Intelligent Numerical Control Programming System Based on Knowledge Graph

Abstract

With the wide application of computer-aided manufacturing (CAM) software, manufacturing enterprises have accumulated a wealth of numerical control (NC) programming data, providing valuable knowledge resources for new products’ development. Efficiently acquiring and reusing existing NC knowledge is essential for enhancing programming efficiency, improving product quality, and shortening manufacturing cycles. This study proposes an intelligent NC programming method based on knowledge graph. Firstly, the relevant knowledge in the NC programming domain is analyzed, and CAM knowledge elements are constructed to reduce the granularity of knowledge. Then, the ontology layer and data layer are constructed to achieve the development of the knowledge graph. Next, knowledge reasoning is performed on the knowledge graph through entity alignment and semantic rule-based reasoning. Furthermore, to address the issues of low reliability, limited applicability and need for frequent manual modifications in NC programming templates guided by the CAM knowledge graph, a CAM knowledge graph completion method based on neighborhood aggregation and semantic enhancement is proposed. Finally, an intelligent NC programming system based on knowledge graph is developed, and comparative experiments with mainstream algorithms on public datasets for few-shot knowledge graph completion are conducted, validating the effectiveness of the proposed method by experimenting with the key components of marine diesel engines.