Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023)

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Application Research of Digital Twin and Deep Learning Technology in Intelligent Manufacturing of Machining Equipment

Authors
Baichen Liu1, *
1Changzhou College of Information Technology, Changzhou Science and Education Town, 22 Mingxin Middle Road, Changzhou, Jiangsu, China
*Corresponding author. Email: 75765893@qq.com
Corresponding Author
Baichen Liu
Available Online 4 September 2023.
DOI
10.2991/978-94-6463-230-9_94How to use a DOI?
Keywords
Digital Twin; deep learning; intelligence; predictive maintenance
Abstract

This study constructs a digital twin model of manufacturing and processing equipment, integrates large-scale production data, conducts in-depth analysis of production behavior, and carries out deep learning and production parameter optimization training. It utilizes the dynamic updating ability of artificial neural networks to accurately determine the production situation of the processing equipment in the time period. Theoretical processing and data application modules are deeply integrated to achieve accurate simulation and predictive analysis of physical equipment. The system has the ability to perceive equipment status and predict functionality, optimize the manufacturing process on the production line, improve manufacturing efficiency and product quality, and promote the intelligent transformation of traditional manufacturing industries.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023)
Series
Atlantis Highlights in Social Sciences, Education and Humanities
Publication Date
4 September 2023
ISBN
10.2991/978-94-6463-230-9_94
ISSN
2667-128X
DOI
10.2991/978-94-6463-230-9_94How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Baichen Liu
PY  - 2023
DA  - 2023/09/04
TI  - Application Research of Digital Twin and Deep Learning Technology in Intelligent Manufacturing of Machining Equipment
BT  - Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023)
PB  - Atlantis Press
SP  - 791
EP  - 798
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-230-9_94
DO  - 10.2991/978-94-6463-230-9_94
ID  - Liu2023
ER  -