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 ...

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 ...

In biology, defects are generally bad. But in materials science, defects can be intentionally tuned to give materials useful ...

Closing the casting-to-machining divide reduces scrap, speeds production and lowers costs without compromising quality.

Robust data from quality assurance provider Intertek CEA?s new (2025) manufacturing quality report reveals the most common ?

This new technical paper titled “End-to-end deep learning framework for printed circuit board manufacturing defect classification” is from researchers at École de technologie supérieure (ÉTS) in ...

Young, T. , Guymon, J. , Pankow, M. and Ngaile, G. (2026) A Material Removal Prediction Framework for Ball EEM Polishing in ...

Machine learning (ML) has emerged as a powerful tool for studying the properties of condensed matter. To date, most research has focused on the bulk properties of solids, however, defects are ...

Ceramic materials are renowned for their hardness and high-temperature resistance, making them indispensable in fields such as aerospace, electronics, and biomedical devices. However, these properties ...