Abstract:  Aiming at the problems of excessive number of workstations, unreasonable cycle time, and unbalanced workload variance in the domestic automobile mixed-model assembly line of a Hydraulic Electronic Control Unit (HECU), mathematical modeling, adaptive genetic algorithm and result analysis were carried out. Firstly, the basic concept of the mixed-model assembly line balancing and the HECU mixed-model assembly line were introduced. Then, based on the traditional mixed-model assembly line balancing problem, the three objective functions of the minimum number of workstations, the smallest cycle time, and the minimum workload variance within workstations were considered to establish a mathematical model of mixed-model assembly line balancing. Then, following the flow chart of genetic algorithm, the steps of the improved adaptive genetic algorithm were described. Finally, MATLAB was used to write an adaptive genetic algorithm to solve the mixed-model assembly line balancing problem, and the running results were analyzed. The research results indicate that the optimization result of adaptive genetic algorithm is significantly better than traditional genetic algorithm. One workstation is reduced, which can decrease the cost of workers and equipment. The cycle time is increased by 2.66 seconds/piece, which achieves the target output and can reduce inventory costs. The minimum workload variance within workstations is reduced by 59.36%, which can make the workload more balanced.

Key words:  mixed-model assembly line balancing; hydraulic electronic control unit;multi-objective optimization; adaptive genetic algorithm

CAI Qi-ming, LI Wei-wei. Optimization of mixed-model assembly line balancing for hydraulic electronic control unit［J］.Journal of Mechanical & Electrical Engineering, 2022,39(1):77-86.