Digital Twin Technology Challenges and Applications: A Comprehensive Review
Проблемы и области применения технологии цифровых двойников: комплексный обзор
2022-03-09
SCID: 54.1/umw8wb5r
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complex systems monitoringdata-driven decision makingdigital twin technologyobject lifecycle managementproduct validation and simulation
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Abstract (AI)
A digital twin is a virtual representation of a physical object or process capable of collecting information from the real environment to represent, validate and simulate the physical twin’s present and future behavior. It is a key enabler of data-driven decision making, complex systems monitoring, product validation and simulation and object lifecycle management. As an emergent technology, its widespread implementation is increasing in several domains such as industrial, automotive, medicine, smart cities, etc. The objective of this systematic literature review is to present a comprehensive view on the DT technology and its implementation challenges and limits in the most relevant domains and applications in engineering and beyond.
Key Findings
1
Digital twin adoption is expanding across industrial, automotive, medical, smart-city, and other engineering-related domains.
2
Digital twin technology enables data-driven decision-making, complex-system monitoring, product validation and simulation, and lifecycle management.
3
Digital twins virtually represent physical objects or processes, using real-environment data to validate and simulate present and future behavior.
4
The review provides a comprehensive overview of digital twin technology and its applications in engineering and beyond.
5
The systematic review examines digital twin implementation challenges and limitations across major application domains.
Research Object
Digital twin (virtual representation of a physical object or process)
Research Subject
Implementation challenges, limitations, and applications of digital twin technology
Publication Details
Publication Date
2022-03-09
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References available in scid.ai8
Digital Twin in Industry: State-of-the-Art2019
A Review of the Roles of Digital Twin in CPS-based Production Systems2017
Digital Twin: Origin to Future2021
The Role of AI, Machine Learning, and Big Data in Digital Twinning: A Systematic Literature Review, Challenges, and Opportunities2021
How to tell the difference between a model and a digital twin2020
Digital Twins: State of the art theory and practice, challenges, and open research questions2022
Leveraging Digital Twin for Sustainability Assessment of an Educational Building2021
A Decision Support System for Urban Agriculture Using Digital Twin: A Case Study With Aquaponics2021