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rend Research
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Digital
Twinsin
Logistics
ADHL perspectiveon theimpactof
digitaltwins on thelogisticsindustry
Contents
Contact us
Contents
Page 2/39
Preface
6. Digital Twins in the Energy Sector
7. Digital Twins in Consumer, Retail and E-commerce
19
20
1 Understanding Digital Twins 4 3 Digital Twins in Logistics 21
1.1 The Digital Twin Comes of Age 4 3.1 Packaging & Container Digital Twins 22
1.2 What Makes a Digital Twin? 6 3.2 Digital Twins of Shipments 23
1.3 Underlying Technologies Enabling Digital Twins 7 3.3 Digital Twins of Warehouses and Distribution Centers 23
1.4 How Digital Twins Create Value 8 3.4 Digital Twins of Logistics Infrastructure 26
1.5 The Digital Twin Through the Product Lifecycle 9 3.5 Digital Twins of Global Logistics Networks 27
1.6 Challenges in Applying Digital Twins 10 4 Logistics Implications of Implementing Digital Twins 28
2 Digital Twins Across Industries 12 4.1 Inbound to Manufacturing 29
2.1 Digital Twins in Manufacturing 13 4.2 In-plant Logistics 30
2.2 Digital Twins in Materials Science 14 4.3 Aftermarket Logistics 32
2.3 Digital Twins in Industrial Products 15 4.4 Orchestrating the Supply Chain 32
2.4 Digital Twins in Life Sciences and Healthcare 16 Conclusion & Outlook 34
2.5 Digital Twins in Infrastructure and Urban Planning 17 Sources 36
Pictorial Sources
Further Information
Recommended Reading
37
38
39
Contact us
For centuries, people have used pictures
and models to help them tackle complex
problems. Great buildings first took shape
on the architect’s drawing board. Classic
cars were shaped in wood and clay.
Over time, our modeling capabilities have
become more sophisticated.Computers
have replaced pencils. 3D computer
models have replaced 2D drawings.
Advanced modeling systems can simulate
the operation and behavior of a product
as well as its geometry.
Until recently,however,there remained
an unbridged divide between model and
reality.No two manufactured objects
are ever truly identical,even if they have
been built from the same set of drawings.
Computer models of machines don’t
evolve as parts wear out and are replaced,
as fatigue accumulates in structures, or as
owners make modifications to suit their
changing needs.
That gap is now starting to close. Fueled
by developmentsin the internet of things
(IoT),big data, artificial intelligence,
cloud computing, and digital reality
technologies, the recent arrival of digital
twins heralds a tipping point where
the physical and digital worlds can be
managed as one, and we can interact
with the digital counterpartof physical
things much like we would the things
themselves,even in 3D space around us.
Led by the engineering, manufacturing,
automotive,and energy industries in
particular,digital twins are already
creating new value. They are helping
companies to design, visualize, monitor,
manage, and maintain their assets more
effectively.And they are unlocking new
business opportunities like the provision
of advanced services and the generation
of valuable insight from operational data.
As logistics professionals, we have been
thinking about how digital twins will
change traditional supply chains, and how
the logistics sector might embrace digital
twins to improve its own processes. Our
objective in writing this report is to share
our findings and to help you answer the
following key questions:
■ What is a digital twin and what does
it mean for my organization?
■ What best-practice examples from
other industries can be applied to
logistics?
■ How will my supply chain change
because of digital twins?
Looking ahead, we believe that the
adoption of digital twins across industries
will drive better decision making in the
physical world. That, in turn, will drive
significant changes in the operation of
supply chains and logistics processes.
In the logistics industry itself,digital
twins will extend the benefits of IoT
already being applied today.They will
bring deeperinsight into the planning,
design, operation, and optimization of
supply chains, from individual assets
and shipments to entire global supply
networks.
We think there has never been a
more exciting time for industries and
logisticians to work together to leverage
the full potential of digital twins. On
behalf of us all at DHL,we look forward to
collaborating with you in this exciting and
potentially transformative field.
Preface
Matthias Heutger
Senior Vice President
Global Head of Innovation & Commercial
Development,DHL
Markus Kueckelhaus
Vice President
Innovation & Trend Research, DHL
Page 3/39
Contents
Contact us
Chapter1
UnderstandingDigitalTwins
1.1THEDIGITALTWIN COMES OFAGE
For many years, scientists and engineers have created
mathematical models of real-world objects and over time
these models have become increasingly sophisticated.Today
the evolution of sensors and network technologies enables
us to link previously offline physical assets to digital models.
In this way, changes experienced by the physical object are
reflected in the digital model, and insights derived from the
model allow decisions to be made about the physical object,
which can also be controlled with unprecedented precision.
Page 4/39
Contents
Contact us

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neo.pptx

  • 1. Powered by DHLT rend Research Page 1/39 Digital Twinsin Logistics ADHL perspectiveon theimpactof digitaltwins on thelogisticsindustry Contents Contact us
  • 2. Contents Page 2/39 Preface 6. Digital Twins in the Energy Sector 7. Digital Twins in Consumer, Retail and E-commerce 19 20 1 Understanding Digital Twins 4 3 Digital Twins in Logistics 21 1.1 The Digital Twin Comes of Age 4 3.1 Packaging & Container Digital Twins 22 1.2 What Makes a Digital Twin? 6 3.2 Digital Twins of Shipments 23 1.3 Underlying Technologies Enabling Digital Twins 7 3.3 Digital Twins of Warehouses and Distribution Centers 23 1.4 How Digital Twins Create Value 8 3.4 Digital Twins of Logistics Infrastructure 26 1.5 The Digital Twin Through the Product Lifecycle 9 3.5 Digital Twins of Global Logistics Networks 27 1.6 Challenges in Applying Digital Twins 10 4 Logistics Implications of Implementing Digital Twins 28 2 Digital Twins Across Industries 12 4.1 Inbound to Manufacturing 29 2.1 Digital Twins in Manufacturing 13 4.2 In-plant Logistics 30 2.2 Digital Twins in Materials Science 14 4.3 Aftermarket Logistics 32 2.3 Digital Twins in Industrial Products 15 4.4 Orchestrating the Supply Chain 32 2.4 Digital Twins in Life Sciences and Healthcare 16 Conclusion & Outlook 34 2.5 Digital Twins in Infrastructure and Urban Planning 17 Sources 36 Pictorial Sources Further Information Recommended Reading 37 38 39 Contact us
  • 3. For centuries, people have used pictures and models to help them tackle complex problems. Great buildings first took shape on the architect’s drawing board. Classic cars were shaped in wood and clay. Over time, our modeling capabilities have become more sophisticated.Computers have replaced pencils. 3D computer models have replaced 2D drawings. Advanced modeling systems can simulate the operation and behavior of a product as well as its geometry. Until recently,however,there remained an unbridged divide between model and reality.No two manufactured objects are ever truly identical,even if they have been built from the same set of drawings. Computer models of machines don’t evolve as parts wear out and are replaced, as fatigue accumulates in structures, or as owners make modifications to suit their changing needs. That gap is now starting to close. Fueled by developmentsin the internet of things (IoT),big data, artificial intelligence, cloud computing, and digital reality technologies, the recent arrival of digital twins heralds a tipping point where the physical and digital worlds can be managed as one, and we can interact with the digital counterpartof physical things much like we would the things themselves,even in 3D space around us. Led by the engineering, manufacturing, automotive,and energy industries in particular,digital twins are already creating new value. They are helping companies to design, visualize, monitor, manage, and maintain their assets more effectively.And they are unlocking new business opportunities like the provision of advanced services and the generation of valuable insight from operational data. As logistics professionals, we have been thinking about how digital twins will change traditional supply chains, and how the logistics sector might embrace digital twins to improve its own processes. Our objective in writing this report is to share our findings and to help you answer the following key questions: ■ What is a digital twin and what does it mean for my organization? ■ What best-practice examples from other industries can be applied to logistics? ■ How will my supply chain change because of digital twins? Looking ahead, we believe that the adoption of digital twins across industries will drive better decision making in the physical world. That, in turn, will drive significant changes in the operation of supply chains and logistics processes. In the logistics industry itself,digital twins will extend the benefits of IoT already being applied today.They will bring deeperinsight into the planning, design, operation, and optimization of supply chains, from individual assets and shipments to entire global supply networks. We think there has never been a more exciting time for industries and logisticians to work together to leverage the full potential of digital twins. On behalf of us all at DHL,we look forward to collaborating with you in this exciting and potentially transformative field. Preface Matthias Heutger Senior Vice President Global Head of Innovation & Commercial Development,DHL Markus Kueckelhaus Vice President Innovation & Trend Research, DHL Page 3/39 Contents Contact us
  • 4. Chapter1 UnderstandingDigitalTwins 1.1THEDIGITALTWIN COMES OFAGE For many years, scientists and engineers have created mathematical models of real-world objects and over time these models have become increasingly sophisticated.Today the evolution of sensors and network technologies enables us to link previously offline physical assets to digital models. In this way, changes experienced by the physical object are reflected in the digital model, and insights derived from the model allow decisions to be made about the physical object, which can also be controlled with unprecedented precision. Page 4/39 Contents Contact us