In software testing, keeping the user interface consistent and error-free requires regular checks after every update. Teams ...

Researchers have published research detailing their development of an AI framework to detect defects in additively ...

Smart manufacturing technologies, such as digital tools and connected systems, can improve visibility, performance and ...

Laser powder bed fusion (LPBF) is revolutionizing metal 3D printing, but ensuring consistent quality is still a challenge. Researchers are now using AI and machine learning to monitor melt pools, ...

This software is a research prototype, solely developed for and published as part of the publication MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot ...

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 and ...

Researchers report a machine learning approach to predict LPBF defects from up-skin and down-skin angles, suggesting there might be angle-aware process control for metal AM. Laser Powder Bed Fusion ...

Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine-learning algorithm designed to identify physical anomalies in solar ...

Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine learning algorithm designed to identify physical anomalies in solar ...