Optimising Manufacturing and Assembly Lines: an Assessment by Simulation in the Automotive Sector

The continuous evolution of manufacturing processes, driven by the need for greater flexibility and improved resource efficiency, creates significant challenges for companies. This paper proposes a methodological framework based on Discrete Event Simulation (DES) to model, analyse, and improve production systems. We apply this approach to a real industrial case study: an automated manufacturing and assembly line for stators used in brushless electric fan engines. By constructing a virtual replica of the system and employing DES, this study thoroughly explores dynamic behaviours, bottlenecks, and resource utilisation under various operating scenarios. Insights from the simulation experiments guided effective optimisation strategies, enhancing total throughput and economic efficiency. The proposed methodology's transferability stems from its structured nature: understanding real system behaviour, building and testing a virtual replica via DES under diverse conditions, and statistically analysing outputs for improvement. This makes it a valuable approach for data-driven decision-making and guiding managerial choices in diverse manufacturing environments.