In order to improve the efficiency of the traditional assembly line,the assembly line is opti-mized.First,a mathematical model to minimize the number of workstations and the number of workers is developed,and an allocation method that allows workstations to share workers under the conditions of an automated assembly line is proposed.Secondly,a hybrid variable neighborhood search genetic algorithm(HVGA)is proposed to solve the large-scale problem for the parallel assembly line balancing problem.Af-terwards,the fuel cell stack assembly line example is simulated to verify and analyze the simulation objec-tives.The simulation model before and after balancing optimization is established,and finally the simulation model is compared and analyzed,and the average utilization rate of the workstation after balancing is in-creased from 75.52%to 82.53%,which is an increase of 7.01%.Meanwhile the average utilization rate of workers increased from 52.1%to 73.2%,an increase of 21.1%,which is basically consistent with the balancing results,verifying the effectiveness of the balancing method of parallel assembly line and the worker allocation method.
flexsimtype of assembly taskworker assignmentelectric stack assembly linegenetic algo-rithmassembly line optimization
NETL
NSTL
万方数据
