UCL Team Develops AI Tool to Monitor Metal Additive Manufacturing

Researchers at University College London are using artificial intelligence to speed up the analysis of metal 3D printing, a critical step in improving part quality and reliability. A new neural network, AM-SegNet, can quickly process X-ray images captured during printing, helping engineers better understand the process and enhance manufacturing outcomes for applications such as aerospace.

Using AI to Understand Metal Printing

Metal additive manufacturing enables the creation of complex parts that are difficult or impossible to make with traditional methods. However, producing reliable components remains a challenge, particularly for high-stakes industries. To investigate the process, mechanical engineering researchers have been using high-powered X-rays to monitor metal as it prints. These experiments generate massive amounts of image data—far beyond what can be analyzed manually.