Tech Xplore

Lower printing temperatures cut defects in aluminum 3D-printed parts, study finds

Scientists at The University of Manchester have uncovered how subtle changes in temperature during a promising metal 3D ...
Officer.com

Zero Defects Belongs to Range Safety, Not Student Learning

While catastrophic safety failures must never be tolerated, meaningful firearms training for law enforcement often happens ...
The Tech Edvocate

How to handle product defects

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 ...
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.
IEEE

Software Defects Identification: Results Using Machine Learning and Explainable Artificial Intelligence Techniques

Abstract: The rising deployment of software in automation and the cognitive skills of machines indicate a machine revolution in modern human civilization. Thus, diagnosing and predicting software ...
IEEE

Machine Learning-Based Multimode Ultrasonic Guided Wave Feature Extraction and Defect Identification Method for Tri-Post Insulators

Abstract: Gas insulated metal-enclosed transmission lines (GILs) have become the optimal solution for long-distance, high-capacity power transmission. However, the tri-post insulator may develop micro ...
Scientific Research Publishing

Wen, Y. and Wang, L. (2024) YOLO-SD: Simulated Feature Fusion for Few-Shot Industrial Defect Detection Based on YOLOv8 and Stable Diffusion. International Journal of Machine ...

ABSTRACT: Effectively detecting subtle surface defects in strip steel is vital for industrial quality assurance; however, most existing approaches fail to strike an optimal balance between accuracy ...
Semiconductor Engineering

Catching Critical Defects In TSVs And Stacked Chips

Variation is becoming a bigger problem in multi-die assemblies with TSVs and hybrid bonding. Multi-modal approaches are required to test these devices. AI plays a role in improving defect capture rate ...
BMJ

Prenatal detection of congenital heart defects using the deep learning-based image and video analysis: protocol for Clinical Artificial Intelligence in Fetal Echocardiography ...

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 ...
Scientific Research Publishing

Defect Detection in Manufacturing: An Integrated Deep Learning Approach ()

This research investigates deep learning-based approach for defect detection in the steel production using Severstal steel dataset. The developed system integrates DenseNet121 for classification and ...
Frontiers

Editorial: Zero defect manufacturing in the era of industry 4.0 for achieving sustainable and resilient manufacturing

The manufacturing sector has experienced steady growth and change in recent years as businesses have been able to fulfill increased client expectations, mostly as a result of the innovations and ...