Technical Library | 2018-07-18 16:28:26.0
Reduction of first pass defects in the SMT assembly process minimizes cost, assembly time and improves reliability. These three areas, cost, delivery and reliability determine manufacturing yields and are key in maintaining a successful and profitable assembly process. It is commonly accepted that the solder paste printing process causes the highest percentage of yield challenges in the SMT assembly process. As form factor continues to get smaller, the challenge to obtain 100% yield becomes more difficult.This paper will identify defects affecting SMT yields in the printing process and discuss their Root Cause. Outer layer copper weight and surface treatment will also be addressed as to their effect on printability. Experiments using leadless and emerging components will be studied and root cause analysis will be presented
Technical Library | 2017-11-08 23:22:04.0
Due to the ongoing trend towards miniaturization of power components, the need for increased thermal conductivity of solder joints in SMT processes gains more and more importance. Therefore, the role of void free solder joints in power electronics becomes more central. Voids developed during soldering reduce the actual thermal transfer and can cause thermal damage of the power components up to their failure. For this reason, the company has developed a new technique to minimize the formation of these voids during the soldering process.
Technical Library | 2010-10-13 17:29:21.0
The number of failures caused by electrostatic discharges (ESD) has been increasing for some time now. So, it is necessary for everyone, who handles electrostatic sensitive devices (ESDS), to know the reasons of such failures. This presentation will give
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 | 2007-11-15 15:54:44.0
At the contractor level once a product is required to be soldered with lead-free solders all the processes must be assessed as to insure the same quality a customer has been accustomed to with a Sn63Pb37 process is achieved. The reflow, wave soldering and hand assembly processes must all be optimized carefully to insure good joint formation as per the appropriate class of electronics with new solder alloys and often new fluxes.
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