Construction of knowledge graph for mechanical manufacturing and application of intelligent process decision-making
机械制造知识图谱构建与智能工艺决策应用

摘要

本文探讨了机械制造知识图谱构建与智能工艺决策应用的关键问题。首先分析了知识图谱构建过程中面临的挑战，包括数据来源复杂、知识抽取难度大、实体与关系识别不准确以及知识动态更新等问题。接着提出了知识图谱在智能工艺决策中的应用策略，涵盖工艺方案优化、生产流程优化、质量控制和设备故障预测等环节。最后通过实际案例展示了知识图谱与智能决策深度融合的实践效果，验证了其在提升生产效率、降低成本和提高产品质量方面的显著优势。结果表明，知识图谱与智能决策的结合为机械制造智能化转型提供了有力支持。

Abstract

This paper explores the key issues in the construction of mechanical manufacturing knowledge graphs and their application in intelligent process decision-making. It first analyzes the challenges faced in the construction of knowledge graphs, including complex data sources, difficulties in knowledge extraction, inaccurate identification of entities and relationships, and dynamic knowledge updates. Subsequently, it proposes application strategies for knowledge graphs in intelligent process decision-making, covering process optimization, production flow optimization, quality control, and equipment failure prediction. Finally, through practical cases, it demonstrates the significant advantages of the deep integration of knowledge graphs and intelligent decision-making in improving production efficiency, reducing costs, and enhancing product quality. The results show that the combination of knowledge graphs and intelligent decision-making provides strong support for the intelligent transformation of mechanical manufacturing.