A new study explores deep learning for image-based defect detection during 3D printing, looking to catch bad builds.

Researchers built an AI system that adapts to process changes, maintaining defect detection accuracy and lowering retraining costs in smart factories. (Nanowerk News) Artificial intelligence is ...

In biology, defects are generally bad. But in materials science, defects can be intentionally tuned to give materials useful new properties. Today, atomic-scale defects are carefully introduced during ...

TDK SensEI’s edgeRX Vision system, powered by advanced AI, accurately detects defects in components as small as 1.0×0.5 mm in real time. Operating at speeds up to 2000 parts per minute, it reduces ...

A research team led by Dr. Jeong Min Park of the Nano Materials Research Division at the Korea Institute of Materials Science (KIMS), in collaboration with Dr. Jaemin Wang and Prof. Dierk Raabe of the ...

The AI model rapidly maps boundary conditions to molecular alignment and defect locations, replacing hours of simulation and enabling fast exploration and inverse design of advanced optical materials.

Printed circuit boards (PCBs) are the foundation of modern electronic devices and demand rigorous quality control to prevent failures caused by manufacturing defects. Contemporary inspection ...