Electrical data analysis methods, apparatus, wafer-level testing equipment, and storage media

Abstract

This application relates to an electrical data analysis method, apparatus, wafer-level testing equipment, and storage medium. The method includes: acquiring electrical test data of a test target; the data attributes of the electrical test data include structurally relevant attributes and test-related attributes of the test target; determining whether the electrical test data of the test target is faulty based on the structurally relevant attributes and a first judgment criterion, thereby identifying electrical failure data; classifying the electrical failure data according to the structurally relevant attributes, test-related attributes, and a second judgment criterion, thereby determining the failure mode corresponding to the electrical failure data; and determining the root cause of the test problem corresponding to the failure mode of the electrical failure data based on a preset relationship between failure modes and test problem classification. This method can improve testing efficiency.

Description

Technical Field

[0001] This application relates to the field of electrical testing technology, and in particular to an electrical data analysis method, apparatus, wafer-level testing equipment, and storage medium. Background Technology

[0002] In the field of semiconductor electrical testing, abnormal test data is a common occurrence. Besides anomalies inherent in the test target itself, various factors such as the stability of the testing equipment, wear and tear on the test probe cards, and the limited applicability of the testing algorithms can also lead to test errors and thus problematic data points. If these problematic data points are processed together with valid data points, it may affect the conclusions drawn from electrical data analysis, even leading to contradictory conclusions, thereby impacting process adjustments and potentially causing economic losses.

[0003] In related technologies, electrical test data only contains the structural and characteristic attributes of the test target itself. Even if a test problem occurs, it is impossible to verify the validity of the test data, let alone determine which part of the test went wrong, which is not conducive to the subsequent improvement of similar problems. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, device, and storage medium capable of electrical data analysis to address the aforementioned technical problems.

[0005] In a first aspect, this application provides an electrical data analysis method, the method comprising:

[0006] Acquire electrical test data of the test target; the data attributes of the electrical test data include structural related attributes and test related attributes;

[0007] Based on the structural related attributes of the electrical test data and the first judgment criterion, it is determined whether the electrical test data of the test target is invalid, so as to identify the electrical failure data;

[0008] Based on the structural related attributes, test related attributes, and second judgment criteria of the electrical test data, the electrical failure data is classified to determine the failure mode corresponding to the electrical failure data.

[0009] Based on the preset relationship between failure modes and test problem classification, the root causes of test problems corresponding to the failure modes of the electrical failure data are determined.

[0010] In some embodiments, the test-related attributes include one or more of the following: test structure type, needle insertion order, probe card, test algorithm, and SMU.

[0011] In some embodiments, determining whether the electrical test data of the test target is faulty based on the structurally relevant attributes of the electrical test data and a first judgment criterion, to identify electrical failure data, includes:

[0012] Determine multiple test items corresponding to the electrical test data of the test target;

[0013] Obtain the standard data range of several structure-related attribute values ​​corresponding to each of the test items;

[0014] The electrical test data are compared and analyzed with the standard data range of the corresponding structural attribute values ​​according to the test items, and the electrical failure data are determined based on the analysis results.

[0015] In some embodiments, the step of classifying the electrical failure data according to the structure-related attributes, test-related attributes, and a second judgment criterion of the electrical test data to determine the failure mode corresponding to the electrical failure data includes:

[0016] Based on the structural and test-related attributes of the electrical test data of the test target, the test data failure rate under each test parameter in the test-related attributes of the electrical failure data is determined.

[0017] The test failure rate corresponding to the test parameters of the electrical failure data is compared with the preset failure standard, and the failure mode corresponding to the electrical failure data is determined based on the comparison result.

[0018] In some embodiments, determining the test data failure rate under each test parameter in the test-related attributes of the electrical failure data based on the structure-related attributes and test-related attributes of the electrical test data of the test target includes:

[0019] Determine multiple test parameters corresponding to the test-related attributes of the electrical failure data;

[0020] For each test parameter, the number of test items for both effective and ineffective electrical data are indexed in the electrical test data of the test target.

[0021] Based on the number of test items in the electrical effective data and the electrical failure data, calculate the test data failure rate under the test parameters;

[0022] Repeat the above steps to obtain the test data failure rate under each test parameter in the test-related attributes of the electrical failure data.

[0023] In some embodiments, comparing the test data failure rate corresponding to the test parameters of the electrical failure data with a preset failure standard, and determining the failure mode corresponding to the electrical failure data based on the comparison results includes:

[0024] When the failure rate of test data corresponding to the same parameter type under the same test parameters is greater than or equal to the first preset threshold, the electrical failure data is determined to be the first type of test failure mode, and the first type of test failure mode is the failure mode corresponding to the parameter type.

[0025] When the failure rate of test data corresponding to all parameter types of the same test parameter is greater than or equal to the second preset threshold and less than the first preset threshold, the second type of test failure mode of the electrical failure data is determined, and the second type of test failure mode is the failure mode corresponding to the test parameter.

[0026] In some embodiments, after classifying the electrical failure data according to the structure-related attributes, test-related attributes, and a second judgment criterion of the electrical test data to determine the failure mode corresponding to the electrical failure data, the method further includes:

[0027] The electrical failure data under different failure modes are labeled;

[0028] The electrical failure data after marking is filtered, and the electrical performance of the test target is analyzed based on the filtered electrical test data.

[0029] Secondly, this application also provides an electrical data analysis device, the device comprising:

[0030] An electrical data acquisition module is used to acquire electrical test data of the test target; the data attributes of the electrical test data include structural related attributes and test related attributes;

[0031] The failure data acquisition module is used to determine whether the electrical test data of the test target is failed based on the structural related attributes of the electrical test data and the first judgment criterion, so as to determine the electrical failure data.

[0032] The failure mode determination module is used to classify the electrical failure data according to the structure-related attributes, test-related attributes and second judgment criteria of the electrical test data, so as to determine the failure mode corresponding to the electrical failure data.

[0033] The root cause determination module is used to determine the root cause of the test problem corresponding to the failure mode of the electrical failure data based on a preset relationship between failure modes and test problem classification.

[0034] Thirdly, this application also provides a wafer-level testing device. The wafer-level testing device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method described above.

[0035] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described above.

[0036] The aforementioned electrical data analysis method, apparatus, wafer-level testing equipment, and storage medium determine whether the electrical test data of the test target is invalid based on the structural correlation attributes of the electrical test data and a first judgment criterion, thereby identifying electrically invalid data. They can also judge and filter abnormal test data based on the structural correlation attributes of the electrical test data, thus identifying the validity of the data when test errors occur in the test analysis process.

[0037] By classifying the electrical failure data according to the structural attributes, test-related attributes, and a second judgment criterion of the test target, the failure modes corresponding to the electrical failure data are determined. Based on the preset relationship between failure modes and test problem classification, the root causes of the test problems corresponding to the failure modes of the electrical failure data are determined. Thus, based on the determination of electrical failure data, and combined with the test-related attributes of the test target, the failure modes and corresponding root causes of test problems are further determined. Specifically, it is determined which test stage has a problem, clarifying whether the root cause of the test problem is the test target itself or the test-related software and hardware, thereby enabling improvements to related problems, preventing the recurrence of similar problems, and improving test efficiency. Attached Figure Description

[0038] Figure 1 This is a flowchart illustrating an electrical data analysis method in one embodiment;

[0039] Figure 2 This is a schematic diagram of the data attribute columns of electrical test data in one embodiment;

[0040] Figure 3 This is a schematic diagram illustrating the relationship between preset failure modes and test problem classifications in one embodiment;

[0041] Figure 4 This is a flowchart illustrating the process of determining the failure mode corresponding to the electrical failure data in one embodiment.

[0042] Figure 5 This is a structural block diagram of an electrical data analysis device in one embodiment;

[0043] Figure 6 This is an internal structural diagram of a wafer-level testing device in one embodiment. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0045] like Figure 1 As shown, this application provides an electrical data analysis method. This embodiment illustrates the method applied to a terminal, but it is understood that the method can also be applied to a server, and further to a system including both a terminal and a server, and implemented through interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0046] Step S12: Obtain the electrical test data of the test target.

[0047] In this embodiment, the terminal can be a wafer-level testing device (WAT, Wafer Acceptance Testing). After the wafer is manufactured and before the chip is packaged, WAT testing (wafer acceptance testing) can be used to extract data information characterizing the process and device performance, which can be used to guide the process development and production control of chip products.

[0048] The test targets can be transistors, basic circuit units, interface modules, or related test structures on the bare die before packaging, used to evaluate and verify semiconductor manufacturing processes, materials, and device performance. Electrical connections are established by contacting the test targets on the wafer using probe cards on the wafer testing equipment to obtain electrical test data.

[0049] The data attributes of the electrical test data include the structure-related attributes and test-related attributes of the test target. The structure-related attributes are attribute parameters related to the structure and characteristics of the test target, used to characterize the physical characteristics of the test target, such as gate length and width, contact and via sizes, metal layer linewidth and length, etc., and also characterize the electrical characteristics of the test target, such as resistance, leakage current, threshold voltage, etc.

[0050] In this embodiment, test-related attributes refer to the test-related hardware and software information involved in the test target. This information not only affects the validity of the test data but also influences the causes of electrical failure data. Hardware information analysis can help identify physical wear or faults in test structures, probe cards, or test equipment components, while software information analysis ensures the correctness of the test program and the accuracy of data processing, thereby improving the accuracy and reliability of test results. Extracting test-related attributes from electrical test data facilitates subsequent analysis and test optimization, improving resource utilization and test efficiency.

[0051] In some embodiments, test-related attributes can be test structure types. In this embodiment, the test structure type can be different types of test structures, such as process monitoring structures for monitoring and evaluating various steps of semiconductor manufacturing processes, or device characteristic test structures for evaluating and measuring the electrical characteristics of semiconductor devices; it can also be different structural variations of the same type of test structure. The test structure type varies depending on the test requirements of different test items, and this application does not limit this. In other embodiments, a probe card physically contacts the pads or contact points on the wafer to perform related tests. The test-related attributes can also be the probe card (e.g., pins on a probe card), or the pin insertion order of the probes on the probe card during multiple insertion processes, i.e., the insertion sequence (TouchDown). In other embodiments, test-related hardware information also includes related accessories for test equipment such as the test SMU (Source Measure Unit) ID, PGU (Pulse Generation Unit), and FMU (Frequency Measurement Unit).

[0052] In this embodiment, the test-related software information is used to execute and manage the test process of the test target to adapt to different test requirements, and can be a test algorithm (Test Algorithm, abbreviated as Algo).

[0053] In actual testing, test-related attributes can be extracted based on the actual hardware and software information used by the test target, which is not limited in this application.

[0054] Step S14: Based on the structural related attributes of the electrical test data and the first judgment criterion, determine whether the electrical test data of the test target is invalid, so as to determine the electrical failure data.

[0055] like Figure 2 As shown, in this embodiment, the first judgment criterion is the test standard for electrical failure data. For each test item in the electrical test output data of the test target, a corresponding test standard is preset. This test standard can be a data range including upper and lower limits. The upper and lower limits represent the boundaries of the data failure standard, used to determine whether the data is within the normal range. Exceeding the upper or lower limit is considered a failure. By comparing and analyzing the structural attributes of the electrical test data with the test standard, the matching degree between the electrical test data and the test standard can be determined, thereby filtering out electrical failure data.

[0056] For example, for a test item in the electrical test output data: testing the threshold voltage of a transistor, if the actual test value of the electrical test data is 0.3V, while the test standard for this test item is an upper limit of 0.28V and a lower limit of 0.2V, then 0.3V exceeds the preset upper limit of 0.28V, and it can be determined that the electrical test data does not match the test standard, and the electrical test data is judged to be electrical failure data.

[0057] Step S16: Based on the structural related attributes, test related attributes, and second judgment criteria of the electrical test data, classify the electrical failure data into categories to determine the failure modes corresponding to the electrical failure data.

[0058] In this embodiment, the second judgment criterion is the classification criterion of electrical failure data. After the electrical failure data is determined, it is necessary to further classify the data by combining the structural related attributes and test related attributes of the electrical test data in order to determine the failure mode.

[0059] To address the root causes of electrical failure data, corresponding judgment criteria and failure modes are pre-defined for different types of electrical failure data. These judgment criteria can be based on the structural and test-related attributes of the electrical test data, combined with experience, or derived from data mining and statistical analysis; this application does not impose any limitations on this. By comparing and analyzing electrical failure data under a second judgment criterion, the matching degree between the electrical failure data and failure modes can be determined, thereby identifying different failure modes of the electrical failure data.

[0060] Step S18: Based on the preset failure mode and test problem classification relationship, determine the root cause of the test problem corresponding to the failure mode of the electrical failure data.

[0061] Specifically, such as Figure 3 As shown, test problems corresponding to different failure modes can be set for multiple distinct failure modes, thus obtaining a classification relationship between failure modes and test problems. During electrical data analysis, the corresponding test problem is indexed in the failure mode-test problem classification relationship based on the failure mode corresponding to the electrical failure data. It can be understood that in this embodiment, one test problem can correspond to one or more failure modes. This facilitates data analysis and allows for the implementation of corresponding engineering measures to prevent recurrence of specific test problems. For example, when the failure mode of the electrical failure data is a specific TouchDown sequence, the position of the specific TouchDown on the probe station needs to be checked and adjusted.

[0062] It should be noted that since the failure mode corresponding to the electrical failure data is determined by comprehensively considering the structure-related attributes and test-related attributes, the test problems corresponding to the failure mode include problems with the test target itself or problems caused by the test software and hardware. Exemplarily, the test problems can be open circuits, over-etching, leakage currents, etc. caused by process deviations, or the test structure type, probe card, SMU, etc.

[0063] The above electrical data analysis method, device, wafer-level test equipment and storage medium determine whether the electrical test data of the test target fails based on the structure-related attributes of the electrical test data and the first judgment criterion, so as to determine the electrical failure data. It can judge and filter the test abnormal data based on the structure-related attributes of the electrical test data, so that when a test error occurs in the test analysis link, the validity of the data can be identified.

[0064] By classifying the electrical failure data according to the structure-related attributes, test-related attributes of the test target and the second judgment criterion, to determine the failure mode corresponding to the electrical failure data; based on the preset classification relationship between the failure mode and the test problem, determine the root cause of the test problem corresponding to the failure mode of the electrical failure data. In this way, on the basis of determining the electrical failure data, further determine the failure mode and the corresponding root cause of the test problem by combining the test-related attributes of the test target, specifically judge which test link has problems, and clarify whether the root cause of the test problem is the test target itself or the test-related software and hardware, so as to improve the relevant problems and avoid the recurrence of similar problems.

[0065] In some embodiments, step S14 includes:

[0066] Step 141, determine multiple test items corresponding to the electrical test data of the test target.

[0067] Step 142, obtain the standard data range of several structure-related attribute values corresponding to each test item.

[0068] Step 143, compare and analyze the electrical test data with the standard data range of several corresponding structure-related attribute values item by item according to the test items, and determine the electrical failure data according to the analysis results.

[0069] In this embodiment, the electrical test data includes a set of electrical test output data corresponding to multiple test items of the test target. The multiple test items corresponding to the electrical test data include DC tests such as resistance, leakage current, and threshold voltage; AC tests such as capacitance measurement and transconductance measurement; and power consumption tests, etc. Correspondingly, different test items in the electrical test data involve several different structure-related attributes. For example, for leakage current testing, structure-related attributes include metal linewidth / spacing, number of vias, etc. For threshold voltage testing, structure-related attributes include leakage current, threshold voltage, standard deviation, gate voltage, etc.

[0070] Under different test items, different structural-related attribute values ​​have different standard data ranges. The electrical test data are compared and analyzed with the corresponding standard data ranges of several structural-related attribute values ​​according to the test item. When the measured value of the electrical test data is outside the standard data range, the data is determined to be electrical failure data; otherwise, the data is not electrical failure data.

[0071] Through the above steps, the electrical data analysis method of this application filters electrical failure data in electrical test data, which facilitates the rapid location of possible failure causes and test anomalies during subsequent electrical data analysis, narrows the scope of root cause analysis of test problems, and improves the efficiency and accuracy of subsequent root cause analysis.

[0072] like Figure 4 As shown, in some embodiments, step S16 includes the following steps S161-S162.

[0073] Step S161: Based on the structural and test-related attributes of the electrical test data of the test target, determine the test data failure rate under each test parameter in the test-related attributes of the electrical failure data.

[0074] In this embodiment, the test-related attributes of electrical failure data include multiple test parameters, each corresponding to the test-related hardware and software information involved in the test target under different test items. As mentioned above, the test parameters can be one or more of the following: test structure type, probe card, pin insertion order, SMU, PGU, FMU, and test algorithm, but are not limited to these, and can be adaptively set according to the actual test situation.

[0075] like Figure 2As shown, under different test items, the test parameters in the test-related attributes corresponding to electrical failure data can be the same, partially the same, or completely different. For example, for test structure type parameters: Class A / Class B / Class C / Class D / Class E represent different test structure (TestKey) types. For test items 1-4, the test structure type (marked as category) corresponding to the electrical test data is Class A; for test items 5-8, the test structure type corresponding to the electrical test data is Class B. For the pin insertion order test parameter, 1 / 2 / 3 / 4 represent different pin insertion orders, used to mark which pin insertion caused the test problem. For test items 1-6, the pin insertion order corresponding to the electrical test data is 1; for test items 7-14, the pin insertion order corresponding to the electrical test data is 2. Other test parameters are not described here.

[0076] Specifically, in some embodiments, step S161 includes steps S1611-S1614.

[0077] Step S1611: Determine multiple test parameters corresponding to the test-related attributes of the electrical failure data.

[0078] Step S1612: For each test parameter, index the number of test items for valid electrical data and invalid electrical data in the electrical test data of the test target.

[0079] Step S1613: Calculate the test data failure rate under the test parameters based on the number of test items in the electrical effective data and the electrical failure data.

[0080] Step S1614: Repeat the above steps to obtain the test data failure rate under each test parameter in the test-related attributes of the electrical failure data.

[0081] In this embodiment, by determining multiple test parameters corresponding to the test-related attributes of electrical failure data, all relevant test parameters that cause electrical test data failure can be screened out, and the analysis scope can be further defined.

[0082] For the same test parameter, the test parameters involved in different test items may differ, potentially leading to different measurement results. To improve the accuracy of the test data failure rate calculation results and ensure that the cause of data failure matches the test parameter, in this embodiment, the number of test items containing the test parameter, i.e., the number of electrical effective data and electrical failure data, is counted. Based on the number of test items containing the electrical effective data and the electrical failure data, the test data failure rate under the test parameter is calculated, specifically as follows:

[0083] δ i =NF / ( N P +N F )

[0084] Where, δ i N represents the test data failure rate of the i-th test parameter. F N represents the number of test items in the electrical failure data. P The number of test items representing valid electrical data.

[0085] Once the test failure rate corresponding to a test parameter is calculated, repeating the above steps can yield the test failure rate of each test parameter in the test-related attributes of electrical failure data.

[0086] It should be noted that, to reduce the impact of random error factors, when calculating the test data failure rate under each test parameter, the number of test items needs to be greater than a first preset number and the number of test target samples needs to be greater than a second preset number. For example, in this embodiment, the number of test target samples is greater than 5 and the number of test items is greater than 50.

[0087] Through the above steps, the test results of the relevant test items for each test parameter corresponding to the electrical failure data are indexed in all electrical test data and statistically calculated to obtain the corresponding test data failure rate. This can accurately reflect the test status of each test parameter, provide direct data support for subsequent analysis, and facilitate the accurate calculation of subsequent failure modes.

[0088] Step S162: The test data failure rate corresponding to the test parameters of the electrical failure data is compared with the preset failure standard, and the failure mode corresponding to the electrical failure data is determined according to the comparison result.

[0089] In this embodiment, different failure criteria are pre-set for all test parameters to determine whether the calculated test data failure rate meets the classification criteria. After obtaining the data failure rate, further comparative analysis is needed based on the preset failure criteria to determine the failure mode corresponding to the electrical failure data based on the comparison results. Specifically, step S162 may include the following steps S1621-S1622.

[0090] Step S1621: When the failure rate of test data corresponding to the same parameter type under the same test parameters is greater than or equal to the first preset threshold, the electrical failure data is determined to be the first type of test failure mode, and the first type of test failure mode is the failure mode corresponding to the parameter type.

[0091] To further refine the classification of electrical failure data and obtain more accurate root cause analysis results for test problems, each test parameter includes one or more parameter types. Correspondingly, for each test parameter type, the number of test items for both valid and failed electrical data is indexed in the electrical test data of the test target, thereby calculating the test data failure rate for each parameter type. The specific calculation method can refer to the test data failure rate calculation method for each test parameter in step S161 above, and will not be elaborated upon here.

[0092] In this embodiment, when the calculated failure rate of the test data under the parameter type is greater than or equal to a first preset threshold, it indicates that the electrical failure data obtained under that parameter type meets the failure mode classification standard. At this time, the electrical failure data is determined to be a first type of test failure mode. The first type of test failure mode is the failure mode corresponding to the parameter type, indicating that the failure category of the electrical failure data matches the corresponding parameter type under the test parameter, thereby specifying the root cause of the test problem to the parameter type of the test error. For example, as shown... Figure 3 As shown, the test parameter is Algo. When the calculated test parameter is the test data failure rate under the parameter type of Algo (i.e., a specific Algo) is greater than or equal to 90% of the first preset threshold, the electrical failure data is determined to be the failure mode corresponding to the specific Algo.

[0093] Step S1622: When the failure rate of test data corresponding to all parameter types of the same test parameter is greater than or equal to the second preset threshold and less than the first preset threshold, the second type of test failure mode of the electrical failure data is determined, and the second type of test failure mode is the failure mode corresponding to the test parameter.

[0094] In this embodiment, when the calculated failure rate of test data under all parameter types for the same test parameter is greater than or equal to the second preset threshold and less than the first preset threshold, it indicates that the electrical failure data obtained under all parameter types does not meet the failure mode classification standard, but the electrical failure data under this test parameter can meet the failure mode classification standard. At this time, the electrical failure data is determined to be a second type of test failure mode. The second type of test failure mode is the failure mode corresponding to the test parameter, indicating that the failure category of the electrical failure data matches the test parameter. At this time, further analysis and classification of test root causes can be performed based on the matching results. For example, as shown... Figure 3As shown, the test parameters are the test structure types, and the parameter types are different test structures. When the calculated failure rate of the test data under all test structures of the test structure type is less than 90% of the first preset threshold and greater than 20% of the second preset threshold, the electrical failure data is determined to be the failure mode corresponding to the test structure type. At this time, further judgment shows that since most of the test structure data is wrong, the specific error problem is unknown. The root cause of the test problem is the probe station problem, which may be unstable needle pressure, slippage, or incomplete puncture, leading to Open.

[0095] The first and second preset thresholds can be adjusted according to different test items or different stages of the same test item, and this application does not limit them.

[0096] Through the above steps, by further classifying each test parameter into one or more parameter types, and by setting the first type of test failure mode and the second type of test failure mode, the electrical failure data is classified to different degrees based on the failure rate calculation results of the electrical failure data. Thus, a more accurate failure mode classification result can be obtained based on the actual situation of the test problem corresponding to the electrical failure data.

[0097] In one embodiment, after step S16, the method further includes:

[0098] Step S171: Mark the electrical failure data under different failure modes;

[0099] Step S172: Filter the marked electrical failure data to perform electrical analysis on the test target based on the filtered electrical test data.

[0100] It is understandable that, since the electrical failure data of the test target contains multiple test items, the structural and test-related attributes of the data under different test items are different, and the causes of data failure may be different. In this embodiment, such as Figure 2 As shown, once electrical failure data is identified, it can be flagged to indicate whether the electrical test data is faulty. For example, if electrical test data is determined to be faulty, it is flagged as 1; otherwise, it is flagged as 0. Furthermore, once the failure mode corresponding to the electrical failure data is determined, corresponding filter flags are added to the electrical failure data under different test items. For instance, if the electrical failure data is the first type of test failure mode TouchDown2, it is flagged as flag2. This facilitates data analysis.

[0101] In this embodiment, by marking electrical failure data, root cause analysis of test problems can be performed based on the electrical failure data, followed by improvements to the test hardware and software, thereby preventing the recurrence of similar test problems. Marking electrical failure data also allows for precise filtering out invalid data points caused by test problems, avoiding interference with valid data points and thus obtaining reliable data analysis conclusions.

[0102] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0103] Based on the same inventive concept, this application also provides an electrical data analysis apparatus for implementing the electrical data analysis method described above. The solution provided by this apparatus is similar to the implementation scheme described in the above method; therefore, the specific limitations in one or more embodiments of the electrical data analysis apparatus provided below can be found in the limitations of the electrical data analysis method described above, and will not be repeated here.

[0104] In one embodiment, such as Figure 5 As shown, an electrical data analysis device 500 is provided, including: an electrical data acquisition module 501, a failure data acquisition module 502, a failure mode determination module 503, and a test root cause determination module 504, wherein:

[0105] The electrical data acquisition module 501 is used to acquire electrical test data of the test target; the data attributes of the electrical test data include the structural related attributes and test related attributes of the test target;

[0106] The failure data acquisition module 502 is used to determine whether the electrical test data of the test target is failed based on the structural related attributes of the electrical test data and the first judgment criterion, so as to determine the electrical failure data.

[0107] The failure mode determination module 503 is used to classify the electrical failure data according to the structure-related attributes, test-related attributes and second judgment criteria of the electrical test data, so as to determine the failure mode corresponding to the electrical failure data.

[0108] The root cause determination module 504 is used to determine the root cause of the test problem corresponding to the failure mode of the electrical failure data based on the preset relationship between failure mode and test problem classification.

[0109] In one embodiment, the test-related attributes include one or more of the following: test structure type, needle insertion order, probe card, test algorithm, and SMU.

[0110] In one embodiment, the failure data acquisition module 502 includes: a test item determination module, a data range acquisition module, and a data determination module.

[0111] The test item determination module is used to determine multiple test items corresponding to the electrical test data of the test target;

[0112] The data range acquisition module is used to acquire the standard data range of several structure-related attribute values ​​corresponding to each of the test items;

[0113] The data determination module is used to compare and analyze the electrical test data with the standard data range of the corresponding structural related attribute values ​​according to the test items, and determine the electrical failure data based on the analysis results.

[0114] In one embodiment, the failure mode determination module 503 includes a failure rate determination module and a mode determination module.

[0115] The failure rate determination module is used to determine the test data failure rate under each test parameter in the test-related attributes of the electrical failure data based on the structure-related attributes and test-related attributes of the electrical test data of the test target.

[0116] The mode determination module is used to compare the test data failure rate corresponding to the test parameters of the electrical failure data with preset failure standards, and determine the failure mode corresponding to the electrical failure data based on the comparison results.

[0117] In one embodiment, the failure rate determination module includes: a test parameter determination unit, a test item number indexing unit, a failure rate calculation unit, and a loop unit.

[0118] The test parameter determination unit is used to determine multiple test parameters corresponding to the test-related attributes of the electrical failure data;

[0119] The test item count index unit is used to index the number of test items for each test parameter in the electrical test data of the test target, respectively, for the effective electrical data and the failed electrical data;

[0120] The failure rate calculation unit is used to calculate the test data failure rate under the test parameters based on the number of test items of the electrical effective data and the electrical failure data.

[0121] The loop unit is used to repeat the above steps to obtain the test data failure rate under each test parameter in the test-related attributes of the electrical failure data.

[0122] In one embodiment, the mode determination module includes: a first type of test failure mode determination unit and a second type of test failure mode determination unit.

[0123] The first type of test failure mode determination unit is used to determine the electrical failure data as the first type of test failure mode when the failure rate of test data corresponding to the same parameter type under the same test parameters is greater than or equal to a first preset threshold. The first type of test failure mode is the failure mode corresponding to the parameter type.

[0124] The second type of test failure mode determination unit is used to determine the second type of test failure mode of the electrical failure data when the failure rate of test data corresponding to all parameter types of the same test parameter is greater than or equal to a second preset threshold and less than a first preset threshold. The second type of test failure mode is the failure mode corresponding to the test parameter.

[0125] In one embodiment, the electrical data analysis device further includes a tagging module and an electrical analysis module.

[0126] A tagging module is used to tag the electrical failure data under different failure modes;

[0127] The electrical analysis module is used to filter the electrical failure data after marking, so as to perform electrical analysis on the test target based on the filtered electrical test data.

[0128] Each module in the aforementioned electrical data analysis device 500 can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of the wafer-level testing equipment in hardware form or independent of it, or stored in the memory of the wafer-level testing equipment in software form, so that the processor can call and execute the operations corresponding to each module.

[0129] In one embodiment, a wafer-level testing device is provided. This wafer-level testing device can be a terminal, and its internal structure diagram can be as follows: Figure 6As shown, this wafer-level testing equipment includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides the environment for the operation of the operating system and computer programs in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals. When the computer program is executed by the processor, it implements an electrical data analysis method.

[0130] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the wafer-level testing equipment to which the present application is applied. Specific wafer-level testing equipment may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0131] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the electrical data analysis method described above.

[0132] It should be noted that all data involved in this application (including but not limited to data used for analysis, data stored, data displayed, etc.) are data authorized by the user or fully authorized by all parties.

[0133] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0134] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0135] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for analyzing electrical data, characterized in that, The method includes: Acquire electrical test data of the test target; the data attributes of the electrical test data include structural related attributes and test related attributes of the test target; wherein, the structural related attributes are attribute parameters related to the structure and characteristics of the test target, used to characterize the physical characteristics of the test target, and the test related attributes are test-related hardware and software information involved in the test target; the test related attributes include one or more of the following: test structure type, needle insertion order, probe card, test algorithm, and SMU; Based on the structural related attributes of the electrical test data and the first judgment criterion, it is determined whether the electrical test data of the test target is invalid, so as to identify the electrical failure data; Based on the structural relevant attributes, test relevant attributes, and a second judgment criterion of the electrical test data, the electrical failure data is categorized to determine the corresponding failure mode. Specifically, categorizing the electrical failure data based on the structural relevant attributes, test relevant attributes, and the second judgment criterion to determine the corresponding failure mode includes: determining the test data failure rate under each test parameter in the test relevant attributes of the electrical failure data based on the structural relevant attributes and test relevant attributes of the electrical test data of the test target; comparing the test data failure rate corresponding to the test parameters of the electrical failure data with preset failure criteria, and determining the corresponding failure mode based on the comparison results. Based on the preset relationship between failure modes and test problem classification, the root causes of test problems corresponding to the failure modes of the electrical failure data are determined.

2. The method according to claim 1, characterized in that, Based on the structural-related attributes of the electrical test data and the first judgment criterion, the method for determining whether the electrical test data of the test target is invalid is used to identify electrical failure data, which includes: Determine multiple test items corresponding to the electrical test data of the test target; Obtain the standard data range of several structure-related attribute values ​​corresponding to each of the test items; The electrical test data are compared and analyzed with the standard data range of the corresponding structural attribute values ​​according to the test items, and the electrical failure data are determined based on the analysis results.

3. The method according to claim 1, characterized in that, The determination of the test data failure rate under each test parameter in the test-related attributes of the electrical test data based on the structure-related attributes and test-related attributes of the electrical failure data, based on the test-related attributes of the electrical failure data, includes: Determine multiple test parameters corresponding to the test-related attributes of the electrical failure data; For each test parameter, the number of test items for both effective and ineffective electrical data are indexed in the electrical test data of the test target. Based on the number of test items in the electrical effective data and the electrical failure data, calculate the test data failure rate under the test parameters; Repeat the above steps to obtain the test data failure rate under each test parameter in the test-related attributes of the electrical failure data.

4. The method according to claim 3, characterized in that, The test failure rate corresponding to the test parameters of the electrical failure data is compared with a preset failure standard. Based on the comparison results, the failure mode corresponding to the electrical failure data is determined, including: When the failure rate of test data corresponding to the same parameter type under the same test parameters is greater than or equal to the first preset threshold, the electrical failure data is determined to be the first type of test failure mode, and the first type of test failure mode is the test failure mode corresponding to the parameter type. When the failure rate of test data corresponding to all parameter types of the same test parameter is greater than or equal to the second preset threshold and less than the first preset threshold, the electrical failure data is determined to be the second type of test failure mode, and the second type of test failure mode is the failure mode corresponding to the test parameter.

5. The method according to claim 1, characterized in that, After classifying the electrical failure data according to the structure-related attributes, test-related attributes, and second judgment criteria to determine the failure mode corresponding to the electrical failure data, the method further includes: The electrical failure data under different failure modes are labeled; The electrical failure data after marking is filtered, and the electrical performance of the test target is analyzed based on the filtered electrical test data.

6. An electrical data analysis device, characterized in that, The device includes: An electrical data acquisition module is used to acquire electrical test data of the test target; the data attributes of the electrical test data include structural related attributes and test related attributes of the test target; wherein, the structural related attributes are attribute parameters related to the structure and characteristics of the test target, used to characterize the physical characteristics of the test target, and the test related attributes are test-related hardware and software information involved in the test target; the test related attributes include one or more of the following: test structure type, needle insertion order, probe card, test algorithm, and SMU; The failure data acquisition module is used to determine whether the electrical test data of the test target is failed based on the structural related attributes of the electrical test data and the first judgment criterion, so as to determine the electrical failure data. The failure mode determination module is used to classify the electrical failure data according to the structure-related attributes, test-related attributes, and a second judgment criterion of the electrical test data to determine the failure mode corresponding to the electrical failure data. Specifically, classifying the electrical failure data according to the structure-related attributes, test-related attributes, and the second judgment criterion to determine the failure mode corresponding to the electrical failure data includes: determining the test data failure rate under each test parameter in the test-related attributes of the electrical failure data based on the structure-related attributes and test-related attributes of the electrical test data of the test target; comparing the test data failure rate corresponding to the test parameters of the electrical failure data with preset failure criteria, and determining the failure mode corresponding to the electrical failure data based on the comparison results. The root cause determination module is used to determine the root cause of the test problem corresponding to the failure mode of the electrical failure data based on a preset relationship between failure modes and test problem classification.

7. A wafer-level testing device, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

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