Anomaly Detection for Solder Joints Using β-VAE

In the assembly process of printed circuit boards (PCBs), most of the errors are caused by solder joints in surface mount devices (SMDs). In the literature, traditional feature extraction-based methods require designing hand-crafted features and rely on the tiered red green blue (RGB) illumination t...

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Veröffentlicht in:	IEEE transactions on components, packaging, and manufacturing technology (2011) Jg. 11; H. 12; S. 2214 - 2221
Hauptverfasser:	Ulger, Furkan, Yuksel, Seniha Esen, Yilmaz, Atila
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.12.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">β -variational autoencoder (VAE) Accuracy Anomalies Anomaly detection Artificial neural networks automated optical inspection (AOI) Automatic optical inspection Circuit boards Errors Feature extraction Illumination Inspection Integrated circuits Model accuracy Representations solder joint inspection (SJI) Soldered joints Soldering Solders Surface-mounted devices Training unsupervised anomaly detection VAE
ISSN:	2156-3950, 2156-3985
Online-Zugang:	Volltext
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