Test sorting method of MLCC

Abstract

The invention relates to a test sorting method for MLCC, which is suitable for test equipment comprising a plurality of annular test tracks. The method comprises the following steps: testing MLCC products in batches on different tracks, and obtaining test data; calculating a dynamic test reference value based on the data distribution, comparing the dynamic test reference value with a preset fixed threshold value, and determining a screening standard; and in the subsequent testing process, qualified products and defective products are sorted according to the screening standard. Compared with a traditional fixed threshold value screening mode, the method can adapt to batch difference and equipment aging, improve screening accuracy, reduce misjudgment and improve the intelligent level of MLCC product quality control.

Description

Technical Field

[0001] The present application relates to the technical field of MLCC product testing, and in particular to a testing and sorting method for MLCC. Background Art

[0002] As a commonly used passive component in electronic products, multilayer ceramic capacitors (MLCC) have extremely high requirements for their electrical performance, especially leakage current parameters, which directly affect the long-term reliability of the device and circuit safety. In the MLCC manufacturing process, leakage current testing is an important part of quality screening, and test sorting machines are usually used for large-scale testing to ensure that the products shipped meet quality requirements.

[0003] The MLCC test sorting machines commonly used in the industry, such as 3-track, 4-track, 6-track, 8-track, 12-track and other multi-test track test equipment, usually work in the following ways:

[0004] MLCC products enter the test hole of the test plate through vacuum adsorption to form a fixed test loop; the test plate rotates to drive the MLCCs into the test station one by one, and the test is completed through the upper and lower electrodes (test roller + shaft core); the test system records the leakage current data and sorts according to the set fixed threshold, that is: leakage current ≤ set threshold → judged as qualified products (OK). Leakage current > set threshold → judged as defective products (NG) and rejected.

[0005] Taking the existing high-precision MLCC four-parameter test mechanism (such as the comparative document CN218727718U) as an example, the test mechanism completes multiple parameter tests of MLCC in sequence by rotating the test disk to ensure the test accuracy. In the comparative document, the test disk only illustrates one annular test track. In other prior arts, there are also multiple annular test tracks that wrap around each other, such as 3-track, 4-track, 6-track, 8-track, 12-track and other multi-test track test equipment.

[0006] Although existing MLCC leakage current test equipment can realize batch automatic detection, there are still the following significant problems in practical applications:

[0007] (1) Changes in equipment status affect test accuracy

[0008] Due to the long-term operation of the test equipment, the wear of the rollers, shaft cores and test discs of the test station will cause unstable contact between the product and the test electrodes, thereby affecting the leakage current test results.

[0009] (2) Poor test consistency between test tracks

[0010] For multi-test track test equipment (such as 8-track tester), the contact time of the product on each test track on the test disc is different, resulting in deviations in the test results between the test tracks: the inner test track has a long contact time and is fully charged, so the test value may be low; the outer test track has a short contact time and is insufficiently charged, so the test value may be high.

[0011] (3) It is difficult to detect equipment abnormalities in a timely manner

[0012] The existing testing system lacks a mechanism to monitor the health status of equipment. Problems such as poor equipment contact and test fixture failure are often only discovered after the defective rate of large batches increases, and no early warning is possible. Summary of the invention

[0013] Based on this, the present application provides a testing and sorting method for MLCC that can solve the above-mentioned technical problems.

[0014] The above-mentioned purpose of the present application is achieved through the following technical solutions:

[0015] The present application provides a test sorting method for MLCC, which is applied to a test device including a plurality of annular test tracks. The method comprises the following steps:

[0016] Batch test the MLCC products on different test tracks, and obtain test data of each test track respectively;

[0017] Calculate the dynamic test reference value of each test track based on the distribution of the test data and a preset value selection strategy of the test track;

[0018] Compare each of the dynamic test reference values ​​with a preset fixed threshold value to determine a screening criterion for each test track: when the dynamic test reference value is lower than the fixed threshold value, the screening criterion is the dynamic test reference value; when the dynamic test reference value is higher than the fixed threshold value, the screening criterion is the fixed threshold value;

[0019] Subsequent MLCC products are tested on different test tracks, and qualified products and defective products are sorted out according to the screening criteria.

[0020] In an optional embodiment, based on the distribution of the test data of each test track and a preset value strategy, calculating the dynamic test reference value of the test track includes:

[0021] If the test data conforms to a normal distribution, the dynamic test reference value is calculated according to the mean and standard deviation of the test data;

[0022] If the test data conforms to the skewed distribution, the percentile value of the test track data is calculated as the dynamic test reference value.

[0023] In an optional embodiment, the method for calculating the dynamic test reference value under normal distribution includes:

[0024] Calculate the mean μ and standard deviation σ of the test data;

[0025] μ+3σ is used as the dynamic test benchmark value;

[0026] The calculation method of dynamic test benchmark value under skewed distribution includes:

[0027] The 99.865% percentile P99.865 of the test data is calculated and used as the dynamic test benchmark value.

[0028] In an optional embodiment, the method further comprises the following steps:

[0029] Calculating the skewness coefficient and kurtosis value of the test data;

[0030] When the absolute value of the skewness coefficient is less than a preset threshold value and the kurtosis value is within a preset range, it is determined that the test data conforms to a normal distribution;

[0031] Otherwise, it is determined that the test data conforms to the skewed distribution.

[0032] In an optional embodiment, the preset threshold is less than 0.5, and the preset range of the kurtosis value is between 2 and 4.

[0033] In an optional embodiment, during the process of testing subsequent MLCC products on different test tracks, when the set trigger condition is met, the following steps are also included:

[0034] Calculating a new dynamic test reference value of each test track according to the real-time test data on the test track;

[0035] The new dynamic test reference value is compared with the dynamic test reference value calculated last time, and if the deviation is greater than a first set deviation value, the screening criterion is updated according to the new dynamic test reference value.

[0036] In an optional embodiment, the setting trigger condition includes at least one of the following:

[0037] The set test time is reached, the set test quantity is reached.

[0038] In an optional embodiment, the method further comprises the following steps:

[0039] If the deviation between the new dynamic test reference value and the dynamic test reference value calculated last time is less than the second set deviation value, then extending the set test time or increasing the set test quantity;

[0040] If the deviation between the new dynamic test reference value and the dynamic test reference value calculated last time is greater than a third set deviation value, shortening the set test time or reducing the set test quantity;

[0041] If the deviation between the new dynamic test reference value and the dynamic test reference value calculated last time is greater than the second set deviation value and less than the third set deviation value, the set test time is maintained or the set test quantity is shortened;

[0042] The first set deviation value is greater than the second set deviation value and less than the third set deviation value.

[0043] In an optional embodiment, the method further comprises the following steps:

[0044] Obtain the dynamic test reference value obtained by the most recent N calculations, and calculate its rate of change;

[0045] If the rate of change is greater than a set rate threshold, an early warning is triggered.

[0046] In an optional embodiment, the method further comprises the following steps:

[0047] If the change rate is greater than a set rate threshold, and the deviation between the new dynamic test reference value and the dynamic test reference value calculated last time is greater than a first set deviation value, a shutdown is triggered.

[0048] This application has the following beneficial effects:

[0049] The MLCC testing and sorting method of the present application improves the screening accuracy while enhancing the system's adaptability to batch changes and equipment aging through a screening strategy that combines a dynamic test reference value with a fixed threshold, thereby improving the intelligence level of MLCC product quality control; recalculates the dynamic test reference value when the set trigger condition is met, which can adapt to the fluctuation of test data in the production process and improve the real-time and effectiveness of the screening criteria; dynamically adjusts the test time and test quantity, optimizes the screening criteria update interval according to the size of the data deviation, improves the test efficiency, reduces unnecessary screening adjustments, and improves production stability; calculates the change rate based on the most recent N dynamic test reference values, and triggers an early warning when it exceeds the set threshold, which can detect production or equipment anomalies in advance and prevent batch defective products from flowing into subsequent processes due to the failure of the screening criteria; triggers a shutdown when the change rate exceeds the limit and the dynamic test reference value deviation exceeds the set threshold, which can automatically suspend production when the screening criteria suddenly changes, avoid quality accidents, and improve the reliability and safety of the production line. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1FIG. 1 is a schematic diagram of the steps of a method for testing and sorting MLCC in an exemplary embodiment. DETAILED DESCRIPTION

[0051] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are described in detail below. In the following description, many specific details are set forth to facilitate a full understanding of the present application. However, the present application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present application, so the present application is not limited by the specific embodiments disclosed below.

[0052] In addition, the terms "first" and "first" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "first" may explicitly or implicitly include at least one of the features. In the description of this application, "plurality" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0054] In response to the technical problems in the background technology, the present application provides a test and sorting method for MLCC, which is applied to a test device including multiple circular test tracks. It overcomes the defect that the traditional technology can only sort defective products by setting a fixed threshold for each test track. It can dynamically adjust the screening criteria according to the distribution of the actual test data of MLCC leakage current, thereby improving the accuracy of MLCC screening and reducing the problem of misjudgment caused by production batch fluctuations or equipment aging.

[0055] like Figure 1 As shown, in one embodiment, the MLCC test sorting method of the present application includes the following steps:

[0056] S01: Batch test MLCC products on different test tracks, and obtain test data of each test track respectively.

[0057] In the production process of MLCC, different batches of products may have slight performance deviations due to differences in production processes, raw materials, environmental factors, and equipment status, especially in leakage current testing, which may affect the accuracy of screening. Therefore, when implementing the method of this application, it is first necessary to select a certain number (such as 100 pcs or more) of MLCC products on each test track for batch preliminary testing in order to obtain test data for each test track. These data are used to analyze the leakage current distribution of MLCC products and provide a basis for setting subsequent screening standards.

[0058] In the test equipment used in the embodiment of the present application, multiple annular test tracks are arranged on the test disk in a concentric circle manner, and the MLCC products on each test track are placed in the disk hole by automated equipment, and voltage is applied through the electrodes at the upper and lower ends for testing. This method is not only applicable to the leakage current test of MLCC, but also to similar electrical parameter tests, such as insulation resistance test, etc.

[0059] S02: Calculate a dynamic test reference value of each test track based on the distribution of the test data of the test track and a preset value selection strategy.

[0060] Since the test data distribution of MLCC products may vary, in order to reasonably set the screening criteria, the method of this application calculates the dynamic test benchmark value of each test track based on the distribution of actual test data. In the actual test process, the test data may show a normal distribution or a skewed distribution, so different calculation strategies need to be adopted:

[0061] If the test data conforms to the normal distribution, the mean (μ) and standard deviation (σ) are calculated, and μ+3σ is used as the dynamic test reference value to ensure that 99.865% of the product data is within the screening range and only the extreme outliers are eliminated. In other embodiments, the dynamic test reference value can also be μ+2σ, or μ+σ, etc.

[0062] If the test data conforms to a skewed distribution, the percentile method (e.g., 99.865% percentile) is used to calculate the dynamic test benchmark value to avoid unreasonable screening ranges due to data skewness.

[0063] Before calculating the dynamic test benchmark value, preferably, the method can also pre-eliminate obvious abnormal data (such as abnormally small values ​​caused by poor equipment contact or abnormally large values ​​caused by poor MLCC) to ensure the accuracy and representativeness of the screening criteria. Compared with the traditional fixed threshold screening method, the method of the present application can adapt to the data distribution of different batches of products, improve screening accuracy, and reduce the misjudgment rate.

[0064] S03: Compare each of the dynamic test benchmark values ​​with a preset fixed threshold value to determine the screening criteria for each test track: when the dynamic test benchmark value is lower than the fixed threshold value, the screening criteria is the dynamic test benchmark value; when the dynamic test benchmark value is higher than the fixed threshold value, the screening criteria is the fixed threshold value.

[0065] In the method of this application, the dynamic test baseline value is usually lower than the fixed threshold value, mainly for the following reasons:

[0066] Factors such as equipment aging and poor contact usually cause the leakage current measurement value to be too small, but will not cause the leakage current to be too large. Therefore, the measured dynamic test benchmark value is generally smaller than the fixed upper limit value.

[0067] The dynamic test benchmark value of each test track is calculated based on the actual measured data of the current batch, which can adapt to the characteristics of the current product and avoid screening misjudgments due to batch differences.

[0068] Therefore, in the method of this application, the setting of each screening criterion follows the following principles:

[0069] When the dynamic test benchmark value is less than the fixed threshold, it indicates that the leakage current distribution of the batch of products is small as a whole. At this time, the dynamic test benchmark value is directly used as the screening criterion to ensure the rationality of the screening, while improving the production yield and avoiding excessive screening that causes qualified products to be misjudged as defective products.

[0070] When the dynamic test benchmark value is higher than the fixed threshold, it means that the overall leakage current level of the current batch of products is high. In order to prevent defective products from flowing into subsequent processes, the fixed threshold is used as the screening criterion to ensure the consistency of quality requirements.

[0071] S04: Testing subsequent MLCC products on different test tracks, and sorting out qualified products and defective products according to the screening criteria.

[0072] After determining the screening criteria for each test track, the method of the present application enters the formal testing phase and performs screening operations on the MLCC products that enter the test later. The screening process mainly includes the following steps:

[0073] In the test equipment, MLCC products enter the disc holes of the test track in turn. The test probe applies a set voltage to the MLCC through the upper and lower electrodes and measures its leakage current value.

[0074] The test results are categorized according to the screening criteria for this test track:

[0075] If the measured leakage current value is ≤ the screening standard, the MLCC product is judged to be qualified (OK) and can proceed to the next process or packaging.

[0076] If the measured leakage current value > the screening standard, the MLCC product is judged as defective (NG) and is removed from the test track through an automatic rejection device to prevent it from entering subsequent production links.

[0077] The MLCC test sorting method of this application is more adaptable and stable than the traditional fixed threshold screening method:

[0078] Reduce misjudgment: Since the dynamic test benchmark value is generally lower than the fixed threshold, the screening criteria can be automatically adjusted according to the batch characteristics to avoid misjudgment caused by equipment status or batch fluctuations;

[0079] Prevent abnormal batches from affecting quality control: If the dynamic test benchmark value of a batch is too high, a fixed threshold is enforced to ensure that product quality does not decline;

[0080] Adapt to equipment aging: If the equipment is aged and the measurement is low, the dynamic test baseline value will be reduced accordingly, thus avoiding the screening criteria being too strict due to the change of equipment status.

[0081] In order to ensure the rationality of the screening criteria, the test data may need to be classified as a normal distribution or a skewed distribution to determine which screening strategy to use. In a preferred embodiment, the present application also includes analyzing the distribution characteristics of the test data in order to select an appropriate screening method.

[0082] The analysis process specifically includes calculating the skewness coefficient and kurtosis. The skewness coefficient is used to measure the symmetry of the data, that is, whether the data is evenly distributed around the mean. When the absolute value of the skewness coefficient is small (for example, less than 0.5), it means that the data is relatively symmetrical and close to the normal distribution; the kurtosis value is used to measure the steepness of the data distribution, whether it is sharper or flatter than the standard normal distribution. If the kurtosis value is between 2 and 4, it means that the data distribution is closer to the standard normal distribution.

[0083] Preferably, if the absolute value of the skewness coefficient is less than 0.5 and the kurtosis value is between 2 and 4, the test data set is determined to be normally distributed, and the mean and standard deviation can be used to calculate the screening criteria. Otherwise, it is determined to be a skewed distribution, and the percentile method is used to calculate the screening criteria.

[0084] In this embodiment, data distribution analysis is performed to ensure that the test data can match the best screening method and avoid screening bias caused by misjudgment of distribution type. The dual judgment criteria of skewness coefficient and kurtosis value are adopted to improve the accuracy of distribution identification and make the test results more reliable. The screening criteria are made more adaptable to the characteristics of different batches of MLCC products, improve product consistency, and reduce the screening misjudgment rate.

[0085] Preferably, in the process of testing subsequent MLCC products on different test tracks, when the set trigger condition is met, the following steps are also included:

[0086] Calculating a new dynamic test reference value of each test track according to the real-time test data on the test track;

[0087] The new dynamic test reference value is compared with the dynamic test reference value calculated last time, and if the deviation is greater than a first set deviation value, the screening criterion is updated according to the new dynamic test reference value.

[0088] During the test process, changes in equipment status, environmental factors, and batch characteristics may cause test data to shift, and the dynamic test benchmark value needs to be recalculated. In this embodiment, the method of the present application can monitor changes in MLCC product test data in real time and dynamically adjust the screening criteria when the trigger conditions are met.

[0089] If the newly calculated dynamic test reference value deviates greatly from the previously calculated value (exceeding the first set deviation value), the screening criteria will be automatically adjusted to ensure screening accuracy.

[0090] The adjustment process does not require human intervention and is completed automatically by the system, which improves the intelligence level of the production line.

[0091] This embodiment dynamically adjusts the screening criteria so that the method of the present application can adapt to changes in MLCC product parameters during the production process and avoid failure of the screening criteria; it ensures that the screening criteria are always based on the latest test data, thereby improving the real-time and accuracy of the screening.

[0092] Specifically, the set trigger condition includes at least one of the following: a set test time is reached, a set test quantity is reached.

[0093] The method of the present application uses test time and test quantity as trigger conditions to ensure that the calculation timing of the dynamic test benchmark value is reasonable; the test time is set to be suitable for a test system that runs continuously for a long time to prevent the screening criteria from becoming invalid due to long-term non-updates; the test quantity is set to be suitable for high-capacity production lines to ensure the statistical representativeness of the test data and improve the accuracy of the screening criteria.

[0094] This embodiment adopts two triggering methods to improve the flexibility of updating the screening criteria, avoid adjusting the screening criteria too early or too late, ensure the representativeness of the data, and improve the accuracy of screening; it is suitable for different production modes and improves the versatility of the method of this application.

[0095] In a preferred embodiment, the MLCC testing and sorting method of the present application further includes the following steps:

[0096] If the deviation between the new dynamic test reference value and the dynamic test reference value calculated last time is less than the second set deviation value, then extending the set test time or increasing the set test quantity;

[0097] If the deviation between the new dynamic test reference value and the dynamic test reference value calculated last time is greater than a third set deviation value, shortening the set test time or reducing the set test quantity;

[0098] If the deviation between the new dynamic test reference value and the dynamic test reference value calculated last time is greater than the second set deviation value and less than the third set deviation value, the set test time or the set test quantity is maintained unchanged;

[0099] The first set deviation value is greater than the second set deviation value and less than the third set deviation value.

[0100] The method of the present application can not only dynamically adjust the screening criteria, but also automatically optimize the test time or test quantity according to the fluctuation of the test data, thereby ensuring the rationality of the test frequency and screening accuracy.

[0101] If the deviation between the new dynamic test reference value and the previously calculated dynamic test reference value is less than the second set deviation value, it means that the test data fluctuates less, indicating that the production process is stable and the equipment is in normal condition. At this time, the test time interval can be appropriately extended or the number of tests can be increased to reduce unnecessary screening standard updates, improve production efficiency, and avoid too frequent screening standard adjustments.

[0102] If the deviation between the new dynamic test reference value and the previously calculated dynamic test reference value is greater than the third set deviation value: it means that the test data has changed significantly, which may be caused by factors such as production batch changes and equipment status changes. At this time, it is necessary to shorten the test time interval or reduce the number of tests in order to quickly respond to data changes and ensure that the screening criteria can be adjusted in time to avoid excessive screening errors.

[0103] If the deviation between the new dynamic test benchmark value and the previously calculated dynamic test benchmark value is greater than the second set deviation value and less than the third set deviation value: it means that the data fluctuation is within the acceptable range and the screening criteria are still applicable. At this time, the test time interval and test quantity remain unchanged, and the existing screening strategy is maintained.

[0104] This embodiment achieves intelligent optimization of screening standard updates by dynamically adjusting test time and test quantity, reduces unnecessary screening adjustments, and improves production efficiency; ensures the stability of screening standard updates to avoid unnecessary misjudgments caused by too frequent screening adjustments; enhances equipment adaptability, and can adaptively adjust the screening frequency according to factors such as equipment aging and production batch changes, thereby improving the long-term stability of screening.

[0105] In a preferred embodiment, the MLCC testing and sorting method of the present application further includes the following steps:

[0106] Obtain the dynamic test reference value obtained by the most recent N calculations, and calculate its rate of change;

[0107] If the rate of change is greater than a set rate threshold, an early warning is triggered.

[0108] In this embodiment, the method of the present application further introduces data change trend analysis, by calculating the change rate of the most recent N dynamic test benchmark values, to determine the stability of the test data, and trigger an early warning mechanism when necessary, so as to detect equipment or production abnormalities in advance.

[0109] During batch testing, the system will continuously record the dynamic test benchmark values ​​of multiple batches. By analyzing the most recent N benchmark values, the changing trend of the data can be observed.

[0110] The formula for calculating the rate of change is:

[0111] Change rate = (latest baseline value - baseline value N times ago) / N.

[0112] The rate of change reflects the fluctuation of the test data. If the change is too fast, it may indicate abnormal equipment status, large environmental changes, or fluctuations in the production process.

[0113] If the rate of change exceeds the set rate threshold, an early warning is triggered: the early warning information can be sent to the system interface or management personnel for manual intervention to check the equipment or process status.

[0114] The MLCC testing and sorting method of this embodiment can detect potential production anomalies or equipment problems in advance, prevent the failure of screening standards due to data drift, and improve production stability; enhance the predictive ability of the screening method, and can provide early warning before equipment or process failure occurs, improve maintenance efficiency, and reduce losses; the screening system is more intelligent, not only can it adapt to current data changes, but also can predict abnormal situations that may occur in the future.

[0115] In a more preferred embodiment, if the change rate is greater than a set rate threshold, and the deviation between the new dynamic test reference value and the dynamic test reference value calculated last time is greater than a first set deviation value, a shutdown is triggered.

[0116] In this embodiment, the method of the present application can not only trigger an early warning, but also automatically trigger a shutdown when the data changes exceed an acceptable range to prevent a large number of defective products from flowing into subsequent production processes.

[0117] Triggering shutdown conditions: the rate of change is greater than the set rate threshold (meaning that the data is drifting rapidly), and at the same time, the deviation between the newly calculated dynamic test reference value and the previous calculated value is greater than the first set deviation value (meaning that the reference value has changed significantly). When these two conditions are met at the same time, the shutdown is automatically triggered.

[0118] When a shutdown is triggered, the system performs the following actions:

[0119] Suspend the operation of test equipment to prevent a large number of abnormal products from entering the subsequent process.

[0120] A shutdown alarm is issued to notify maintenance personnel to check the equipment status, including the contact condition of the test electrodes, the degree of equipment aging, the stability of the power supply, etc.

[0121] Record abnormal data to analyze downtime causes and optimize screening criteria when restarting equipment.

[0122] The MLCC testing and sorting method of this embodiment can prevent a large number of NG products from flowing into subsequent processes due to equipment abnormalities or changes in production batches, thereby improving the quality control capability of the production line; reduce the risk of large-scale misjudgment, avoid a large number of qualified products being misjudged as defective products due to sudden failure of screening standards, and improve the yield rate; improve the intelligence level of the production process, and the system can automatically shut down according to data trends, reduce manual intervention, and improve management efficiency.

[0123] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described 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.

[0124] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims, and the description may be used to interpret the contents of the claims.

Claims

1. A test sorting method for MLCC, applied to a test device including a plurality of annular test tracks, characterized in that: The method comprises the following steps: Batch test the MLCC products on different test tracks, and obtain test data of each test track respectively; Calculate the dynamic test reference value of each test track based on the distribution of the test data and a preset value selection strategy of the test track; Compare each of the dynamic test reference values ​​with a preset fixed threshold value to determine a screening criterion for each test track: when the dynamic test reference value is lower than the fixed threshold value, the screening criterion is the dynamic test reference value; when the dynamic test reference value is higher than the fixed threshold value, the screening criterion is the fixed threshold value; Subsequent MLCC products are tested on different test tracks, and qualified products and defective products are sorted out according to the screening criteria.

2. The MLCC testing and sorting method according to claim 1, characterized in that: Based on the distribution of the test data of each test track and a preset value strategy, a dynamic test reference value of the test track is calculated, including: If the test data conforms to a normal distribution, the dynamic test reference value is calculated according to the mean and standard deviation of the test data; If the test data conforms to the skewed distribution, the percentile value of the test track data is calculated as the dynamic test reference value.

3. The MLCC testing and sorting method according to claim 2, characterized in that: The calculation method of dynamic test benchmark value under normal distribution includes: Calculate the mean μ and standard deviation σ of the test data; Adopt μ+3σ as the dynamic test benchmark value; The calculation method of dynamic test reference value under skewed distribution includes: Calculate the 99.865% percentile P of the test data 99.865 , and use it as the dynamic test benchmark value.

4. The MLCC testing and sorting method according to claim 2, characterized in that: The following steps are also included: Calculating the skewness coefficient and kurtosis value of the test data; When the absolute value of the skewness coefficient is less than a preset threshold value and the kurtosis value is within a preset range, it is determined that the test data conforms to a normal distribution; Otherwise, it is determined that the test data conforms to the skewed distribution.

5. The MLCC testing and sorting method according to claim 4, characterized in that: The preset threshold is less than 0.5, and the preset range of the kurtosis value is between 2 and 4.

6. The MLCC testing and sorting method according to claim 2, characterized in that: In the process of testing subsequent MLCC products on different test tracks, when the set trigger conditions are met, the following steps are also included: Calculating a new dynamic test reference value of each test track according to the real-time test data on the test track; The new dynamic test reference value is compared with the dynamic test reference value calculated last time, and if the deviation is greater than a first set deviation value, the screening criterion is updated according to the new dynamic test reference value.

7. The MLCC testing and sorting method according to claim 6, characterized in that: The setting trigger condition includes at least one of the following: The set test time is reached, the set test quantity is reached.

8. The MLCC testing and sorting method according to claim 7, characterized in that: The following steps are also included: If the deviation between the new dynamic test reference value and the dynamic test reference value calculated last time is less than the second set deviation value, then extending the set test time or increasing the set test quantity; If the deviation between the new dynamic test reference value and the dynamic test reference value calculated last time is greater than a third set deviation value, shortening the set test time or reducing the set test quantity; If the deviation between the new dynamic test reference value and the dynamic test reference value calculated last time is greater than the second set deviation value and less than the third set deviation value, the set test time is maintained or the set test quantity is shortened; The first set deviation value is greater than the second set deviation value and less than the third set deviation value.

9. The MLCC testing and sorting method according to claim 6, characterized in that: The following steps are also included: Obtain the dynamic test reference value obtained by the most recent N calculations, and calculate its rate of change; If the rate of change is greater than a set rate threshold, an early warning is triggered.

10. The MLCC testing and sorting method according to claim 9, characterized in that: The following steps are also included: If the change rate is greater than a set rate threshold, and the deviation between the new dynamic test reference value and the dynamic test reference value calculated last time is greater than a first set deviation value, a shutdown is triggered.

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