Search results

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 Q_η, a measure of success for high reliability of the solder joints reflowed.

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.

Heating mechanism analysis and experiments demonstrate that the combinatorial parameters based method is feasible to do thermal profiling.

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.

Provides a methodology for designing an oven recipe for reflow soldering production.

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.

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.

A study of the Sn‐Ag‐Cu lead‐free solder reflow profile has been conducted. The purpose of the work was to determine the Sn‐Ag‐Cu reflow profile that produced solder bumps with a thin intermetallic compound (IMC) layer and fine microstructure. Two types of reflow profiles were studied. The results of the experiment indicated that the most significant factor in achieving a joint with a thin IMC layer and fine microstructure was the peak temperature. The results suggest that the peak temperature for the Sn‐Ag‐Cu lead‐free solder should be 230°C. The recommended time above liquidus is 40 s for the RSS reflow profile and 50‐70 s for the RTS reflow profile.

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.

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.

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.

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.

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.

This paper aims to establish a method to optimize reflow profiles and achieve high reliability of solder joints on the basis of the heating factor, Q_η, a measure of the reflow profile related to reliability of reflow processed products.

The focus of the paper is on how to realize the optimal range of Q_η, since there is no need to pay particular attention to the shape of a reflow profile when performing a heating factor‐based optimization. The coldest point on the printed circuit board assembly (PCA), which experiences the minimum heating factor (Q_η^min) during the reflow process, was used to set the lower limit of the optimal range (Q_η^L). If Q_η^min approaches Q_η^L and the temperature difference across the PCA is minimized, then the solder joints on the PCA will all experience heating factors within the optimal range, ensuring high quality reflow soldering. Establishing an initial reflow profile may be performed using profiling software. The resultant oven recipe may then be used as the reference recipe by which to apply the heating factor‐based optimization. A combinatorial parameter, H_t, is defined to represent the temperature settings of all the top heating zones within the heating section of the reflow oven. The relative difference between H_t and each top heating zone temperature setting is derived from the reference recipe, and H_t is then adjusted to achieve Q_η^L for Q_η^min. This is achieved by using a least squares estimation method to build a regression model for Q_η^min versus H_t.

Experiments and regression analysis have demonstrated that Q_η^min varied linearly with H_t, with α denoting its slope. With a measured Q_η^min in response to the reference setup after the first run of a PCA, H_t should be increased by ((Q_η^L−Q_η^min)/α) to attain Q_η^L in the second run. Thereby, a suitable reflow process recipe can be obtained with only two reflow runs where Q_η^min is close to Q_η^L.

The optimal range of heating factor for lead‐free solder pastes is currently unknown, and the method to establish the required oven recipe for achieving a required reflow profile requires further exploration.

Provides a methodology for reducing the risk of process‐related reliability issues in lead‐free soldering.

Q_η^L can be fairly quickly achieved for Q_η^min with the approach established in this paper, facilitating the formation of solder joints with high reliability during the reflow soldering process.

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.

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.

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.

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.

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.

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.

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.

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.

The influence of the thermal reflow profile on the formation and resultant morphology of the intermetallic layer that developed at the Ni particle reinforcements within an eutectic Sn‐Ag composite solder matrix was investigated. The composite solder was fabricated by mechanically dispersing 15 vol% Ni particles into eutectic Sn‐3.5Ag solder paste. Two distinct intermetallic compound (IMC) morphological microstructures were observed around the Ni reinforcements. IMC morphological microstructure apparently varied depending on the amount of heat input and differences in heating rates used in the reflow profile. A “sunflower” IMC morphology was typically noted when the total amount of heat input was small. However, with sufficient heat input, a faceted “blocky” IMC morphology was consistently achieved. Multiple‐reflow thermal profiling experiments were conducted to measure and compare the amount of heat input necessary to change the sunflower IMC morphology around Ni particle reinforcements to the blocky morphology.

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.

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.

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.

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.

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.

For reflow soldering in today's changing component and soldering technology, requirements with respect to profiling seem to be difficult to determine and even harder to meet. State‐of‐the‐art reflow trackers can be of help here, but, without some knowledge of the fundamentals in profiling, it will be easy to misunderstand measurements. The use of nitrogen as a protective gas for reflow soldering can be advantageous for fine pitch technology, bare copper boards and low residue solder pastes. However, because reflow solder defects are related to more than just the use of nitrogen, one may find different benefits for the use of nitrogen, depending on how the investigations are carried out. Wetting under nitrogen is certainly better and more reproducible, while the near absence of oxygen is beneficial to oxidation‐related problems. For high numbers of solder joints per board, it is not easy to achieve an acceptable first pass yield. Only with low, controlled defect levels found within a robust reproducible process is it possible to achieve this. Using forced convection together with nitrogen for reflow soldering is becoming the preferred method.