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Applications of Digital Twin across Industries: A Review
by
Kuts, Vladimir
, Singh, Maulshree
, Srivastava, Rupal
, Qiao, Yuansong
, Murray, Niall
, Devine, Declan
, Fuenmayor, Evert
in
Aeronautics
/ Aerospace industry
/ Aircraft
/ COVID-19
/ Digital Twin
/ Industry 4.0
/ Manufacturing
/ Pandemics
/ predictive maintenance
/ Preventive maintenance
/ Smart Manufacturing
/ system optimization
2022
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Applications of Digital Twin across Industries: A Review
by
Kuts, Vladimir
, Singh, Maulshree
, Srivastava, Rupal
, Qiao, Yuansong
, Murray, Niall
, Devine, Declan
, Fuenmayor, Evert
in
Aeronautics
/ Aerospace industry
/ Aircraft
/ COVID-19
/ Digital Twin
/ Industry 4.0
/ Manufacturing
/ Pandemics
/ predictive maintenance
/ Preventive maintenance
/ Smart Manufacturing
/ system optimization
2022
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Applications of Digital Twin across Industries: A Review
by
Kuts, Vladimir
, Singh, Maulshree
, Srivastava, Rupal
, Qiao, Yuansong
, Murray, Niall
, Devine, Declan
, Fuenmayor, Evert
in
Aeronautics
/ Aerospace industry
/ Aircraft
/ COVID-19
/ Digital Twin
/ Industry 4.0
/ Manufacturing
/ Pandemics
/ predictive maintenance
/ Preventive maintenance
/ Smart Manufacturing
/ system optimization
2022
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Journal Article
Applications of Digital Twin across Industries: A Review
2022
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Overview
One of the most promising technologies that is driving digitalization in several industries is Digital Twin (DT). DT refers to the digital replica or model of any physical object (physical twin). What differentiates DT from simulation and other digital or CAD models is the automatic bidirectional exchange of data between digital and physical twins in real-time. The benefits of implementing DT in any sector include reduced operational costs and time, increased productivity, better decision making, improved predictive/preventive maintenance, etc. As a result, its implementation is expected to grow exponentially in the coming decades as, with the advent of Industry 4.0, products and systems have become more intelligent, relaying on collection and storing incremental amounts of data. Connecting that data effectively to DTs can open up many new opportunities and this paper explores different industrial sectors where the implementation of DT is taking advantage of these opportunities and how these opportunities are taking the industry forward. The paper covers the applications of DT in 13 different industries including the manufacturing, agriculture, education, construction, medicine, and retail, along with the industrial use case in these industries.
Publisher
MDPI AG
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