AI plays a role in improving defect capture rate and distinguishing between yield-killing and nuisance defects. New developments in wafer edge inspection are proving essential to bonded wafer yields.

Machine learning (ML) is reshaping pipeline integrity management (PIM) from physics-based to data-driven paradigms. This ...

BACKGROUND: Congenital heart disease (CHD), the most common birth defect and a leading cause of infant mortality, is ...

NVIDIA GTC Taipei — NVIDIA today announced that TSMC, the world’s leading semiconductor company, is using NVIDIA accelerated computing and AI to advance semiconductor design and manufacturing.

Nvidia and the world’s largest foundry TSMC are collaborating to speed up semiconductor design and manufacturing. Under the ...

The number of defects detected through inspection is exploding at each new process node. There are now millions of defects being identified on each wafer, but only a fraction of those can cause ...

Researchers from South Korean organisations Pohang University of Science and Technology (POSTECH), Korea Institute of Materials Science (KIMS), and the Hyundai Motor Group, and the Japanese University ...

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 ...

How might aerospace quality engineers progress from defect detection to making defects obsolete entirely? The key to doing so lies in the intersection of AI-based inspection technology, predictive ...

At present, surface defect equipment based on machine vision has widely replaced artificial visual inspection in various industrial fields, including 3C, automobiles, home appliances, machinery ...

A breakthrough contactless inspection system developed at the University of New South Wales (UNSW) Sydney could soon become the new global standard in solar cell testing – cutting waste, doubling ...