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Digital twin-enabled machining process modeling

delete2022-10-01
delete39
PRE
AI
刘
刘金锋 (Jinfeng Liu) *
X
Xiaojian Wen
H
Honggen Zhou
S
Sushan Sheng
P
Peng Zhao
刘小军 封面图
刘小军 (Xiaojun Liu)
C
Chao Kang
Y
Yu Chen
DOI:10.1016/j.aei.2022.101737delete
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摘要

摘要

En 中文
Considering the new generation of information technology, the digitalization and intellectualization of the machining process have become the major core in intelligent manufacturing. The complex and diverse requirements, as well as the processing sites force the machining sequence to move towards cyber-physical integration. This paper presents a multidimensional modeling approach for machining processes, by introducing Digital Twin (DT) technology. The method is oriented towards the design and execution phases of the machining process and is used to support intelligent machining. The working mechanism of modeling, simulation, prediction and control of machining process is described based on the interpretation of the modeling and application methods of machining process design, inspection process, fault diagnosis and quality prediction, as based on digital twin technology. Finally, key components of diesel engines are targeted as test objects, demonstrating increased material removal rate by 5.1%, reduced deformation by 22.98% and 30.13%, respectively, verifying the effectiveness of the applied framework and the proposed method.
Keyword:
Digital twin
Machining process
Process model
Process design

期刊

Advanced Engineering Informatics 封面图
Advanced Engineering Informatics
IF:
9.9
论文数:
4.4K
被引数:
1.7W

机构

S
southeast university - china
学者数:
5.3W
论文数: 4.9W
被引数: 57
J
jiangsu university of science & technology
学者数:
9.0K
论文数: 6.9K
被引数: 9
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