...Mayur Jiyalal Prajapati; Heng-Hsiang Chang; Dong Ruan; Wojciech Macek; Cho-Pei Jiang Purpose The study aims to develop an intelligent and real-time defect detection framework for Fused Filament Fabrication ( FFF ) to address limitations in process reliability and quality control. It focuses...

... 2026 31 03 2026 © 2026 Emerald Publishing Limited 2026 Emerald Publishing Limited Licensed re-use rights only Additive manufacturing Fused filament fabrication Layer shifting Defect detection Machine learning MEMS sensors Science and Engineering Research Board (SERB...

... and XceptionNet performed best in cracking detection at 99.32%. For multiple defect detection, MobileNetV2 outperformed with 98.90% accuracy. Originality/value This research presents a novel approach for defect detection in 3D-printed parts by comparing DL models in detecting individual defects as well...

... control. Design/methodology/approach This study develops an explainable artificial intelligence (AI) framework, a zero-bias deep neural network (DNN) model for real-time defect detection during the AM process. In this method, the last dense layer of the DNN is replaced by two consecutive parts...

... manufacturing Process monitoring Defect detection Non-destructive methods Additive manufacturing (AM) comprises a technology in which three-dimensional physical objects are created by adding layer-upon-layer feedstock material such as plastic, ceramic and metal. AM has been developed rapidly...