Originated by a real-world case study from the automotive industry, this paper attempts to address the assembly lines balancing problem with human-robot collaboration and heterogeneous operators while optimizing the cycle time. A genetic algorithm (GA) with customized parameters and features is proposed while considering the characteristics of the problem. The computational results show that the developed GA can provide the decision-makers with efficient solutions with heterogeneous humans and robots. Furthermore, the results reveal that the cycle time is highly influenced by order of the operators’ skills, particularly when a fewer number of humans and robots exist at the stations. ; CC BY-NC-ND 4.0 Corresponding author: Amir Nourmohammadi This study is funded by the Knowledge Foundation (KKS), Sweden, through the VF-KDO and ACCURATE 4.0 projects at the University of Skövde, Sweden. ; VF-KDO ; ACCURATE 4.0
A genetic algorithm for heterogenous human-robot collaboration assembly line balancing problems
2022-01-01
doi:10.1016/j.procir.2022.05.172
Article (Journal)
Electronic Resource
English
DDC: | 629 |
Balancing and scheduling assembly lines with human-robot collaboration tasks
BASE | 2022
|Balancing and scheduling assembly lines with human-robot collaboration tasks
BASE | 2022
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