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 ...
EurekAlert!

Ensuring flawless metal 3D printing: New research tackles high-fidelity, high-resolution process monitoring

Researchers from Northwestern University, University of Virginia, Carnegie Mellon University, and Argonne National Laboratory have made a significant advancement in defect detection and process ...
Science Daily

Researchers use machine learning to detect defects in additive manufacturing

Researchers have developed a new method for detecting defects in additively manufactured components. Researchers at the University of Illinois Urbana-Champaign have developed a new method for ...
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.
Semiconductor Engineering

Can Your ATPG Do This? Cut Defects Escaping Detection With ML

Chipmakers worldwide consider Automatic Test Pattern Generation (ATPG) their go-to method for achieving high test coverage in production. ATPG generates test patterns designed to detect faults in the ...
Frontiers

Smart Additive Manufacturing of Advanced Materials Using Artificial Intelligence and Machine Learning

The field of additive manufacturing is undergoing a profound transformation as artificial intelligence (AI) and machine learning (ML) become integral to the ...