TY - JOUR
T1 - Welding parameters and sequences integrated decision-making considering carbon emission and processing time for multi-characteristic laser welding cell
AU - Ge, Weiwei
AU - Li, Hongcheng
AU - Cao, Huajun
AU - Li, Chengchao
AU - Wen, Xuanhao
AU - Zhang, Chaoyong
AU - Mativenga, Paul
N1 - Funding Information:
This work was supported by the Project of International Cooperation and Exchanges NSFC (Grant No. 51861165202 ); the National Natural Science Foundation of China NSFC (Grant NO. 51975076 ); and the Liuzhou Science and Technology Project (Grant NO. 2021AAB0101 ). The authors also gratefully acknowledge the reviewers and editors for their insightful comments.
Publisher Copyright:
© 2023 The Society of Manufacturing Engineers
PY - 2023/10/1
Y1 - 2023/10/1
N2 - Welding parameters and sequences significantly impact the carbon emission and processing time for laser welding cells. Considering the multi-characteristic of the laser welding cell, achieving integrated decision-making on welding parameters and sequences for laser welding cells remains the challenge. To tackle the gap, this research carries out the welding parameters and sequences integrated decision-making considering carbon emission and processing time for multi-characteristic laser welding cell. Firstly, the 6 M characteristics (multi-source, multi-device, multi-state, multi-feature, multi-stage, and multi-sequence) of the laser welding cell are proposed for revealing the time-series coupling and dynamics of the carbon emission. Then, an integrated decision-making model of welding parameters and sequences for laser welding cell is proposed for minimizing carbon emission and processing time. To obtain the optimal solution, a two-layer solving algorithm combined with the state compression dynamic programming (SCDP) and multi-objective marine predator algorithm (MOMPA) is developed, and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is employed for decision-making on solution set. Finally, the case study of one laser welding cell for aluminum alloy body-in-white is performed for demonstrating the reliability and effectiveness of the integrated decision-making model and solving method, and the carbon-reduction and time-saving potential of the laser welding cell is analyzed.
AB - Welding parameters and sequences significantly impact the carbon emission and processing time for laser welding cells. Considering the multi-characteristic of the laser welding cell, achieving integrated decision-making on welding parameters and sequences for laser welding cells remains the challenge. To tackle the gap, this research carries out the welding parameters and sequences integrated decision-making considering carbon emission and processing time for multi-characteristic laser welding cell. Firstly, the 6 M characteristics (multi-source, multi-device, multi-state, multi-feature, multi-stage, and multi-sequence) of the laser welding cell are proposed for revealing the time-series coupling and dynamics of the carbon emission. Then, an integrated decision-making model of welding parameters and sequences for laser welding cell is proposed for minimizing carbon emission and processing time. To obtain the optimal solution, a two-layer solving algorithm combined with the state compression dynamic programming (SCDP) and multi-objective marine predator algorithm (MOMPA) is developed, and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is employed for decision-making on solution set. Finally, the case study of one laser welding cell for aluminum alloy body-in-white is performed for demonstrating the reliability and effectiveness of the integrated decision-making model and solving method, and the carbon-reduction and time-saving potential of the laser welding cell is analyzed.
KW - Carbon emission
KW - Integrated decision-making
KW - Laser welding cell
KW - Multi-characteristic
KW - Welding parameters and sequences
UR - https://www.scopus.com/pages/publications/85164713353
UR - https://www.mendeley.com/catalogue/286b8d27-ade5-327f-b657-1ee89665524a/
U2 - 10.1016/j.jmsy.2023.07.001
DO - 10.1016/j.jmsy.2023.07.001
M3 - Article
AN - SCOPUS:85164713353
SN - 0278-6125
VL - 70
SP - 1
EP - 17
JO - Journal of Manufacturing Systems
JF - Journal of Manufacturing Systems
ER -
