Technical Library: void rate (Page 1 of 1)

Effects of Assebly Process Variables on Voiding at a Thermal Interface.

Technical Library | 2007-04-04 11:43:41.0

The present work offers a discussion and a first case study to identify and illustrate voiding mechanisms for a particular TIM between a heat spreader and the back of a flip chip. Pronounced differences were observed between stencil printing and dispensing in terms of initial void formation, apparently related to the specific properties of the material. Measurements of the effects of heat ramp rate and peak temperature showed the subsequent evolution and final void size distribution to be determined by the initial part of the cure profile up to the material gelling temperature.

Universal Instruments Corporation

Enhanced X-Ray Inspection of Solder Joints in SMT Electronics Production using Convolutional Neural Networks

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.

Siemens Process Industries and Drives

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