A Framework for Validating Data-Driven Discrete-Event Simulation Models of Cyber-Physical Production Systems

Abstract

In recent years, there has been a significant increase in the deployment of Cyber-physical Production Systems (CPPS) across various industries. CPPS consist of interconnected devices and systems that combine physical and digital elements to enhance the efficiency, productivity, and reliability of manufacturing processes. Due to the continuous and fast-paced evolution of the behavior of CPPS, there is an increasing interest in generating data-driven Discrete-event Simulation (DES) models of such systems. The validation of these models, however, remains a challenge, and traditional approaches may be insufficient to ensure their accuracy. To address this challenge, we propose a framework for validating data-driven DES models of CPPS. We emphasize the importance of continuously monitoring the validity of data-driven DES models and updating them when necessary to ensure their accuracy over time. We, furthermore, demonstrate our proposed approach through a case study in reliability assessment and discuss challenges and limitations of our framework.