Hybrid knowledge based system supporting Digital Twins in the Industry 5.0

Abstract

Digital twins are employed to monitor, analyze, and predict the behavior of a manufacturing system. In literature, the concept of digital twin is mainly associated with simulation models, and only a few works addressed the integration between physics-based and data driven models. This work extends this definition and describes how different kinds of knowledge can be integrated in a hybrid knowledge based system supporting digital twin. Following the Industry 5.0 paradigm, the hybrid system can improve the human-centricity, sustainability, and resilience of a manufacturing system. The hybrid digital twin is structured as an enterprise information system, which can be connected to the other information systems of the company, such as ERP, MES, and PLM, as well as other platforms of total quality management and total productive maintenance. A discussion on the application of the proposed approach in fusion welding, as an example of a very complex process, is also presented.