Spread the love“`html In any product-driven industry, dealing with product defects is a given. No matter how stringent the quality checks or how dedicated the design team, issues can arise during ...

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

Abstract: This paper presents a novel approach to automating aircraft surface inspection by leveraging deep learning techniques for the classification of thirteen different types of defects across the ...

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.

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 ...

At present, surface defect equipment based on machine vision has widely replaced artificial visual inspection in various industrial fields, including 3C, automobiles, home appliances, machinery ...

Introduction Congenital heart defect (CHD) is a significant, rapidly emerging global problem in child health and a leading cause of neonatal and childhood death. Prenatal detection of CHDs with the ...

What if manufacturing companies could pinpoint the exact cause of a defect the moment it occurs, preventing costly production delays and ensuring top-notch quality? Generative artificial intelligence ...

Machine learning (ML) has emerged as a powerful tool for studying the properties of condensed matter. To date, most research has focused on the bulk properties of solids, however, defects are ...