Technical Library | 2023-01-17 17:12:33.0
Reflowed indium metal has for decades been the standard for solder thermal interface materials (solder TIMs or sTIMs) in most high-performance computing (HPC) TIM1 applications. The IEEE Heterogeneous Integration Thermal roadmap states that new thermal interface materials solutions must provide a path to the successful application of increased total-package die areas up to 100cm2. While GPU architectures are relatively isothermal during usage, CPU hotspots in complex heterogeneously-integrated modules will need to be able to handle heat flux hotspots up to 1000W/cm2 within the next two years. Indium and its alloys are used as reflowed solder thermal interface materials in both CPU and GPU "die to lid/heat spreader" (TIM1) applications. Their high bulk thermal conductivity and proven long-term reliability suit them well for extreme thermomechanical stresses. Voiding is the most important failure mode and has been studied by x-ray. The effects of surface pretreatment, pressure during reflow, solder flux type/fluxless processing, and preform design parameters, such as alloy type, are also examined. The paper includes data on both vacuum and pressure (autoclave) reflow of sTIMs, which is becoming necessary to meet upcoming requirements for ultralow voiding in some instances.
Technical Library | 2023-09-15 10:00:02.0
Experience top-tier quality inspection with our DIP Inverted Camera Online PCBA AOI solution. Ensure flawless PCB assemblies and detect defects with precision using advanced technology. Improve efficiency and minimize production issues with this cutting-edge automated optical inspection system.
Technical Library | 2020-01-06 07:54:53.0
ASCEN technology make the mini PCB magazine loader without magazine rack to save more space for most of production line,PCB mini loader can use as the PCB unloader or loading machine in different station and let the factory maximized to using the space
Technical Library | 2023-09-16 03:40:41.0
Wave soldering machines are the most efficient way to solder PCBs. They are used to solder components to a PCB by passing the PCB through a wave of molten solder. This process is fast, accurate, and repeatable, making it ideal for mass production. In this article, we will discuss the basics of wave soldering machines, including their components, operation, and benefits. We will also provide a buying guide to help you choose the right wave soldering machine for your needs.
Technical Library | 2024-08-29 18:30:46.0
The mechanical experience of consumption (i.e., feel, softness, and texture) of many foods is intrinsic to their enjoyable consumption, one example being the habit of twisting a sandwich cookie to reveal the cream. Scientifically, sandwich cookies present a paradigmatic model of parallel plate rheometry in which a fluid sample, the cream, is held between two parallel plates, the wafers. When the wafers are counterrotated, the cream deforms, flows, and ultimately fractures, leading to separation of the cookie into two pieces. We introduce Oreology (/Oriːˈɒl@dʒi/), from the Nabisco Oreo for "cookie" and the Greek rheo logia for "flow study," as the study of the flow and fracture of sandwich cookies. Using a laboratory rheometer, we measure failure mechanics of the eponymous Oreo's "creme" and probe the influence of rotation rate, amount of creme, and flavor on the stress–strain curve and postmortem creme distribution. The results typically show adhesive failure, in which nearly all (95%) creme remains on one wafer after failure, and we ascribe this to the production process, as we confirm that the creme-heavy side is uniformly oriented within most of the boxes of Oreos. However, cookies in boxes stored under potentially adverse conditions (higher temperature and humidity) show cohesive failure resulting in the creme dividing between wafer halves after failure. Failure mechanics further classify the creme texture as "mushy." Finally, we introduce and validate the design of an open-source, three-dimensionally printed Oreometer powered by rubber bands and coins for encouraging higher precision home studies to contribute new discoveries to this incipient field of study
Technical Library | 2013-07-03 10:31:54.0
It has been demonstrated in numerous pieces of work that stencil printing, one of the most complex PCB assembly processes, is one of the largest contributors to defects (Revelino et el). This complexity extends to prototype builds where a small number of boards need to be assembled quickly and reliably. Stencil printing is becoming increasingly challenging as packages shrink in size, increase in lead count and require closer lead spacing (finer pitch). Prototype SMT assembly can be further divided between industrial and commercial work and the DIYer, hobbyist or researcher groups. This second group is highly price sensitive when it comes to the materials used for the board assembly as their funds are sourced from personal or research monies as opposed to company funds. This has led to development of a lower cost SMT printing stencil made from plastic film as opposed to the more traditional stainless steel stencil used by industrial and commercial users.This study compares the performance of these two traditional materials and their respective impact on solder paste printing including efficiency and print quality.
Technical Library | 2012-02-23 21:16:28.0
Installed for the first time 20 years ago, Automated Optical Inspection (AOI) more recently has become an essential part of our SMT environment. Today, most process engineers are turning to machines as an inspection strategy for addressing quality and pro
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 | 2017-08-28 17:14:41.0
PCB suppliers in the automotive space are vastly accelerating their time to market by using automated optical inspection (AOI) systems during PCB assembly. However, this next-generation technique is not limited in scope to the automotive industry – it has powerful implications for the entire PCB industry.
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).
