Abstract: As digitalization and intelligence continue to develop in the industrial field,enterprises are facing challenges in improving production efficiency,reducing production costs,optimizing production processes,and achieving real-time monitoring.Digital twin technology has received widespread attention as an effective solution.However,there are difficulties in data acquisition and integration,model construction and updating,and real-time performance and accuracy in the process of industrial digital twin construction.To address these issues,this paper proposes a concept-instance-module structure design method based on digital twin knowledge graph.The digital twin knowledge graph model proposed in this paper adopts a three-layer architecture of concept-instance-module.The concept layer establishes a comprehensive and organic knowledge network through the knowledge graph.The instance layer achieves digital modeling to reproduce theoretical parameters realistically.The knowledge module layer integrates the knowledge of the previous two layers to form functional modules for comprehensive monitoring and control.This model can provide more accurate and detailed modeling and analysis of industrial processing knowledge,helping enterprises to achieve advanced application functions such as digital modeling,accurate simulation,predictive analysis,and anomaly detection.

Key words: Digital twin, Knowledge graph, Intelligent manufacturing, Optimization of the production process, Quality control