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1 – 10 of over 12000A reflow profile is proposed which is engineered to optimize soldering performance based on defect mechanism analysis. In general, a slow ramp‐up rate is desired in order to…
Abstract
A reflow profile is proposed which is engineered to optimize soldering performance based on defect mechanism analysis. In general, a slow ramp‐up rate is desired in order to minimize hot slump, bridging, tombstoning, skewing, wicking, opens, solder beading, solder balling, and components cracking. A minimized soaking zone reduces voiding, poor wetting, solder balling, and opens. Use of a low peak temperature lessens charring, delamination, intermetallics, leaching, dewetting, and voiding. A rapid cooling rate helps to reduce grain size as well as intermetallic growth, charring, leaching and dewetting. However, a slow cooling rate reduces solder or pad detachment. The optimized profile favors that the temperature ramps up slowly until reaching about 180°C. Implementation of the optimized profile requires the support of a heating‐efficient reflow technology with a controllable heating rate. Emergence of the forced air convection reflow provides a controllable heating rate. In addition, it is not sensitive to variation in parts’ features, thus allows the realization of the optimized profile.
Lubomir Livovsky and Alena Pietrikova
This paper aims to present a new method of real-time monitoring of thermal profiles applied in vapour phase soldering (VPS) reflow processes. The thermal profile setting is a…
Abstract
Purpose
This paper aims to present a new method of real-time monitoring of thermal profiles applied in vapour phase soldering (VPS) reflow processes. The thermal profile setting is a significant variable that affects the quality of joints. The method allows rapid achievement of a required thermal profile based on software control that brings new efficiency to the reflow process and enhanced joint quality, especially for power electronics.
Design/methodology/approach
A real-time monitoring system based on computerized heat control was realized in a newly developed laboratory VPS chamber using a proportional integral derivation controller within the soldering process. The principle lies in the strictly accurate monitoring of the real defined reflow profile as a reference.
Findings
Very accurate maintenance of the required reflow profile temperature was achieved with high accuracy (± 2°C). The new method of monitoring and control of the reflow real-time profiling was verified at various maximal reflow temperatures (230°C, 240°C and 260°C). The method is feasible for reflowing three-dimensional (3D) power modules that use various types of solders. The real-time monitoring system based on computerised heat control helped to achieve various heights of vapour zone.
Originality/value
The paper describes construction of a newly developed laboratory-scale VPS chamber, including novel real-time profiling of the reflow process based on intelligent continuously measured temperatures at various horizontal positions. Real-time profiling in the laboratory VPS chamber allowed reflow soldering on 3D power modules (of greater dimensions) by applying various flux-less solder materials.
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Jin Gang Gao, Yi Ping Wu, Han Ding and Nian Hong Wan
This paper aims to offer a convenient method to develop an oven recipe for a specific soldering profile in a reflow process. The method is devised to quickly achieve proper profile…
Abstract
Purpose
This paper aims to offer a convenient method to develop an oven recipe for a specific soldering profile in a reflow process. The method is devised to quickly achieve proper profile shape and heating factor Qη, a measure of success for high reliability of the solder joints reflowed.
Design/methodology/approach
An in‐depth analysis of the heating mechanism and some experiments of the reflow soldering process are performed to research on how to realize a specific shape reflow profile were conducted.
Findings
Heating mechanism analysis and experiments demonstrate that the combinatorial parameters based method is feasible to do thermal profiling.
Research limitations/implications
The mapping function among a particular configured PCBA, an oven used, a target reflow profile and an optimal range of the heating factor should be further established for fast and reliable production of reflow soldering.
Practical implications
Provides a methodology for designing an oven recipe for reflow soldering production.
Originality/value
An oven recipe can be quickly attained with the approach established in this paper, facilitating the formation of solder joints with high reliability during the reflow soldering process.
Yangyang Lai and Seungbae Park
This paper aims to propose a method to quickly set the heating zone temperatures and conveyor speed of the reflow oven. This novel approach intensely eases the trial and error in…
Abstract
Purpose
This paper aims to propose a method to quickly set the heating zone temperatures and conveyor speed of the reflow oven. This novel approach intensely eases the trial and error in reflow profiling and is especially helpful when reflowing thick printed circuit boards (PCBs) with bulky components. Machine learning (ML) models can reduce the time required for profiling from at least half a day of trial and error to just 1 h.
Design/methodology/approach
A highly compact computational fluid dynamics (CFD) model was used to simulate the reflow process, exhibiting an error rate of less than 1.5%. Validated models were used to generate data for training regression models. By leveraging a set of experiment results, the unknown input factors (i.e. the heat capacities of the bulkiest component and PCB) can be determined inversely. The trained Gaussian process regression models are then used to perform virtual reflow optimization while allowing a 4°C tolerance for peak temperatures. Upon ensuring that the profiles are inside the safe zone, the corresponding reflow recipes can be implemented to set up the reflow oven.
Findings
ML algorithms can be used to interpolate sparse data and provide speedy responses to simulate the reflow profile. This proposed approach can effectively address optimization problems involving multiple factors.
Practical implications
The methodology used in this study can considerably reduce labor costs and time consumption associated with reflow profiling, which presently relies heavily on individual experience and skill. With the user interface and regression models used in this approach, reflow profiles can be swiftly simulated, facilitating iterative experiments and numerical modeling with great effectiveness. Smart reflow profiling has the potential to enhance quality control and increase throughput.
Originality/value
In this study, the employment of the ultimate compact CFD model eliminates the constraint of components’ configuration, as effective heat capacities are able to determine the temperature profiles of the component and PCB. The temperature profiles generated by the regression models are time-sequenced and in the same format as the CFD results. This approach considerably reduces the cost associated with training data, which is often a major challenge in the development of ML models.
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Fred F. Farshad, James D. Garber and Juliet N. Lorde
A novel approach using artificial neural networks (ANNs) for predicting temperature profiles evaluated 27 wells in the Gulf of Mexico. Two artificial neural network models were…
Abstract
A novel approach using artificial neural networks (ANNs) for predicting temperature profiles evaluated 27 wells in the Gulf of Mexico. Two artificial neural network models were developed that predict the temperature of the flowing fluid at any depth in flowing oil wells. Back propagation was used in training the networks. The networks were tested using measured temperature profiles from the 27 oil wells. Both neural network models successfully mapped the general temperature‐profile trends of naturally flowing oil wells. The highest accuracy was achieved with a mean absolute relative percentage error of 6.0 per cent. The accuracy of the proposed neural network models to predict the temperature profile is compared to that of existing correlations. Many correlations to predict temperature profiles of the wellbore fluid, for single‐phase or multiphase flow, in producing oil wells have been developed using theoretical principles such as energy, mass and momentum balances coupled with regression analysis. The Neural Network 2 model exhibited significantly lower mean absolute relative percentage error than other correlations. Furthermore, in order to test the accuracy of the neural network models to that of Kirkpatrick’s correlation, a mathematical model was developed for Kirkpatrick’s flowing temperature gradient chart.
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Prashant Dineshbhai Vyas, Harish C. Thakur and Veera P. Darji
This paper aims to study nonlinear heat transfer through a longitudinal fin of three different profiles.
Abstract
Purpose
This paper aims to study nonlinear heat transfer through a longitudinal fin of three different profiles.
Design/methodology/approach
A truly meshfree method is used to undertake a nonlinear analysis to predict temperature distribution and heat-transfer rate.
Findings
A longitudinal fin of three different profiles, such as rectangular, triangular and concave parabolic, are analyzed. Temperature variation, along with the fin length and rate of heat transfer in steady state, under convective and convective-radiative environments has been demonstrated and explained. Moving least square (MLS) approximants are used to approximate the unknown function of temperature T(x) with Th(x). Essential boundary conditions are imposed using the penalty method. An iterative predictor–corrector scheme is used to handle nonlinearity.
Research limitations/implications
Modelling fin in a convective-radiative environment removes the assumption of no radiation condition. It also allows to vary convective heat-transfer coefficient and predict the closer values to the real problems for the corresponding fin surfaces.
Originality/value
The meshless local Petrov–Galerkin method can solve nonlinear fin problems and predict an accurate solution.
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Massimo Fabbri, Antonio Morandi and Francesco Negrini
To investigate the feasibility of a novel scheme of high‐efficiency induction heater for nonmagnetic metal billets which use superconducting coils.
Abstract
Purpose
To investigate the feasibility of a novel scheme of high‐efficiency induction heater for nonmagnetic metal billets which use superconducting coils.
Design/methodology/approach
The idea is to force the billet to rotate in a static magnetic field produced by a DC superconducting magnet. Since a static superconducting magnet has no losses, the efficiency of the system is the efficiency of the motor used. In order to evaluate the temperature distribution arising from the field profile produced by a given SC coil configuration, a numerical model, based on an equivalent electric network with temperature‐dependent parameters, is developed.
Findings
A substantial independence of the shape of the temperature profile on the angular velocity and the value of the uniform magnetic field applied, is observed. A strong temperature gradient is observed in the radial direction in the proximity of the penetration front and in the axial direction at the top and bottom surface of the billet. Small temperature gradient was observed in the central part of the billet.
Research limitations/implications
The reported temperature profile is inadequate for an actual extrusion process which is desired to happen at a constant temperature. The appropriate profile along the billet length can be achieved by a suitable axial shaping of the magnetic field, through the optimization of the coil layout, whereas the undesired radial gradient can be reduced by interspacing the rotation with temperature smoothing intervals.
Practical implications
The investigation of the profile of applied magnetic field and the heating procedure which allow to achieve the distribution of temperature suitable for the extrusion process can be carried out by using the present model.
Originality/value
A high‐efficiency induction heater for nonmagnetic metal billets using superconducting coils in a novel scheme is investigated.
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T.J. Ennis, N. Brady, B. Keane and A. Donnelly
The effects of varying reflow profiles on the tensile pull strength and structure of solder joints of components with tin plated and nickel‐palladium plated leads were studied. It…
Abstract
The effects of varying reflow profiles on the tensile pull strength and structure of solder joints of components with tin plated and nickel‐palladium plated leads were studied. It was found that, in the case of tin plated leads, the structure and the tensile pull strength of the resultant solder joints were not significantly affected by varying the reflow conditions from Profile 1 (peak temperature range: 174°C to 195°C, reflow time 24 seconds) and Profile 2 (peak temperature range: 198°C to 218°C, reflow time 30 seconds). On the other hand, the mean pull strength of solder joints of nickel‐palladium plated lead was found to be significantly higher for joints reflowed with profile 2 than that of joints reflowed with Profile 1. Also, for both reflow profiles, the pull strengths of joints of nickel‐palladium plated leads were significantly higher than those of tin plated leads. This higher average pull strength may be due to the dissolution of palladium in the solder and/or the increased density of intermetallic precipitates in the solder fillet, and the increased intermetallic layer thickness at the lead/solder interface.
Faisal Rehman, Rafiq Asghar, Kashif Iqbal, Ali Aman and Agha Ali Nawaz
In surface mount assembly (SMA) process, small components are subjected to high temperature variations, which result in components’ deformation and cracking. Because of this…
Abstract
Purpose
In surface mount assembly (SMA) process, small components are subjected to high temperature variations, which result in components’ deformation and cracking. Because of this phenomenon, cracks are formed in the body of carbonyl powder ceramic inductor (CPCI) in the preheat and cooling stages of the reflow oven. These cracks become the main cause of board failure in the ageing process. The purpose of this paper is to ascertain the thermal stress, thermal expansion of carbonyl iron ceramics and its effects on crack commencement and proliferation in the preheat stage of reflow oven. Moreover, this paper also categorized and suggested important parameters of reflow profile that could be used to eliminate these thermal shock failures.
Design/methodology/approach
In this paper, two different reflow profiles were studied that evaluate the thermal shock of CPCI during varying ΔT at the preheat zone of the reflow oven. In the first profile, the change in temperature ΔT at preheat zone was set to 3.26°C/s, which has resulted in a number of device failures because of migration of micro cracks through the CPCI. In the second profile, this ΔT at preheat stage is minimized to 2.06°C/s that eliminated the thermal stresses; hence, the failure rates were significantly reduced.
Findings
TMPC0618H series lead (Pb)-free CPCI is selected for this study and its thermal expansion and thermal shock are observed in the reflow process. It is inferred from the results that high ΔT at preheat zone generates cracks in the carbonyl powder-type ceramics that cause device failure in the board ageing process. Comparing materials, carbonyl powder ceramic components are less resistant to thermal shock and a lower rate of temperature change is desirable.
Originality/value
The proposed study presents an experimental analysis for mitigating the thermal shock defects. The realization of the proposed approach is validated with experimental data from the printed circuit boards manufacturing process.
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Yangyang Lai, Ke Pan, Yuqiao Cen, Junbo Yang, Chongyang Cai, Pengcheng Yin and Seungbae Park
This 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…
Abstract
Purpose
This 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/approach
In 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.
Findings
Integrated 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 implications
The 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/value
This 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.
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