Reflow Soldering Process Virtual Test Based on BPNN-GA and ANSYS

Sun, Zhi Li; Guo, Yu; Pan, Er Shun; Song, Wei

doi:10.4028/www.scientific.net/amm.281.417

Cited by 4 publications

(2 citation statements)

References 2 publications

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“…The distribution of the selected articles in different years and different stages are illustrated in Figure 3. It can be seen that 17% (17 articles) were related to the stage of product and manufacturing process design [26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42], and more than 75% (80 articles) applied DM and Big Data to production management and control in the stage of production , but less than 8% (8 articles) of applications focused on the stage of sale, service, and recycling [123][124][125][126][127][128][129][130]. The fluctuation in quantity of the selected articles in different years presents no obvious tendency, however, it indicates that the topic has attracted ongoing attention and research during the past decades, and the application areas have been extended and many new approaches have been developed.…”

Section: Article Selection and Distributionmentioning

confidence: 99%

“…(2) The optimization of the manufacturing process parameter is the main task of process planning, such as the parameter optimization of stencil printing process (SPP) [26,27,36], reflow soldering [29,31,32], fluid dispensing for microchip encapsulation [33], wave soldering [35,41], and hot solder dip [39] for component surface mounts on PCBs. These models always combined ANN, SVR, and regression for the quality prediction with GA for parameters optimization [26,[31][32][33].…”

Section: Application Of Dm and Big Data For Designmentioning

confidence: 99%

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A Review of Data Mining with Big Data towards Its Applications in the Electronics Industry

Kim

Zheng

et al. 2018

Applied Sciences

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Data mining (DM) with Big Data has been widely used in the lifecycle of electronic products that range from the design and production stages to the service stage. A comprehensive analysis of DM with Big Data and a review of its application in the stages of its lifecycle will not only benefit researchers to develop strong research themes and identify gaps in the field but also help practitioners for DM application system development. In this paper, a brief clarification of DM-related topics is presented first. A flowchart of DM and the main content of the flowchart steps are given in which commonly used data preparation and preprocessing approaches, DM functions and techniques, and performances indicators are summarized. Then, a comprehensive review covering 105 articles from 2007 to 2017 on DM or Big Data applications in the electronics industry is provided according to the flowchart from various points of view such as data handling, applications of DM, or Big Data at different lifecycle stages, and the software used in the applications. On this basis, a diagram of data content for different knowledge areas and a framework for DM and Big Data applications in the electronics industry are established. Finally, conclusions and future research directions are given.

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Section: Article Selection and Distributionmentioning

confidence: 99%

Section: Application Of Dm and Big Data For Designmentioning

confidence: 99%

A Review of Data Mining with Big Data towards Its Applications in the Electronics Industry

Kim

Zheng

et al. 2018

Applied Sciences

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Study on Influencing Factors and Laws of Temperature Field Distribution of Infrared Hot Air Reflow Soldering

Pang

Zheng³

et al. 2021

J. Phys.: Conf. Ser.

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The quality of solder joints formed by reflow soldering is closely related to the temperature profile of solder joint during the hot air reflow soldering process. The temperature profile of solder joint is directly determined by the process parameters of the reflow furnace as the layout of the PCB design remains same. In this paper, the temperature model of the printed board assembly during reflow soldering is numerically built and simulated to obtain the temperature distribution. Furtherly, several process parameters, such as the temperature of each temperature zone, convective heat transfer coefficient and conveyor belt speed of reflow soldering furnace, are selected as the input variables, and the heating factor, time of super liquidus and peak temperature are aimed as the output parameters. The Latin hypercube sampling design is applied to construct the response surface of the output parameters. The influence of these process parameters during the reflow soldering on the temperature profile of PCBA is studied comprehensively. The main influencing process parameters of the reflow soldering are identified and their influence laws are obtained. The research results provide valuable reference and basis for reflow soldering process design.

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Research on the Influence of Device Thermal Equivalent Model on the Temperature Field of Infrared Hot Air Reflow Soldering

Yin

Gong

2021

J. Phys.: Conf. Ser.

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Infrared hot air reflow soldering is an important process in SMT assembly process. The temperature field of infrared hot air reflow soldering of PCBA will directly affect the reliability of solder joints. The different simplified equivalent models have a certain influence on the temperature field of infrared hot air reflow soldering PCBA, which is mainly reflected in accuracy and efficiency. This paper studies the influence of three different thermal models on the temperature field of reflow soldering PCBA, and selects four groups of points in the same position of the three models, and comprehensively compares their temperatures. The results show that the maximum temperature deviation of the three models is as high as 7℃ in the soldering zone and 4℃ in the cooling zone, and the temperature difference is small. It can be concluded that the complex solder ball model can be used for high precision applications, and the simplified single-layer solder model and the thermal equivalent model can be used for low precision applications. These conclusions provide some references for the modeling of infrared hot air reflow soldering.

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Reflow Soldering Process Virtual Test Based on BPNN-GA and ANSYS

Cited by 4 publications

References 2 publications

A Review of Data Mining with Big Data towards Its Applications in the Electronics Industry

A Review of Data Mining with Big Data towards Its Applications in the Electronics Industry

Study on Influencing Factors and Laws of Temperature Field Distribution of Infrared Hot Air Reflow Soldering

Research on the Influence of Device Thermal Equivalent Model on the Temperature Field of Infrared Hot Air Reflow Soldering

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