Prototyping of an Emulation-Based Digital Twin Framework and Its Application to Anomaly Detection in Factory Production Equipment

Abstract

Digital twin refers to a digital replica of a physical object created in the cyber space of a computer, aiming to enable real-time monitoring, prediction, control, and optimization through the exchange of data and information between physical objects like machines and equipment and their corresponding digital twins. Recently, there has been increasing expectation for digital twins to address challenges in manufacturing processes, such as improving productivity, inheriting technologies, and optimizing processes. However, the lack of a simple implementation framework for constructing digital twins and data exchange has hindered practical application. In this study, we prototyped a digital twin framework for factory equipment models using the emulation software Emulate3D, and conducted anomaly detection by comparing the data from physical objects obtained from control devices with the behavior of the digital twin model. This presentation will summarize the results and discuss challenges related to full implementation and automation.