Digital Twin in Industry: State-of-the-Art

Цифровой двойник в промышленности: современное состояние
A.Y.C. Nee, Ang Liu, Fei Tao, He Zhang
2019-04-01

Cyber-physical integrationDigital twinIndustry 4.0Prognostics and health managementSmart manufacturing
Digital twin (DT) is one of the most promising enabling technologies for realizing smart manufacturing and Industry 4.0. DTs are characterized by the seamless integration between the cyber and physical spaces. The importance of DTs is increasingly recognized by both academia and industry. It has been almost 15 years since the concept of the DT was initially proposed. To date, many DT applications have been successfully implemented in different industries, including product design, production, prognostics and health management, and some other fields. However, at present, no paper has focused on the review of DT applications in industry. In an effort to understand the development and application of DTs in industry, this paper thoroughly reviews the state-of-the-art of the DT research concerning the key components of DTs, the current development of DTs, and the major DT applications in industry. This paper also outlines the current challenges and some possible directions for future work.
1
DTs have been applied successfully across multiple industrial domains, including product design, production, and prognostics and health management.
2
Despite ~15 years since its proposal, no prior paper has specifically reviewed industrial DT applications, motivating this comprehensive review.
3
Digital Twin (DT) is a key enabling technology for smart manufacturing and Industry 4.0, integrating cyber and physical spaces.
4
This paper reviews DT key components, current development, major industrial applications, and outlines current challenges and future research directions.

Digital twin (DT) in industrial/manufacturing contexts

State-of-the-art development, key components, current applications, challenges and future directions of digital twins for smart manufacturing and Industry 4.0

Publication Details
Publication Date
2019-04-01
Journal
Publisher
ISSN
Access Type
Author Information
Authors
A.Y.C. Nee
Ang Liu
Fei Tao
He Zhang
Explore further
Open the scid.ai AI chat with a ready-made request: it will find papers on a similar topic and help build a literature review.
Find similar papers in the chat
Make a presentation
100%