Generation and Tuning of Discrete Event Simulation Models for Manufacturing Applications

In order to successfully develop and apply cyber-physical systems in manufacturing it is fundamental to ensure the availability of up-to-date digital models. Production systems are intricate environments and are subject to frequent changes due to both external and internal factors. Therefore, it is complex to guarantee that a digital model can correctly represent the real system at any time. Literature is rich with methods for the automated generation of discrete event simulation models. However, the generated representations may be excessively accurate and describe also unnecessary activities. The automated development of digital models with an appropriate level of detail can avoid useless efforts and misguided predictions. This paper proposes a method that generates a simulation model and adjusts its level of detail exploiting the manufacturing system properties. The method has been applied in two test cases and can be used effectively to generate both Petri Net and simulation graph models.