate with other industries to unlock their full potential.

Conclusion

Digital twins are revolutionizing the logistics industry by offering real-time insights, predictive analytics, and enhanced operational efficiency. As the technology matures and becomes more accessible, its applications in logistics will continue to expand, leading to more intelligent and responsive supply chain systems.