An ontology-based shop-floor digital twin configuration approach

Abstract

Digital Twin (DT) technology has been considered as the one of key enabling technologies of intelligent manufacturing. DT is regarded as the digital representation of physical entities to mirror their state and behavior in the virtual space. The development of modeling and simulation technology makes the construction of DT professional and systematic. A lot of modeling methods and virtual models for DT construction are accumulated. However, the value of existing scattered models is not fully considered. These models could be used as virtual resources for the DT construction to save time and costs. Therefore, this paper proposes an ontology-based approach to support the configuration of Shop-floor Digital Twin (SDT). The ontologies are defined based on the analysis of the multi-domain heterogeneous models and knowledge. The top-level ontology is represented as the demand-oriented integration view of SDT. The shop-floor manufacturing resources and activities could be represented by the object-oriented virtual resources based on the resource-level ontology and are integrated into a SDT scheme with the domain specific meta-modeling method, which contributes to the rapid configuration of SDT. Finally, the feasibility of this approach is verified by the case of the Fischer Learning Factory 4.0 (FLF4.0).