A quality evaluation method of a memory chip

Abstract

The application relates to the technical field of data analysis, and particularly discloses a quality evaluation method for storage chips, which comprises the following steps: S1: determining a quality parameter of a target chip, and obtaining a quality score of the target chip; S2: generating a coordinate point, fitting the coordinate point to obtain a fitting curve, determining an abnormality proportion according to the fitting curve, determining a judgment value according to the total abnormality proportion and the fitting curve, calculating an average judgment value, and determining an abnormal production line; and S3: dividing a production serial number interval to obtain a production serial number subinterval, and carrying out sampling inspection on the storage chips in the production serial number subinterval. The application can improve the detection efficiency and reduce the omission of quality problem chips.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data analysis, and particularly relates to a quality evaluation method of a storage chip. BACKGROUND

[0002] The storage chip is a semiconductor device for storing data, and its main function is to save programs and data and to automatically complete program or data access at high speed during computer operation. As a core component of modern electronic devices, the quality of the storage chip is directly related to the performance of the device and the user experience.

[0003] The quality evaluation of the storage chip requires professional technical personnel and detection equipment. In the actual production process, a large number of storage chips need to be evaluated one by one, which consumes a large amount of labor and time cost. In order to reduce the cost and improve the overall detection efficiency, the batch chips are usually evaluated by sampling inspection. However, the conventional sampling inspection method may miss a large number of storage chips with quality problems, affecting the reliability of the entire product batch. SUMMARY

[0004] The purpose of the present application is to provide a quality evaluation method of a storage chip, which solves the following technical problems:

[0005] The conventional sampling inspection method may miss a large number of storage chips with quality problems, affecting the reliability of the entire product batch.

[0006] The purpose of the present application can be achieved by the following technical solutions:

[0007] A quality evaluation method of a storage chip, comprising the following steps:

[0008] S1: obtaining the sampling record of the storage chip, marking the storage chip in the sampling record as a target chip, determining the quality parameters of the target chip, the quality parameters including read delay H1, write delay H2 and erase time H3, and determining the quality score D of the target chip as D=H1+H2+H3;

[0009] S2: generating a coordinate point (Bi, Di), Bi representing the production serial number of the i-th target chip, and Di representing the quality score of the i-th target chip, fitting the coordinate points to obtain a fitting curve f(x), and x representing the production serial number;

[0010] Marking the curve part of the a-th fitting curve above the b-th fitting curve as an abnormal curve, counting the proportion of the abnormal curve in the a-th fitting curve as an abnormal proportion, calculating the total abnormal proportion A, and calculating a judgment value C, the calculation formula of which is:

[0011]

[0012] Wherein, Ast, Aend represent the minimum production serial number and the maximum production serial number of the target chip respectively;

[0013] Calculate the average judgment value CPJ, when the screening value AC = C-CPJ >= ACys, the production line corresponding to the screening value C is regarded as the abnormal production line;

[0014] S3: Calculate the sampling length BCS represents the preset initial sampling length, and β represents the preset first correction coefficient and β>1, The production serial number interval [BDQ, BYC] is divided into n production serial number sub-intervals of the same length, BDQ represents the current production serial number, the pending production serial number BYC=BDQ+BCJ, n is a preset number, and the storage chips corresponding to the production serial number sub-intervals are sampled according to the preset sampling ratio.

[0015] As a further scheme of the application: the process of sampling the storage chips corresponding to the production serial number sub-intervals in step S3 specifically includes:

[0016] The production serial number sub-intervals are sorted in time sequence to obtain a sub-interval order, and the sampling ratio CJk of the kth production serial number sub-interval in the sorting is 1-μ*k / n, k<n, and μ is a preset coefficient and μ<1. Cj1*(BYC-BDQ) / n storage chips are randomly selected in the first production serial number sub-interval for detection;

[0017] Determine the proportion F of the number of chips with a quality score higher than the quality score threshold to the sampling number CJ1*(BYC-BDQ) / n corresponding to the first production serial number sub-interval, update the sampling ratio CJ2 corresponding to the second production serial number sub-interval, and the updated value is CJ2*F*η, and η represents a preset update coefficient;

[0018] Repeat the above steps until the sampling of the nth production serial number sub-interval is completed.

[0019] As a further scheme of the application: in step S2, when the sampling length BCJ is greater than or equal to the preset production serial number difference, send a warning message for reporting.

[0020] As a further scheme of the application: in step S2, the following steps are further included:

[0021] The ratio of the number of abnormal proportions of 0 to the total number of abnormal proportions is calculated, and when the ratio is less than a preset ratio threshold, the corresponding production line is not regarded as an abnormal production line.

[0022] As a further scheme of the present application: in step S2, when the judgment value C is greater than or equal to Cys, the corresponding production line is marked as an abnormal production line, and Cys represents a preset judgment value threshold.

[0023] As a further scheme of the present application: in step S2, the process of calculating the average judgment value further includes the following steps:

[0024] The variance of the judgment value is calculated, when the variance is greater than a preset variance threshold, the minimum judgment value is removed and the variance is calculated again until the variance is less than or equal to the variance threshold.

[0025] The beneficial effects of the present application: in this scheme, by determining the quality parameter of each chip and scoring the quality of each chip, the quality of each chip can be more objectively and accurately evaluated, the subjective factors are reduced, after establishing the scoring system, the data can be analyzed and decided, the scientificity and accuracy of detection are improved; then, the fitting curve of the relationship between the production serial number and the quality score is determined, the judgment value is determined according to the fitting curve, the production lines with poor overall quality performance are identified, all production lines do not need to be checked one by one, the abnormal production line that needs to be focused on is quickly screened out through A and C values, time and resources are saved; it is worth noting that one production serial number corresponds to one time, one production serial number corresponds to one chip produced by the production line, therefore, the fitting curve can be regarded as a curve of the quality score of a single production line changing with time, it is worth noting that the production serial number in this scheme is a virtual production serial number, the production serial numbers of different memory chips are different in actual situation, while in this scheme, the production serial numbers of the mth memory chips produced on different production lines are the same (i.e. the virtual production serial number), m is an arbitrary real number; then, the potential problem serial number interval (i.e. the production serial number interval [BDQ, BYC]) is predicted, by dividing the sub-interval and dynamically adjusting the sampling ratio, it is ensured that the high-risk sub-interval is detected with higher frequency, the probability of missing defective chips is reduced, the sampling process is refined, the detection is more targeted, time and resources are saved, and the detection coverage is improved. The present application not only effectively reduces the labor and time cost, but also significantly improves the detection efficiency and accuracy, reduces the omission of quality problem chips, and thus improves the reliability and market competitiveness of the entire product batch. BRIEF DESCRIPTION OF DRAWINGS

[0026] The present application will be further described below with reference to the accompanying drawings.

[0027] Figure 1 is a flowchart of a quality evaluation method of a memory chip according to the present application. DETAILED DESCRIPTION

[0028] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described, obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0029] Please refer to Figure 1 The present application is a quality evaluation method of a storage chip, comprising the following steps:

[0030] S1: obtaining the sampling record of the storage chip, marking the storage chip in the sampling record as a target chip, determining the quality parameter of the target chip, the quality parameter comprising read delay H1, write delay H2 and erase time H3, determining the quality score D of the target chip H1+H2+H3;

[0031] S2: generating a coordinate point (Bi, Di), Bi representing the production serial number of the i-th target chip, Di representing the quality score of the i-th target chip, fitting the coordinate point to obtain a fitting curve f(x), x representing the production serial number;

[0032] marking the curve part of the a-th fitting curve above the b-th fitting curve as an abnormal curve, counting the proportion of the abnormal curve in the a-th fitting curve as an abnormal proportion, calculating the total abnormal proportion A, calculating the judgment value C, and the calculation formula is:

[0033]

[0034] Wherein, Asta and Aend represent the minimum production serial number and the maximum production serial number of the target chip respectively;

[0035] calculating the average judgment value CPJ, when the screening value ΔC=C-CPJ≥ΔCys, the production line corresponding to the screening value C is regarded as an abnormal production line;

[0036] S3: calculating the sampling length BCS represents the preset initial sampling length, β represents the preset first correction coefficient and β>1, represents rounding down C*β, dividing the production serial number interval [BDQ, BYC] into n production serial number sub-intervals with the same length, BDQ represents the current production serial number, the to-be-determined production serial number BYC=BDQ+BCJ, n is a preset number, and the storage chips corresponding to the production serial number sub-intervals are sampled according to the preset sampling ratio.

[0037] It should be noted that by determining the quality parameters of each chip and scoring the quality of each chip, the quality of each chip can be more objectively and accurately evaluated, the subjective factors are reduced, after the scoring system is established, data analysis and decision-making can be carried out, and the scientificity and accuracy of detection are improved; then, the fitting curve of the relationship between the production serial number and the quality score is determined, the judgment value is determined according to the fitting curve, the production lines with poor overall quality performance are identified, all production lines do not need to be checked one by one, the abnormal production line that needs to be focused on is quickly screened out through A and C values, time and resources are saved; it should be noted that one production serial number corresponds to one time, one production serial number corresponds to one chip produced by the production line, therefore, the fitting curve can be regarded as a curve of the quality score of a single production line changing with time, it should be noted that the production serial number in the scheme is a virtual production serial number, the production serial numbers of different storage chips are different in actual situation, and in the scheme, the production serial numbers of the mth storage chips produced on different production lines are the same (that is, the virtual production serial number), and m is any real number; then, a potential problem serial number interval (that is, a production serial number interval [BDQ, BYC]) is predicted, by dividing the sub-interval and dynamically adjusting the sampling ratio, it is ensured that the high-risk sub-interval is detected more frequently, the probability of missing defective chips is reduced, the sampling process is refined, the detection is more targeted, time and resources are saved, and the detection coverage is improved.

[0038] In another preferred embodiment of the application, the step S3 of sampling the storage chips corresponding to the production serial number sub-interval specifically comprises the following steps.

[0039] The production serial number sub-intervals are sorted in time sequence to obtain a sub-interval sequence, the sampling ratio CJk of the kth production serial number sub-interval in the sorting is CJk=1-μ*k / n, k

[0040] The proportion F of the number of chips with a quality score higher than the quality score threshold to the sampling number CJ1*(BYC-BDQ) / n corresponding to the first production serial number sub-interval is determined, the sampling ratio CJ2 corresponding to the second production serial number sub-interval is updated, and the updated value is CJ2*F*η, wherein η represents a preset update coefficient.

[0041] The above steps are repeated until the sampling of the nth production serial number sub-interval is completed.

[0042] And it is worth noting that by updating the sampling ratio of the next sub-interval after sampling each sub-interval, the sampling strategy is not rigid, forming an automatic adjustment mechanism; compared with the fixed proportion sampling scheme, this method can allocate more sampling resources to the intervals that need more attention, to improve the overall detection efficiency and avoid excessive sampling or insufficient sampling.

[0043] In another preferred embodiment of the present application, in the step S2, when the sampling length BCJ is greater than or equal to the preset production serial number difference, a warning information is sent for reporting.

[0044] In another preferred embodiment of the present application, the step S2 further comprises the following steps:

[0045] The ratio of the number of abnormal proportions of 0 to the total number of abnormal proportions is calculated, and when the ratio is less than a preset ratio threshold value, the corresponding production line is not regarded as an abnormal production line.

[0046] In another preferred embodiment of the present application, in the step S2, when the judgment value C is greater than or equal to Cys, the corresponding production line is marked as an abnormal production line, and Cys represents a preset judgment value threshold.

[0047] In another preferred embodiment of the present application, in the step S2, in the process of calculating the average judgment value, the following steps are further included:

[0048] The variance of the judgment value is calculated, and when the variance is greater than a preset variance threshold value, the minimum judgment value is removed and the variance is calculated again until the variance is less than or equal to the variance threshold value.

[0049] The above describes one embodiment of the present application in detail, but the content described is only the preferred embodiment of the present application, and cannot be considered as limiting the scope of the present application. Any equivalent changes and improvements made in the scope of the present application should still belong to the scope of the present application.

Claims

1. A quality evaluation method of a memory chip, characterized by, The method is used for transverse comparison of different production lines, and comprises the following steps: S1: obtaining the sampling record of the storage chip, marking the storage chip in the sampling record as a target chip, determining the quality parameter of the target chip, the quality parameter comprising read delay H1, write delay H2 and erase time H3, and determining the quality score D of the target chip H1+H2+H3; S2: generating coordinate points (B i , D i ), B i represents the production serial number of the i-th target chip, D i represents the quality score of the i-th target chip, and the coordinate points of each production line are fitted respectively to obtain a fitting curve f(x) of a single production line, wherein x represents the production serial number, the production serial numbers of the memory chips on different production lines are the same, and one production serial number corresponds to one time; Marking the curve part of the a-th fitting curve above the b-th fitting curve as an abnormal curve, counting the proportion of the abnormal curve in the a-th fitting curve as an abnormal proportion, calculating the total abnormal proportion A, and calculating the judgment value C, the calculation formula of which is: ； Wherein, Asta and Aend represent the minimum production serial number and the maximum production serial number of the target chip respectively; Calculating the average judgment value CPJ, and when the screening value ΔC=C-CPJ≥ΔCys, the production line corresponding to the screening value C is regarded as an abnormal production line; S3: calculating the sampling length BCS represents a preset initial sampling length, β represents a preset first correction coefficient and β > 1, representing that C*β is rounded down, the production serial number interval [BDQ, BYC] is divided into n production serial number sub-intervals of the same length, BDQ represents the current production serial number, the pending production serial number BYC = BDQ + BCS, n is a preset number, and the storage chips corresponding to the production serial number sub-intervals are sampled according to a preset sampling ratio.

2. The method of claim 1, wherein, The process of sampling the storage chip corresponding to the production serial number sub-interval in step S3 comprises the following steps: The sub-intervals are sorted according to the time axis to obtain a sub-interval sequence, and the sampling ratio CJ of the kth production serial number sub-interval corresponds to k =1-μ*k / n, k In the first production serial number sub-interval, CJ1* (BYC-BDQ) / n storage chips are randomly selected for detection. Determining the proportion F of the number of chips with a quality score higher than the quality score threshold in the sampling number CJ1* (BYC-BDQ) / n corresponding to the first production serial number sub-interval, updating the sampling proportion CJ2 corresponding to the second production serial number sub-interval, and the updated value is CJ2*F*η, wherein η represents a preset update coefficient; Repeat the above steps until the sampling of the n-th production serial number sub-interval is completed.

3. The method of claim 1, wherein, In step S2, when the sampling length BCJ is greater than or equal to the preset production serial number difference, send a warning information for reporting.

4. The method of claim 1, wherein, In step S2, the following steps are further included: Counting the ratio of the number of abnormal proportions of 0 to the total number of abnormal proportions, and when the ratio is less than a preset ratio threshold, the corresponding production line is not regarded as an abnormal production line.

5. The method of claim 1, wherein, In step S2, when the judgment value C≥Cys, the corresponding production line is marked as an abnormal production line, and Cys represents a preset judgment value threshold.

6. The method of claim 1, wherein, In step S2, the process of calculating the average judgment value further comprises the following steps: Calculating the variance of the judgment value, when the variance is greater than a preset variance threshold, removing the minimum judgment value and calculating the variance again until the variance is less than or equal to the variance threshold.

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