The increasing complexity of modern production systems, driven by rising product variety and demand fluctuations, requires manufacturers to continuously adapt their production and planning strategies. This master’s thesis explores the use of Discrete Event Simulation (DES) in factory planning, focusing on the analysis of a use case of an assembly system in the railway sector. The company’s re-planning was motivated by the need to increase production from 5,276 wheelsets per year to 6,000, while eliminating the night shift and the need to adapt the system to the variety of products in the company’s portfolio. The research began with the theoretical review of factory planning principles, production systems and simulation methodologies. The practical part was divided into three phases, which consisted of different stages in the development of the simulation model. The first phase involved the understanding of the real production system and its translation into the simulation model while maintaining the correctness and accuracy. The second phase consisted of a feasibility analysis of the production system that had been designed in the planning process carried out by the company, which was validated to be feasible. The model in this phase was used to analyze the weaknesses of the layout and identify possible optimizations. Finally, some extra implementations were made into the simulation model to find answers to some emerging questions by using more advanced tools in the simulation software Witness, like the implementation of an Automated Guided Vehicle and the use of the Witness Experimenter tool. The results confirmed that while the new system can meet the yearly demand, the modular area remains significantly underutilized. The needed investment in additional infrastructure, resources and planning efforts does not provide sufficient benefits to justify the implementation. This research demonstrates that simulation-based factory planning is a valuable tool for decision-making, that can enable manufacturers to evaluate different production configurations before real-world implementation. Future steps for the company in the use case should involve going back into the planning process to re-design a new layout where they consider the results of this simulation project. The new layout should also be tested by Discrete Event Simulation before implementing it in the production facility to ensure optimal system performance.
