Creation of a Digital Twin of a Truck Assembly Process

Author(s):  
Irina Makarova ◽  
Polina Buyvol ◽  
Larysa Gubacheva
2019 ◽  
Vol 55 (17) ◽  
pp. 110
Author(s):  
GUO Feiyan ◽  
LIU Jianhua ◽  
ZOU Fang ◽  
ZHAI Yunong ◽  
WANG Zhongqi ◽  
...  

2021 ◽  
Author(s):  
Yukun Jiang ◽  
Changjiang Chen ◽  
Xiaojun Liu

2021 ◽  
Author(s):  
Qiangwei Bao ◽  
Gang Zhao ◽  
Yong Yu ◽  
Sheng Dai ◽  
Wei Wang

Abstract Digital twin (DT) technology has been entrusted with the tasks of modeling and monitoring of the product, process and production system. Moreover, the development of semantic modeling and digital perception provides the feasibility for the application of DT in the manufacturing industry. However, the application of DT technology in assembly workshop modeling and management is immature for the discreteness of assembly process, diversity of assembly resource and complexity of dataflow in the assembly task execution. A method of ontology-based modeling and evolution of DT for the assembly workshop is proposed to deal with this situation. Firstly, the ontology-based modeling method is given for the assembly resource and process. By instantiating in the ontology, resources and processes can be involved in the modeling and evolution of the DT workshop. Secondly, the DT assembly workshop framework is introduced with the detailed discussions of dataflow mapping, DT evolution, storage and tracing of historical data generated during the operation of the workshop. In addition, a case study is illustrated to show the entire process of construction and evolution of DT modeled on an experimental field, indicating the feasibility and validity of the method proposed.


2021 ◽  
Vol 10 (1) ◽  
pp. 52
Author(s):  
Yunxi Zhang ◽  
Gangfeng Wang ◽  
Dong Zhang ◽  
Qi Zhang

The construction machinery arm is the key component of construction machinery to complete the operation task; its assembly link directly affects the product quality and operational performance of the whole machinery. To solve the problems of low assembly efficiency and the inability to fully reflect the assembly process indexes and product characteristics in the traditional construction machinery arm assembly, this paper studies assembly process modeling and simulation for the construction machinery arm based on assembly sensing data and digital twin. By extracting and processing the assembly resource data and field measurement data of the machinery arm, the assembly process information database under the digital twin environment is constructed, which lays the foundation for the virtual assembly model construction of the machinery arm. Through the real-time data interaction between virtual space and physical space, a complete assembly of digital twin spaces is formed. Finally, taking the assembly line of an excavator armed as an example, it is shown that the digital twin-based assembly simulation can monitor the assembly process in real-time and optimize its configuration to improve assembly efficiency. Therefore, an effective closed-loop feedback mechanism is constructed for the whole assembly process of the construction machinery arm.


Author(s):  
Bilal Ahmad

The objective of this paper is to utilize deep learning technology to develop an intelligent digital twin for the operational support of a human-robot assembly station. Digital twin, as a virtual portrayal, is used to design, simulate, and optimize the complexity of the assembly system. For testing purposes, a convolutional neural network (CNN) is integrated with a digital twin. It is used for the application of a collaborative robot for an assembly application. Collaborative robots are a new form of industrial robots that are safe for humans and can work alongside humans and have received ample attraction in recent years for automation of simple to complex tasks.


Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1006-P
Author(s):  
BENYAMIN GROSMAN ◽  
ANIRBAN ROY ◽  
DI WU ◽  
NEHA PARIKH ◽  
LOUIS J. LINTEREUR ◽  
...  

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