Digital twin-driven complexity management in intelligent manufacturing [version 1; peer review: 2 approved]

Complexity management is one of the most crucial and challenging issues in manufacturing. As an emerging technology, digital twin provides an innovative approach to manage complexity in a more autonomous, analytical and comprehensive manner. This paper proposes an innovative framework of digital twi...

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Bibliographic Details
Main Authors: Ang Liu, Yuchen Wang, Xingzhi Wang, Fei Tao
Format: Article
Language:English
Published: F1000 Research Ltd 2021-11-01
Series:Digital Twin
Subjects:
Online Access:https://digitaltwin1.org/articles/1-9/v1
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Summary:Complexity management is one of the most crucial and challenging issues in manufacturing. As an emerging technology, digital twin provides an innovative approach to manage complexity in a more autonomous, analytical and comprehensive manner. This paper proposes an innovative framework of digital twin-driven complexity management in intelligent manufacturing. The framework will cover three sources of manufacturing complexity, including product design, production lines and supply chains. Digital twin provides three services to manage complexity: (1) real-time monitors and data collections; (2) identifications, diagnoses and predictions of manufacturing complexity; (3) fortification of human-machine interaction. A case study of airplane manufacturing is presented to illustrate the proposed framework.
ISSN:2752-5783