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Digital Twin of Intelligent Small Surface Defect Detection with Cyber-manufacturing Systems.
- Source :
- ACM Transactions on Internet Technology; Nov2023, Vol. 23 Issue 4, p1-20, 20p
- Publication Year :
- 2023
-
Abstract
- With the remarkable technological development in cyber-physical systems, industry 4.0 has evolved by use of a significant concept named digital twin (DT). However, it is still difficult to construct a relationship between twin simulation and a real scenario considering dynamic variations, especially when dealing with small surface defect detection tasks with high performance and computation resource requirements. In this article, we aim to construct cyber-manufacturing systems to achieve a DT solution for small surface defect detection task. Focusing on DT-based solution, the proposed system consists of an Edge-Cloud architecture and a surface defect detection algorithm. Considering dynamic characteristics and real-time response requirement, Edge-Cloud architecture is built to achieve smart manufacturing by efficiently collecting, processing, analyzing, and storing data produced by factory. A deep learning-based algorithm is then constructed to detect surface defeats based on multi-modal data, i.e., imaging and depth data. Experiments show the proposed algorithm could achieve high accuracy and recall in small defeat detection task, thus constructing DT in cyber-manufacturing. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15335399
- Volume :
- 23
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- ACM Transactions on Internet Technology
- Publication Type :
- Academic Journal
- Accession number :
- 173841770
- Full Text :
- https://doi.org/10.1145/3571734