Abstract
Efficient coordination is essential in automotive assembly lines, where multiple workers collaborate on a single product. This study focuses on optimising the cycle time of assembly processes involving human workers assigned specific tasks. A simulation routine was developed by enhancing an existing crowd-simulation algorithm to calculate and evaluate cycle time. Three optimisation models with various configurations were then implemented and assessed. The algorithms containing each of these three models utilise the simulation routine to identify performance bottlenecks and iteratively refine the solution. The simulation routine also generates the initial input data for the models. Using only this input with no iterations results in an estimated cycle time that serves as a lower bound on the optimal simulated cycle time. The simulation proved critical in accounting for small time disturbances, such as prolonged operations or collision avoidance, which significantly impact the cycle time. For the tested instance, all the solutions generated using the three algorithms achieved realistic cycle times, being approximately 11% above the derived initial lower bound. This is to be compared with the initial solutions, before any refining iterations were performed, which were approximately 18%, 27%, and at least 136%, respectively, above the initial lower bound. While all three algorithms demonstrated a potential for solving the type of problem addressed, further testing across diverse scenarios is required to generalise our findings. Future work could refine the optimisation models, adding more aspects necessary in reality, like workload and ergonomics, to enhance productivity in realworld assembly lines.