Production Control and Deadlock Prevention in Conveyor-Based Manufacturing Systems: a Case Study on Control Logic Design

The thesis investigates production control and deadlock prevention in conveyor-based manufacturing systems through a discrete-event simulation approach. The work is focused on a case study that is the model of a real assembly line for electric motor stators. The line is characterized by a complex conveyor network with multiple loops, where congestion and deadlocks frequently occur due to high work-in-progress (WIP) levels and routing constraints. The research aims to evaluate how different control logics and parameter settings affect the overall performance of the line in terms of throughput, stability, and deadlock prevention. Two routing strategies — static and dynamic — are compared, both designed to redirect jobs through longer paths when local loop congestion exceeds predefined thresholds. The simulation model, developed in Arena®, reproduces the operational behavior of the system and allows the assessment of several configurations under varying WIP limits and control parameters. Results show that a dynamic, adaptive routing significantly improves system stability and throughput while effectively preventing deadlocks, especially under high WIP conditions. The analysis also highlights the importance of parameter monitoring at multiple levels: while a global CONWIP control ensures balanced flow across the entire line, local supervision of specific loops ensures early detection of bottlenecks and more responsive corrective actions. From a managerial perspective, the study emphasizes that major performance improvements can be achieved through smarter control logic and real-time monitoring, with the crucial help of simulation in finding the best working scenarios. Continuous adjustment of routing rules and WIP parameters enables faster, data-driven decision-making, ensuring greater flexibility and resilience in automated manufacturing environments.