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.
Technical Library | 2022-09-12 14:07:47.0
Unique component handling issues can arise when an assembly factory uses highly-moisture sensitive surface mount devices (SMDs). This work describes how the distribution of moisture within the molded plastic body of a SMD is an important variable for survivability. JEDEC/IPC [1] moisture level rated packages classified as Levels 4-5a are shown to require additional handling constraints beyond the typical out-of-bag exposure time tracking. Nitrogen or desiccated cabinet containment is shown as a safe and effective means for long-term storage provided the effects of prior out-of-bag exposure conditions are taken into account. Moisture diffusion analyses coupled with experimental verification studies show that time in storage is as important a variable as floor-life exposure for highly-moisture sensitive devices. Improvements in floor-life survivability can be obtained by a handling procedure that includes cyclic storage in low humidity containment. SMDs that have exceeded their floor-life limits are analyzed for proper baking schedules. Optimized baking schedules can be adopted depending on a knowledge of the exposure conditions and the moisture sensitivity level of the device.
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