Method and apparatus for determining conditions of aging test

Abstract

The application provides a method and device for determining aging test conditions, the method comprising: providing a wafer to be tested, dividing the wafer to be tested into a plurality of test unit groups; providing a plurality of predicted aging conditions, placing the plurality of test unit groups in the plurality of predicted aging conditions respectively for aging test, the predicted aging conditions comprising a plurality of aging acceleration factors, controlling at least one of the plurality of aging acceleration factors as a variable to form the plurality of predicted aging conditions; determining a final aging time of the test unit group under each predicted aging condition; comparing the plurality of final aging times under the plurality of predicted aging conditions, determining a minimum aging time in the plurality of final aging times; and determining the corresponding predicted aging condition as a final aging test condition based on the minimum aging time. According to the method for determining aging test conditions, the final aging test condition is determined to be optimal, and the aging test time is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of semiconductor, in particular to a method and device for determining burn-in test conditions. BACKGROUND

[0002] Failure problems are inevitable in the development, production and use of chips. After the production of wafers is completed, the wafers will be tested to check the quality of the wafers. The tests mainly include a chip probe test (CP test) and a final test (FT). The wafers passing the CP test will be subjected to the FT, and the burn-in (BI) test will be performed in the FT. The purpose of the BI test is to provide a high-temperature, high-pressure and high-current environment for the wafer particles, so that the particles with poor quality can be damaged as soon as possible in the environment, and the stable and reliable particles are retained.

[0003] In the prior art, a fixed time is determined as the total time of the burn-in test through a large number of experimental results. In the burn-in test process, multiple batches of wafers need to be subjected to multiple batches of burn-in tests, and the test conditions in the burn-in test are single conditions, i.e., tests, or are set according to experience, so that a large amount of time is consumed for the multiple batches of burn-in tests. SUMMARY

[0004] The present application aims to provide a method for determining burn-in test conditions, which can determine optimal final burn-in test conditions and reduce the length of the burn-in test.

[0005] The method for determining burn-in test conditions according to an embodiment of the present application comprises: providing a wafer to be tested, dividing the wafer to be tested into multiple test unit groups; providing multiple predicted burn-in conditions, placing the multiple test unit groups in the multiple predicted burn-in conditions respectively for burn-in tests, the predicted burn-in conditions comprising multiple burn-in acceleration factors, and controlling at least one of the multiple burn-in acceleration factors to be a variable to form the multiple predicted burn-in conditions.

[0006] determining the final burn-in time of the test unit group under each of the predicted burn-in conditions; comparing the multiple final burn-in times under the multiple predicted burn-in conditions to determine the minimum burn-in time in the multiple final burn-in times; and determining the corresponding predicted burn-in condition as the final burn-in test condition based on the minimum burn-in time.

[0007] According to some embodiments of the present application, in the step of dividing the wafer to be tested into multiple test units, the wafer to be tested is divided into multiple wafer particles to form the multiple test unit groups, and each of the test unit groups comprises multiple wafer particles.

[0008] According to some embodiments of the present application, the predicted aging conditions include a first aging acceleration factor and a second aging acceleration factor, the first aging acceleration factors in the plurality of predicted aging conditions are the same and the second aging acceleration factors are different.

[0009] According to some embodiments of the present application, the first aging acceleration factor includes a test temperature, a test voltage pressure and a test humidity, and the second aging acceleration factor includes a test voltage and a test current.

[0010] According to some embodiments of the present application, in the step of determining the final aging time of the test unit group under each predicted aging condition, the step includes: dividing a test time into a plurality of time periods, obtaining a test result of the test unit after an aging experiment in each time period ends, the test result being pass or failure; determining a failure distribution model of the test unit at a current time according to the test result of the tested time period; determining a predicted aging time corresponding to the failure distribution model according to the failure distribution model at the current time; if the predicted aging time corresponding to the failure distribution model is not less than the current time, entering a next time period for aging test; if the predicted aging time corresponding to the failure distribution model is less than the current time, determining the predicted aging time corresponding to the failure distribution model as the final aging time.

[0011] According to some embodiments of the present application, the failure distribution model includes any one of the following models: a Weibull distribution model, a normal distribution model or a lognormal distribution model.

[0012] According to some embodiments of the present application, the step of determining the predicted aging time corresponding to the failure distribution model according to the failure distribution model at the current time includes: calculating a failure rate of the test unit at the current time according to parameters of the failure distribution model corresponding to the current time; and determining the current time as the predicted aging time when the failure rate at the current time is less than a preset failure rate.

[0013] According to some embodiments of the present application, the step of determining the predicted aging time corresponding to the failure distribution model according to the failure distribution model at the current time includes: calculating failure rates of the test unit at at least three times respectively according to parameters of the failure distribution models corresponding to the at least three times, the at least three times including the current time; fitting a failure distribution curve according to the failure rates corresponding to the at least three times, the horizontal axis of the failure distribution curve being time and the vertical axis being failure rate; determining a tangent line of the failure distribution curve; and determining a time corresponding to an intersection of the tangent line and the horizontal axis as the predicted aging time.

[0014] According to some embodiments of the present application, the determining the predicted aging time corresponding to the failure distribution model according to the current time comprises: calculating the failure rate of the test unit at each of at least three times according to the parameters of the failure distribution model corresponding to the at least three times, wherein the at least three times include the current time; fitting a failure distribution curve according to the failure rates corresponding to the at least three times, wherein the horizontal axis of the failure distribution curve is time and the vertical axis is failure rate; determining a tangent line of the failure distribution curve and the intersection point of the tangent line and the horizontal axis; determining the time T2 corresponding to the point on the failure distribution curve closest to the intersection point; determining the T2 as the predicted aging time, or multiplying the T2 by a preset coefficient to obtain the predicted aging time, wherein the preset coefficient is greater than 0.

[0015] The present application further provides a device for determining an aging test condition.

[0016] The device for determining an aging test condition according to an embodiment of the present application comprises: a division module configured to divide the wafer to be tested into a plurality of test unit groups; an aging test module configured to provide a plurality of predicted aging conditions, and place the plurality of test unit groups in the plurality of predicted aging conditions for aging test, wherein the predicted aging conditions comprise a plurality of aging acceleration factors, and at least one of the aging acceleration factors is controlled as a variable to form the plurality of predicted aging conditions.

[0017] A first determination module configured to determine the final aging time of the test unit group under each of the predicted aging conditions; a comparative analysis module configured to compare the final aging times under the plurality of predicted aging conditions, and determine the minimum aging time among the final aging times; and a second determination module configured to determine the predicted aging condition corresponding to the minimum aging time as the final aging test condition.

[0018] According to some embodiments of the present application, the division module is configured to divide the wafer to be tested into a plurality of wafer particles and form the plurality of test unit groups, and each of the test unit groups comprises a plurality of wafer particles.

[0019] According to some embodiments of the present application, the aging acceleration factors are test temperature, test pressure and test humidity, and the predicted aging conditions comprise at least two of the aging acceleration factors.

[0020] The present application further provides an electronic device comprising at least one processor and a memory, wherein the memory stores computer-executable instructions, and the at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the method of any of the above embodiments.

[0021] The application further provides a computer readable storage medium, characterized in that the computer readable storage medium stores computer execution instructions, and the computer execution instructions are used to implement the method of any of the above embodiments when executed by a processor.

[0022] The application further provides a computer program product, characterized in that the computer program product comprises a computer program, and the computer program is used to implement the method of any of the above embodiments when executed by a processor.

[0023] The method and device for determining aging test conditions according to the embodiments of the application can reduce the time consumed by the aging test, and avoid the problems of over-aging and under-aging by performing pre-aging tests on products under different predicted aging conditions, obtaining final aging times under the different predicted aging conditions, comparing the final aging times to determine the time of aging tests under different aging acceleration factors, and obtaining the predicted aging condition of the minimum aging time, and determining the predicted aging condition as the final aging test condition of the subsequent aging time. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 A flowchart of the method for determining aging test conditions according to the embodiments of the application;

[0025] Figure 2 A schematic diagram of the obtained failure distribution curve;

[0026] Figure 3 Another schematic diagram of the obtained failure distribution curve;

[0027] Figure 4 A structural schematic diagram of the device for determining aging test conditions according to the embodiments of the application;

[0028] Figure 5 A division schematic diagram of a sample wafer used in the method for determining aging test conditions according to the embodiments of the application.

[0029] REFERENCE NUMERALS:

[0030] 100: device for determining aging test conditions

[0031] 1: division module, 2: aging test module, 3: comparison and analysis module, 4: first determination module, 5: second determination module. DETAILED DESCRIPTION

[0032] The method for determining aging test conditions according to the application is further described in detail below in combination with the accompanying drawings and specific embodiments.

[0033] The method for determining aging test conditions according to the embodiments of the application is described below with reference to the accompanying drawings.

[0034] like Figure 1 As shown, the method for determining aging test conditions according to an embodiment of the present invention includes: providing a wafer to be tested and dividing the wafer to be tested into multiple test unit groups; providing multiple predicted aging conditions and placing the multiple test unit groups under the multiple predicted aging conditions for aging tests, wherein the predicted aging conditions include multiple aging acceleration factors, and controlling at least one of the multiple aging acceleration factors as a variable to form multiple predicted aging conditions; determining the final aging time of the test unit group under each predicted aging condition; comparing the multiple final aging times under the multiple predicted aging conditions and determining the minimum aging time among the multiple final aging times; and determining the corresponding predicted aging condition as the final aging test condition based on the minimum aging time.

[0035] Specifically, S1: Provide a wafer to be tested and divide the wafer to be tested into multiple test unit groups.

[0036] In some embodiments of the present invention, there may be multiple wafers to be tested, and the multiple wafers to be tested are divided into multiple test unit groups. Each test unit group may include multiple test units, wherein a test unit may be an entire wafer or a part of a wafer, so as to reduce the amount of sample and sample waste.

[0037] In other embodiments of the present invention, the wafer under test can be a single wafer. The relationship between the number of test samples and the confidence level of the failure rate is as follows: C = 1 - Rn, R = 1 - F, where C is the confidence level, F is the failure rate, n is the number of samples, and F * 1,000,000 yields the parts per million (PPM) failure rate, which is the number of failed samples out of one million samples. To achieve a confidence level of 0.95, R needs to reach 0.999 and F needs to reach 0.001, thus requiring 2999 test samples.

[0038] In order to solve the problem of sample capacity, in one embodiment of the present application, by dividing one wafer to be tested into a plurality of die particles and forming a plurality of test unit groups, each test unit group including a plurality of die particles, and then subdividing each die into a plurality of test units, the division rule of the test units can be divided by bank, and generally one die has 16 banks, so that n reaches 16*900, which fully meets the test sample size. Of course, 2, 3 or 4 banks can also be divided into one test unit, and the embodiments of the present application do not limit this. In this way, one test unit in each die particle is taken as the smallest test unit, which not only expands the sample capacity and reduces the waste of test samples, but also uses the same wafer as a sample for testing, which can also avoid the differences caused by different wafers as samples, and improve the accuracy of aging test.

[0039] As Figure 5 shown is a structural schematic diagram of dividing one wafer to be tested into a plurality of die particles, each test unit group including a plurality of die particles, and the area distribution of each test unit group can be randomly allocated, for example, the wafer particles of the test unit group can be divided as shown in Figure 5 , the wafer particles represented by the same letter can form one test unit group, that is, the wafer particles represented by letters C, D, E and F form four test unit groups, and the four test units are randomly distributed in the same wafer to be tested to improve the accuracy of the test. Of course, it is also possible that a plurality of test unit groups can be divided according to certain rules, for example, the wafer particles of each test unit are concentratedly distributed to facilitate the control of the predicted aging conditions of each test unit group.

[0040] S2: providing a plurality of predicted aging conditions, placing the plurality of test unit groups in the plurality of predicted aging conditions for aging test, the predicted aging conditions including a plurality of aging acceleration factors, and controlling at least one of the plurality of aging acceleration factors as a variable to form a plurality of predicted aging conditions.

[0041] The predicted aging condition is the test condition of the wafer during the predicted aging test. The pre-aging test can be performed before the product is subjected to the aging test, and the test conditions for the aging test are determined by the pre-aging test of the product, so as to obtain the aging test conditions with the shortest test time and the best test effect, and the aging test conditions obtained by the predicted aging test are used to test the product, so as to reduce the time of the aging test and improve the aging test effect and prevent over-aging.

[0042] The prediction aging condition can include a plurality of aging acceleration factors, which can be test temperature, test pressure, test humidity, test voltage, test current, etc. Each prediction aging condition can include a plurality of aging acceleration factors, and different aging acceleration factors can be selected for wafer aging test when performing aging time experiments. The prediction aging condition can be pre-set according to actual conditions, the parameters of the aging acceleration factors can be pre-set according to actual conditions, and the parameters of the aging acceleration factors in the plurality of prediction aging conditions are variables, that is, the parameters of the aging acceleration factors in the plurality of test aging conditions are different. The parameters of the aging acceleration factors in the plurality of prediction aging conditions can be set in an increasing or decreasing manner.

[0043] S3: determining the final aging time of the test unit group under each prediction aging condition.

[0044] The plurality of test unit groups are placed in a plurality of prediction aging conditions for aging test, and the final aging time of the product under different prediction aging conditions can be obtained. The effects of different prediction aging conditions on the aging test of the product are different. The effects of the aging acceleration factors on the aging state of the product can be obtained according to the final aging time obtained under different prediction aging conditions.

[0045] S4: comparing a plurality of final aging times under a plurality of prediction aging conditions to determine the minimum aging time in the plurality of final aging times.

[0046] The product is subjected to aging test under a plurality of prediction aging conditions, and a plurality of final aging times are obtained. The effects of the aging acceleration factors on the aging test of the product can be obtained according to the plurality of final aging times and the different aging acceleration factors under the plurality of prediction aging conditions. The minimum aging time in the plurality of final aging times is determined, that is, the minimum aging time under the plurality of prediction aging conditions is determined as the aging time of the product in the pre-aging test.

[0047] S5: determining the corresponding prediction aging condition as the final aging test condition based on the minimum aging time.

[0048] The prediction aging condition corresponding to the minimum aging time is the prediction aging condition with the shortest aging time in the pre-aging test of the product, that is, the aging test time is the shortest when the aging test is performed under the prediction aging condition. The prediction aging condition is determined as the final aging test condition. When the product is subjected to aging test, the product can be placed in the test condition for aging test to test the life of the product, thereby reducing the time spent in the aging test of the product and avoiding the problems of over-aging and under-aging.

[0049] The method for determining the aging test condition according to the embodiment of the present application can reduce the time consumed by the aging test, and avoid the problems of over-aging and under-aging.

[0050] Optionally, the predicted aging condition can include two aging acceleration factors or three aging acceleration factors, or the predicted aging condition can include more than three aging acceleration factors. Further, in the multiple predicted aging conditions, the parameter of one aging acceleration factor can be a constant, and the parameter values of other aging acceleration factors can be variables, or in the multiple predicted aging conditions, one aging acceleration factor can be a variable, and the parameter values of other aging acceleration factors can be constants, which can be selected according to actual conditions and experience summary.

[0051] In some embodiments of the present application, the predicted aging condition can include a first aging acceleration factor and a second aging acceleration factor, the first aging acceleration factors in the multiple aging test conditions are the same, and the second aging acceleration factors are different, and multiple test unit groups are placed in the multiple aging test conditions to perform aging tests, so that the aging time or PPM (million failure rate) performance of different test unit groups under different second aging acceleration factors can be obtained, the influence of the second aging acceleration factor on the aging test of the wafer to be tested can be obtained, and the parameter of the second aging acceleration factor with the minimum aging time can be determined, and the aging test under the condition of the parameter of the second aging acceleration factor and the first aging acceleration factor can be selected.

[0052] Optionally, the first aging acceleration factor can include a test temperature, a test pressure, and a test humidity, and the second aging acceleration factor can include a test voltage and a test current. In the method for determining the aging test condition, one or more of the test temperature, the test pressure, and the test humidity in the multiple predicted aging conditions can be set as a constant, and at least one of the test voltage and the test current can be set as a variable. In the test method of the embodiment, when the sample is tested, especially the same wafer to be tested, for the test area of one test unit group, the test voltage and the test current can be adjusted individually, and the aging acceleration factors such as the test temperature, the test pressure, and the test humidity are not easy to be set differently for each wafer particle or test area of the same wafer.

[0053] In some specific examples of the present application, the first aging acceleration factor can be test pressure V, the second aging acceleration factor can be test voltage U, the test pressure is the same in the plurality of predicted aging conditions, and the test voltage is different, for example, the plurality of test unit groups can include a first test unit group, a second test unit group, a third test unit group, and an Nth test unit group, the predicted aging conditions can be a first predicted aging condition, a second predicted aging condition, a third predicted aging condition, and an Nth predicted aging condition, the test pressure in the first predicted aging condition can be V1, and the test voltage can be U1, the test pressure in the second predicted aging condition can be V1, and the test voltage can be U2, the test pressure in the third predicted aging condition can be V1, and the test voltage can be U3, the test pressure in the Nth predicted aging condition can be V1, and the test voltage can be Un, the plurality of test unit groups are respectively placed in the first predicted aging condition, the second predicted aging condition, the third predicted aging condition, and the Nth predicted aging condition to perform aging tests, the final aging time of each group of test unit groups is determined and compared and analyzed to determine the influence of the test voltage on the aging test, and the predicted aging condition corresponding to the minimum aging time is determined as the final aging test condition to reduce the time length of the aging test.

[0054] However, it can be understood that tests can also be performed by setting different test temperatures, test pressures, and test humidities. In some other specific examples of the present application, the first aging acceleration factor can be test pressure V, the second aging acceleration factor can be test temperature T, the test pressure is the same in the plurality of predicted aging conditions, and the test temperature is different, for example, the plurality of test unit groups can include a first test unit group, a second test unit group, a third test unit group, and an Nth test unit group, the predicted aging conditions can be a first predicted aging condition, a second predicted aging condition, a third predicted aging condition, and an Nth predicted aging condition, the test pressure in the first predicted aging condition can be V1, and the test temperature can be T1, the test pressure in the second predicted aging condition can be V1, and the test temperature can be T2, the test pressure in the third predicted aging condition can be V1, and the test temperature can be T3, the test pressure in the Nth predicted aging condition can be V1, and the test temperature can be Tn, the plurality of test unit groups are respectively placed in the first predicted aging condition, the second predicted aging condition, the third predicted aging condition, and the Nth predicted aging condition to perform aging tests, the final aging time of each group of test unit groups is determined and compared and analyzed to determine the influence of the test temperature on the aging test, and the predicted aging condition corresponding to the minimum aging time is determined as the final aging test condition to reduce the time length of the aging test.

[0055] In some embodiments of the present application, the predicted aging conditions can further include a first aging acceleration factor, a second aging acceleration factor, and a third aging acceleration factor. The first aging acceleration factor can be the same in the plurality of predicted aging conditions, and the second and third aging acceleration factors can be different. For example, the test temperature can be the same, and the test voltage and test current can be different. Alternatively, the first and second aging acceleration factors can be the same, and the third aging acceleration factor can be different. For example, the test temperature and test humidity can be the same, and the test voltage can be different. Alternatively, the first, second, and third aging acceleration factors can all be variables, and the specific values of the first, second, and third aging acceleration factors can be selected according to actual conditions and experience.

[0056] In some embodiments of the present application, the step of determining the final aging time of the test unit group under each predicted aging condition can include:

[0057] The test time is divided into a plurality of time periods. After the aging experiment in each time period ends, the test result of the test unit is obtained. The test result is pass or fail.

[0058] The test time is the total duration of the aging experiment of the wafer. The test time is divided into a plurality of time periods. The size of each time period can be the same or different, and the present embodiment does not limit this. For example, the test time is 1 minute. The test time can be divided into 12 time periods, and the size of each time period is 5 seconds (s). Alternatively, the test time can be divided into 10 time periods, and the size of each time period is 6 s.

[0059] The wafer is subjected to aging treatment in each time period, and then the test result of each test unit is obtained. The test result of each test unit is pass or fail.

[0060] According to the test result of the tested time period, the failure distribution model of the test unit at the current time is determined. Specifically, the aging experiment is sequentially performed on each time period in time order, and the test result is obtained. The tested time period is relative to the current time. The current time is the end time of the last tested time period. The tested time period can include one or more time periods. For example, the test time is divided into 12 time periods. If the tested time period is the first 3 time periods, the current time is the end time of the third time period. If the tested time is 5 time periods, the current time is the end time of the fifth time period. Alternatively, the current time can be considered as a cumulative time. The initial value of the current time is 0. From the start of the aging experiment, the current time gradually accumulates and changes.

[0061] The failure distribution model is used for a schematic diagram of distribution of failure rate of the reaction test unit over time, and the failure distribution model can be expressed by a failure distribution function. The failure distribution model includes any one of the following models: Weibull distribution model, normal distribution model, or lognormal distribution model. Different failure distribution models are obtained at different times as time accumulates.

[0062] Taking the Weibull distribution model as an example, parameters of the Weibull distribution model are determined according to test results of a tested time period. The Weibull distribution model includes two forms of three parameters and two parameters, and the three-parameter Weibull distribution model can be converted into the two-parameter Weibull distribution model. In this embodiment, the three-parameter Weibull distribution model or the two-parameter Weibull distribution model can be used.

[0063] The parameters of the three-parameter Weibull distribution model include β, η, and γ. β is a shape parameter, the value of β is greater than 0, and β determines the shape of the distribution curve. η is a scale parameter, the value of η is greater than 0, and η plays a role in amplifying or reducing the scale of the horizontal coordinate. γ is a position parameter, the value of γ is greater than or equal to 0, and γ determines the starting position of the distribution curve. When the value of γ is 0, the three-parameter Weibull distribution model is converted into the two-parameter Weibull distribution model.

[0064] The failure distribution function of the two-parameter Weibull distribution model is shown in formula (1).

[0065]

[0066] The regression estimation method is used for parameter estimation, formula (1) is deformed, and formula (2) is obtained.

[0067]

[0068] Formula (3) is obtained by taking the natural logarithm of formula (2).

[0069]

[0070] Formula (4) is obtained by taking the natural logarithm of formula (3) again.

[0071] ln[-1n(1-F(t)]=βlnt-βlnη (4)

[0072] Let x=lnt and y=ln[-ln(1-F(t)], and the value of x and y can be obtained by bringing F(t)=1-R(t) into formula (4), where R(t) is a test passing rate of the test unit. The ratio of the number of test units with a test result of pass to the total number of test units is taken as R(t), and t is the current time.

[0073] After the x and y corresponding to each tested time period are calculated, the parameters β and η of the Weibull distribution model are obtained by the following formulas (5)-(7), wherein each time period corresponds to a set of x and y.

[0074]

[0075]

[0076]

[0077] wherein x is the x corresponding to the current time period, y is the y corresponding to the current time period, the current time period is the last tested time period, is the average value of the x corresponding to each tested time period, y is the average value of the y corresponding to each tested time period, and n is the number of test units.

[0078] After β and η are calculated, the parameters β and η are brought into formula (1) or formula (2) to obtain the failure distribution function F(t), and the failure distribution model is represented by the failure distribution function.

[0079] It can be understood that the failure distribution functions of different failure distribution models are different, and here only the Weibull distribution is taken as an example for illustration, and the calculation of other failure distribution functions is not listed one by one.

[0080] According to the failure distribution model of the current time, the predicted aging time corresponding to the failure distribution model is determined;

[0081] For example, the failure rate of the current time corresponding to the failure distribution model of the test unit can be obtained according to the parameters of the failure distribution model, and whether to end the aging experiment is determined according to the failure rate of the current time, and the time of ending the aging experiment is the final aging time. Or, according to the failure distribution model, the failure distribution curve corresponding to the failure distribution function is obtained, and the predicted aging time is determined according to the failure distribution curve.

[0082] Method one, according to the parameters of the failure distribution model corresponding to the current time, the failure rate of the test unit at the current time is calculated, and when the failure rate of the current time is less than the preset failure rate, the current time is determined as the predicted aging time.

[0083] Taking the Weibull distribution model as an example, the failure rate corresponding to the failure distribution model can be calculated by using formula (8), formula (9) or formula (10), and the failure rate corresponding to the failure distribution model is the failure rate of the current time.

[0084]

[0085]

[0086]

[0087] The δ in the formula (10) is a constant.

[0088] Optionally, the failure rate can also be PPM, and the failure rate calculated by the formula (8), (9) or (10) is multiplied by one million to obtain the PPM.

[0089] The failure rate corresponding to the failure distribution model is compared with the preset failure rate, if the failure rate corresponding to the failure distribution model is less than the preset failure rate, it is determined that the current time is the predicted aging time, and the aging test experiment is ended. If the failure rate corresponding to the failure distribution model is not less than (i.e. greater than or equal to) the preset failure rate, the aging test of the next time period is continued until the test time is ended.

[0090] In the second mode, the failure rates of the test unit at the respective times are calculated according to the parameters of the failure distribution models corresponding to the at least three times, and a failure distribution curve is fitted according to the failure rates corresponding to the at least three times, the horizontal axis of the failure distribution curve being time and the vertical axis being failure rate. A tangent line of the failure distribution curve is determined, and the time corresponding to the intersection of the tangent line and the X-axis is determined as the predicted aging time. The calculation of the failure rate can refer to the description of the first mode, which will not be repeated here.

[0091] Taking three time points as an example, the three times correspond to three time periods, the parameters of three failure distribution models are obtained from the data of the three time periods selected from the tested time periods, and then the failure rates of the three times are obtained according to the parameters of the failure distribution models. A failure distribution curve is fitted according to the three times and the failure rates of the three times, the horizontal axis of the failure distribution curve being time and the vertical axis being failure rate. At least 3 points (corresponding to three times) of data are required when the failure distribution curve is fitted, of course, the more data points taken, the more accurate the failure distribution curve fitted.

[0092] Similarly, a straight line is fitted using the data of the at least three times, the straight line being represented as y=kx+b, wherein k is the slope of the straight line, x is the time t, y is the failure rate corresponding to the time t, and k and b are constants. After the slope k is obtained, a point on the failure distribution curve with the slope k is found as a tangent point, and a tangent line is drawn through the tangent point, the tangent line having an intersection with the horizontal axis of the failure distribution curve.

[0093] Optionally, the data of the first three time periods after the start of the test time can be selected to fit the failure distribution curve and the straight line.

[0094] Figure 2As shown in a schematic view of the obtained failure distribution curve, a tangent line L of the failure distribution curve is determined, the tangent line L has an intersection point A with the horizontal axis, and the time corresponding to the intersection point A is taken as the predicted aging time in this embodiment, that is, T1 in the figure.

[0095] In mode three, the failure distribution curve is obtained by using the method of mode two, then a tangent line of the failure distribution curve is determined, and an intersection point of the tangent line with the horizontal axis is determined, and the time T2 corresponding to the point on the failure distribution curve closest to the intersection point is taken as the predicted aging time.

[0096] The determination of the tangent line of the failure distribution curve in this mode is the same as that in mode two, and will not be repeated here.

[0097] Figure 3 As shown in another schematic view of the obtained failure distribution curve, a tangent line L of the failure distribution curve is determined, the tangent line L has an intersection point A with the horizontal axis, and a point B on the failure distribution curve closest to the intersection point A is found, and the time corresponding to the point B is taken as the predicted aging time, that is, T2 in the figure.

[0098] In mode four, the difference between mode four and mode three is that after T2 is determined, T2 is multiplied by a preset coefficient to obtain the predicted aging time, the preset coefficient is greater than 0, and the preset coefficient is, for example, 2.

[0099] If the predicted aging time corresponding to the failure distribution model is not less than the current time, the aging test in the next time period is entered; if the predicted aging time corresponding to the failure distribution model is less than the current time, the predicted aging time corresponding to the failure distribution model is determined as the final aging time.

[0100] The corresponding predicted aging time is obtained for each time period, and the current time is compared with the corresponding predicted aging time. Among them, the predicted aging time obtained by different failure distribution models is also different, and compared with the fixed aging time in the prior art, the method of the embodiment can obtain the aging time matched with the product according to the actual difference of the product, and avoid the problems of over-aging or insufficient aging.

[0101] The application further provides a device for determining an aging test condition.

[0102] As shown in the figure, the device 100 for determining an aging test condition according to the embodiment of the application can comprise: Figure 4 A division module 1 is configured to divide the wafer to be tested into a plurality of test unit groups.

[0103]

[0104] ​aging test module 2, configured to provide a plurality of predicted aging conditions, and to place each of the test unit groups in a plurality of the predicted aging conditions for aging test, wherein the predicted aging conditions comprise a plurality of aging acceleration factors, and at least one of the aging acceleration factors is controlled as a variable to form the plurality of the predicted aging conditions;

[0105] first determination module 4, configured to determine a final aging time of the test unit group in each of the predicted aging conditions;

[0106] comparison and analysis module 3, configured to compare a plurality of the final aging times in the plurality of the predicted aging conditions, and to determine a minimum aging time in the plurality of the final aging times;

[0107] second determination module 5, configured to determine, based on the minimum aging time, that the corresponding predicted aging condition is a final aging test condition.

[0108] In some embodiments of the present application, the division module 1 is configured to divide the one wafer under test into a plurality of wafer particles and form the plurality of test unit groups, and each of the test unit groups comprises a plurality of the wafer particles.

[0109] Optionally, the aging acceleration factors can be test temperature, test pressure and test humidity, and the predicted aging conditions comprise at least two of the aging acceleration factors.

[0110] The present application further provides an electronic device, comprising at least one processor and a memory; the memory stores computer-executable instructions; and the at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the method of any one of the above embodiments.

[0111] The present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are executed by a processor to implement the method of any one of the above embodiments.

[0112] The present application further provides a computer program product, comprising a computer program, wherein the computer program is executed by a processor to implement the method of any one of the above embodiments.

[0113] The above description is only preferred embodiments of the present application, and it should be pointed out that, for those skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present application.

Claims

1. A method for determining an aging test condition, characterized by, The method comprises the following steps: providing a wafer to be tested, and dividing the wafer to be tested into a plurality of test unit groups; providing a plurality of predicted aging conditions, and placing the plurality of test unit groups in the plurality of predicted aging conditions respectively for aging test, wherein the plurality of predicted aging conditions comprise a plurality of aging acceleration factors, and at least one of the plurality of aging acceleration factors is controlled as a variable to form the plurality of predicted aging conditions; determining a final aging time of the test unit group under each of the predicted aging conditions; comparing the final aging times under the plurality of predicted aging conditions to determine a minimum aging time among the plurality of final aging times; determining, based on the minimum aging time, that a corresponding predicted aging condition is a final aging test condition.

2. The method of determining the aging test conditions according to claim 1, characterized in that, In the step of dividing the wafer to be tested into a plurality of test units, the wafer to be tested is divided into a plurality of wafer particles to form the plurality of test unit groups, and each of the test unit groups comprises a plurality of wafer particles.

3. The method of determining the conditions of an aging test according to claim 1, characterized by, The predicted aging conditions comprise a first aging acceleration factor and a second aging acceleration factor, and the first aging acceleration factors in the plurality of predicted aging conditions are the same and the second aging acceleration factors are different.

4. The method of determining the aging test conditions according to claim 3, characterized in that, The first aging acceleration factors comprise a test temperature, a test voltage, and a test current, and the second aging acceleration factors comprise a test voltage and a test current.

5. The method of determining the conditions of an aging test according to claim 1, characterized by, In the step of determining the final aging time of the test unit group under each of the predicted aging conditions, the method comprises the following steps: dividing a test time into a plurality of time periods, obtaining a test result of the test unit after the aging test in each time period, and the test result is pass or failure; determining, according to the test result of the tested time period, a failure distribution model of the test unit at a current time; determining, according to the failure distribution model at the current time, a predicted aging time corresponding to the failure distribution model; if the predicted aging time corresponding to the failure distribution model is not less than the current time, proceeding to the next time period for aging test; if the predicted aging time corresponding to the failure distribution model is less than the current time, determining that the predicted aging time corresponding to the failure distribution model is the final aging time.

6. The method of determining the aging test conditions according to claim 5, wherein The failure distribution model comprises any one of the following models: a Weibull distribution model, a normal distribution model, or a lognormal distribution model.

7. The method of determining the conditions of an aging test according to claim 6, wherein The step of determining, according to the failure distribution model at the current time, the predicted aging time corresponding to the failure distribution model comprises the following steps: calculating, according to parameters of the failure distribution model corresponding to the current time, a failure rate of the test unit at the current time; when the failure rate at the current time is less than a preset failure rate, determining that the current time is the predicted aging time.

8. The method of determining the aging test conditions according to claim 6, wherein The step of determining, according to the failure distribution model at the current time, the predicted aging time corresponding to the failure distribution model comprises the following steps: calculating, according to parameters of the failure distribution model corresponding to at least three times, failure rates of the test unit at the at least three times, wherein the at least three times comprise the current time; fitting a failure distribution curve according to the failure rates corresponding to the at least three times, wherein an abscissa axis of the failure distribution curve is time, and an ordinate axis of the failure distribution curve is failure rate; and determining a tangent line of the failure distribution curve; determining a time corresponding to an intersection of the tangent line and the horizontal axis as the predicted aging time.

9. The method of determining the conditions of an aging test according to claim 6, wherein The method according to any one of claims 1 to 9, wherein the determining of the predicted aging time corresponding to the failure distribution model according to the current time comprises: calculating failure rates of the test unit at respective times according to parameters of the failure distribution model corresponding to at least three times, the at least three times including the current time; fitting a failure distribution curve according to the failure rates corresponding to the at least three times, the horizontal axis of the failure distribution curve being time and the vertical axis being failure rate; determining a tangent line of the failure distribution curve and an intersection of the tangent line and the horizontal axis; determining a time T2 corresponding to a point on the failure distribution curve closest to the intersection; determining the T2 as the predicted aging time, or multiplying the T2 by a preset coefficient to obtain the predicted aging time, the preset coefficient being greater than 0.

10. An apparatus for determining aging test conditions, characterized in that, The method according to any one of claims 1 to 9, comprising: a dividing module configured to divide a wafer to be tested into a plurality of test unit groups; an aging test module configured to provide a plurality of predicted aging conditions, place the plurality of test unit groups in the plurality of predicted aging conditions respectively for aging test, the predicted aging conditions including a plurality of aging acceleration factors, and control at least one of the plurality of aging acceleration factors to be a variable to form the plurality of predicted aging conditions; a first determining module configured to determine a final aging time of the test unit group in each of the predicted aging conditions; a comparative analysis module configured to compare a plurality of final aging times in the plurality of predicted aging conditions and determine a minimum aging time in the plurality of final aging times; a second determining module configured to determine, based on the minimum aging time, that a corresponding one of the predicted aging conditions is a final aging test condition.

11. The device for determining the aging test conditions according to claim 10, characterized in that, The dividing module divides one of the wafers to be tested into a plurality of wafer particles and forms the plurality of test unit groups, each of the test unit groups including a plurality of the wafer particles.

12. The device for determining the aging test conditions according to claim 10, characterized in that, The aging acceleration factors are test temperature, test pressure and test humidity, and the predicted aging conditions include at least two of the aging acceleration factors.

13. An electronic device, comprising: The method according to any one of claims 1 to 9, comprising: at least one processor and a memory; the memory storing computer-executable instructions; the at least one processor executing the computer-executable instructions stored in the memory, so that the at least one processor executes the method according to any one of claims 1 to 9.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are executed by a processor to implement the method according to any one of claims 1 to 9.

15. A computer program product comprising a computer program, characterized in that, The computer program is executed by a processor to implement the method according to any one of claims 1 to 9.

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