Technical Library | 2023-09-13 13:03:25.0
SMT auto aqueous stencil cleaning machines are an essential tool for any SMT production line. These machines use a variety of methods to remove contaminants and debris from SMT stencils, which can cause defects and reliability issues.
Technical Library | 2021-12-31 06:09:47.0
The packaging method of surface mount components has become an important part of the SMT system. It directly affects the efficiency of assembly production and must be optimized in combination with the type and number of feeders of the SMT machine. There are four main types of packaging for surface mount components, Tape, tube, tray and bulk.
Technical Library | 2023-11-20 18:10:20.0
The electronics production is prone to a multitude of possible failures along the production process. Therefore, the manufacturing process of surface-mounted electronics devices (SMD) includes visual quality inspection processes for defect detection. The detection of certain error patterns like solder voids and head in pillow defects require radioscopic inspection. These high-end inspection machines, like the X-ray inspection, rely on static checking routines, programmed manually by the expert user of the machine, to verify the quality. The utilization of the implicit knowledge of domain expert(s), based on soldering guidelines, allows the evaluation of the quality. The distinctive dependence on the individual qualification significantly influences false call rates of the inbuilt computer vision routines. In this contribution, we present a novel framework for the automatic solder joint classification based on Convolutional Neural Networks (CNN), flexibly reclassifying insufficient X-ray inspection results. We utilize existing deep learning network architectures for a region of interest detection on 2D grayscale images. The comparison with product-related meta-data ensures the presence of relevant areas and results in a subsequent classification based on a CNN. Subsequent data augmentation ensures sufficient input features. The results indicate a significant reduction of the false call rate compared to commercial X-ray machines, combined with reduced product-related optimization iterations.
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