Cognitive Digital Twin enabled by Semantic Modeling and Model-Based Systems Engineering
ABSTRACT
As a key enabling technology of Industry 4.0, Digital Twin has been applied to various industrial domains covering different lifecycle phases to provide a comprehensive virtual description of products and systems. While the benefit of Digital Twin is undoubted, it faces challenges when dealing with certain complex industrial systems, which requires integrating all relevant data, information and knowledge involving multiple domains and across the entire lifecycle. Semantic technologies, such as ontology engineering and knowledge graphs, provide potential solutions by empowering Digital Twins with augmented interoperability and cognitive capabilities. The Model Based Systems Engineering (MBSE) technology facilitates the formalized application of modeling to support cross-domain and cross-lifecycle information representation. Enabled by these state-of-the-art technologies, the Cognitive Digital Twin (CDT) concept has been recently proposed which reveals a promising evolution of the current Digital Twin concept towards a more intelligent, comprehensive, and full lifecycle representation of complex systems. In this seminar, the concept of CDT and its key features will be presented, together with application cases developed in collaborative projects with EU industries.
BIOGRAPHY
Dr. Xiaochen Zheng is a postdoc scientist of the ICT for Sustainable Manufacturing Group (ICT4SM) at EPFL, Switzerland. His research interests include Cognitive Digital Twins, Semantic Technologies, Industrial Ontologies, Internet of Things and Model Based Systems Engineering. He is an active member of the Industrial Ontologies Foundry (IOF) and the chair of the Product Service System (IOF-PSS) working group. He is also an expert of the CEN-CENELEC/WS Zero-Defect Manufacturing (ZDMTerm) workshop. He has author more than thirty research publications and played key roles in several large EU H2020 projects in the smart manufacturing domain.