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 | 2010-04-22 14:55:51.0
It is now widely accepted that using designed experiments is the most effective way to optimize surface mount technology (SMT) processes. This situation begs the question "what is an effective strategy in implementing this powerful tool?" This paper will present such a strategy that incorporates Taguchi's approach for screening, full factorial analysis for optimization and central composite design for precise modeling. We will present these techniques using MINITABTM Release 13 statistical software and printed circuit board industry applications.
Technical Library | 2009-11-18 23:37:52.0
Accurate component placement is a basic requirement for any pick and place machine. The first step towards accurate placement is accurate centering, or measurement of the component’s position on the placement head. One of the most widely used centering methods for ICs, connectors, and odd‐shaped components are a camera based system that measures the component position relative to a known point. Camera based centering systems include three main elements: lighting, camera, and software. Each of these elements are critical to obtaining an accurate measurement of the component and ultimately for accurate component placement on the PCB. As the old adage goes, the system is only as strong as its weakest link.
Technical Library | 2024-04-29 21:39:52.0
In this paper, we develop and put into practice an Automatic Optical Inspection (AOI) system based on machine vision to check the holes on a printed circuit board (PCB). We incorporate the hardware and software. For the hardware part, we combine a PC, the three-axis positioning system, a lighting device and CCD cameras. For the software part, we utilize image registration, image segmentation, drill numbering, drill contrast, and defect displays to achieve this system. Results indicated that an accuracy of 5µm could be achieved in errors of the PCB holes allowing comparisons to be made. This is significant in inspecting the missing, the multi-hole and the incorrect location of the holes. However, previous work only focusses on one or other feature of the holes. Our research is able to assess multiple features: missing holes, incorrectly located holes and excessive holes. Equally, our results could be displayed as a bar chart and target plot. This has not been achieved before. These displays help users analyze the causes of errors and immediately correct the problems. Additionally, this AOI system is valuable for checking a large number of holes and finding out the defective ones on a PCB. Meanwhile, we apply a 0.1mm image resolution which is better than others used in industry. We set a detecting standard based on 2mm diameter of circles to diagnose the quality of the holes within 10 seconds.
Technical Library | 2010-05-06 18:46:29.0
Stencil printing technology has come a long way since the early 80’s when SMT process gained importance in the electronics packaging industry. In those early days, components were fairly large, making the board design and printing process relatively simple. The current trend in product miniaturization has led to smaller and more complex board designs. This has resulted into designs with maximum area utilization of the board space. It is not uncommon, especially for hand held devices, to find components only a few millimeters from the edge of the board. The board clamping systems used in the printing process have become a significant area of concern based on the current board design trend.
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