TY - GEN
T1 - Hybrid Disassembly Line Balancing for Human-robot Collaborative Remanufacturing
AU - Guo, Feng
AU - Guo, Xi Wang
AU - Zhou, Meng Chu
AU - Wang, Weitian
AU - Qin, Shu Jin
AU - Kang, Qi
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - As technologies advance rapidly, the urgency of remanufacturing is escalating. Efficient disassembly processes are crucial at the outset of remanufacturing. This work proposes an innovative disassembly scheme aimed at amplifying efficiency through the utilization of parallelization and human-robot collaboration in the context of a hybrid disassembly line. A single-objective mixed-integer programming model is developed to optimize disassembly profit. A discrete salp swarm algorithm is proposed to solve it since it is NP-hard. We have proposed and integrated uniform variation and two-point crossover operators in this algorithm. After comparing its results with those of the exact solver and other intelligent optimization methods, we conclude its competitive performance in both solution quality and efficiency.
AB - As technologies advance rapidly, the urgency of remanufacturing is escalating. Efficient disassembly processes are crucial at the outset of remanufacturing. This work proposes an innovative disassembly scheme aimed at amplifying efficiency through the utilization of parallelization and human-robot collaboration in the context of a hybrid disassembly line. A single-objective mixed-integer programming model is developed to optimize disassembly profit. A discrete salp swarm algorithm is proposed to solve it since it is NP-hard. We have proposed and integrated uniform variation and two-point crossover operators in this algorithm. After comparing its results with those of the exact solver and other intelligent optimization methods, we conclude its competitive performance in both solution quality and efficiency.
UR - http://www.scopus.com/inward/record.url?scp=85208268650&partnerID=8YFLogxK
U2 - 10.1109/CASE59546.2024.10711350
DO - 10.1109/CASE59546.2024.10711350
M3 - Conference contribution
AN - SCOPUS:85208268650
T3 - IEEE International Conference on Automation Science and Engineering
SP - 2912
EP - 2917
BT - 2024 IEEE 20th International Conference on Automation Science and Engineering, CASE 2024
PB - IEEE Computer Society
T2 - 20th IEEE International Conference on Automation Science and Engineering, CASE 2024
Y2 - 28 August 2024 through 1 September 2024
ER -