基于迁移学习和合成数据生成的印刷电路板装配制造自动光学检测

Syed Saad Saif, Kerem Aras, A. Giuseppi
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引用次数: 0

摘要

自动光学检测(AOI)是生产线上最常见和最有效的质量检查之一。本文详细介绍了深度学习解决方案的设计,该解决方案是为解决印刷电路板组装(PCBA)制造过程中的特定质量控制而开发的。开发的深度神经网络利用迁移学习和合成数据生成过程进行训练,即使可用的数据样本数量很低。整个AOI系统被设计为部署在计算能力有限的低成本硬件上,以简化其在工业环境中的部署。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated Optical Inspection for Printed Circuit Board Assembly Manufacturing with Transfer Learning and Synthetic Data Generation
Automated Optical Inspection (AOI) is among the most common and effective quality checks employed in production lines. This paper details the design of a Deep Learning solution that was developed for addressing a specific quality control in a Printed Circuit Board Assembly (PCBA) manufacturing process. The developed Deep Neural Network exploits transfer learning and a synthetic data generation process to be trained even if the quantity of the data samples available is low. The overall AOI system was designed to be deployed on low-cost hardware with limited computing capabilities to ease its deployment in industrial settings.
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