面向高密度互连电子器件的微结构模具数字化加工路径规划技术OA

With the advancement of technology,while CNC technology has made significant progress,it has also been accompanied by new challenges.The development of high-density interconnect(HDI)electronic devices towards miniaturization,three dimensionalization,and heterogeneous integration has made the manufacturing of microstructure molds a key bottleneck that restricts their performance and reliability.This article proposes a CNC machining tool path planning model that combines deep learning(DL)and ant colony algorithm(ACO).Based on the geometric structure and working principle of multi axis CNC machine tools and cutting tools,construct corresponding mathematical models.Using DL algorithm,identify the tool status from both position and posture aspects,and plan the tool path based on the current tool pose as the initial value;Then,using ACO in artificial intelligence(AI)algorithms,multi-objective search is used to quickly select and determine the shortest path among feasible machining paths.Simulation experiments have shown that the path planned by the model in this article reduces machining time while maintaining high accuracy,significantly reduces cutting force fluctuations,and effectively suppresses tool wear when processing similar complex microstructure molds.