Process Optimization for Complex Product Assembly Workshops with AGV Integration via Discrete Event Simulation

For complex assembly workshops, optimizing AGV scheduling is critical to enhancing production efficiency and resource utilization. Traditional scheduling methods often rely on fixed priority rules and basic path planning algorithms, which are insufficient to accommodate the dynamic changes in resource availability and task demands. To overcome these limitations, this study proposes a DES-based optimization approach that dynamically adjusts AGV task allocation and path planning to improve scheduling performance in complex manufacturing environments. By integrating lean production principles with intelligent simulation technologies, a comprehensive simulation model was developed using the Plant Simulation platform. This model simulates the coordination between AGVs and workstations while optimizing workstation layout and material flow. Simulation results demonstrate that the proposed approach significantly improves AGV scheduling efficiency and overall production performance. Notably, workstation utilization increased from below 6% to over 28%, while the work-in-progress rate dropped from 94% to under 74%. This study offers a practical and effective AGV scheduling strategy for complex product assembly workshops, with strong potential for real-world implementation.