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Product-part level digital twin modeling method for digital thread framework

delete2023-05-01
delete6
PRE
AI
L
Linbei Jiang
S
Shaohui Su *
裴
裴欣 (Xin Pei)
C
Changyong Chu
K
Kuan Wang
DOI:10.1016/j.cie.2023.109168delete
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摘要

摘要

En 中文
Digital twin (DT) is not only a core technology of smart manufacturing but also a dynamic intelligent system. By organically combining virtual and realistic models with multiple data sources, DT is used in monitoring product operation status and in predicting product life. A systematic modeling method with high fidelity, punctuality, and efficiency has an important meaning to DT model. However, most of the current DT modeling approaches focus on individual objects and individual aspects of products, and lack of modeling approaches for the whole life cycle and multiple objects, which is not conducive to the mining and utilization of data from all aspects of products. On account of this, a part-level DT modeling approach is proposed based on PLM/PDM theory, integrating the property model, the process model, the simulation model, and the feedback model within a digital thread communication framework, with their modeling methods and application algorithms investigated separately. The results of the Part Digital Twin Model (PDTM) are presented by virtue of a visualization platform. There is interaction among customers, designers, and processors throughout the entire system, ensuring real-time monitoring of product manufacturing process. Finally, a test case of hanging axle is implemented, aiming at validating the proposed part-level DT modeling method. According to the result of this case, the proposed method in this paper can be used in generating the property of hanging axle, and giving real-time monitoring to the whole lifecycle of hanging axle, thereby demonstrating its feasibility.
Keyword:
Digital twin
Full lifecycle management
Digital thread
Smart manufacturing

期刊

Computers and Industrial Engineering 封面图
Computers and Industrial Engineering
IF:
6.5
论文数:
1.0W
被引数:
3.8W

机构

H
Hangzhou Dianzi University
学者数:
1.3W
论文数: 9.6K
被引数: 7.5K
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