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.

k-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 ...

Abstract: Automated detection of metallic surface defects has increasingly become essential for industrial quality control and safety. In this work, we evaluate the balance between deep learning model ...

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 ...

US researchers say a self-supervised machine-learning tool can identify long-term physical defects in solar assets weeks or years before conventional inspections, potentially reducing operations and ...

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 ...

ABSTRACT: Regular pipeline inspections are crucial for timely identification of critical defects and ensuring pipeline integrity. To address the challenges of detecting defects in PE gas pipelines ...

A study published in Molecules and led by researchers from the Changchun Institute of Optics, Fine Mechanics and Physics (CIOMP) of the Chinese Academy of Sciences demonstrated how deep learning can ...

Abstract: Defects occurring in manufacturing processes can lead to customer dissatisfaction, reduced product quality, and increased operational costs. Accurately predicting product defects is critical ...