Why do we need Digital twin?
Characteristics of Digital twin
Architecture
Architecture Diagram
Features of Digital twin
Advantages and Disadvantages
Applications
Conclusion
10, References
7 +s
What are Digital
Pe,
Twins ?
+ A digital twin is made up of data sets and it is a virtual
representation of a physical object which can accurately
mimic the performance of the physical object in a virtual
platform.
+ The concept of Digital Twin was first used in Davin gall
Inger's 1991 book called mirror worlds.
e digital twin has been adopted as-4 conceptual basis
in the astronautics and aerospace arca in recent years by
NASA.
Why do we need
Digital twin?
« It helps in designing and optimization part
Ithelps to predict the aging effect
It is capable of monitoring the performance of the
physical object throughout the whole life cycle
al twin also integrate historical data from past
machine usage to factor into its digital model
CHARACTERISTICS OF DIGITAL TWIN
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Connectivity
Charact
of Digit
Digital traces
CHARACTERISTICS OF DIGITAL TWIN
O Connectivity
A digital twin is based on connectivity. It enables connection between
the physical element and its digital counterpart. The sensors create the
connectivity of physical products that obtain, integrate and
communicate data using various integration technologies.
UHomogenization
Homogenization has two component steps; firstly, spatially aligning
data; and secondly ensuring the quality of the data is compatible
ODigital traces
Digital twin technologies leave digital traces. The trails are helpful to diagnose the
source of the problem that occurred in case of machine malfunctions
QModularity
Modularity is referred to the design and customization of products and
production modules. The addition of modularity to functional models helps
manufacturers gain the ability to tWeak machines and models.
UReprogrammable and Smart
Digital twins automatically enable re-programmability through sensors, artificial
A | U ee eee 2a
ARCHITECTURE DIAGRAM
Process
Historian
System
EAM Data Data Data Data
System . an Pipelines Integrity = HDFS
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isa Readiness
van
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ARCHITECTURE
The different stages in the architecture of Digital Twin service
involves;-
Data and Data Collection
*
Do
Pod
* Data Pipelines
a
«>
Data Integrity
=
%* Data Egress
Q 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,
O Data Pipelines
Merge all data sources from data collection into a single model and exported into element
graph.
Q 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.
Q 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,
FEATURES
FEATURES
Document Management
Model
3D Representation
Simulation
FUNCTIONALITY
All document (drawings,instructions,etc.)
Assossiated to equipment throughout its
lifecycle.
Digital representation of the equipment that can
mimic properties and behaviors of a physical device
Properties of a physical device (measured or
simulated) mapped to a 3D digital representation
Representation of a physical device in a simulation
Environment to study its behavior
FEATURES
Data Model
Visualization
Model Synchronization
Connected Analytics
FUNCTIONALITY
Standardized data model for
connectivity,analytics,and/or visualization
Graphical Representation of the object either
of a supervisory screen or personal device
Alignment of a model with real world parameters
(potentially in real time)
Algorithms and computational results based on
measured properties of a physical device
ADVANTAGES
ate
* Improved design
O
* Improved build
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2
* Better early detection and warnings
% New opportunities
2
* Aggregated data
JE. HE AA SN |. AP
DISADVANTAGES
The success of technology is dependent on internet connectivity.
The security is at stake.
+.
D
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.
*,
hos
Applications of Digital twins
OManufacturing
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.
OShop 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.
OPredictive maintenance
Digital twins help manufacturefs predict potential downtimes of machines to
improve their overall productivity by minimizing non-value-adding
maintenance activities,
Other Applications
ORetail
nthe retail sector, digital twins are used for modeling and augment
customer experience at prominent shopping centers and individual stores.
QAutomotive
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
rnarle
ÜHealthcare
Digital twins virtualize healthcare services and help healthcare providers to
optimize patient care, cost and performance. It aims to improve the
operational efficiency of healthcare processes and enhance personalized
care.
OSmart 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.