Industry 4.0 has brought transformative changes to manufacturing, emphasizing automation, adaptability, and efficiency to meet the growing demands for customization. A key aspect of this evolution is the shift from centralized to decentralized control systems, driven by traditional centralized architectures’ limitations in addressing scalability, resilience, and dynamic adaptability. Decentralized systems, relying on Multi-Agent System (MAS) architectures, enable intelligent and autonomous collaboration between manufacturing entities (e.g., machines). Line-less Assembly Systems (LAS) exemplify this shift by replacing fixed conveyor systems with Autonomous Mobile Robots (AMRs) for job transportation, significantly enhancing the mass personalization of products. Subsequently, the current work presents a decentralized control mechanism based on the MAS framework to demonstrate the effectiveness of distributed intelligence in addressing coordination and uncertainty challenges without requiring human intervention in a LAS scenario. Using simulation technologies, like ROS2 and SPADE, the shop floor entities are modeled as agents equipped with Finite State Machines (FSM), facilitating autonomous coordination and decision-making. The simulation study indicates that decentralization enhances the robustness and flexibility of LAS.