Track: Simulation Competition

Abstract

Discrete event simulations are becoming increasingly important in the management of complex manufacturing systems, however, the raw data collection and processing from various physical systems is laborious and time consuming with current methods. 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 based macro 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.

Keywords:

Discrete Event Simulation, Data Preparation, Data Processing, Manufacturing Execution Systems, Python-based Automation tool.