In today's highly dynamic manufacturing landscape, the demand for flexibility, customization, and responsiveness has made traditional assembly systems increasingly inadequate. Reconfigurable Assembly Lines (RALs) have emerged as a promising solution, offering adaptability in both structure and function to cope with changes in product design, demand volume, and production conditions. RALs allow rapid modification of tasks, stations, and resource allocation with minimal downtime or cost. This adaptability is particularly crucial in environments where mixed-model production and frequent product variations are the norm. Designing and operating such systems introduces complex decision-making challenges, especially in task assignment,
worker routing, and line balancing under uncertainty. These challenges are compounded when incorporating multi-manned stations, human-robot collaboration, or fluctuating takt times. To address these, advanced methods such as optimization, simulation, and hybrid simulationoptimization are essential. These tools enable planners to evaluate and improve the performance of RALs across multiple dimensions, including efficiency, robustness, and ergonomic.