Explore how six smart Singapore factories are using advanced technologies to gain global recognition in manufacturing. Read ...

Researchers at The University of Manchester have built a machine-learning model that prevents simulated molecules from flying ...

A new model measures defects that can be leveraged to improve materials' mechanical strength, heat transfer, and ...

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 ...

ABSTRACT: Effectively detecting subtle surface defects in strip steel is vital for industrial quality assurance; however, most existing approaches fail to strike an optimal balance between accuracy ...

Abstract: Semiconductor manufacturing process involves various steps: fabrication of Wafers, testing of wafers, assembly of each single die and package level final test. Out of which, testing of wafer ...

Abstract: Advancements in technology have made deep learning a hot research area, and we see its applications in various fields. Its widespread use in silicon wafer defect recognition is replacing ...

Researchers report a machine learning approach to predict LPBF defects from up-skin and down-skin angles, suggesting there might be angle-aware process control for metal AM. Laser Powder Bed Fusion ...

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 ...

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 ...