Edge Computing Enhanced Digital Twins for Smart Manufacturing

Abstract

Abstract Digital Twin is one of the key enabling technologies for smart manufacturing in the context of Industry 4.0. The combination with advanced data analytics and information and communication technologies allows Digital Twins to perform real-time simulation, optimization and prediction to their physical counterparts. Efficient bi-directional data exchange is the foundation for Digital Twin implementation. However, the widely mentioned cloud-based architecture has disadvantages, such as high pressure on bandwidth and long latency time, which limit Digital Twins to provide real-time operating responses in dynamic manufacturing processes. Edge computing has the characteristics of low connectivity, the capability of immediate analysis and access to temporal data for real-time analytics, which makes it a fit-for-purpose technology for Digital Twin development. In this paper, the benefits of edge computing to Digital Twin are first explained through the reviews of the two technologies. The Digital Twin functions to be performed at the edge are then elaborated. After that, how the data model will be used in the edge for data mapping to realize the Digital Twin is illustrated and the data mapping strategy based on the EXPRESS schemas is discussed. Finally, a case study is carried out to verify the data mapping strategy based on EXPRESS schema. This research work refers to ISO/DIS 23247 Automation systems and integration — Digital Twin framework for manufacturing.