Technical Library | 2021-11-22 20:44:44.0
Many automated optical inspection (AOI) companies use supervised object detection networks to inspect items, a technique which expends tremendous time and energy to mark defectives. Therefore, we propose an AOI system which uses an unsupervised learning network as the base algorithm to simultaneously generate anomaly alerts and reduce labeling costs. This AOI system works by deploying the GANomaly neural network and the supervised network to the manufacturing system. To improve the ability to distinguish anomaly items from normal items in industry and enhance the overall performance of the manufacturing process, the system uses the structural similarity index (SSIM) as part of the loss function as well as the scoring parameters. Thus, the proposed system will achieve the requirements of smart factories in the future (Industry 4.0).
Technical Library | 2015-06-30 22:02:41.0
This paper describes the losses from defects at the placement process in the SMT line. Two case studies of European and Taiwanese SMT manufacturers illustrate the actual losses from their defects. An evaluation method to select a pre-reflow AOI system maximizing the return on investment (ROI) is introduced. In the end, ROIs of three commercial pre-reflow AOI systems are compared to demonstrate the importance of selecting an appropriate AOI system. This paper will increase the probability that anyone installing an AOI system during the pre-reflow process will obtain a successful gain with short payback period.
Technical Library | 1999-05-06 11:42:16.0
The most reliable and well-designed electronic device can malfunction or fail if it overheats. Considering thermal issues early in the design process results in a thermally conscious system layout and minimizes costs through the use of passive cooling and off-the-shelf components. When thermal issues are left until completion of the design, the only remaining solution may be a costly custom heat sink that requires all the space available. Incorporating a heat sink or a fan into a product after it is fully developed can be expensive, and still may not provide sufficient cooling of the device.
Technical Library | 2009-09-30 23:12:29.0
Being involved in the electronics assembly industry for more than 23 years, specifically in the field of defluxing and cleanliness testing, I have seen my share of environmental regulations. Long before the debate over lead-free alloys, there was the Montreal Protocol.
Technical Library | 2004-05-23 17:18:26.0
This is an article written by our company's experts to help our customers to make informed decision on PC boards purchasing. It introduces the materials that are used in the PCB manufacturing and the cost analysis of different materials.
Technical Library | 2007-05-02 15:00:17.0
This brief study of lead-free wave soldering focuses upon copper dissolution and solder maintenance issues. Unfortunately, it is determined that waste and changeover costs can dramatically increase with lead-free wave soldering.
Technical Library | 2017-06-08 17:31:23.0
Recently, there has been an upsurge in efforts dedicated to developing low-cost flexible electronics by exploiting innovative materials and direct printing technologies. This interest is motivated by the need for low-cost mass-production, shapeable, and disposable devices, and the rapid prototyping of electronics and sensors. This review, following a short overview of main printing processes, reports examples of the development of flexible transducers through low-cost inkjet printing technology.
Technical Library | 2022-06-27 16:50:26.0
Electronics industry is one of the fastest evolving, innovative, and most competitive industries. In order to meet the high consumption demands on electronics components, quality standards of the products must be well-maintained. Automatic optical inspection (AOI) is one of the non-destructive techniques used in quality inspection of various products. This technique is considered robust and can replace human inspectors who are subjected to dull and fatigue in performing inspection tasks. A fully automated optical inspection system consists of hardware and software setups. Hardware setup include image sensor and illumination settings and is responsible to acquire the digital image, while the software part implements an inspection algorithm to extract the features of the acquired images and classify them into defected and non-defected based on the user requirements. A sorting mechanism can be used to separate the defective products from the good ones. This article provides a comprehensive review of the various AOI systems used in electronics, micro-electronics, and opto-electronics industries. In this review the defects of the commonly inspected electronic components, such as semiconductor wafers, flat panel displays, printed circuit boards and light emitting diodes, are first explained. Hardware setups used in acquiring images are then discussed in terms of the camera and lighting source selection and configuration. The inspection algorithms used for detecting the defects in the electronic components are discussed in terms of the preprocessing, feature extraction and classification tools used for this purpose. Recent articles that used deep learning algorithms are also reviewed. The article concludes by highlighting the current trends and possible future research directions.
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 | 2019-08-19 23:55:20.0
Electronic dry cabinet for MSD storage Humidity is one of the key reasons for rejected products, many manufacturers are taking measures to control the humidity to increase production efficiency and save cost. In semiconductor and electronic industry, the key section of rejected products mostly happen during SMT heating process, Climatest Symor® auto dry cabinet is a superior solution to avoid the cracking. Warranty: two years with lifetime technical support
