TY - GEN
T1 - An MBD-Enabled Digital Twin Modeling Method for Cognition Assistance in Human-Centric Smart Assembly
AU - Pang, Jiazhen
AU - Zheng, Pai
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023/8
Y1 - 2023/8
N2 - In line with the emerging Industry 5.0 paradigm's human-centricity characteristic, manual assembly has long been an indispensable element of small-batch and customized products. However, the complex assembly information brings a huge cognition burden for the worker, which restricts the development of the human-centric assembly. To take advantage of the valuable model-based definition (MBD) information in the intelligent manufacturing environment for cognition assistance, an MBD-enabled digital twin modeling method is studied. Firstly, the MBD information is divided into five layers to describe the information according to the assembly process. Based on the assembly layer information of the MBD model, an MBD-digital twin (MBD-DT) model framework is established to illustrate the connection between the MBD model and the digital twin assembly. The MBD-DT modeling problem is solved by an optimization method for assembly model mapping. Finally, the cognition needs in the manual assembly process are analyzed, and the cognition assistance method using the MBD-DT model is discussed. The research of this paper can be applied to digital manufacturing enterprises, extending MBD resources from the design end to the on-site assembly end, providing real-time assistance for manual assembly, and achieving sustainability in human-centric smart assembly, which meets the core value of Industry 5.0.
AB - In line with the emerging Industry 5.0 paradigm's human-centricity characteristic, manual assembly has long been an indispensable element of small-batch and customized products. However, the complex assembly information brings a huge cognition burden for the worker, which restricts the development of the human-centric assembly. To take advantage of the valuable model-based definition (MBD) information in the intelligent manufacturing environment for cognition assistance, an MBD-enabled digital twin modeling method is studied. Firstly, the MBD information is divided into five layers to describe the information according to the assembly process. Based on the assembly layer information of the MBD model, an MBD-digital twin (MBD-DT) model framework is established to illustrate the connection between the MBD model and the digital twin assembly. The MBD-DT modeling problem is solved by an optimization method for assembly model mapping. Finally, the cognition needs in the manual assembly process are analyzed, and the cognition assistance method using the MBD-DT model is discussed. The research of this paper can be applied to digital manufacturing enterprises, extending MBD resources from the design end to the on-site assembly end, providing real-time assistance for manual assembly, and achieving sustainability in human-centric smart assembly, which meets the core value of Industry 5.0.
UR - http://www.scopus.com/inward/record.url?scp=85174415057&partnerID=8YFLogxK
U2 - 10.1109/CASE56687.2023.10260573
DO - 10.1109/CASE56687.2023.10260573
M3 - Conference article published in proceeding or book
AN - SCOPUS:85174415057
T3 - IEEE International Conference on Automation Science and Engineering
BT - 2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023
PB - IEEE Computer Society
T2 - 19th IEEE International Conference on Automation Science and Engineering, CASE 2023
Y2 - 26 August 2023 through 30 August 2023
ER -