Artificial Intelligence Technologies and Applications in Additive Manufacturing

Abstract

Additive manufacturing (AM) has played an important role in the manufacturing system in various areas of applications such as industrial, defense, biomedical and aerospace. There are various AM processes available for producing components. Due to the complexities of design, material selection, and process parameters, it is quite difficult to optimize AM processes. Remarkably, AM expeditiously progressed with the application of artificial intelligence (AI), offering improved process parameters optimization, design optimization, quality prediction, and process control. This study primarily investigates ML algorithms, computer vision, and NLP and how they have been utilized in AM to optimize real-time monitoring, accuracy of defect detection, predictive process mapping, and predictive process parameters. Recent approaches that leverage CNN, ANN, GPR, DT, NLP, computer vision, and reinforcement learning models are improving the optimization and efficiency of AM. This paper also deals with an overview of the challenges, limitations, and future directions of the potential AI applications in AM. And explains that AI accelerates technological advancement as well as facilitates the development of smart and autonomous manufacturing environments.