Research on Mixed-Model Assembly Line Rebalancing Considering Skill Differences and Series–Parallel Design

The primary challenge facing mixed-flow assembly lines is how to effectively balance the production process to accommodate diverse product combinations and constantly changing demands. This study actively addresses the problem of rebalancing mixed-flow assembly lines by considering variations in assembly task complexities, differences in worker skills, and the serial-parallel operation modes of workstations. A mathematical model is constructed with the objective of minimizing production cycle time, workstation smoothness index, and rebalancing costs. To solve this problem, a hybrid Gray Wolf-Genetic Algorithm is designed. Finally, the feasibility and effectiveness of the proposed model and algorithm are verified through a case study involving the reconfiguration of a mixed-flow assembly line for mobile phone case production at Company H. This research aims to help manufacturing companies better adapt to changing market demands, potentially enhancing production efficiency and competitiveness.