人工智能代理模型在激光金属增材中的典型应用OA

Additive manufacturing(AM)has demonstrated substantial application potential in aerospace,automotive,bio-medical,and high-end equipment industries,owing to its exceptional geometric freedom and customization capabilities.However,for metal additive manufacturing,the efficient design of high-performance structures that satisfy specific func-tional requirements,along with the accurate prediction of their mechanical behavior and service performance under complex working conditions,remains a critical bottleneck hindering its widespread industrial adoption.This paper presents a concise review of recent research on artificial intelligence surrogate models,constrained by both data-driven approaches and physi-cal mechanisms,in laser-based metal additive manufacturing.The review primarily covers typical applications in structural design optimization,rapid prediction of macroscopic properties,and correlation analysis among process parameters,micro-structure,and macroscopic properties.Furthermore,several recommendations are provided regarding the current challenges and corresponding strategies in the integration of laser metal additive manufacturing with artificial intelligence.The objec-tive is to offer valuable insights and references for researchers and engineers in related fields,thereby promoting the develop-ment of metal additive manufacturing toward greater intelligence,efficiency,and reliability.