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

TSMC has expanded its three-decade partnership with NVIDIA by integrating accelerated computing, CUDA-X libraries, and machine learning models directly into its semiconductor fabrication facilities to ...

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 ...

Pickup defects, which we define at late pickups from a vendor or shipper site, represent a very costly challenge in transportation cost management. Pickup defects often cascade to late departures from ...

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 ...

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 ...

New papers on Apple's machine learning blog detail how AI can be used for faster, cheaper, and more effective QE testing, as well as for bug fixing and identification. Now, one of its new studies ...

Detecting sub-5nm defects creates huge challenges for chipmakers, challenges that have a direct impact on yield, reliability, and profitability. In addition to being smaller and harder to detect, ...

Abstract: As electrical devices take on more life-critical roles, such as in autonomous driving, ensuring the quality of solder joints during production becomes increasingly important. Recently, there ...