Abstract: If the information of parts and components in the machine tool and the relationship between parts are displayed in the form of graph, which can more effectively learn the information of parts connected around the parts and the positioning details of current parts. It can also assist the assembly of factory CNC machine tools, and solve the current problems of machine tools such as scattered assembly data, non-standard and low assembly efficiency. At present, there are many software describing 3D information of machine tools, so there are many corresponding file formats, which makes it difficult to digitally manage complex assembly products. At the same time, the traditional single connection relationship is difficult to comprehensively depict 3D graphics, so that the efficiency of in-depth learning model in this respect is not high, the knowledge of machine tool model cannot be truly understood, and the knowledge reasoning ability is almost not available. The knowledge graph, in the form of graph, can represent the connection relationship of various model components. The ability to understand knowledge is far beyond the single connection relationship, which can improve the ability of knowledge reasoning. The construction from three-dimensional model to knowledge graph is completed through the steps of machine tool assembly data preparation, assembly knowledge extraction, knowledge reasoning, knowledge storage and knowledge visualization.