Technical Library | 2023-07-22 02:26:05.0
Patch offset; Uneven patches throughout the substrate (each substrate is offset in a different way); Only part of the substrate is offset; Only certain components are offset; The patch Angle is offset; Component absorption error; Laser identification (component identification) error; Nozzle loading and unloading error; Mark (BOC mark, IC mark) identification error; Image recognition error (KE-2060 only); Analysis of the main reasons for throwing material. More information about KINGSUN please Contact US at jenny@ksunsmt.com or visit www.ksunsmt.com
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 | 2013-07-02 16:44:31.0
AOI and AXI systems can address multiple tasks in various locations of the manufacturing process and have become the leading technologies in the quest to identify defects and improve process yields.
Technical Library | 2013-08-07 21:52:15.0
PCB architectures have continued their steep trend toward greater complexities and higher component densities. For quality control managers and test technicians, the consequence is significant. Their ability to electrically test these products is compounded with each new generation. Probe access to high density boards loaded with micro BGAs using a conventional in-circuit (bed-of-nails) test system is greatly reduced. The challenges and complexity of creating a comprehensive functional test program have all but assured that functional test will not fill the widening gap. This explains why sales of automated-optical and automated X-ray inspection (AOI and AXI) equipment have dramatically risen...
Technical Library | 2015-04-29 03:29:56.0
Statistical Appearance Modelling technology enables an AOI system to “learn real world variation” based on operator interaction with inspection task results. This provides an accurate statistical description of normal variation in a product. With modelling technology, the user does not have to anticipate potential defects as the system will “flag” anything outside the “normal production range”. And, since the system is programmed with real production variation, it is sensitive to small subtle changes enabling reliable defect detection. Autonomous prediction of process variation enables an AOI system to be set up from a single PCB with production-ready performance. Setup time can be
Technical Library | 2015-04-02 20:12:58.0
The demands on volume delivery and positioning accuracy for solder paste deposits are increasing as the size and complexity of circuits continue to develop in the electronics industry. According to the iNEMI 2013 placement accuracy for these kinds of components will reach 6 sigma placement accuracy in X and Y of 30 um by 2023.This study attempts to understand the dependencies on piezo actuation pulse profile on jetting deposit quality, especially focused on positioning, satellites and shape. The correlation of deposit diameter and positioning deviation as a function of piezo actuation profile shows that positioning error for deposits increase almost monotonically with decreasing droplet volume irrespective of the piezo-actuation profile. The trends for shape and satellite levels are not as clear and demand further study.
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 | 2020-07-08 20:05:59.0
There is a compelling need for functional testing of high-speed input/output signals on circuit boards ranging from 1 gigabit per second (Gbps) to several hundred Gbps. While manufacturing tests such as Automatic Optical Inspection (AOI) and In-Circuit Test (ICT) are useful in identifying catastrophic defects, most high-speed signals require more scrutiny for failure modes that arise due to high-speed conditions, such as jitter. Functional ATE is seldom fast enough to measure high-speed signals and interpret results automatically. Additionally, to measure these adverse effects it is necessary to have the tester connections very close to the unit under test (UUT) as lead wires connecting the instruments can distort the signal. The solution we describe here involves the use of a field programmable gate array (FPGA) to implement the test instrument called a synthetic instrument (SI). SIs can be designed using VHDL or Verilog descriptions and "synthesized" into an FPGA. A variety of general-purpose instruments, such as signal generators, voltmeters, waveform analyzers can thus be synthesized, but the FPGA approach need not be limited to instruments with traditional instrument equivalents. Rather, more complex and peculiar test functions that pertain to high-speed I/O applications, such as bit error rate tests, SerDes tests, even USB 3.0 (running at 5 Gbps) protocol tests can be programmed and synthesized within an FPGA. By using specific-purpose test mechanisms for high-speed I/O the test engineer can reduce test development time. The synthetic instruments as well as the tests themselves can find applications in several UUTs. In some cases, the same test can be reused without any alteration. For example, a USB 3.0 bus is ubiquitous, and a test aimed at fault detection and diagnoses can be used as part of the test of any UUT that uses this bus. Additionally, parts of the test set may be reused for testing another high-speed I/O. It is reasonable to utilize some of the test routines used in a USB 3.0 test, in the development of a USB 3.1 (running at 10 Gbps), even if the latter has substantial differences in protocol. Many of the SI developed for one protocol can be reused as is, while other SIs may need to undergo modifications before reuse. The modifications will likely take less time and effort than starting from scratch. This paper illustrates an example of high-speed I/O testing, generalizes failure modes that are likely to occur in high-speed I/O, and offers a strategy for testing them with SIs within FPGAs. This strategy offers several advantages besides reusability, including tester proximity to the UUT, test modularization, standardization approaching an ATE-agnostic test development process, overcoming physical limitations of general-purpose test instruments, and utilization of specific-purpose test instruments. Additionally, test instrument obsolescence can be overcome by upgrading to ever-faster and larger FPGAs without losing any previously developed design effort. With SIs and tests scalable and upward compatible, the test engineer need not start test development for high-speed I/O from scratch, which will substantially reduce time and effort.
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