International Journal of Mechanical Engineering

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.

Mechanical manufacturing; Knowledge graph; Intelligent process decision-making; Knowledge extraction; Application practice