Mount Components Research Articles

Design and Development of a Precision Defect Detection System Based on a Line Scan Camera Using Deep Learning

The manufacturing industry environment is rapidly evolving into smart manufacturing. It prioritizes digital innovations such as AI and digital transformation (DX) to increase productivity and create value through automation and intelligence. Vision systems for defect detection and quality control are being implemented across industries, including electronics, semiconductors, printing, metal, food, and packaging. Small and medium-sized manufacturing companies are increasingly demanding smart factory solutions for quality control to create added value and enhance competitiveness. In this paper, we design and develop a high-speed defect detection system based on a line-scan camera using deep learning. The camera is positioned for side-view imaging, allowing for detailed inspection of the component mounting and soldering quality on PCBs. To detect defects on PCBs, the system gathers extensive images of both flawless and defective products to train a deep learning model. An AI engine generated through this deep learning process is then applied to conduct defect inspections. The developed high-speed defect detection system was evaluated to have an accuracy of 99.5% in the experiment. This will be highly beneficial for precision quality management in small- and medium-sized enterprises

Digital holographic microscope for high spatial and temporal resolution in situ observation of dynamic phenomena of metals

A digital holographic microscope (DHM) was developed for the purpose of simultaneous observation and measurement of surface relief formation during deformation and phase transformation of steels. It was designed to accommodate the sample mounting component of a custom tensile tester. The Gabor wavelet transform method was used in the image reconstruction. To verify performance, the DHM was used to observe and measure height of slip bands formed during the monotonic loading 316L stainless steel. Data obtained has high temporal resolution (limited only by the camera’s frame rate capability) with lateral resolution approaching the diffraction limit. The results clearly show the evolving microstructures with height information available within each captured image.

Real-Time Defect Detection in Electronic Components during Assembly through Deep Learning

This paper introduces a pioneering method for real-time image processing in electronic component assembly, revolutionizing quality control in manufacturing. By promptly capturing images from pick-and-place machines during the interval between component pick-up and mounting, defects are identified and promptly addressed in line. This proactive approach ensures that defective components are rejected before mounting, effectively preventing issues from ever occurring, thus significantly enhancing efficiency and reliability. Leveraging rapid network protocols such as gRPC and orchestration via Kubernetes, in conjunction with C++ programming and TensorFlow, this approach achieves an impressive average turnaround time of less than 5 milli-seconds. Rigorously tested on 20 operational production machines, it not only ensures adherence to IPC-A-610 and IPC-STD-J-001 standards but also optimizes production efficiency and reliability.

Voiding in Parylene-C Encapsulation of Surface Mount LEDs for an Optogenetic Epilepsy Neuroprosthesis

It is often assumed that Parylene-C encapsulation films are void-free & conformal by nature of their vapour deposition. We present a case study in an optrode device where voiding occurs; we argue the voids originate from the geometry of the substrate and from the use of surface mount components. The segment under study consists of a commercial LED bonded with Au/Au thermosonic bonding onto a custom silicon substrate. We demonstrate via micro-sectioning that there is polymer voiding behaviour (1) in sub-LED surfaces; and (2) within through-hole vias in the silicon substrate (channels designed to allow polymer vapour ingress during deposition). By making a comparison to the solutions found in the IC industry around tungsten vapour filling of blind vias, we present geometric solutions for failure mitigation.

Semantic part segmentation of spatial features via geometric deep learning for automated control cabinet assembly

Industries with batch size one manufacturing philosophies for highly customized products have been largely limited in manufacturing automation. The control cabinet industry is particularly affected by this problem during the mounting and wiring of components due to high variety, variance, and complexity of components as well as handling tasks. Rapid advances in the field of machine learning are opening new possibilities for automating previously manual processes. This paper proposes a concept for identifying geometric features of electrical components that starts from STEP files and transforms them into modular metrics relevant to build a digital twin and (automatic)manufacturing. The architecture is tested on a self-aggregated and processed dataset of control cabinet components and achieves an average dice score of 65.27% and an intersection over union of 51.41% across all segmentation classes. In addition to semantic part segmentation of the components, the cluster, volume and surface centroids, the normal vectors and the size of each feature are computed. The paper evaluates the suitability of cutting-edge techniques such as diffusion as well as established deep learning architectures. The result is a hybrid end-to-end inference pipeline suitable for general spatial assembly processes.

Accurate modelling of the bifacial gain potential of rooftop solar photovoltaic systems

Bifacial solar modules have emerged as a promising technology in utility-scale photovoltaic systems, experiencing significant growth and capturing a substantial market share worldwide, as reported by the International Technology Roadmap for Photovoltaic (ITRPV) 2023. Despite this progress, the potential of bifacial modules in rooftop applications remains largely unexplored. This paper aims to address this knowledge gap by conducting a comprehensive study utilizing Monte Carlo Ray Tracing techniques coupled with detailed electrical modelling. The primary objective of this study is to investigate the viability of implementing bifacial solar modules on rooftops by examining the potential energy yield gains. By conducting a detailed analysis on a representative rooftop in Canberra, Australia, real-world conditions, and variations are incorporated, providing a more accurate assessment of the energy yield gains achievable in such settings. The simulation results reveal that the implementation of bifacial solar modules on rooftops within Australia can result in energy yield gains of up to 22.6%. These findings demonstrate the considerable potential of bifacial technology in maximizing solar energy production in rooftop applications. The analysis shows significant implications of module and system design on the potential gain. For example, electrical optimisation of individual modules in a system accounted for 1.4% of the bifacial gain. The analysis considers full annual time-step simulation, typical mechanical mounting components, installation orientations and module characteristics, ensuring practical relevance and reliability of the results.

Effect of Differently Shaped Solder Joints of Chip Resistor on Fatigue Life

Abstract As surface mount components shrink in size, smaller apertures on stencils during solder paste printing can lead to uneven solder volume on a single resistor. This can result in the formation of irregular solder shapes, which are often deemed acceptable criterion depending on assembly house. However, such irregularities can potentially introduce variations in the fatigue life of the surface mount component. This study employs experimental and numerical approaches to investigate the reliability of differently shaped SAC305 solder joints on a single chip resistor. Four distinct solder shapes, concave, straight, tiny convex, and convex, are generated using varying volumes of solder paste controlled by uniquely designed apertures on a stencil. Eight pairs of differently shaped solder joints are assembled to hold a chip resistor in place. The test assembly involves R1005 and R0402 soldered with SAC305 and undergoes thermal shock cycling. As a single chip resistor assembly consists of two solder joints connecting termination and pads, the effect of solder volume difference between two solder joints are investigated. The fatigue life corresponds to decrease as the solder volume difference increase as 40%, 80%, and 120%. Conversely, total volume of two solder joints in a single chip resistor increases in scenarios with the same volume difference between two solder joints. Experimental data and finite element analysis lead to a new set of Darveaux's constants specific to this assembly. This study provides guideline to control the solder paste volumes in relation to fatigue life and enables numerical solution using a new Darveaux's constants.

Manufacturability Analysis and Research of PCB Component Mounting

In the traditional production mode, the disconnection between PCB design and manufacturing leads to many disadvantages such as more design rework, difficult processing, and high cost. To address this issue, this paper achieves manufacturability analysis at the PCB design stage by establishing a manufacturability analysis system for PCB component placement and simulating the placement process of the placement machine on the computer, taking into account the functional and process requirements of PCB board-level circuits simultaneously, so as to facilitate design decisions in the global tendency of the PCB manufacturing system to be optimal.

A Fine Technique for Automatic Inspection of Surface Mount Components

In this paper, a machine vision technology is used to inspect surface mount components (SMC). It can receive the purpose of improving manufacturing losses caused by misjudgments of manual inspection. The detection includes missing parts, wrong parts, skew, reverse polarity, missing pin, bridging, broken pin, etc. The surface mount components to be tested in this paper include QFP (Quad Flat Package) and SOP (Small Outline Package). The proposed method consists of four parts: (1) image capture: capture the printed circuit board (PCB) image in XY-Table through camera; (2) detection: use correlation coefficient to detect missing and wrong parts; (3) positioning: judge from the RGB histogram of the shifting element; (4) segmentation: detect disconnection and bridging defects according to the segmentation result of the cumulative projection.

A modal analysis based optimal mounting support locations of a printed circuit board

Purpose This paper aims to improve the life of the printed circuit boards (PCB) used in computers based on modal analysis by increasing the natural frequency of the PCB assembly. Design/methodology/approach In this work, through experiments and numerical simulations, an attempt has been made to increase the fundamental natural frequency of the PCB assembly as high as practically achievable so as to minimize the impacts of dynamic loads acting on it. An optimization tool in the finite element software (ANSYS) was used to search the specified design space for the optimal support location of the six fastening screws. Findings It is observed that by changing the support locations based on the optimization results the fundamental natural frequency can be raised up to 51.1% and the same is validated experimentally. Research limitations/implications Manufacturers of PCBs used in computers fix the support locations based on symmetric feature of the board not on the dynamic behavior of the assembly. This work might lead manufacturers to redesign the location of other surface mount components. Practical implications This work provides guidelines for PCB manufacturers to finalize their support locating points which will improve the dynamic characteristics of the PCB assembly during its functioning. Originality/value This study provides a novel method to improve the life of PCB based on support locations optimization which includes majority of the surface mount components that contributes to the total mass the PCB assembly.

Assessing sustainability hotspots in the production of paper-based printed electronics

Novel printed electronics are projected to grow and be manufactured in the future in large volumes. In many applications, printed electronics are envisaged as sustainable alternatives to conventional (PCB-based) electronics. One such application is in the semi-quantitative drug detection and point-of-care device called ‘GREENSENSE’ that uses paper-based printed electronics. This paper analyses the carbon footprint of GREENSENSE in order to identify and suggest means of mitigating disproportionately high environmental impacts, labeled ‘sustainability hotspots’, from materials and processes used during production which would be relevant in high-volume applications. Firstly, a life cycle model traces the flow of raw materials (such as paper, CNCs, and nanosilver) through the three ‘umbrella’ processes (circuit printing, component mounting, and biofunctionalization) manufacturing different electronic components (the substrate, conductive inks, energy sources, display, etc) that are further assembled into GREENSENSE. Based on the life cycle model, life cycle inventories are modeled that map out the network of material and energy flow throughout the production of GREENSENSE. Finally, from the environmental impact and sustainability hotspot analysis, both crystalline nanocellulose and nanosilver were found to create material hotspots and they should be replaced in favor of lower-impact materials. Process hotspots are created by manual, lab-, and pilot-scale processes with unoptimized material consumption, energy use, and waste generation; automated and industrial-scale manufacturing can mitigate such process hotspots.

Study on Controlling Residual Stress in Thick Copper Film for Heat Sink Using Graphene

Nowadays, high-density electronic devices and component mounting have gained popularity. Because of the heat generated from these devices, efficiency of the electronic parts is significantly lowered and life time of these devices is considerably shortened. Therefore, it is very important to efficiently dissipate the heat generated from the device to extend product. In this study, a copper thick film was deposited using a sputtering technique using plasma. In addition, graphene, a two-dimensional nanomaterial, was inserted in the form of a sandwich structure between the deposited copper (Cu) layers of various thicknesses. Through this, a study was conducted to control the residual stress of thick copper foil deposited by sputtering. In this study, the residual stress was measured according to the location where graphene was inserted, the treatment method, and the transfer area. As a result, the highest residual stress reduction effect was observed when the transfer area of graphene was about 70%. Reduction of residual stress was observed by inserting graphene into the deposited copper thick film of various thicknesses. In addition, by increasing the number of layers of graphene inserted, changes in residual stress were observed.

Technologies and materials for the assembly and installation of electrical elements

The article is devoted to the creation of a multifunctional machine for microsoldering and mounting of electrical components for the board. The problems of designing machine tools, existing analogues and prototypes are considered, as well as technologies and materials for fastening electrical elements and connecting them to each other are selected. Keywords machine tool manufacture, automation, analogues, soldering, electronics, electrical mounting, flux, solder, jumper

Reflow Recipe Establishment Based on CFD-Informed Machine Learning Model

This article proposes a computational fluid dynamics-based machine learning (ML) model to set the temperature of a convection reflow oven and control conveyor speed. Due to the thermal mass variation of printed circuit boards (PCB) and surface mount components, the reflow recipe should be specified for each PCB assembly individually. Instead of relying on process engineers’ skills and experience, the machine learning model supported by heat transfer mechanisms provides a clear and logical path in the reflow recipe setup. An ideal recipe should let the largest component reach the minimum reflow temperature, meanwhile, the temperature cannot damage the small or heat-sensitive components. To simulate the reflow soldering process, the computational fluid dynamics (CFD) model was used after being validated with experiment results. A system was programmed to feed the output of the CFD model as the input to the ML model. Benefiting from the interpolation and fast response brought by ML models, we can rapidly obtain the results subjected to millions of recipes, which are the combination of preset temperatures of all the heating zones and the conveyor speed in the oven. Using a weighting filter function, the optimal recipe can be obtained. This methodology is especially beneficial to reflowing smaller batches of complex PCB assemblies with a big heat capacity.

A scalable cryogenic LED module for selectively illuminating kinetic inductance detector arrays.

We present the design and measured performance of a light emitting diode (LED) module for spatially mapping kinetic inductance detector (KID) arrays in the laboratory. Our novel approach uses a multiplexing scheme that only requires seven wires to control 480 red LEDs, and the number of LEDs can be scaled up without adding any additional wires. This multiplexing approach relies on active surface mount components that can operate at cryogenic temperatures down to 10K. Cryogenic tests in liquid nitrogen and inside our cryostat demonstrate that the multiplexer circuit works at 77 and 10K, respectively. The LED module presented here is tailored for our millimeter-wave detector modules, but the approach could be adapted for use with other KID-based detector systems.

Preclinical evaluation of a prototype freehand drill video guidance system for orthopedic surgery.

Purpose: Internal fixation of pelvic fractures is a challenging task requiring the placement of instrumentation within complex three-dimensional bone corridors, typically guided by fluoroscopy. We report a system for two- and three-dimensional guidance using a drill-mounted video camera and fiducial markers with evaluation in first preclinical studies. Approach: The system uses a camera affixed to a surgical drill and multimodality (optical and radio-opaque) markers for real-time trajectory visualization in fluoroscopy and/or CT. Improvements to a previously reported prototype include hardware components (mount, camera, and fiducials) and software (including a system for detecting marker perturbation) to address practical requirements necessary for translation to clinical studies. Phantom and cadaver experiments were performed to quantify the accuracy of video-fluoroscopy and video-CT registration, the ability to detect marker perturbation, and the conformance in placing guidewires along realistic pelvic trajectories. The performance was evaluated in terms of geometric accuracy and conformance within bone corridors. Results: The studies demonstrated successful guidewire delivery in a cadaver, with a median entry point error of 1.00mm (1.56mm IQR) and median angular error of 1.94deg (1.23deg IQR). Such accuracy was sufficient to guide K-wire placement through five of the six trajectories investigated with a strong level of conformance within bone corridors. The sixth case demonstrated a cortical breach due to extrema in the registration error. The system was able to detect marker perturbations and alert the user to potential registration issues. Feasible workflows were identified for orthopedic-trauma scenarios involving emergent cases (with no preoperative imaging) or cases with preoperative CT. Conclusions: A prototype system for guidewire placement was developed providing guidance that is potentially compatible with orthopedic-trauma workflow. First preclinical (cadaver) studies demonstrated accurate guidance of K-wire placement in pelvic bone corridors and the ability to automatically detect perturbations that degrade registration accuracy. The preclinical prototype demonstrated performance and utility supporting translation to clinical studies.

밀폐형 한돈 사육환경 내 전자 기판의 부식 양상과 개선을 위한 컨포멀 코팅 적용 효과 연구

Purpose: This study aimed to analyze the corrosion pattern on the circuit board of an environmental measurement instrument in a closed Korean pig breeding environment and to verify the effectiveness of conformal coating applied to the circuit board as a corrosion mitigation method. The closed Korean pig breeding environment was associated with factors such as humidity, dust, and corrosive gases in a complex manner, which can lead to corrosion and malfunction of the electronic measuring device. Thus, it was necessary to ensure the reliability of the device.<BR>Methods: A printed circuit board (PCB), which is a core element of electronic devices, was selected as the experimental material. Experimental specimens were divided into those coated with a conformal coating and those without conformal coating. The specimens were placed in a breeding environment to examine the corrosion patterns and effect of the coating. The corroded specimens were analyzed using cross-sections and scanning electron microscopy and energy-dispersive X-ray spectroscopy methods.<BR>Results: In specimens without conformal coating, corrosion of the PCB occurred in the solder, component mounting pads, and through-vias (except for the photo solder resist), and sulfur was detected in the oxides and corroded parts. No corrosion was detected in the specimens coated with conformal coating.<BR>Conclusion: In an environment such as that found in the closed Korean pig breeding area, it is necessary to protect sensitive electronics from external environmental factors, such as hydrogen sulfide, that can cause PCB corrosion of solder, component mounting pads, and through-vias. The application of conformal coating to the PCBs of electronic devices is expected to be an effective solution to prevent corrosion.

Smarter Temperature Setup for Reflow Oven to Minimize Temperature Variation Among Components

The thermomechanical reliability of surface mount components (SMCs) is closely related to the reflow soldering process. With the rise of board complexity, an optimal reflow profile must consider the mix of large and small components, the density of the components on the board, and the board dimensions. It has been a significant challenge to achieve uniform temperature on SMCs with different sizes and different thermal masses, such as capacitors, transistors, quad-flat no-leads (QFN), and ball grid array (BGA) packages. To reflow large components such as BGA packages, the minimum reflow temperature should be reached, meanwhile, the temperature should not exceed the damaging temperature of the smaller or heat-sensitive components. The recommended reflow profile is defined as a band or process window. To achieve good quality soldering, the temperature applied to the solder under varied sizes of components should be within the recommended band. This article introduces a numerical method based on a compact model to predict the reflow profile for bulky BGA packages. The impinging gas temperature is used as the boundary condition to predict the temperature distribution throughout a board with different sized components. The proper oven temperature setting to achieve the ideal profiles is obtained finally.

Machine tool for assembling and mounting electrical components

The article is devoted to the creation of a multifunctional machine tool for microsoldering and mounting of electrical components of the board. Attention to the choice of engines, components of the machine tool and design is paid. The design of a soldering iron with pulsed heating, a mechanism for supplying a mixture of flux and solder, and a device for supplying wire jumpers are described. For clarity, determining the dimensions of the machine tool and its layout, a 3D model is created. Keywords machine tool building, automation, electronics, electrical mounting, engine, flux, solder, wire

A Study on the Control of Residual Stress of Copper Thick-Film Using 2D Nanomaterial.

With the rapid development of the electronics industry, high-density electronic devices and component mounting have gained popularity. Because of the heat generated from these devices, efficiency of the electronic parts is significantly lowered and life of various electronic devices is considerably shortened. Therefore, it is essential to efficiently dissipate the heat generated from the device to extend product life and ensure high efficiency of electronic components. This study evaluated how residual stress is impacted by the thickness of the deposited copper film, which is widely used as a heat dissipation material, and the number of graphene layers. The results confirmed that the residual stress decreased with increasing thickness. Moreover, the residual stress changed based on the transfer area of graphene, which had an elastic modulus eight times that of copper, indicating that the residual stress of the deposited copper film can be controlled.