Chipmakers are using more and different traditional tool types than ever to find killer defects in advanced chips, but they are also turning to complementary solutions like advanced forms of machine ...

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 ...

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 ...

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 ...

Advanced machine learning is beginning to make inroads into yield enhancement methodology as fabs and equipment makers seek to identify defectivity patterns in wafer images with greater accuracy and ...

50% of companies that embrace AI over the next five to seven years have the potential to double their cash flow with manufacturing leading all industries due to its heavy reliance on data according to ...

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 ...

Structural defects that form during additive manufacturing, also known as 3D printing, are a barrier to some applications of this technology. Researchers used diagnostic tools and machine learning to ...