A review on AI integration with FDM printing to enhance precision, efficiency, and process optimization
Sundarakannan Rajendran, Geetha Palani, Shankar Sanjeevi, Arumugaprabu Veerasimman, Herri Trilaksana, Vickram Sundaram, M. Uthayakumar, Yo-Lun Yang, Vigneshwaran Shanmugam
Abstract
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.