Towards continuously updated simulation models: combining automated raw data collection and automated data processing

Abstract

Discrete Event Simulation (DES) is a powerful tool for efficiency improvements in production. However, instead of integrating the tool in the daily work of production engineers, companies apply it mostly in single-purpose studies such as major investment projects. One significant reason is the extensive time-consumption for input data management, which has to be performed for every simulation analysis to avoid making decisions based upon obsolete facts. This paper presents an approach that combines automated raw data collection and automated processing of raw data to simulation information. MTConnect is used for collection of raw data and the GDM-Tool is applied for data processing. The purpose is to enable efficient reuse of DES models by reducing the time-consumption for input data management. Furthermore, the approach is evaluated using production data from the aerospace industry.