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 new properties. Today, atomic-scale defects are carefully introduced during ...

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

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

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 ...

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 ...

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

Assembly houses are fine-tuning their methodologies and processes for automotive ICs, optimizing everything from inspection and metrology to data management in order to prevent escapes and reduce the ...