Reflow soldering process parameter optimization method based on NSGA-II algorithm
Through the reflow soldering process parameter optimization method based on the NSGA-II algorithm, the problem of unstable welding quality in the prior art is solved, the temperature difference and cooling stress of the solder joint are optimized, and the welding quality and product reliability are improved.
Patent Information
- Application Number
- CN202510025439.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-07
- Publication Date
- 2025-05-09
AI Technical Summary
The existing solder joint temperature and stress measurement methods are difficult to quickly and accurately reflect the temperature and stress distribution during the welding process, and the lack of optimization methods leads to unstable quality of reflow soldering.
The reflow soldering process parameter optimization method based on NSGA-II algorithm is adopted. Through finite element modeling and thermal-structure coupled simulation analysis, combined with experimental verification and response surface test, the regression equations of the temperature difference and cooling stress of the solder joint are obtained, and the process parameters are optimized to reduce the temperature difference and cooling stress of the solder joint.
It effectively reduces the solidification temperature difference and cooling stress of the welding joints, reduces welding defects, and improves welding quality and product reliability.
Smart Images
Figure CN119962475A_ABST
Abstract
Description
Technical Field
[0001] This patent relates to the field of electronic manufacturing technology, specifically, this patent relates to the field of electronic manufacturing technology, specifically, a reflow soldering process parameter optimization method based on NSGA-II algorithm. Background Art
[0002] With the miniaturization and high performance of electronic products, the welding quality of printed circuit board assembly (PCBA) is particularly important. Reflow soldering is a welding technology widely used in the electronics manufacturing industry. The solidification temperature difference and cooling stress of the solder joints in the process are key factors affecting the welding quality. Too large a solder joint temperature difference or too high a cooling stress may cause welding defects such as voids and cracks, which in turn affect the reliability and service life of electronic products. The process parameter value is a key parameter that plays a decisive role in the solidification temperature difference and cooling stress of the PCBA solder joints during the reflow soldering process. Generally, by adjusting the process parameter value, the temperature difference and cooling stress at the time of solder joint solidification can be reduced.
[0003] Existing methods for measuring solder joint temperature and stress mainly include thermocouple measurement and strain gauge testing. Thermocouple measurement directly attaches the thermocouple to the solder joint to monitor temperature changes in real time, but its large size may affect the soldering process, and it is impossible to measure the temperature distribution of all solder joints. Strain gauge testing infers stress distribution by measuring resistance changes, but it can only provide local stress information, and the installation process is complicated and easily introduces measurement errors. These technologies are difficult to quickly and accurately reflect the temperature and stress distribution during the soldering process, and lack optimization methods, which restricts further improvement of reflow soldering quality. Summary of the invention
[0004] The present invention relates to a reflow soldering process parameter optimization method based on the NSGA-II algorithm. The method aims to reduce the temperature difference and stress of PCBA in the reflow soldering process through precise simulation and experimental verification, optimize the reflow soldering process parameters, and improve the stability of soldering quality and product reliability.
[0005] First, the PCBA to be studied is preliminarily selected based on the specific application requirements. This includes determining the geometric parameters and material properties of the PCBA, such as PCB material, component layout, and packaging type. These parameters are critical to establishing an accurate physical model because they directly affect heat conduction and stress distribution.
[0006] Next, ANSYS APDL software is used for finite element modeling and thermal-structural coupling simulation analysis. This step is the core technical link. Through the finite element analysis function of ANSYS APDL, the temperature field and stress field of PCBA during reflow soldering can be simulated. Thermal-structural coupling simulation takes into account factors such as material thermal expansion and thermal stress caused by temperature changes, and stress relaxation during cooling. These simulation results can more accurately derive the thermal stress and temperature difference distribution of solder joints.
[0007] In order to verify the accuracy of the simulation results, the present invention establishes an experimental test platform. The actual reflow soldering temperature curve is applied to the test sample, and the temperature and cooling stress of the PCBA solder joint are measured. These test data are used to calibrate and verify the simulation model to ensure that the simulation results are consistent with the actual situation.
[0008] Then, a response surface experiment was designed to further derive the correlation equation between the solder joint temperature difference and cooling stress and the reflow soldering process parameters. By changing the process parameters, such as peak temperature, reflow time, cooling rate, etc., the solder joint temperature difference and cooling stress values under different conditions can be obtained.
[0009] After obtaining enough data, these data are fitted and analyzed to obtain the regression equations of temperature difference and cooling stress. The NSGA-II algorithm is used to reduce the solidification temperature difference and cooling stress value of the solder joint under reflow soldering conditions, thereby optimizing the reflow soldering parameters and obtaining multiple sets of optimized reflow parameter combinations. A set of process parameters is selected according to the actual application, which can effectively reduce the temperature difference and cooling stress of the solder joint, thereby reducing welding defects and improving the welding quality and product reliability of PCBA. This is especially important for the manufacturing of high-precision and high-reliability electronic products. BRIEF DESCRIPTION OF THE DRAWINGS
[0010] In order to more clearly explain the process of the embodiment of the present invention, the drawings involved in the embodiment are briefly introduced below. It is worth noting that the drawings described below are only part of the many method embodiments of the present invention. For ordinary technicians in this field, without additional creative work, more relevant drawings can be obtained based on these drawings to more fully understand and apply the present invention.
[0011] Figure 1 It is the finite element analysis model of the research object in this embodiment;
[0012] Figure 2 is a soldering point temperature distribution diagram obtained by simulation in this embodiment;
[0013] Figure 3 is a solder point cooling stress distribution diagram obtained by simulation in this embodiment;
[0014] Figure 4This is a distribution diagram of the objective function values of individuals in the population after optimization by the NSGA-II algorithm in this embodiment;
[0015] Figure 5 The present invention is a flowchart of the method. DETAILED DESCRIPTION
[0016] The method of the present invention will be implemented in combination with an actual PCBA board, and the implementation process of the present invention will be clearly and completely described. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0017] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation process descriptions.
[0018] This example selects a PCBA object, including BGA, QFP, QFN, SOP, PCB board and other components. The model contains 8 components, and the solder joints are all lead-free solder SAC305. Considering the complex structure of the actual PCBA, it is partially simplified, omitting the copper wiring and pads on the board. The finite element analysis model of the solder joint temperature difference and cooling stress during the PCBA reflow soldering process obtained by modeling with ANSYS APDL software is shown in the figure below. Figure 1 As shown in the figure, in order to ensure the accuracy of the simulation, necessary mesh encryption is performed on the solder joints and areas near the solder joints.
[0019] Based on the reflow soldering heating mechanism, the thermal-structural indirect coupling method is required to realize the temperature and stress simulation of the PCBA reflow soldering process through ANSYS APDL software. That is, thermal analysis is first performed, and the temperature field of the board-level circuit module solder point model is obtained by applying convection load to the outer surface of the model. Then, thermal-structural analysis is performed. After converting the thermal unit type SOLID70 into the structural unit type SOLID185, the thermal analysis results are applied to the model as body loads, and then thermal-structural stress analysis is performed. Figure 2 , Figure 3 They are PCBA solder point temperature distribution diagram and stress distribution diagram respectively.
[0020] In order to verify the accuracy of the simulation results, the simulation results were then tested and verified. The measurement platform used in the test mainly includes: strain gauges, thermocouples, T-890 infrared rework station, and dynamic and static strain gauges. The strain gauges are pasted on the test specimens to measure the strain, and the temperature is measured by thermocouples, and then compared with the simulation result values of the measured positions. If the test error is within 20%, it can be proved that the simulation method used has a certain accuracy and reference value.
[0021] During the test, the T-890 infrared rework station was first used to load the temperature curve and heat the experimental sample to the solidification temperature of the solder joint. The temperature of the solder joint was monitored in real time by the thermocouple on the rework station, and the temperature difference when the solder joint solidified was recorded. Subsequently, the heating function of the rework station was turned off to simulate the cooling process of the reflow soldering until the sample temperature dropped to room temperature (25°C). During the cooling process, the changes in the strain value of the solder joint were collected by a dynamic resistance strain gauge, and the stress value generated during the cooling process was calculated by the stress calculation formula. In this case, the experimental results were compared with the simulation results, and the error between the experimental and simulated stress results was 11.89% and 8.68%, respectively. The error between the simulation value and the experimental value was less than 20%, which proved the accuracy of the simulation analysis.
[0022] According to the number of selected reflow soldering process parameter variables, the central composite experimental design method is used for response surface analysis. Through this method, the relationship between the solidification temperature difference of the solder joint and the reflow soldering process parameters, as well as the relationship between the maximum cooling stress of the PCBA solder joint and the reflow soldering process parameters are established. In this example, the holding time, reflow time, reflow temperature and cooling rate are selected as the four main influencing factors. Five level values are selected for each factor, as shown in Table 1. According to the values in Table 1, the response surface experimental group is designed, and the simulation results of each experimental group are recorded. The temperature difference value at the solidification moment of the solder joint and the maximum cooling stress value of the solder joint at the end of the reflow are taken. The results are shown in Table 2.
[0023] Table 1 Factor level table
[0024]
[0025] Table 2 Response surface test groups
[0026]
[0027]
[0028] By performing regression fitting on the data in Table 2, two binary multiple regression equations are obtained, and the equations are as follows:
[0029] Y 1 =152.4+0.144×X 1 -0.688×X 2 -1.129×X 3 -10.98×X 4 +0.000507×X 1 ×X 1 +0.00125×X 2 ×X 2 +0.00232×X 3 ×X 3 +0.0372×X4 ×X 4 +0.001147×X 1 ×X 2 -0.001204×X 1 ×X 3 +0.00073×X 1 ×X 4 +0.00205×X 2 ×X 3 +0.00499×X 2 ×X 4 +0.04644×X 3 ×X 4 (1)Y 2 =-75+0.971×X 1 +1.26×X 2 +15.65×X 4 -0.000391×X 1 ×X 1 -0.00174×X 2 ×X 2 +0.00111×X 3 ×X 3 -0.6242×X 4 ×X 4 -0.00218×X 1 ×X 2 -0.00319×X 1 ×X 3 -0.0115×X 1 ×X 4 -0.00350×X 2 ×X 3 -0.0138×X 2 ×X 4 -0.0102×X 3 ×X 4 (2)
[0030] X in equation (1) and equation (2) 1 (holding time), X 2 (Reflow time), X 3 (Reflow temperature), X 4 (cooling rate) as the input variable of the equation, Y 1 (solder point temperature difference) and Y 2 (Cooling stress) is used as the output variable of the equation. Based on the two regression equations obtained, the process parameters are optimized by using the NSGA-II algorithm through MATLAB software with the cooling stress and solder joint temperature difference as the target under the reflow process conditions.
[0031] According to Table 1, the constraints are as follows: 80≤X 1 ≤120,30≤X 2 ≤50,230≤X 3 ≤250,2≤X 4 ≤6(X 1 is the holding time, X 2 is the reflow time, X 3 is the reflow temperature, X 4 is the cooling rate), the number of individuals in the population is 100, the maximum number of generations is 100, and the number of target variables is 4. Based on the NSGA-II algorithm, the operations of the genetic algorithm (such as selection, crossover, mutation, etc.) are used to iterate the population. In each generation, a set of non-dominated solutions is selected based on mechanisms such as non-dominated sorting and crowding distance. The distribution of the objective function values of individuals in the population after iteration is as follows: Figure 4 As shown in the figure, the horizontal axis target 1 is the temperature difference of the soldering point, and the vertical axis target 2 is the stress value. Each point in the figure represents a set of solutions. It can be seen from Table 3 that there are 34 solutions in total, and these optimized combined solutions constitute a set of non-dominated solution sets.
[0032] Table 3 Optimized combination
[0033]
[0034]
[0035] According to Table 3, the optimized reflow soldering combination significantly reduces the maximum temperature difference and cooling stress, which is better than the results in Table 2. The optimized solution set shows a variety of optimal process parameter combinations under different trade-off conditions for solder joint temperature difference and cooling stress. Through the method of the present invention, the reflow soldering parameters are effectively optimized and the soldering quality is significantly improved.
[0036] The above embodiments describe the implementation process of the present invention in detail. Figure 5 The method implementation flow chart shown is for illustration only and does not limit the application scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made by ordinary technicians in this field to the technical solution of the present invention should fall within the protection scope determined by the claims of the present invention.
Claims
1. A reflow soldering process parameter optimization method based on NSGA-II algorithm, comprising the following steps: (1) Preliminary selection of PCBA based on application requirements and determination of its geometric parameters and material parameters; (2) Use ANSYS APDL for finite element modeling and thermal-structural coupling simulation analysis; (3) Build a reflow soldering temperature and stress test platform to test and verify the simulation results; (4) Design a response surface experiment based on the selected reflow process parameters to obtain the solidification temperature difference and cooling stress value of the solder joint; (5) Perform regression analysis on the test data and establish a regression equation between the reflow soldering process parameters and the solder joint solidification temperature difference and cooling stress value; (6) Based on the obtained regression equation, the NSGA-II algorithm is used to perform dual-objective optimization on the solder joint solidification temperature difference and cooling stress value of PCBA reflow soldering; (7) Use the obtained optimization results to guide the optimization of actual reflow soldering process parameters.
2. The method according to claim 1, characterized in that The thermal-structural coupling simulation analysis described in step (2) is based on the heating mechanism and process characteristics of reflow soldering, and uses ANSYS APDL software to implement PCBA modeling and temperature and stress simulation of the reflow soldering process. That is, first, a thermal analysis is performed, and the temperature field of the board-level circuit module solder point model is obtained by applying a thermal load of the reflow temperature curve to the outer surface of the model. Then, after the thermal unit type SOLID70 is converted into the structural unit type SOLID185, the thermal analysis results are applied to the model as body loads, and then a thermal-structural analysis is performed to obtain the cooling stress value of the solder point.
3. The method according to claim 1, characterized in that The test platform in step (3) includes strain gauges, thermocouples, solder joint rework stations, dynamic and static strain gauges, etc., which together constitute a temperature and stress test platform for reflow soldering.
4. The method according to claim 1, characterized in that: In step (4), the solidification temperature difference and cooling stress value of the solder joint under different combinations of reflow soldering process parameters are obtained through response surface experimental design, and the experimental data are based on finite element simulation calculation results.
5. The method according to claim 1, characterized in that The solder point solidification temperature difference and cooling stress value obtained in step (4) are the maximum temperature difference when all solder points of the PCBA solidify and the maximum cooling stress value of the solder points at the end of reflow.
6. The method according to claim 1, characterized in that In step (6), based on the quadratic polynomial regression equation between the reflow process parameters and the cooling stress established by response surface analysis, and the quadratic polynomial regression equation between the reflow process parameters and the solder solidification temperature difference, the NSGA-II algorithm is used in MATLAB software to optimize the reflow process parameters with the optimization goal of simultaneously reducing the solder solidification temperature difference and cooling stress during the reflow soldering process.
7. The method according to claim 1, characterized in that The method includes modeling and simulation analysis through ANSYS APDL software, and verifying the accuracy of the simulation results in combination with experiments; further fitting the regression equation through the response surface test method, and optimizing the reflow soldering process parameters based on the NSGA-II algorithm, and the optimization results are used to guide the adjustment of the actual reflow soldering process parameters, thereby reducing the solidification temperature difference and cooling stress value of the solder joint, and realizing the optimization of the reflow soldering process.