DIGITAL_TWINnsjsjsjsjsjsnsnddbdbdbdb.pdf

DIGITAL TWIN
TECHNOLOGY
RAHUL GARAI
DEPARTMENT OF COMPUTER SCIENCE
VIDYASAGAR UNIUVERSITY, MIDNAPORE

CONTENTS
1. What are digital twins?
2. Why do we need Digital twin?
3. Characteristics of Digital twin
4. Architecture
5. Architecture Diagram
6. Features of Digital twin
7. Advantages and Disadvantages
8. Applications
9. Conclusion
10. References

What are Digital
Twins ?
 A digital twin is a virtual model of physical object or
process that helps predict and understand how the physical
object perform.
Digital twins are updated in real-time using data from
the physical object.
 The concept of Digital Twin was first used in Davin
gall Inger's 1991 book called mirror worlds.

Why do we need
Digital twin?
 It helps in designing and optimization part
 It helps to predict the aging effect
 It is capable of monitoring the performance of the
physical object throughout the whole life cycle
A digital twin also integrate historical data from past
machine usage to factor into its digital model

CHARACTERISTICS OF DIGITAL TWIN

CHARACTERISTICS OF DIGITAL TWIN
 Connectivity
A digital twin is based on connectivity. It enables connection between
the physical element and its digital counterpart. Digital twins are
connected to the physical world through sensors that collect data.
 Homogenization
Digital twins allow information to be decoupled from its physical form.
 Data analytics
Digital twins use machine learning and artificial intelligence to
analyse data from sensors.

 Digital trail
Digital twins create digital footprints that helps to identify problems and
improve the performance of the physical object.
 Modularity
Digital twin can be divided into parts or layers, which helps with
manufacturing and monitoring.
 Reprogrammability
Digital twins automatically enable re-programmability through sensors,
artificial intelligence techniques and predictive analysis.

ARCHITECTURE
The different stages in the architecture of Digital Twin service
involves;-
 Data and Data Collection
 Data Pipelines
 Data Integrity
 Data Egress

 Data and Data Collection
There is two types of data;
 Model Data
Used to construct digital representation of real world thing by using graph models.
 Time Series Data
Represent the observation of the state of some physical thing at a given time. It can be
continuous or discrete.
 Data Pipelines
Merge all data sources from data collection into a single model and exported into element
graph.

 Data Integrity
It also looks at the actual data stream for reducing issues with calibrations, connectivity
physical issues with the instrumentation that collect the physical data. This is a set of
analysis on either single varied or multi varied data.
 Data Egress
The collected and organised data into digital twin is analyse to ensure the accuracy of that
data. The final stage is making use of that digital twin, we have built to analogue a whole
range of analytics value.

ADVANTAGES
 Improved design
 Improved build
 Better early detection and warnings
 New opportunities
 Aggregated data
 Post-manufacturing visibility of products

DISADVANTAGES
 The success of technology is dependent on internet connectivity.
 The security is at stake.
 The digital twins concept is based on 3D models and not on 2D
drawings
 Digital twin will be required across entire supply chains.
 The challenges involved here include globalization and new
manufacturing techniques.

Applications of Digital twins
Manufacturing
In the manufacturing industry, digital twins are used for
facilitating product development, design customization, shop
floor performance improvement and predictive maintenance.

In the manufacturing industry
Product development
Engineers gain benefits from digital twins as it helps to test the
feasibility of upcoming products before launching
Design customization
Digital twins help businesses design multiple permutations of the
product and offer personalized products and services to their clients.

Shop floor performance improvement
Digital twins are helpful in monitoring and analyzing the end products. It
helps engineers to spot the defective and low-performing products in the lot.
Predictive maintenance
Digital twins help manufacturers predict potential downtimes of machines to
improve their overall productivity by minimizing non-value-adding
maintenance activities.

Other Applications
Retail
In the retail sector, digital twins are used for modeling and augment
customer experience at prominent shopping centers and individual stores.
Automotive
Digital twins are highly used for creating virtual models of connected
vehicles. Automotive companies simulate and analyze the production phase
to identify the potential problems during production or when the car hits the
roads.

Healthcare
Digital twins applications for healthcare include hospital management,
facility design, workflow development, decision making, as well as
individualized therapy and personalized patient care.
Smart cities
The digital twin can help cities to become more economically, socially and
environmentally sustainable. Virtual models can guide planning decisions
and offer solutions to the many complex challenges faced by modern cities.

CONCLUSION
combined with the latest machine learning and artificial intelligence
tools which helping companies across many industries reduce
operational costs, increase productivity, improve performance, and
change the way predictive maintenance is done. For product
manufacturers in particular, digital twin technology is crucial to
achieving more efficient production lines and faster time-to-market.

REFERENCES
 www.google.com
 www.wikipedia.com

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