Overview of Different Approaches in Numerical Modelling of Reflow Soldering Applications

István Bozsóki (), Attila Géczy and Balázs Illés
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István Bozsóki: Department of Electronics Technology, Budapest University of Technology and Economics, 1111 Budapest, Hungary
Attila Géczy: Department of Electronics Technology, Budapest University of Technology and Economics, 1111 Budapest, Hungary
Balázs Illés: Department of Electronics Technology, Budapest University of Technology and Economics, 1111 Budapest, Hungary

Energies, 2023, vol. 16, issue 16, 1-20

Abstract: This paper gives a review of different applications in the numerical modelling of reflow soldering technology from recent years. The focus was on detailing the different process types, the physical background, and related mathematical models. Reflow soldering is the main connection technology of surface mounting. Firstly, the solder in paste form is stencil-printed onto the solder pads of the applied substrate, and then surface mounted devices are placed onto the solder deposits. Finally, the whole assembly is heated over the melting temperature of the solder alloy, which melts and forms solder joints. Surface mounting technology needs a low defect rate which is determined by process parameters, material properties, and the printed circuit board design. Accompanying the experiment and measurement, the identification and elimination of root causes can be effectively improved with numerical modelling, which also grants details to such physical mechanisms that are not even conventionally measurable. This paper is dealing with the following topics from the modelling point of view: an introduction of the different reflow technologies; a brief introduction of primary partial differential equations and calculation procedures; heat transfer mechanisms and thermomechanical stresses; and a brief summary of the results of selected studies. A short overview is also given about soft computing methods applied in reflow process optimisation.

Keywords: reflow soldering technology; numerical modelling; thermomechanical stress; heat transfer; machine learning (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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