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 | 2019-01-02 21:51:49.0
Failed solder joints remain a constant source of printed circuit board failure. Soldering is the bonding of metallic surfaces via an intermetallic compound (IMC). The interaction between thermal energy delivery, flux chemistry, and solder chemistry creates the solder bond or joint. Today, reliability relies on visual inspection; operator experience and skill, control of influencers e.g. tip geometry, tip temperature, and collection and analysis of process data. Each factor involved with the formation of the solder joint is an element of risk and can affect either throughput or repeatability. Mitigating this risk in hand soldering requires the identification of these factors and a means to address them.
Technical Library | 2020-03-04 23:53:17.0
Critical to maintaining quality control in high-throughput screening is the need for constant monitoring of liquid-dispensing fidelity. Traditional methods involve operator intervention with gravimetric analysis to monitor the gross accuracy of full plate dispenses, visual verification of contents, or dedicated weigh stations on screening platforms that introduce potential bottlenecks and increase the plate-processing cycle time. We present a unique solution using open-source hardware, software, and 3D printing to automate dispenser accuracy determination by providing real-time dispense weight measurements via a network-connected precision balance. This system uses an Arduino microcontroller to connect a precision balance to a local network. By integrating the precision balance as an Internet of Things (IoT) device, it gains the ability to provide real-time gravimetric summaries of dispensing, generate timely alerts when problems are detected, and capture historical dispensing data for future analysis. All collected data can then be accessed via a web interface for reviewing alerts and dispensing information in real time or remotely for timely intervention of dispense errors. The development of this system also leveraged 3D printing to rapidly prototype sensor brackets, mounting solutions, and component enclosures.
Technical Library | 2016-11-30 15:53:15.0
The use of microvias in Printed Circuit Boards (PCBs) for military hardware is increasing as technology drives us toward smaller pitches and denser circuitry. Along with the changes in technology, the industry has changed and captive manufacturing lines are few and far between. As PCBs get more complicated, the testing we perform to verify the material was manufactured to our requirements before they are used in an assembly needs to be reviewed to ensure that it is sufficient for the technology and meets industry needs to better screen for long-term reliability. The Interconnect Stress Testing (IST) protocol currently used to identify manufacturing issues in plated through holes, blind, or buried vias are not necessarily sufficient to identify problems with microvias. There is a need to review the current IST protocol to determine if it is adequate for finding bad microvias or if there is a more reliable test that will screen out manufacturing inconsistencies. The objective of this research is to analyze a large population of PCB IST coupons to determine if there is a more effective IST test to find less reliable microvias in electrically passing PCB product and to screen for manufacturing deficiencies. The proposed IST test procedure will be supported with visual inspection of corresponding microvia cross sections and Printed Wiring Assembly (PWA) acceptance test results. The proposed screening will be shown to only slightly affect PCB yield while showing a large benefit to screening before PCBs are used in an assembly.
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