Optimization design method of epoxy plastic package structure

Abstract

The application provides an optimization design method of an epoxy plastic package structure, which comprises the following steps: S10, screening physical property parameter factors which have influences on the performance of the epoxy plastic package structure; S20, designing an orthogonal test table according to the selected physical property parameter factors; S30, establishing a finite element model and performing simulation test according to the orthogonal test table; S40, processing the test data and establishing a regression model; S50, performing F test analysis on the regression model to determine whether there is a physical property parameter factor which has a significant influence; S60, performing T test analysis on the regression model to determine the physical property parameter factor which has a significant influence; and S70, guiding the optimization design of the epoxy plastic package structure according to the analysis result. The application combines the method of test design and statistical analysis, processes the data through simulation test, so that the optimization design of the epoxy plastic package structure can be theoretically supported and the design cost can be reduced.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of packaging structure, and particularly relates to an optimization design method of an epoxy plastic packaging structure. BACKGROUND

[0002] With the development of electronic information technology and the needs of society, electronic products are constantly developing towards miniaturization, lightweight, high performance, multifunction and low cost, and electronic packaging technology plays an important role in it. The packaging form has also transitioned from the original ceramic packaging and metal packaging to plastic packaging, and now the epoxy plastic packaging structure has gradually become the mainstream of plastic packaging form.

[0003] In the epoxy plastic packaging structure, due to the different material properties between EMC (epoxy plastic sealing material), chips, substrates and other materials, such as thermal expansion coefficient, Young's modulus and other physical parameters, the stress between the interfaces of different materials is different during the reflow process, and different degrees of deformation occur, resulting in packaging structure failure.

[0004] At present, the failure form and failure reason of the epoxy plastic packaging structure have been studied a lot at home and abroad, such as using epoxy plastic sealing materials with different physical parameters, substrates with different material properties, etc., and doing some reliability tests to observe the specific position of failure and the failure reason. The prior art only describes the test results according to the test phenomena, although it can give relatively correct conclusions within a specific test range, but it has no specific theoretical support, and the data obtained from the overall test sample is not reliable, and the cost required for specific test is high. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides an optimization design method of an epoxy plastic packaging structure, so that the optimization design of the epoxy plastic packaging structure can be theoretically supported and the design cost can be reduced.

[0006] In order to solve the above problems, the present application adopts the following technical scheme:

[0007] An optimization design method of an epoxy plastic packaging structure, comprising the following steps:

[0008] S10, screening physical parameter factors having an influence on a certain performance of the epoxy plastic packaging structure according to existing experience, and determining high level values and low level values of each physical parameter factor;

[0009] S20, designing an orthogonal test table according to the selected physical parameter factors;

[0010] S30, establishing a finite element model according to the selected physical parameter factors, and performing simulation test according to the orthogonal test table, and filling the test results obtained into the orthogonal test table to form a complete test data table;

[0011] S40, processing all the test data of the test data table, establishing a regression model, calculating sample mean and fitting value;

[0012] S50, performing F test analysis on the regression model to determine whether there is a physical property parameter factor having significant influence on the certain performance; if yes, performing next step processing, and if no, returning to step S10 to adjust the selected physical property parameter factor;

[0013] S60, performing T test analysis on the regression model to determine the physical property parameter factor having significant influence on the certain performance;

[0014] S70, guiding the optimization design of the epoxy plastic packaging structure according to the above analysis results.

[0015] Specifically, the certain performance is thermal stress, warping level or moisture stress.

[0016] Specifically, the physical property parameter factor includes Young's modulus, thermal expansion coefficient and thickness of the epoxy plastic packaging material, and also includes Young's modulus, thermal expansion coefficient and thickness of the substrate.

[0017] Specifically, the step S60 further includes: drawing a Pareto chart according to the result of the T test analysis to visually display the physical property parameter factor having significant influence.

[0018] Specifically, in the step S30, for a certain simulation test, if there is corresponding reliability test data, the reliability test data is imported to improve the accuracy of the simulation model.

[0019] The optimization design method of the epoxy plastic packaging structure provided by the embodiment of the present application uses the method combining test design and statistical analysis, obtains certain theoretical support through simulation test and data analysis and processing in the theoretical level, so that the optimization design of the epoxy plastic packaging structure can be theoretically supported and the design cost can be reduced. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 is the flow chart of the optimization design method of the epoxy plastic packaging structure in the embodiment of the present application;

[0021] Figure 2 is the Pareto chart of the standardized effect drawn according to the result of the T test in the embodiment of the present application. DETAILED DESCRIPTION

[0022] In order to make the objects, technical solutions and advantages of the present application clearer, the specific embodiments of the present application will be described in detail below with reference to the drawings. The examples of these preferred embodiments are illustrated in the drawings. The embodiments of the present application shown in the drawings and described according to the drawings are merely exemplary, and the present application is not limited to these embodiments.

[0023] It should be noted here that, in order to avoid obscuring the present application due to unnecessary details, only the structures and / or processing steps closely related to the solutions according to the present application are shown in the drawings, and other details not closely related to the present application are omitted.

[0024] The present application provides an optimization design method for an epoxy plastic packaging structure. Referring to Figure 1 , the method comprises the following steps:

[0025] S10, screening physical property parameter factors that have an influence on a certain performance of the epoxy plastic packaging structure according to existing experience, and determining high and low level values of each physical property parameter factor.

[0026] Specifically, the certain performance is thermal stress size, warping level or wet stress size.

[0027] Specifically, the physical property parameter factors include Young's modulus, thermal expansion coefficient and thickness of the epoxy plastic packaging material, and also include Young's modulus, thermal expansion coefficient and thickness of the substrate.

[0028] In a specific embodiment of the present application, the certain performance is selected to be thermal stress size, and the physical property parameter factors include Young's modulus, thermal expansion coefficient and thickness of the epoxy plastic packaging material (EMC) and Young's modulus, thermal expansion coefficient and thickness of the substrate (Substrate). The physical property parameter factors selected in this embodiment that can have a significant influence on the thermal stress size of the epoxy plastic packaging are shown in Table 1 below.

[0029] Table 1:

[0030]

[0031] It should be noted that in Table 1, "low" represents the low level value of the corresponding physical property parameter factor, "high" represents the high level value of the corresponding physical property parameter factor, and T1-T3 represent temperature conditions, T1=25℃, T2=125℃ and T3=220℃.

[0032] S20, designing an orthogonal test table according to the selected physical property parameter factors.

[0033] In this embodiment, according to the physical property parameter factors in Table 1, the orthogonal test table in Table 2 below is designed.

[0034] Table 2:

[0035]

[0036] It should be noted that in Table 2, the serial number in the standard sequence is the serial number when the simulation test is designed, and the running sequence is the serial number when the simulation test is performed; in the columns corresponding to the physical property parameter factors EMC and Substrate: "1" represents the high level value of the corresponding physical property parameter factor, and the specific value is obtained from Table 1; "-1" represents the low level value of the corresponding physical property parameter factor, and the specific value is obtained from Table 1.

[0037] S30, according to the selected physical property parameter factors, a finite element model is established, and simulation test is performed according to the orthogonal test table (as shown in Table 2), and the test results obtained are filled into the orthogonal test table to form a complete test data table.

[0038] In this embodiment, the test results of the simulation test are the thermal stress values of each test model.

[0039] In a preferred embodiment, in the step S30, for a certain simulation test, if there is corresponding reliability test data, the reliability test data is imported to improve the accuracy of the simulation model.

[0040] S40, all test data of the test data table are processed, a regression model is established, and the sample mean and the fitting value

[0041] The fitting value is calculated according to the following equation:

[0042] Formula 1: Xb=Y, wherein X is the value of the physical property parameter factor, b is the coefficient of each term in the regression model, and Y is the test result, i.e. the thermal stress value.

[0043] Since the equation set is an overdetermined equation, i.e. the number of equations is greater than the number of independent variables, the equation set needs to be transformed into a matrix as follows:

[0044] Formula 2: X T Xb=X T Y;

[0045] Formula 3: b=(X T X) -1 X T Y.

[0046] The solution set b obtained by solving is the coefficients of the regression equation, and then the fitting value of each group of tests is calculated.

[0047] S50, performing F test analysis on the regression model to determine whether there is a property parameter factor having a significant influence on the certain performance; if yes, performing next step processing, and if no, returning to step S10 to adjust the selected property parameter factor.

[0048] The F value of the regression model is calculated according to the following steps:

[0049] (1) Regression sum of squares:

[0050] (2) Regression degrees of freedom: df R =k, k is the number of independent variables, i.e. the number of selected property parameter factors;

[0051] (3) Residual sum of squares:

[0052] (4) Residual degrees of freedom: df E =n-k-1, n is the number of tests, and k is the number of independent variables, i.e. the number of selected property parameter factors;

[0053] (5) F value of the regression model:

[0054]

[0055] In the above formulae, yi, respectively correspond to the sample mean, sample value and fitting value.

[0056] According to the degrees of freedom obtained, the critical F value of the selected significant level (in this embodiment, the significant level is a=0.05) is determined from the F distribution critical value table according to the size of the horizontal axis degrees of freedom df R and the vertical axis degrees of freedom df E , and then the F value of the regression model obtained is compared with the critical F value. If the F value of the regression model is greater than the critical F value, it means that the model is reliable, i.e. there is a factor having a significant influence on the result in the model, and the next step of analysis can be performed. Otherwise, the influence factor needs to be reselected and the above steps are repeated.

[0057] S60, performing T test analysis on the regression model to determine the property parameter factor having a significant influence on the certain performance.

[0058] Specifically, the T value of the property parameter factor A is calculated according to the following steps:

[0059] (1) Effect of A = [average value of Y | A = high] - [average value of Y | A = low], where [average value of Y | A = high] refers to the average value of the test result Y when the physical property parameter factor A takes a high level value, and [average value of Y | A = low] refers to the average value of the test result Y when the physical property parameter factor A takes a low level value;

[0060] (2) The coefficient of A = the effect of A / 2;

[0061] (3)

[0062] (4)

[0063] (5) The T value of the physical property parameter factor A A = Coefficient of A / Standard error of coefficient of A

[0064] In the above formula, yi, These correspond to the sample value and the fitted value, respectively, and n is the number of trials.

[0065] Calculate the T value for each physical property parameter factor according to the above steps, and then calculate the residual degrees of freedom df obtained in step S50. E The critical T value of the selected significance level (in this embodiment, the significance level is two-sided α = 0.05) is determined by looking up the critical T value table of the T distribution. Then, the T value of each physical property parameter factor is compared with the critical T value. If the T value of a certain physical property parameter factor is greater than the critical T value, then the physical property parameter factor is a factor that has a significant impact on the experimental results; otherwise, it is not.

[0066] In this embodiment, a Pareto chart is plotted based on the results of the T-test analysis to visually display the material property parameters with significant influence. Specifically, the Pareto chart is plotted as follows: the T-values ​​obtained from the T-tests of each material property parameter are used as the vertical axis and arranged according to their absolute values. Based on the selected significance level α (5% for two-sided tests), a critical value for the T-value is given (2.26 in this embodiment). Factors with absolute values ​​exceeding the critical value are selected as significant influencing factors.

[0067] Figure 2 The Pareto plot of the standardized effect is plotted based on the results of the T-test in this embodiment. As can be seen from the plot, the coefficient of thermal expansion and Young's modulus of EMC (epoxy molding compound) are significant influencing factors on the magnitude of thermal stress in the packaging structure in this embodiment. They have a large impact and should be given special consideration in the design of the packaging structure and material selection to avoid packaging structure failure caused by these parameters.

[0068] S70. Based on the above analysis results, provide guidance for the optimized design of epoxy molding encapsulation structure.

[0069] In summary, the optimization design method of the epoxy plastic packaging structure provided by the embodiment of the present application uses the method of combining experimental design and statistical analysis, obtains certain theoretical support of the test conclusion on the theoretical level through simulation test and data analysis and processing, so that the optimization design of the epoxy plastic packaging structure can be theoretically supported and the design cost is reduced. The present application can screen out the factor that has the greatest impact on the packaging structure failure, so that corresponding measures can be proposed to reduce the packaging structure failure caused by the factor.

[0070] Although the present application has been shown and described with respect to particular embodiments, it will be understood by those skilled in the art that certain changes and modifications can be made hereto without departing from the spirit and scope of the application as defined by the claims and their equivalents.

Claims

1. An optimal design method of an epoxy plastic package structure, characterized in that, The method comprises the following steps: S10, screening physical property parameter factors which have influence on a certain performance of an epoxy plastic package structure according to existing experience, and determining high level values and low level values of each physical property parameter factor; S20, designing an orthogonal test table according to the selected physical property parameter factors; S30, establishing a finite element model according to the selected physical property parameter factors, and performing simulation test according to the orthogonal test table, and filling the obtained test results into the orthogonal test table to form a complete test data table; S40, processing all test data of the test data table, establishing a regression model, and calculating sample mean and fitting value; S50, performing F test analysis on the regression model, and judging whether there is a physical property parameter factor which has significant influence on the certain performance; If yes, the next step is performed, and if no, returning to step S10 to adjust the selected physical property parameter factors; S60, performing T test analysis on the regression model, and determining the physical property parameter factor which has significant influence on the certain performance; S70, guiding the optimization design of the epoxy plastic package structure according to the analysis results; The certain performance is thermal stress, warping level or wet stress. The physical property parameter factors include Young's modulus, thermal expansion coefficient and thickness of the epoxy plastic package material, and also include Young's modulus, thermal expansion coefficient and thickness of the substrate.

2. The method of claim 1, wherein the method further comprises: The step S60 further comprises drawing a Pareto chart according to the T test analysis results, so as to directly display the physical property parameter factor which has significant influence.

3. The method of claim 1 or 2, wherein the method is characterized by: In the step S30, for a certain simulation test, if there is corresponding reliability test data, the reliability test data is imported to improve the accuracy of the simulation model.

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