Wafer high-temperature needle insertion precision compensation method and device and probe station
By constructing a needle-pinning deviation prediction model, using parameters such as position area, movement platform speed and wafer chuck temperature to compensate for needle-pinning deviation in real time, solving the problem of decreasing wafer needle-pinning accuracy in high-temperature environments, and realizing accurate testing of high-temperature needle-pinning.
Patent Information
- Application Number
- CN202510706249.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-29
- Publication Date
- 2025-08-12
AI Technical Summary
In high temperature environments, the accuracy of wafer needle pins is affected by the thermal expansion of the material, wear of mechanical components and changes in the performance of electronic components, resulting in a decrease in the test accuracy.
A needle-pin deviation prediction model was constructed, and by obtaining position area variables, movement platform speed, needle-pin number and wafer chuck temperature, the least squares method fit coefficients, and real-time calculation and compensation for needle-pin position deviation.
The accuracy of wafer high-temperature needle insertion is improved and accurate needle insertion is achieved in high-temperature environments.
Smart Images
Figure CN120468628A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of semiconductor technology, and in particular to a method and device for compensating wafer high-temperature needle insertion accuracy, and a probe station. Background Art
[0002] Testing is an important part of the semiconductor manufacturing process. By testing and screening out unqualified products, the product qualification rate can be ensured. High-temperature wafer needle testing is a test operation on the wafer, which is generally performed on a probe station. The probe station has a motion platform and a needle card. The motion platform is used to drive the wafer chuck to move to adjust the position of the wafer chuck. The wafer chuck is used to fix the wafer. During the high-temperature needle testing of the wafer, the motion platform drives the wafer on the wafer chuck to a preset position, and then the needle card on the probe station punctures the wafer on the wafer chuck. The needle card contacts the pad (pressure welding point) of the grain on the wafer to transmit electrical signals. During the wafer needle testing process, in a high-temperature environment, the needle accuracy will be affected due to the thermal expansion of the material, the wear of mechanical parts and the performance changes of electronic components. Summary of the Invention
[0003] In view of this, the present invention provides a method, device and probe station for compensating wafer high-temperature needle insertion accuracy. The main technical problem to be solved is: how to improve the needle insertion accuracy of wafers during high-temperature testing.
[0004] To achieve the above objectives, the present invention mainly provides the following technical solutions: An embodiment of the present invention provides a wafer high-temperature needle insertion accuracy compensation method, which includes the steps of constructing a needle insertion deviation prediction model and predicting the needle insertion deviation and compensating the position of the needle insertion deviation using the needle insertion deviation prediction model;
[0005] The acupuncture deviation prediction model constructed in the step of constructing the acupuncture deviation prediction model is: ;
[0006] Y is the predicted needle position deviation, X1 is the position area variable, X2 is the motion platform speed, X3 is the number of needles stuck, and X4 is the wafer chuck temperature; β0, β1, β2, β3, and β4 are all coefficients;
[0007] The step of predicting the acupuncture deviation and compensating the position of the acupuncture deviation using the acupuncture deviation prediction model includes: Step S21: Obtaining the position area variable X1, the motion platform speed X2, the number of needles inserted X3 and the wafer chuck temperature X4 during wafer needle insertion;
[0008] Step S22: Based on the position region variable X1, the motion platform speed X2, the number of needle clamps X3 and the wafer chuck temperature X4 obtained in step S21, the needle position deviation Y is calculated using the needle deviation prediction model;
[0009] Step S23: performing position compensation for the high-temperature needle insertion of the wafer according to the predicted needle insertion position deviation Y.
[0010] In some embodiments, the step of constructing a needle insertion deviation prediction model includes: Step S11: Acquire N sets of needle-puncture sample data, each set of needle-puncture sample data including position region variables, motion platform speed, needle number, wafer chuck temperature, and corresponding actual needle-puncture position deviation during needle-puncture; N is a positive integer greater than or equal to 2;
[0011] Step S12: Establish a loss function L; wherein the loss function L is:
[0012] Among them, Y i is the actual acupuncture position deviation during the i-th acupuncture, X 1i is the location variable of the i-th acupuncture, X 2i is the speed of the motion platform during the i-th acupuncture, X 3i is the number of needles stuck during the i-th acupuncture session, X 4i is the wafer chuck temperature during the i-th needle insertion;
[0013] Step S13: Calculate coefficients β0, β1, β2, β3, and β4 by minimizing the loss function;
[0014] Step S14: constructing the acupuncture deviation prediction model; .
[0015] In some embodiments, in step S13, the coefficients β0, β1, β2, β3, and β4 are calculated by minimizing the loss function, specifically:
[0016] By taking the partial derivatives of the loss function L with respect to each coefficient and setting them to zero, we can obtain the solution of the least squares method:
[0017] X is a data matrix containing all input parameter variables, each row represents a sample, and the columns are different input variables. X also includes a column of constant terms 1 as β0;
[0018] is the actual needle deviation vector;
[0019] β is the coefficient vector [β0, β1, β2, β3, β4].
[0020] In some embodiments, during the high-temperature needle penetration test on the wafer, new needle penetration sample data is collected, and the coefficients β0, β1, β2, β3, and β4 of the needle penetration deviation prediction model are updated through a recursive algorithm.
[0021] The present invention also provides a wafer high-temperature needle-piercing accuracy compensation device, which includes:
[0022] A model building module is used to build a needle deviation prediction model;
[0023] The parameter acquisition module is used to obtain the position area variable X1, the motion platform speed X2, the number of needles X3 and the wafer chuck temperature X4 when the wafer is needled;
[0024] A prediction module is used to obtain the position area variable X1, the motion platform speed X2, the number of needle clamps X3 and the wafer chuck temperature X4, and use the needle clamping deviation prediction model to calculate the predicted needle clamping position deviation Y;
[0025] The compensation module is used to perform position compensation for the high-temperature needle insertion of the wafer according to the predicted needle insertion position deviation Y.
[0026] The present invention also provides a probe station, which uses any one of the above-mentioned wafer high-temperature needle insertion accuracy compensation methods to perform position compensation for high-temperature needle insertion of a wafer.
[0027] By means of the above technical solution, the wafer high temperature needle insertion accuracy compensation method, device and probe station of the present invention have at least the following beneficial effects:
[0028] Compared with the traditional fixed data compensation algorithm, the present invention incorporates parameters such as different position area variables X1, motion platform speed X2, needle card needle number X3 and wafer chuck temperature X4, which can compensate for needle marks in real time and accurately, thereby improving the high-temperature needle insertion accuracy of the wafer.
[0029] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and implement it according to the contents of the specification, the following is a detailed description of the preferred embodiments of the present invention with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS
[0030] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.
[0031] Figure 1 This is a flow chart of a method for compensating wafer high-temperature needle insertion accuracy provided by one embodiment of the present invention. DETAILED DESCRIPTION
[0032] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.
[0033] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indications will also change accordingly.
[0034] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features specified as "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between the various embodiments can be combined with each other, but this must be based on the fact that ordinary technicians in this field can implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.
[0035] like Figure 1 As shown, an embodiment of the present invention provides a wafer high-temperature needle insertion accuracy compensation method, which includes the steps of constructing a needle insertion deviation prediction model and predicting the needle insertion deviation and compensating the position using the needle insertion deviation prediction model.
[0036] The acupuncture deviation prediction model constructed in the step of constructing the acupuncture deviation prediction model is: .
[0037] Where Y is the predicted needle insertion position deviation; X1 is the positional variable, which is the coordinates (x, y) of the probe insertion point on the needle card. These coordinates (x, y) are determined based on the positioning of the motion platform and the wafer image. X2 is the motion platform speed, which drives the wafer chuck; X3 is the number of needles inserted; X4 is the wafer chuck temperature, which secures the wafer. β0, β1, β2, β3, and β4 are coefficients.
[0038] The steps of predicting the acupuncture deviation and compensating the position of the acupuncture deviation using the acupuncture deviation prediction model include:
[0039] Step S21: Obtain the position area variable X1, the motion platform speed X2, the number of needles X3 and the wafer chuck temperature X4 when the wafer is needled.
[0040] Step S22: Based on the position area variable X1, motion platform speed X2, needle number X3 and wafer chuck temperature X4 obtained in step S21, the needle position deviation Y is predicted by calculating using the needle deviation prediction model mentioned above.
[0041] Step S23: Position compensation is performed on the wafer high-temperature needle insertion according to the predicted needle insertion position deviation Y. In actual operation, the predicted deviation Y can be calculated based on the real-time measured parameter variables X1, X2, X3, and X4, and dynamic position compensation is performed through the control system.
[0042] In the above example, compared with the traditional fixed data compensation algorithm, the present invention incorporates parameters such as different position area variables X1, motion platform speed X2, needle card needle number X3 and wafer chuck temperature X4, which can compensate for needle marks in real time and accurately, thereby improving the high-temperature needle insertion accuracy of the wafer.
[0043] In some embodiments, the step of constructing the acupuncture deviation prediction model includes:
[0044] Step S11: Acquire N sets of needle insertion sample data; N is a positive integer greater than or equal to 2. Each set of needle insertion sample data includes the position region variable, motion platform speed, number of needles engaged, and wafer chuck temperature during needle insertion. Each set of needle insertion sample data also includes the actual needle insertion position deviation under the selected position region variable, motion platform speed, number of needles engaged, and wafer chuck temperature parameters.
[0045] Step S12: Establish a loss function L. In order to solve the coefficients β0, β1, β2, β3 and β4 of the acupuncture deviation prediction model, the least squares method can be used to fit the difference between the actual acupuncture position deviation and the predicted value. The loss function L is:
[0046] Among them, Y i is the actual acupuncture position deviation during the i-th acupuncture, X 1i is the location variable of the i-th acupuncture, X 2i is the speed of the motion platform during the i-th acupuncture, X 3i is the number of needles stuck during the i-th acupuncture session, X 4i is the wafer chuck temperature during the i-th needle insertion.
[0047] Step S13: Calculate coefficients β0, β1, β2, β3, and β4 by minimizing the loss function;
[0048] Step S14: constructing the acupuncture deviation prediction model; .
[0049] The above steps S11 to S14 can be combined to construct the aforementioned acupuncture deviation prediction model.
[0050] In some embodiments, the coefficients β0, β1, β2, β3, and β4 are calculated in step S13 by minimizing the loss function, specifically:
[0051] By taking the partial derivatives of the loss function L with respect to each coefficient and setting them to zero, we can obtain the solution of the least squares method:
[0052] X is a data matrix containing all input parameter variables X1, X2, X3, and X4. Each row of the data matrix represents a sample, and each column is a different input variable. X also includes a column of constant terms 1 as β0. is the actual needle deviation vector. β is the coefficient vector [β0, β1, β2, β3, β4].
[0053] In the above example, by taking the partial derivatives of the loss function with respect to each coefficient and setting them to zero, we can obtain the solution of the least squares method and the values of the coefficients β0, β1, β2, β3, and β4.
[0054] In some embodiments, during the high-temperature needle penetration test on the wafer, new needle penetration sample data can be continuously collected, and the coefficients β0, β1, β2, β3 and β4 of the needle penetration deviation prediction model can be updated through a recursive algorithm to achieve the update of the model.
[0055] In the above example, in actual applications, the wafer chuck temperature X4 and other input parameter variables X1, X2, and X3 may change in real time. Therefore, the system needs to regularly monitor the input parameter variables through temperature sensors, position sensors, etc., and adjust the model coefficients β0, β1, β2, β3, and β4 of the needle deviation prediction model in real time. In this case, recursive least squares or weighted least squares can be used to enable the needle deviation prediction model to be quickly updated when new data arrives, so that it can adapt to the new operating environment.
[0056] In some embodiments, the present invention also provides a wafer high-temperature needle precision compensation device, which includes a model building module, a parameter acquisition module, a prediction module and a compensation module. The model building module is used to construct a needle deviation prediction model. The parameter acquisition module is used to obtain the position area variable X1, the motion platform speed X2, the number of needles X3 and the wafer chuck temperature X4 when the wafer is needled. The prediction module is used to obtain the position area variable X1, the motion platform speed X2, the number of needles X3 and the wafer chuck temperature X4, and calculate the predicted needle position deviation Y using the needle deviation prediction model. The compensation module is used to perform position compensation for the high-temperature needle of the wafer according to the predicted needle position deviation Y.
[0057] In some embodiments, the present invention further provides a probe station that uses any one of the above-described wafer high-temperature needle insertion accuracy compensation methods to perform position compensation for high-temperature needle insertion on a wafer.
[0058] Among them, when the wafer is subjected to a high-temperature needle test, the needle test can be performed after the wafer on the probe station is heated to the target temperature and preheating time. With the assistance of the mechanism, the actual needle offset data can be obtained, and the variables such as the position area variable X1, the motion platform speed X2, the number of needles X3 and the wafer chuck temperature X4 during the needle test are recorded at the same time. The needle position area variable X1, the motion platform speed X2, the number of needles X3 and the wafer chuck temperature X4 are used as input parameters, and the final needle coordinates are calculated by the algorithm to achieve high-precision high-temperature needle test. The algorithm of the present invention takes into account the position, speed, number of needles and Chuck temperature conditions, and adjusts and optimizes the needle path so that the accuracy in a high-temperature environment is kept within a reasonable range.
[0059] The present invention uses a simple mechanism to calculate needle mark offset data based on the needle mark conditions of multiple high-temperature needle insertions under the same variables. This needle mark offset data is used as an input parameter in the algorithm to obtain the final needle insertion coordinates, achieving precise needle insertion accuracy. The same steps can be used for testing and compensation at different temperatures. The present invention solves the problem of high-temperature needle insertion offset using a low-cost, simple mechanism-coordinated algorithm. Furthermore, the algorithm is based on the traditional least-squares fitting algorithm and incorporates variables such as different position areas, motion platform speed, needle card number, and machine chuck temperature, thereby improving high-temperature needle insertion accuracy.
[0060] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. All equivalent structural transformations made by using the contents of the present invention description and drawings under the inventive concept of the present invention, or direct / indirect application in other related technical fields are included in the patent protection scope of the present invention.
Claims
1. A wafer high temperature needle precision compensation method, characterized in that: The method comprises the steps of constructing a needle puncture deviation prediction model and predicting and compensating the needle puncture deviation using the needle puncture deviation prediction model; The acupuncture deviation prediction model constructed in the step of constructing the acupuncture deviation prediction model is: ； Y is the predicted needle position deviation, X1 is the position area variable, X2 is the motion platform speed, X3 is the number of needles stuck, and X4 is the wafer chuck temperature; β0, β1, β2, β3, and β4 are all coefficients; The step of predicting the acupuncture deviation and compensating the position of the acupuncture deviation using the acupuncture deviation prediction model includes: Step S21: Obtaining the position area variable X1, the motion platform speed X2, the number of needles inserted X3 and the wafer chuck temperature X4 during wafer needle insertion; Step S22: Based on the position region variable X1, the motion platform speed X2, the number of needle clamps X3 and the wafer chuck temperature X4 obtained in step S21, the needle position deviation Y is calculated using the needle deviation prediction model; Step S23: performing position compensation for the high-temperature needle insertion of the wafer according to the predicted needle insertion position deviation Y.
2. The wafer high temperature needle insertion accuracy compensation method according to claim 1, characterized in that: The step of constructing the acupuncture deviation prediction model includes: Step S11: Acquire N sets of needle-puncture sample data, each set of needle-puncture sample data including position region variables, motion platform speed, needle number, wafer chuck temperature, and corresponding actual needle-puncture position deviation during needle-puncture; N is a positive integer greater than or equal to 2; Step S12: Establish a loss function L; wherein the loss function L is: Among them, Y i is the actual acupuncture position deviation during the i-th acupuncture, X 1i is the location variable of the i-th acupuncture, X 2i is the speed of the motion platform during the i-th acupuncture, X 3i is the number of needles stuck during the i-th acupuncture session, X 4i is the wafer chuck temperature during the i-th needle insertion; Step S13: Calculate coefficients β0, β1, β2, β3, and β4 by minimizing the loss function; Step S14: constructing the acupuncture deviation prediction model; 。 3. The wafer high temperature needle insertion accuracy compensation method according to claim 2, characterized in that: In step S13, the coefficients β0, β1, β2, β3 and β4 are calculated by minimizing the loss function, specifically: By taking the partial derivatives of the loss function L with respect to each coefficient and setting them to zero, we can obtain the solution of the least squares method: X is a data matrix containing all input parameter variables, each row represents a sample, and the columns are different input variables. X also includes a column of constant terms 1 as β0; is the actual needle deviation vector; β is the coefficient vector [β0, β1, β2, β3, β4].
4. The wafer high temperature needle insertion accuracy compensation method according to claim 2 or 3, characterized in that: During the high-temperature needle penetration test on the wafer, new needle penetration sample data is collected, and the coefficients β0, β1, β2, β3 and β4 of the needle penetration deviation prediction model are updated through a recursive algorithm.
5. A wafer high temperature needle precision compensation device, characterized in that: include: A model building module is used to build a needle deviation prediction model; The parameter acquisition module is used to obtain the position area variable X1, the motion platform speed X2, the number of needles X3 and the wafer chuck temperature X4 when the wafer is needled; A prediction module is used to obtain the position area variable X1, the motion platform speed X2, the number of needle clamps X3 and the wafer chuck temperature X4, and use the needle clamping deviation prediction model to calculate the predicted needle clamping position deviation Y; The compensation module is used to perform position compensation for the high-temperature needle insertion of the wafer according to the predicted needle insertion position deviation Y.
6. A probe station, characterized in that The probe station uses the wafer high-temperature needle insertion accuracy compensation method according to any one of claims 1 to 4 to perform position compensation for the high-temperature needle insertion of the wafer.