Researchers have developed a new method for detecting defects in additively manufactured components. Researchers at the University of Illinois Urbana-Champaign have developed a new method for ...

UC San Francisco researchers have found a way to double doctors’ accuracy in detecting the vast majority of complex fetal heart defects in utero – when interventions could either correct them or ...

Detecting sub-5nm defects creates huge challenges for chipmakers, challenges that have a direct impact on yield, reliability, and profitability. In addition to being smaller and harder to detect, ...

Whether the discussion is about smart manufacturing or digital transformation, one of the biggest conversations in the semiconductor industry today centers on the tremendous amount of data fabs ...

Researchers have devised and tested a new, highly sensitive method of detecting and counting defects in transistors -- a matter of urgent concern to the semiconductor industry as it develops new ...

Using X-ray beams and machine learning for detecting structural defects, such as pore formation, can help prevent failure of metal 3D-printed parts. Systematic computer-based material design uses ...

What if manufacturing companies could pinpoint the exact cause of a defect the moment it occurs, preventing costly production delays and ensuring top-notch quality? Generative artificial intelligence ...

Amazon today announced the general availability of Amazon Lookout for Vision, a cloud service that analyzes images using computer vision to spot product or process defects and anomalies in ...

Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine-learning algorithm designed to identify physical anomalies in solar ...

Longitudinal (top) and axial (middle) images of X-Ray CT data of parts with 6 internal defects: a spherical clog, a stellated shaped clog, a cone shaped void, a blob shaped void, an elliptical warp of ...