材料科学
过程(计算)
工艺工程
3D打印
熔融沉积模型
工艺优化
制造工程
工程制图
机械工程
计算机科学
复合材料
工程类
操作系统
环境工程
作者
Sundarakannan Rajendran,Geetha Palani,Shankar Sanjeevi,Sundarakannan Rajendran,Herri Trilaksana,Vickram Sundaram,M. Uthayakumar,Yo-Lun Yang,Vigneshwaran Shanmugam
标识
DOI:10.1177/07316844251358587
摘要
Fused deposition modeling (FDM) is widely applied in industries such as automotive, aerospace, and healthcare; however, it is limited by print quality, material consumption, and process efficiency. Artificial intelligence (AI) is a game-changing technology that is intended to overcome such limitations. In this review, the use of AI in FDM 3D printing, with special application in real-time error detection, material optimization, predictive maintenance, and generative design, is discussed in detail. AI allows real-time monitoring of the printing process, which leads to dynamic adjustments that improve reliability, minimize material wastage, and enhance structural strength. Efforts have been made on this review in addressing the capability of AI-based solutions to minimize downtime, print setting optimization, and enable mass production of complex, customized parts. Furthermore, the potential of fully autonomous AI-integrated FDM systems in the foreseeable future is discussed. This integration is a significant leap towards the development of FDM efficiency, reliability, and flexibility for industrial applications.
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