In industry, the detection of anomalies such as scratches, dents, and discolorations is crucial to ensure product quality and safety. However, conventional methods rely on heavy computational ...

Recently, defect detection systems using artificial intelligence (AI) sensor data have been installed in smart factory manufacturing sites. However, when the manufacturing process changes due to ...

As technology nodes shrink, end users are designing systems where each chip element is being targeted for a specific technology and manufacturing node. While designing chip functionality to address ...

RAILWAY AGE MARCH 2022 ISSUE: Since 2020, Transportation Technology Center, Inc. (TTCI) has been conducting tests to evaluate the capability of electromagnetic acoustic transducer (EMAT) ...

Amazon today announced the general availability of Amazon Lookout for Vision, a cloud service that analyzes images using computer vision to spot product or process defects and anomalies in ...

SiC is extensively used in microelectronic devices owing to its several unique properties. However, low yield and high cost of the SiC manufacturing process are the major challenges that must be ...

Siliconware Precision Industries (SPIL) has achieved satisfactory results from applying AI to detect defects on packaging lines following nine months of efforts, according to KH Wan, director of ...

Researchers have devised and tested a new, highly sensitive method of detecting and counting defects in transistors -- a matter of urgent concern to the semiconductor industry as it develops new ...

Advanced machine learning is beginning to make inroads into yield enhancement methodology as fabs and equipment makers seek to identify defectivity patterns in wafer images with greater accuracy and ...

ATPG targets faults at IC-gate boundaries, but 50% of defects are located within cells. Learn how cell-aware ATPG and user-defined fault models help to ferret out these hard-to-squash bugs.