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 | 2015-04-23 18:48:18.0
Smart phones are complex, costly devices and therefore need to be reworked correctly the first time. In order to meet the ever-growing demand for performance, the complexity of mobile devices has increased immensely, with more than a 70% greater number of packages now found inside of them than just a few years ago. For instance, 1080P HD camera and video capabilities are now available on most high end smart phones or tablet computers, making their production more elaborate and expensive. The printed circuit boards for these devices are no longer considered disposable goods, and their bill of materials start from $150.00, with higher end smart phones going up to $238.00, and tablets well over $300.00.
Technical Library | 2020-09-30 19:23:47.0
There is an increase in the number of optical sensors and cameras being integrated into electronics devices. These go beyond cell phone cameras into automotive sensors, wearables, and other smart devices. The applications can be lens bonding, waveguide imprinting, or other applications where the adhesive is in the optical pathway. To support these various optical applications, new materials with tailorable optical properties are required. There is often a mismatched refractive index between plastic lenses such as PC (Poly Carbonate), COP (Cyclo Olefin Polymer), COC (Cyclo Olefin Copolymer), PMMA (Poly Methyl Methacrylate), and UV curable liquid adhesive. A UV curable liquid adhesive is needed where you can alter the refractive index from 1.470 to 1.730, and maintain high optical performance as yellowness index, haze, and transmittance. This wide range of refractive index possibilities provides optimized optical design. Using particular plastic lens must consider how chemical attack is occurring during the process. Another consideration is that before the UV curable liquid adhesive is cured, chemical raw component can attack the plastic lens which then cracks and delaminates. We will also show engineering and reliability data which defined root cause and provided how optical performance is maintained under different reliability conditions.
Technical Library | 2007-09-27 16:18:15.0
Considerable interest exists in the process known as the pinin- paste, or the Alternative Assembly and Reflow Technology (AART) process. The AART process allows for the simultaneous reflow of both odd-form and through hole devices as well as surface mount components. This process has several advantages over the typical mixed technology process sequence that includes wave soldering and/or hand soldering, often in addition to reflow soldering.
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.
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