Research on the Optimization and Simulation of Assembly Line Balancing Based on Improved PSO Algorithm

In response to the deficiencies of commonly used optimization methods for assembly lines, a production demand-oriented optimization method for assembly lines is proposed. Taking a certain compressor assembly line as an example, the production rhythm and the number of workstations are calculated based on production requirements and working systems. With assembly rhythm and smoothing index as optimization goals, an improved particle swarm optimization algorithm is employed for process allocation. Subsequently, Flexsim simulation is used to analyze the assembly line. The final results show that after optimization using the improved particle swarm algorithm, the assembly line balance rate increased from 71.1% to 85.9%, and the assembly line smoothing index decreased from 47.4 to 29.8, significantly enhancing assembly efficiency. This demonstrates the effectiveness of the proposed optimization method for the assembly line and provides a reference for other products in the same industry.