Circuit Board Assembly Research Articles

Solder Joint Defect Inspection Method Based on ConvNeXt-YOLOX

ConvNeXt-YOLOX model, an improved deep learning algorithm based on the YOLOX neural network, is proposed for surface mount technology (SMT) production line printed circuit board assembly (PCBA) solder joint defect detection with high accuracy and speed. The improved model employs the classification neural network ConvNeXt to enhance the feature extraction capability of the YOLOX backbone feature extraction network, thus enhancing the target detection accuracy and speed as well as the small target detection capability while maintaining the same number of parameters. A solder joint defect detection dataset containing 759 PCBA solder joint defect images is constructed, on which the improved model ConvNeXt-YOLOX, the original model YOLOX, and the lightweight model YOLOX-s are trained. Subsequently, the training results of the three models are compared. The comparison shows that the mean average precision (mAP) of the improved model ConvNeXt-YOLOX is 97.21%, which is 0.82% and 3.02% higher than that of YOLOX and YOLOX-s, respectively, while the mAP at (0.5:0.95) is increased from 76.3 to 77.5. Moreover, the detection speed is increased from the original 27.06 to 27.88 frames/s. In summary, the improved model ConvNeXt-YOLOX has strong small target feature extraction and detection capabilities, which are consistent with the actual requirements of solder joint defect detection.

THERMAL-INDUCED DAMAGE ON SOLDER JOINTS OF HIGH-DENSITY ADJACENT BALL GRID ARRAY COMPONENTS DURING THE REWORK PROCESS

Correlation between adjacent ball grid array (BGA) components' temperature and thermal-induced damage to their solder joints on both the top and bottom printed circuit board assembly (PCBA) sides during the rework process is studied in this work. Total often adjacent BGA components from the rework area on the top (F - K) and bottom (A - E) PCBA side were observed. The dye and pull (D&P) test results, infrared thermography images, and temperature measurements were analyzed for solder joint crack induced by the thermal damage with precise temperature measurement on each adjacent BGA component. Scanning electron microscope (SEM) analysis complemented the post-D&P test solder joint crack observation. The D&P test results shows that 76 % or higher and solder joint separation locations at the copper pad on BGA occurred when the temperature of the adjacent components of the rework location exceeded 195 °C and 210 °C on the centre and corner of the component, respectively.

Embedded systems and printed circuit boards as weak spots in HV-H3TRB tests

Wide-band-gap (WBG) devices and embedding technology offer a huge advantage when increasing the power density of power electronics. However, the miniaturisation leads to new reliability challenges. The critical spot prone to humidity degradation moves outside the actual device under test (DUT) to the periphery, i.e. printed circuit board assemblies (PCBA). In the case of High Voltage Embedding Technology (HVET) devices, the housing of the power element is completely omitted. The materials used in HVET must entirely ensure the moisture protection of the power unit and the passive components of the embedded systems.In this work, results on various batches of PCBA and HVET after several thousand hours of testing in High Voltage-High Humidity High Temperature Reverse Bias (HV-H3TRB) are presented. Failure analyses have identified degradation mechanisms such as conductive anodic filament (CAF) formed inside the FR-4 printed circuit boards (PCB) and anodic migration phenomenon (AMP) in HVET devices as the root cause of failures. Therefore, special preventive procedures are required in harsh climatic conditions.

Effect of heat shield locations on rework-induced thermal management in ball grid array solder joint

This study investigated the effectiveness of heat shield placement locations during the rework process to avoid thermal and mechanical damage to adjacent ball grid array components and their solder joints on double-sided printed circuit board assembly. Three types of heat shield placement locations were used: sample X, individual heat shield placement on adjacent components of the rework location; sample Y, a U-shaped, and sample Z, a square-shaped heat shield placed respectively at the heat source location. The dye and pull test results, infrared thermography, and temperature measurements were analysed to understand the relationship between the location of the heat shield and solder joint damage during rework. Heat shield placement at the heat source location on the reworked component can reduce the peak temperatures on the adjacent rework component locations by up to 8.18%. The peak temperatures of the centre and corner of the BGA component can be maintained below 195 °C and 210 °C, respectively to improve the adjacent rework component locations' solder joint quality by reducing solder joint damage by more than 50% solder cracks. This is useful for thermal management during rework involving high-density ball grid array component placements on double-sided printed circuit board assembly.

Reliability Sensibility Analysis of the PCB Assembly concerning Warpage during the Reflow Soldering Process

As a vital component of electronic products, the quality of the printed circuit board (PCB) assembly directly affects the applications and service life. During the reflow soldering process, the PCB assembly may suffer excessive warpage. Therefore, in order to avoid such a failure, this paper conducts the finite element simulation of the PCB assembly temperature change and the deformation process according to a theoretical model for heat transfer and then explores the causes of warpage and predicts the percentage of warpage that occurs during the reflow soldering. A reliability sensitivity analysis is creatively applied in the PCB assembly warpage study in order to uncover the quantitative influence of multiple factors with random errors on warpage. Moreover, the reliability calculation provides a theoretical basis for the allowable error range of geometric dimensions, material properties and process parameters of the PCB assembly. This research has a remarkable significance and is valuable to engineering in promoting quality and reliability, and increasing the yield of PCB assembly in mass production.

Ergonomic Risk Assessment of Static Postures and Repetitive Tasks using Rapid Entire Body Assessment and Strain Idex

This study aims to assess the risk levels of work-related musculoskeletal disorders (WMSDs) of Vietnamese female workers performing repetitive tasks and static postures. The workers perform the repetitive tasks which are printed circuit board assembly and printing on housing in a factory in Ho Chi Minh City, Vietnam. The risk assessment tools are used consisting of Rapid Entire Body Assessment and Strain Index. The result shows that the risk levels of WMSDs of workers are from medium to high levels. Therefore, ergonomic measures are needed to reduce the risk levels and improve the working conditions. The suggestions of ergonomic interventions are ergonomic workstation redesign considering anthropometric data of Vietnamese female workers, appropriate work methods and training for workers.

Application of a Non-Dominated Sorting Genetic Algorithm to Solve a Bi-Objective Scheduling Problem Regarding Printed Circuit Boards

An unrelated parallel machine scheduling problem motivated by the scheduling of a printed circuit board assembly (PCBA) under surface mount technology (SMT) is discussed in this paper. This problem involved machine eligibility restrictions, sequence-dependent setup times, precedence constraints, unequal job release times, and constraints of shared resources with the objectives of minimizing the makespan and the total job tardiness. Since this scheduling problem is NP-hard, a mathematical model was first built to describe the problem, and a heuristic approach using a non-dominated sorting genetic algorithm (NSGA-II) was then designed to solve this bi-objective problem. Multiple near-optimal solutions were provided using the Pareto front solution and crowding distance concepts. To demonstrate the efficiency and effectiveness of the proposed approach, this study first tested the proposed approach by solving test problems on a smaller scale. It was found that the proposed approach could obtain optimal solutions for small test problems. A real set of work orders and production data was provided by a famous hardware manufacturer in Taiwan. The solutions suggested by the proposed approach were provided using Gantt charts to visually assist production planners to make decisions. It was found that the proposed approach could not only successfully improve the planning time but also provide several feasible schedules with equivalent performance for production planners to choose from.

Effect of the IMC layer geometry on a solder joint thermomechanical behavior

PurposeIn a printed circuit board assembly (PCBA), the coefficient of thermal expansion (CTE) mismatch between the solder joint materials has a detrimental impact on reliability. The mechanical stresses caused by the thermal changes of the assembly lead to fatigue and sometimes the failure of the solder joints. The purpose of this study is to propose a novel pad design to obtain an interrupted solder/substrate interface, to improve the PCBA reliability.Design/methodology/approachAn interruption in the continuous intermetallic compound (IMC) layer of a solder joint was implemented, by the deposition of a silicone film in the pad, changing its geometry. That change allows a redistribution of stresses in the most ductile zone of the solder joint, the solder. The stress concentration at the solder/substrate interface is reduced, as well as the general state of stress at the solder joint.FindingsA new way was developed to reduce the stress on the solder joints, caused by thermal variations, because of the different components CTEs mismatch. This new method consists of interrupting the IMC layers of the solder joint, strategically, redirecting the usual stresses to a more ductile area of the joint, the solder. This is an innovative method that allows increase the lifetime of PCBAs and the equipments.Originality/valueIn this study, a new pad design concept for higher solder joint reliability was developed to reduce the shear stress in the solder joints because of the CTE mismatch between all the solder joint components.

The effect of crusher type on printed circuit board assemblies’ liberation and dust generation from waste mobile phones

Waste electrical and electric equipment entering our recycling system poses various challenges in different stages of the whole treatment chain. Losses of valuable metals in the crushing of electrical devices through dusts and fines have been identified as one such challenge. Crushing is nevertheless crucial in order to liberate metals from each other for efficient separation in the sequential mechanical unit processes. This study investigated the relation of crushing mechanism on Printed Circuit Assemblies’ (PCAs) liberation and fines generation in the size reduction of waste mobile phones using two crusher types. The results revealed that a fast-rotating hammer mill produced better liberated PCAs with an overall PCA grade, presenting the purity of PCA fraction of 77% compared to a slow-rotating cutting mill with 58% PCA grade. However, the hammer mill produced over two times the amount of fines compared to the cutting mill. The fines fraction mainly comprised silicon and base metals but also noble metals and harmful elements which need to be taken into account when further treatment is considered. Even though the same elements could be found in the fines from both crushers, differences in the concentrations were observed. In the cutting mill, higher concentrations of ductile materials such as gold and copper were observed in the fines fraction with particle size below 4 mm compared to the hammer mill.

Failure patterns of solder joints identified through lifetime vibration tests

ABSTRACT A method for non-destructively tracking the integrity of flip chip solder joints through life is investigated in this paper. An industry standard double-sided PCB was designed and manufactured with 14 flip chips to assess the failure patterns of each flip chip and each solder joint in lifetime vibration tests. Two configurations of PCB finish were tested, Electro Nickel Immersion Gold (ENIG) and Hot Air Surface Levelled lead (Pb HASL) using automotive industry manufacturing processes and quality standards. A random vibration test over a frequency range 10 Hz to 1000 Hz was specified by automotive engineers to replicate vibrations typically found on road vehicles. This vibration profile was applied to test circuit board assemblies (CBA) for 4-minute intervals until failure of all chips. At each interval test boards were extensively scanned by an acoustic micro-imaging (AMI) microscope to non-destructively measure parameters of solder joints. This enabled tracking of mechanical joint connection through-life. Methods were developed to process the large number of acoustic images of each solder joint and form metrics to evaluate solder joint integrity. Results from AMI show that the solder joints exhibit three distinct zones as they age: crack initiation, crack propagation and then failure.

Development of a highly sensitive and portable particulate matter SAW sensor and interface electronics

In this study, a highly sensitive and portable surface acoustic wave (SAW)-based PM2.5 sensor and its interface electronics were developed for real-time monitoring of air quality. Two 2-port SAW resonators were employed for the sensor system to eliminate any environmental disturbance (temperature and humidity variations) on the output of the sensor. The overall system comprised a 2-port SAW resonator for a particulate matter (PM) sensor, a reference sensor covered with polydimethylsiloxane (PDMS) on the top surface, two self-oscillators, an RF mixer, a low-pass filter, a comparator, a field-programmable gate array, and a personal computer. All electronic components were integrated into a single printed circuit board assembly. COMSOL simulations were performed to determine the optimal center frequency for the operation of the PM2.5-based SAW sensor. Based on COMSOL simulation, the sensors were fabricated and their characteristics categorized using a custom-built testbed. We experimentally observed the effect of the center frequency on the frequency response of PM2.5. The experimental data showed that the sensor operating at a center frequency of 180 MHz exhibited the largest frequency shift when exposed to PM2.5, suggesting that 180 MHz is the optimal center frequency for operating a PM2.5-based SAW sensor. Herein, a simple mechanism is proposed to understand the working principle of the PM2.5 sensor. Our results suggest that for the effective detection of PM2.5 particles, it is necessary to use different center frequencies of the SAW sensor with optimal penetration depth to match the size of PM2.5.

Amino Acids as Activators for Wave Solder Flux Systems: Investigation of Solderability and Humidity Effects

The role of flux activators in flux formulation is to remove oxides from metal surface and, hence, allow the formation of metallurgical bond between metal substrate and solder alloy. However, flux activator in the no-clean flux residue on printed circuit board assemblies (PCBAs) affects the climatic reliability due to its hygroscopic and ionic behavior under humidity exposure. Four amino acids-based wave flux was investigated using wetting balance test and microscopy inspection, and the humidity effects of four amino acids were analyzed using electrochemical impedance spectroscopy (EIS) and chronoamperometry under various testing conditions. Water absorption and thermal degradation were analyzed using gravimetric method and Fourier-transform infrared spectroscopy (FT-IR). Combined results indicate that glutamine-based model flux obtained superior solderability for 96.5Sn-3Ag-0.5Cu (SAC 305) alloy due to suitable melting and activation temperature of amino group for the oxides removal. The robust humidity reliability of amino acids was dependent upon relative high deliquescence point and low moisture absorption under harsh climatic conditions.

Support vector machine applied to the problem of thermal diagnostics of design defects in radio electronic devices

The paper describes a new approach to diagnostics of the technical condition of printed circuit board (PCB) assemblies of electronic devices based on mathematical modelling of thermal processes and on the support vector machine as a tool for classifying design defects of electronic equipment. This work continues the previous study of thermal diagnostics of malfunctions in PCB assemblies. The developed method combines mathematical modelling and physical tests of PCB assemblies under study with subsequent analysis of the obtained characteristics. The tools for method implementation include special-purpose software suites for PCB and hardware design such as Altium Designer, SolidWorks, NI Multisim as well as mathematical modelling software packages and the Python programming language.

Selection of Solder Paste Inspection Machines by Multi-Criteria Decision Analysis

One of the most important factors to give an inspection automation decision is the precision of measurements taken by the inspection machine. This paper aims to provide help in the selection of an automatic optical inspection (AOI) machine for a printed circuit board (PCB) assembly line of an electronics manufacturer. Since the visual inspection of soldered surfaces on a PCB is a crucial step, AOI machines bring great speed and accuracy to the inspection process. The main goal is to find the best automatic inspection machine alternative among the three AOI machine offerings according to nine selection criteria by integrating coefficient of variation statistic with TOPSIS and VIKOR, which are well-known multicriteria decision analysis methods. For this purpose, three different brands of AOI machines have been tested for the same PCBs, with 10 different components. After calculation of TOPSIS and VIKOR rank scores, the coefficient of variation of rank scores for all components is obtained and the selection of the AOI machine is finalized.

Solving the feeder assignment, component sequencing, and nozzle assignment problems for a multi-head gantry SMT machine using improved firefly algorithm and dynamic programming

This paper proposes a two-stage framework for developing hybrid approaches to solve the three printed circuit board assembly (PCBA) problems, component sequencing problem (CSP), feeder assignment problem (FAP), and nozzle assignment problem (NAP), simultaneously for a multi-head gantry SMT (surface-mounting technology) machine. The three essential PCBA problems affect the productivity of a multi-head gantry SMT machine considerably. However, due to the difficulty and complexity, the NAP (which assigns a given set of nozzles to the assembly heads of a machine) has been often neglected or roughly resolved in past research. The lack of considering the NAP leads to the underestimation of the total assembly time required for one printed circuit board (PCB) and eventually results in inaccurate production planning. The two-stage framework consists of metaheuristic and dynamic programming (DP) methods, which can deal with the three PCBA problems systematically. Various metaheuristics including firefly algorithm (FA), improved FA (IFA), genetic algorithm (GA), particle swarm optimization (PSO), and whale optimization algorithm (WOA) have been respectively used in this framework and experiments have been conducted to investigate their effectiveness. The results show that the hybridization of IFA with DP outperforms the others in terms of total assembly time.

The Use of a Convolutional Neural Network in Detecting Soldering Faults from a Printed Circuit Board Assembly

Automatic Optical Inspection (AOI) is any method of detecting defects during a Printed Circuit Board (PCB) manufacturing process. Early AOI methods were based on classic image processing algorithms using a reference PCB. The traditional methods require very complex and inflexible preprocessing stages. With recent advances in the field of deep learning, especially Convolutional Neural Networks (CNN), automating various computer vision tasks has been established. Limited research has been carried out in the past on using CNN for AOI. The present systems are inflexible and require a lot of preprocessing steps or a complex illumination system to improve the accuracy. This paper studies the effectiveness of using CNN to detect soldering bridge faults in a PCB assembly. The paper presents a method for designing an optimized CNN architecture to detect soldering faults in a PCBA. The proposed CNN architecture is compared with the state-of-the-art object detection architecture, namely YOLO, with respect to detection accuracy, processing time, and memory requirement. The results of our experiments show that the proposed CNN architecture has a 3.0% better average precision, has 50% less number of parameters and infers in half the time as YOLO. The experimental results prove the effectiveness of using CNN in AOI by using images of a PCB assembly without any reference image, any complex preprocessing stage, or a complex illumination system. Doi: 10.28991/HIJ-2022-03-01-01 Full Text: PDF

A Contactless PCBA Defect Detection Method: Convolutional Neural Networks With Thermographic Images

In the mass production of electronic products, in-circuit-test (ICT) and printed circuit board assembly (PCBA) quality tests are performed. ICT measures resistance values and capacitance, but not only does it require the use of a fixture that is expensive and requires frequent replacement but also the fixture’s needles may cause PCBA defects. To overcome these limitations, various studies tried to replace ICT using visual inspection methods; however, visual inspection methods cannot be applied to chip resistors and chip capacitors that do not have externally visible characteristics. In this article, we propose a contactless inspection method that can detect PCBA defects without the use of the fixture and ICT by using the comparison of thermal images and deep learning (DL) analysis. We review the existing contactless inspection methods and compare them with our proposed thermal image analysis method. We analyzed thermal images by applying a structural similarity index map as a rule-based object detection method, and we used convolutional neural networks (CNNs), regions with CNN features, and an autoencoder as DL analysis methods. As a result, we achieved highly accurate defective component detection and location in real time.

Comparison of a Bat and Genetic Algorithm Generated Sequence Against Lead Through Programming When Assembling a PCB Using a Six-Axis Robot With Multiple Motions and Speeds

An optimal component feeder arrangement and robotic placement sequence are both important for improving assembly efficiency. Both problems are combinatorial in nature and known to be NP-hard. This article presents a novel discrete hybrid bat-inspired algorithm for solving the feeder slot assignment and placement sequence problem encountered when planning robotic assembly of electronic components. In our method, we use the concepts of swap operators and swap sequence to redefine position and velocity operators from the basic bat algorithm (BA). Furthermore, we propose an improved local search method based on genetic operators of crossover and mutation enhanced by the 2-opt search procedure. The algorithm is formulated with the objective of minimizing the total traveling distance of the pick-and-place device. Through numerical experiments, using a real printed circuit board (PCB) assembly scenario, we demonstrate the considerable effectiveness of the proposed discrete BA to improve the selection of feeder arrangement and placement sequence in PCB assembly operations and achieve high throughput production. The results also highlighted that even though the algorithms outperformed traditional lead through programming techniques, the programmer must consider the influence of different robot motions and speeds.

An intelligent system for reflow oven temperature settings based on hybrid physics-machine learning model

PurposeThis paper aims to provide the proper preset temperatures of the convection reflow oven when reflowing a printed circuit board (PCB) assembly with varied sizes of components simultaneously.Design/methodology/approachIn this study, computational fluid dynamics modeling is used to simulate the reflow soldering process. The training data provided to the machine learning (ML) model is generated from a programmed system based on the physics model. Support vector regression and an artificial neural network are used to validate the accuracy of ML models.FindingsIntegrated physical and ML models synergistically can accurately predict reflow profiles of solder joints and alleviate the expense of repeated trials. Using this system, the reflow oven temperature settings to achieve the desired reflow profile can be obtained at substantially reduced computation cost.Practical implicationsThe prediction of the reflow profile subjected to varied temperature settings of the reflow oven is beneficial to process engineers when reflowing bulky components. The study of reflowing a new PCB assembly can be started at the early stage of board design with no need for a physical profiling board prototype.Originality/valueThis study provides a smart solution to determine the optimal preset temperatures of the reflow oven, which is usually relied on experience. The hybrid physics–ML model providing accurate prediction with the significantly reduced expense is used in this application for the first time.

Cell Division Genetic Algorithm for Component Allocation Optimization in Multifunctional Placers

Optimizing all the objectives of the printed circuit board assembly (PCBA) optimization in a multifunctional placer remains a formidable challenge till now. This article converts the original PCBA optimization problem to a newly defined component allocation problem, which decides the component-type handled by each head per pickup-and-place (PAP) cycle. The component allocation problem is a quadratic 3-D assignment problem (Q3AP) and effectively combines the optimization of all the main objectives. It is possible that one head stays idle, so the assigning 2-D locations are uncertain. We propose the cell division genetic algorithm (CDGA) to solve such a complex Q3AP. The CDGA allocates a component cell as the basic unit. Each of the first-generation component cells contains the mounting points of the same type. A cell chromosome decoding heuristic is designed to determine the next assigning head. By doing so, the problem dimension is reduced, so the conventional GA can be used for searching the optimal component allocation formed by the current-generation cells. When a better allocation can no longer be found by allocating the current cells, the cell division operation is performed to divide each cell into two new cells. The new cells are used in the next round of GA searching, which further optimizes the allocation from two perspectives: better balancing the minimization of nozzle changes and PAP cycles, more flexibly maximizing the simultaneous pickups with the uncertain locations. The CDGA works continuously until the current cells cannot bring any improvement. In simulations and experiments using the industrial samples, the proposed algorithm significantly reduces the PCBA time compared to two recent studies and the built-in optimizer of the widely used multifunctional placer, Hanwha SM482 PLUS, which demonstrates its effectiveness and superiority.