Construction of CNC Machining Process Knowledge Base and Intelligent Decision-Making Method

Abstract

To address the issues of dispersed process knowledge, strong reliance on tacit experience, and low automation in intelligent decision-making within the field of CNC machining, this paper investigates the construction of a CNC machining process knowledge base and intelligent decision-making methods. By constructing a semantic representation model for process elements, achieving the extraction and cleaning of multi-source heterogeneous data, and completing the standardized description of knowledge based on ontology, this research resolves the problem of structured knowledge representation. Furthermore, a hierarchical and progressive architecture for the process knowledge base is designed, a self-organizing evolution mechanism for knowledge rules is proposed, and an information integration interface with CNC systems is defined, thereby establishing a dynamic and scalable knowledge management infrastructure. Building upon this knowledge base, the generation of process chains based on constraint satisfaction and reasoning is realized, a multi-objective collaborative optimization strategy for process parameters that integrates domain knowledge is proposed, and a simulation verification and confidence assessment system for decision solutions is established, ultimately forming a complete theoretical and methodological framework that spans from knowledge aggregation and organization to the generation of intelligent decisions.