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Digital Twin ppt-2 (2).pptx
1.
2. INDEX
1. Introduction
2. History
3. Types of Digital Twin
4. Working of Digital Twin
5. Difference between CAD and Digital Twin
6. Applications of Digital Twin
7. Advantages
8. Disadvantages
9. Future of Digital Twin
10. Conclusion
3. INTRODUCTION
Digital twin technology involves creating a virtual replica or digital counterpart of a
physical object, process, or system.
A Digital Twin consists of three distinct parts: The physical part, the Digital
Part and the connection between the two.
Its components are physical object, virtual model, sensors/IoT devices,
data integration, analytics, and visualization.
4. HISTORY
1960s-2002s:
• The concept of "Mirror models" was introduced by NASA scientist James E. Albus in the 1960s.
• Dr . Michael Grieves, a researcher at the University of Michigan, coined the term "digital twin" in 2002, defined it as a virtual
representation of a physical product, process.
2010s:
• In 2010, the U.S. National Aeronautics and Space Administration (NASA) started using digital twin technology for space
missions. They used digital twins to simulate and monitor the performance of space systems and vehicles.
2020s:
• Digital twin technology continued to gain traction across industries, including manufacturing, healthcare, smart cities, and
transportation. Companies and organizations increasingly adopted digital twin solutions for optimization, predictive
maintenance, and improved decision-making.
5. "The concept and model of the digital twin was first publicly introduced in 2002 by Michael Grieves, at
a Society of Manufacturing Engineers conference in Troy, Michigan."
6. Types Of Digital Twin
1. Product Digital Twin:
Represents an individual physical product, enables virtual testing, simulation and optimization of the product's
design, performance, and maintenance.
2. Process Digital Twin:
Models and analyses a specific manufacturing or industrial process, provides real-time monitoring, analysis, and
optimization to improve efficiency, productivity, and quality.
3. System Digital Twin:
Integrates multiple digital twins of individual components or subsystems to simulate and optimize the
behaviour of a larger system.
4. Asset Digital Twin:
Represents physical assets, enables monitoring, maintenance, and optimization of asset performance, energy
usage, and lifespan.
5. Network Digital Twin:
A network digital twin is a virtual representation of a complex network of interconnected systems, such as
transportation networks, energy grids, telecommunications networks, or supply chain networks.
7.
8. Working of Digital Twin
Step 1: Object Selection
Step 2: Data Collection
Step 3: Data Integration
Step 4: Digital Model Creation
Step 5: Sensor Data Mapping
Step 6: Simulation and Analytics
Step 7: Visualization and User Interface
Step 8: Continuous Monitoring and Updates
9.
10. Difference between CAD and Digital Twin
CAD Digital Twin
Focuses on design and engineering
Goes beyond design to capture real-time
data and behavior
Geometric representation
Comprehensive representation capturing
behavior, interactions, and real-time data
Primarily used for visualization
Supports visualization and real-time
interaction
Design-oriented Lifecycle-oriented
Static design data Integrates real-time data
Widely used in engineering, architecture,
and manufacturing
Broad applications across industries such as
manufacturing, energy, healthcare,
transportation, and more
Individual component focus
Considers interdependencies and dynamics
of multiple systems
Limited scope within design phase Covers the entire lifecycle
11. Applications of Digital Twin
Manufacturing: Digital twins optimize production processes, improve quality control,
and enable predictive maintenance.
Healthcare: Digital twins help monitor patients, simulate medical procedures, and
personalize treatment plans.
Smart Cities: Digital twins enable urban planning, resource optimization, and real-time
monitoring of infrastructure.
Energy and Utilities: Digital twins optimize energy consumption, manage grids, and
support renewable energy integration.
13. Disadvantages
1. Data Privacy and Security
2. Complex implementation, Analytics, Interpretation and Integration
3. Cost and Infrastructure Requirements
4. Data Quality and Overreliance on Accuracy
5. Scalability, compatibility, and limited standardization
14. Future of Digital Twin
Digital twin technology revolutionizes industries, offering innovation, efficiency
improvements, and data-driven decision-making.
They will become an integral part of the IoT ecosystem, where physical objects and
devices are connected and share data.
They will continue to evolve as powerful tools for virtual testing and simulation and
will play a crucial role in the development of smart cities.
Blockchain technology can enhance the trust, security, and transparency of digital twin
data.
15. Conclusion
Digital twin technology enables a virtual representation of physical objects and systems.
It offers numerous benefits, including improved efficiency, predictive maintenance, and data-
driven insights.
It revolutionizes industries by bridging the gap between physical and digital realms.
In conclusion, digital twin technology is a game-changer that will shape the future of various
industries, revolutionizing the way we design, operate, and optimize physical systems.
