Materials scientists at Rice University have developed a new workflow methodology for measuring microscopic defects in ...

Ford rehired roughly 350 veteran engineers to reprogram and retrain artificial intelligence tools used for quality control ...

When the defect-engineered MOF-525 interacts with phosphonyl fluoride nerve agents, it triggers a distinct red fluorescence signal. This dual-sieving strategy, combining molecular size exclusion and ...

A new study explores deep learning for image-based defect detection during 3D printing, looking to catch bad builds.

Whether the discussion is about smart manufacturing or digital transformation, one of the biggest conversations in the semiconductor industry today centers on the tremendous amount of data fabs ...

Researchers have tested eight stand-alone deep learning methods for PV cell fault detection and have found that their accuracy was as high as 73%. All methods were trained and tested on the ELPV ...

Detecting macro-defects early in the wafer processing flow is vital for yield and process improvement, and it is driving innovations in both inspection techniques and wafer test map analysis. At the ...

The ongoing evolution of software defect detection methodologies leveraging large language models is rapid; however, the ...

TrackEi enables real-time defect detection and predictive maintenance using NVIDIA Jetson edge AI. Credit: APChanel/Shutterstock. L&T Technology Services (LTTS) has announced the launch of TrackEi, an ...