Semiconductor Engineering

Using Automatic Defect Classification To Reduce The Escape Rate Of Defects

Automated optical inspection (AOI) is a cornerstone in semiconductor manufacturing, assembly and testing facilities, and as such, it plays a crucial role in yield management and process control.
Edex Live on MSN

Greenwood High alumni win top prize at Purdue AI showcase

Two alumni of Greenwood High International School have secured first place in the poster competition at Purdue University's ...
Glass Magazine

k-Space Introduces Machine Learning Upgrade for Inline Glass Defect Detection

Space Associates, Inc., a provider of advanced metrology and inspection solutions, announced new machine learning capabilities for its kSA Glass Breakage & Defect Detection tool. The enhancement adds ...
EDN

Electroglas adds auto defect classification to wafer inspection

SAN JOSE, Calif. – Electroglas Inc., a supplier of process management tools for the semiconductor industry, has introduced automatic defect classification software that it calls DefectID. DefectID ...
pv magazine International

Ensemble deep learning for PV cell defect detection

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 ...
Semiconductor Engineering

AI Models Transform Defect Inspection And Review, But Can Fail To Scale

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.