Discrete event simulations are becoming increasingly important in the management of complex manufacturing systems, however, a significant issue with current methods is the collection and processing of data from various physical systems. This data is often of poor quality and incomplete, making it difficult to produce accurate results. To address this problem, a Python-based automation tool was created to collect, analyse, and store data from Manufacturing Execution Systems (MES) using a multi-step data preparation algorithm and a dedicated simulation database. This tool is more efficient than using tools such as Microsoft Excel and includes a user-friendly interface for data entry and visualization. This automation tool is expected to improve the quality and accuracy of simulation results, while reducing the time and effort required for data preparation in the automobile manufacturing production line.