Technical Library | 2021-04-15 14:49:27.0
In this study, a predefined template-based image processing system is proposed to automatically detect of PCB soldering defects that negatively affect circuit operation. The proposed system consists of a scaled inspection structure, a camera, an image processing algorithm merged with Fuzzy and template guided inspection process. The prototype is produced using a plastic material, depending on the focal length of the camera and the PCB size. Image processing step comprises two steps. Firstly, solder joints are determined and boxed using Fuzzy C-means clustering algorithm.
Technical Library | 2021-08-04 18:46:25.0
The process of printed circuit board assembly (PCBA) involves several machines, such as a stencil printer, placement machine and reflow oven, to solder and assemble electronic components onto printed circuit boards (PCBs). In the production flow, some failure prevention mechanisms are deployed to ensure the designated quality of PCBA, including solder paste inspection (SPI), automated optical inspection (AOI) and in-circuit testing (ICT). However, such methods to locate the failures are reactive in nature, which may create waste and require additional effort to be spent re-manufacturing and inspecting the PCBs. Worse still, the process performance of the assembly process cannot be guaranteed at a high level. Therefore, there is a need to improve the performance of the PCBA process. To address the aforementioned challenges in the PCBA process, an intelligent assembly process improvement system (IAPIS) is proposed, which integrates the k-means clustering method and multi-response Taguchi method to formulate a pro-active approach to investigate and manage the process performance.
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 | 2023-01-17 17:16:43.0
A test program was developed to evaluate the effectiveness of vacuum reflow processing on solder joint voiding and subsequent thermal cycling performance. Area array package test vehicles were assembled using conventional reflow processing and a solder paste that generated substantial void content in the solder joints. Half of the population of test vehicles then were re-processed (reflowed) using vacuum reflow. Transmission x-ray inspection showed a significant reduction in solder voiding after vacuum processing. The solder attachment reliability of the conventional and vacuum reflowed test vehicles was characterized and compared using two different accelerated thermal cycling profiles. The thermal cycling results are discussed in terms of the general impact of voiding on solder thermal fatigue reliability, results from the open literature, and the evolving industry standards for solder voiding. Recommendations are made for further work based on other void reduction methods and additional reliability studies.
Technical Library | 2021-12-16 01:33:11.0
Ball Grid Array devices, BGAs, are widely used in a vast range of products including consumer, telecommunications and office based systems. As an area array device of solder joints, it provides high packing density with a relatively easy introduction cycle. However, over the last couple of years engineers have started to experiment, and in some cases implement, stacked packages, of the type often called Package on Package, or POP. In simple terms, POP devices are the stacking of components, one on top of the other, either during the original component manufacture or during printed board assembly.
Technical Library | 2018-09-26 20:33:26.0
Bottom terminated components, or BTCs, have been rapidly incorporated into PCB designs because of their low cost, small footprint and overall reliability. The combination of leadless terminations with underside ground/thermal pads have presented a multitude of challenges to PCB assemblers, including tilting, poor solder fillet formation, difficult inspection and – most notably – center pad voiding. Voids in large SMT solder joints can be difficult to predict and control due to the variety of input variables that can influence their formation. Solder paste chemistries, PCB final finishes, and reflow profiles and atmospheres have all been scrutinized, and their effects well documented. Additionally, many of the published center pad voiding studies have focused on optimizing center pad footprint and stencil aperture designs. This study focuses on I/O pad stencil modifications rather than center pad modifications. It shows a no-cost, easily implemented I/O design guideline that can be deployed to consistently and repeatedly reduce void formation on BTC-style packages.
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