A method, system and medium for improving the yield of storage-computing integrated chip

Abstract

The present application provides a method, system and medium for improving the yield of integrated storage and computing chips. The method includes: according to a preset number of production process data in the production process of the integrated storage and computing chip, processing to obtain effective lithography data, effective thin film deposition data, effective ion implantation data, effective annealing data and effective pickling data, and respectively calculating to obtain the first process yield influencing data and the second process yield influencing data, obtaining standard production environment data and real-time production environment data and calculating to obtain the process environment yield influencing factor, and then calculating to obtain the process comprehensive yield influencing parameter, and then obtaining the process yield influencing state data and production process processing scheme through threshold comparison; thereby further realizing the technology of improving the yield of integrated storage and computing chips through calculation and analysis based on the comprehensive process yield influencing parameter.

Description

Technical Field

[0001] The present application relates to the field of integrated storage and computing chips, and more specifically, to a method, system and medium for improving the yield of integrated storage and computing chips. Background Art

[0002] With the rapid development of information technology, integrated storage and computing chips, as a new computing architecture, have shown great application potential in the fields of big data processing and artificial intelligence. However, due to the complexity and particularity of the production process of integrated storage and computing chips, their yield is often seriously affected. There are problems of low yield and unstable yield in the manufacturing process, which seriously affects the production cost and market competitiveness of the chip. Therefore, how to improve the yield of integrated storage and computing chips has become a problem that needs to be solved at present.

[0003] In view of the above problems, effective technical solutions are urgently needed. Summary of the invention

[0004] The purpose of this application is to provide a method, system and medium for improving the yield of storage and computing integrated chips, which can further realize the technology of improving the yield of storage and computing integrated chips by calculating and analyzing the parameters affecting the comprehensive process yield.

[0005] The present application also provides a method for improving the yield of a storage-computing integrated chip, comprising the following steps:

[0006] Obtain a preset amount of production process data during the production process of the storage-computing integrated chip, and process and obtain effective production process data, including effective photolithography data, effective thin film deposition data, effective ion implantation data, effective annealing data, and effective pickling data;

[0007] Calculate and obtain the first process yield impact data according to the effective photolithography data and the effective thin film deposition data;

[0008] Calculate and obtain the second process yield impact data according to the effective ion implantation data, the effective annealing data and the effective pickling data;

[0009] Obtain standard production environment data and real-time production environment data, and calculate the process environment yield influencing factors based on the standard production environment data and the real-time production environment data;

[0010] Obtaining a comprehensive process yield influencing parameter by calculation according to the first process yield influencing data, the second process yield influencing data and the process environment yield influencing factor;

[0011] Comparing the process comprehensive yield impact parameter with a preset process comprehensive yield impact threshold to obtain process yield impact state data;

[0012] A production process treatment plan is obtained according to the matching of the process yield influencing status data.

[0013] Optionally, in the method for improving the yield of the integrated storage and computing chip described in the present application, the obtaining of a preset amount of production process data in the production process of the integrated storage and computing chip, and processing to obtain effective production process data, including effective lithography data, effective thin film deposition data, effective ion implantation data, effective annealing data, and effective pickling data, specifically includes:

[0014] Obtain a preset number of production process data in the production process of the storage-computing integrated chip, calculate the average value of the production process data, and obtain effective production process data;

[0015] The effective production process data includes effective photolithography data, effective thin film deposition data, effective ion implantation data, effective annealing data and effective pickling data;

[0016] Extract light source wavelength data, exposure measurement data, focal length data and hole diameter data according to effective lithography data;

[0017] Extracting uniformity data, thickness data, step coverage data and film forming rate data according to the effective thin film deposition data;

[0018] Extracting dose Q data and energy KE data according to the effective ion implantation data;

[0019] Extracting temperature setting data, holding time data and cooling rate data according to the effective annealing data;

[0020] Acid solution concentration data, pickling temperature data and pickling time data are extracted according to the effective pickling data.

[0021] Optionally, in the method for improving the yield of the integrated storage and computing chip described in the present application, the first process yield influencing data is calculated based on the effective lithography data and the effective thin film deposition data, specifically including:

[0022] Inputting the light source wavelength data, exposure metering data, focal length data, hole diameter data, uniformity data, thickness data, step coverage data, and film forming rate data into a preset process first yield impact model for processing to obtain process first yield impact data;

[0023] The calculation formula of the process first yield impact data in the process first yield impact model is:

[0024] ;

[0025] in, The first yield rate impact data for the process, is the light source wavelength data, is the exposure metering data, is the focal length data, is the hole diameter data, is the uniformity data, is the thickness data, is the step coverage data, is the film forming rate data, , , , , , , , , , , , is the preset characteristic coefficient.

[0026] Optionally, in the method for improving the yield of the integrated storage and computing chip described in the present application, the second process yield influencing data is calculated based on the effective ion implantation data, the effective annealing data, and the effective pickling data, specifically including:

[0027] Input the dose Q data, energy KE data, temperature setting data, holding time data, cooling rate data, acid concentration data, pickling temperature data and pickling time data into a preset process second yield impact model for processing, and obtain process second yield impact data;

[0028] The calculation formula of the process second yield impact data in the process second yield impact model is:

[0029] ;

[0030] in, This is the process second yield impact data, is the dose Q data, is the energy KE data, is the acid concentration data, is the pickling temperature data, is the pickling time data, Set the data for temperature. is the holding time data, is the cooling rate data, , , , , , , , , , , , , , , , , , , is the preset characteristic coefficient.

[0031] Optionally, in the method for improving the yield of the integrated storage and computing chip described in the present application, the obtaining of standard production environment data and real-time production environment data, and calculating the process environment yield influencing factor according to the standard production environment data and the real-time production environment data specifically include:

[0032] Obtain standard production environment data, including standard temperature data, standard humidity data and standard cleanliness data;

[0033] Obtain real-time production environment data, including real-time temperature data, real-time humidity data, and real-time cleanliness data;

[0034] Calculate and obtain the process environment yield influencing factor according to the standard temperature data, standard humidity data, standard cleanliness data, real-time temperature data, real-time humidity data and real-time cleanliness data;

[0035] The calculation formula of the process environment yield influencing factor is:

[0036] ;

[0037] in, is the process environment yield influencing factor, , , They are real-time temperature data, real-time humidity data and real-time cleanliness data. , , They are standard temperature data, standard humidity data and standard cleanliness data. , , is the preset characteristic coefficient.

[0038] Optionally, in the method for improving the yield of the integrated storage and computing chip described in the present application, the process comprehensive yield influencing parameter is calculated based on the first process yield influencing data, the second process yield influencing data and the process environment yield influencing factor, specifically including:

[0039] Inputting the first process yield influencing data, the second process yield influencing data and the process environment yield influencing factor into a preset process comprehensive yield model for processing to obtain a process comprehensive yield influencing parameter;

[0040] The calculation formula of the process comprehensive yield influencing parameter in the process comprehensive yield model is:

[0041] ;

[0042] in, The parameters that affect the comprehensive process yield are: The first yield rate impact data for the process, This is the process second yield impact data, is the process environment yield influencing factor, , and The preset characteristic coefficient

[0043] Optionally, in the method for improving the yield of a storage-computing integrated chip described in the present application, the step of comparing the process comprehensive yield influencing parameter with a preset process comprehensive yield influencing threshold to obtain process yield influencing status data specifically includes:

[0044] Comparing the process comprehensive yield impact parameter with a preset process comprehensive yield impact threshold to obtain process yield impact state data;

[0045] Extracting a first threshold and a second threshold according to the process comprehensive yield impact threshold, and the first threshold is greater than the second threshold;

[0046] Comparing the comprehensive process yield influencing parameter with the first threshold and the second threshold;

[0047] If the process comprehensive yield influencing parameter is greater than the first threshold, the process yield influencing state data is accurate operation data;

[0048] If the process comprehensive yield influencing parameter is greater than the second threshold and less than or equal to the first threshold, the process yield influencing state data is buffer state data;

[0049] If the comprehensive process yield influencing parameter is less than or equal to the second threshold, the process yield influencing status data is early warning adjustment status data.

[0050] Optionally, in the method for improving the yield of the integrated storage and computing chip described in the present application, obtaining the production process processing scheme according to the process yield influencing state data matching specifically includes:

[0051] Obtaining a production process treatment plan according to the process yield impact status data, including a maintenance process, a load fine-tuning process or a no-load adjustment process;

[0052] If the process yield influencing state data is accurate operation data, the production process treatment plan is to maintain the process;

[0053] If the process yield influencing state data is buffer state data, the production process processing solution is a load fine-tuning process;

[0054] The process yield impact status data is early warning adjustment status data, and the production process processing solution is a no-load adjustment process.

[0055] In a second aspect, the present application provides a system for improving the yield of a storage-computing integrated chip, the system comprising: a memory and a processor, the memory comprising a program of a method for improving the yield of a storage-computing integrated chip, and the program of the method for improving the yield of a storage-computing integrated chip is executed by the processor to implement the following steps:

[0056] Obtain a preset amount of production process data during the production process of the integrated storage and computing chip, and process and obtain effective production process data, including effective photolithography data, effective thin film deposition data, effective ion implantation data, effective annealing data, and effective pickling data;

[0057] Calculate and obtain the first process yield influencing data according to the effective photolithography data and the effective thin film deposition data;

[0058] Calculate and obtain the second process yield impact data according to the effective ion implantation data, the effective annealing data and the effective pickling data;

[0059] Obtain standard production environment data and real-time production environment data, and calculate the process environment yield influencing factors based on the standard production environment data and the real-time production environment data;

[0060] Obtaining a comprehensive process yield influencing parameter by calculation according to the first process yield influencing data, the second process yield influencing data and the process environment yield influencing factor;

[0061] Comparing the process comprehensive yield impact parameter with a preset process comprehensive yield impact threshold to obtain process yield impact state data;

[0062] A production process treatment plan is obtained according to the matching of the process yield influencing status data.

[0063] In the third aspect, the present application also provides a readable storage medium, which includes a method program for improving the yield of a storage and computing integrated chip. When the method program for improving the yield of a storage and computing integrated chip is executed by a processor, the steps of the method for improving the yield of a storage and computing integrated chip as described in any one of the above items are implemented.

[0064] From the above, it can be seen that the method, system and medium for improving the yield of storage-computing integrated chips provided by the present application. The method obtains effective lithography data, effective thin film deposition data, effective ion implantation data, effective annealing data and effective pickling data according to a preset number of production process data in the production process of the storage-computing integrated chip, and respectively calculates and obtains the first process yield influencing data and the second process yield influencing data, obtains the standard production environment data and the real-time production environment data and calculates and obtains the process environment yield influencing factor, and then calculates and obtains the process comprehensive yield influencing parameters, and then obtains the process yield influencing status data and the production process processing scheme through threshold comparison; thereby, through the calculation and analysis based on the comprehensive process yield influencing parameters, the technology for improving the yield of storage-computing integrated chips is further realized.

[0065] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or understood by practicing the present application. The purpose and other advantages of the present application can be realized and obtained by the structures particularly pointed out in the written description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0067] Figure 1 A flow chart of a method for improving the yield of a storage-computing integrated chip provided in an embodiment of the present application;

[0068] Figure 2 A flow chart of obtaining effective production process data for a method for improving the yield of a storage-computing integrated chip provided in an embodiment of the present application;

[0069] Figure 3 A flow chart of obtaining process environment yield influencing factors for the method of improving the yield of a storage-computing integrated chip provided in an embodiment of the present application. DETAILED DESCRIPTION

[0070] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0071] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0072] Please refer to Figure 1 , Figure 1 1 is a flow chart of a method for improving the yield of a storage-computing integrated chip in some embodiments of the present application. The method for improving the yield of a storage-computing integrated chip is used in a terminal device, such as a computer. The method for improving the yield of a storage-computing integrated chip includes the following steps:

[0073] S11, obtaining a preset amount of production process data in the production process of the storage-computing integrated chip, and processing to obtain effective production process data, including effective lithography data, effective thin film deposition data, effective ion implantation data, effective annealing data, and effective pickling data;

[0074] S12, calculating and obtaining the first process yield influencing data according to the effective photolithography data and the effective thin film deposition data;

[0075] S13, calculating and obtaining the second process yield influencing data according to the effective ion implantation data, the effective annealing data and the effective pickling data;

[0076] S14, obtaining standard production environment data and real-time production environment data, and calculating the process environment yield influencing factor according to the standard production environment data and the real-time production environment data;

[0077] S15, calculating and obtaining a comprehensive process yield influencing parameter according to the first process yield influencing data, the second process yield influencing data and the process environment yield influencing factor;

[0078] S16, comparing the process comprehensive yield influencing parameter with a preset process comprehensive yield influencing threshold to obtain process yield influencing status data;

[0079] S17, obtaining a production process treatment plan according to the process yield influencing state data matching.

[0080] Among them, the production of integrated storage and computing chips is a very complex process, so there are many influencing factors. In the production process, the process links involve many factors, which are crucial to the impact of integrated storage and computing chips. Therefore, the improvement and control of the process links can improve the yield of integrated storage and computing chips; obtain a preset number of production process data in the production process of integrated storage and computing chips, and then obtain effective production process data, including effective lithography data, effective thin film deposition data, effective ion implantation data, effective annealing data, and effective pickling data, and then calculate the process first yield impact data, process second yield impact data and process environment yield impact factor, and then process to obtain the process comprehensive yield impact parameters, compare the process comprehensive yield impact parameters with thresholds to obtain process yield impact status data, and finally obtain the production process processing plan; through the processing of different production process processing plans, the technology of improving the yield of integrated storage and computing chips is realized.

[0081] Please refer to Figure 2 , Figure 2 It is a flowchart of obtaining effective production process data of the method for improving the yield of the integrated storage and computing chip provided by the embodiment of the present application. According to the embodiment of the present invention, the acquisition of a preset amount of production process data in the production process of the integrated storage and computing chip, and processing to obtain effective production process data, including effective lithography data, effective thin film deposition data, effective ion implantation data, effective annealing data and effective pickling data, specifically includes:

[0082] S21, obtaining a preset number of production process data in the production process of the storage-computing integrated chip, calculating an average value of the production process data, and obtaining effective production process data;

[0083] S22, the effective production process data includes effective lithography data, effective thin film deposition data, effective ion implantation data, effective annealing data and effective pickling data;

[0084] S23, extracting light source wavelength data, exposure measurement data, focal length data, and hole diameter data according to the effective lithography data;

[0085] S24, extracting uniformity data, thickness data, step coverage data and film formation rate data according to the effective thin film deposition data;

[0086] S25, extracting dose Q data and energy KE data according to the effective ion implantation data;

[0087] S26, extracting temperature setting data, holding time data and cooling rate data according to the effective annealing data;

[0088] S27. Extracting acid solution concentration data, pickling temperature data and pickling time data according to the effective pickling data.

[0089] Among them, the production process of the storage and computing integrated chip involves many influencing factors, and this is a dynamic process. In order to better reflect the production process data, it is necessary to obtain a preset number of production process data. The preset number can be customized according to user needs, and the method for obtaining the preset number of production process data can also be set according to user needs. In this example, a fixed time period interval sampling method is adopted; the obtained production process data are added respectively and divided by the number of data to obtain the average value, and then the effective production process data is obtained. The effective production process data refers to representative data that can stably reflect the production process data; the effective production process data includes effective lithography data, effective thin film deposition data, effective ion implantation data, effective annealing data and effective pickling data. Lithography is a major process in the production of planar transistors and integrated circuits. Effective lithography data refers to representative data that can effectively reflect the relevant data in the lithography process. Thin film deposition is a technology for preparing extremely thin material layers on the surface of a substrate. These films are usually at the micron or nanometer level and usually have a single crystal or polycrystalline structure. Effective thin film deposition data refers to data that can effectively reflect the thin film. Representative data of relevant data in the film deposition process. Similarly, the effective ion implantation data, effective annealing data and effective pickling data in the production process of the integrated computing chip can be known; the light source wavelength data, exposure measurement data, focal length data and hole diameter data are extracted based on the effective lithography data. The light source wavelength data, exposure measurement data, focal length data and hole diameter data are all commonly used parameters in the chip production process; similarly, the uniformity data, thickness data, step coverage data and film formation rate data are extracted based on the effective thin film deposition data. The step coverage data refers to the thickness of the thin film at the step ( The relative relationship between the thickness at the bottom or side wall and the thickness at the flat surface is an indicator to measure the thickness loss of the film when it crosses the surface steps (such as holes, uneven places); extract the dose Q data and energy KE data based on the effective ion implantation data; the dose Q data represents the number of ions injected per unit area of ​​the target surface, and the energy KE data is generally expressed as the product of the electron charge and the potential difference; extract the temperature setting data, the holding time data and the cooling rate data based on the effective annealing data; extract the acid concentration data, the pickling temperature data and the pickling time data based on the effective pickling data.

[0090] According to an embodiment of the present invention, the step of calculating and obtaining the first process yield influencing data according to the effective lithography data and the effective thin film deposition data specifically includes:

[0091] Inputting the light source wavelength data, exposure metering data, focal length data, hole diameter data, uniformity data, thickness data, step coverage data, and film forming rate data into a preset process first yield influence model for processing to obtain process first yield influence data;

[0092] The calculation formula of the process first yield impact data in the process first yield impact model is:

[0093] ;

[0094] in, The first yield rate impact data for the process, is the light source wavelength data, is the exposure metering data, is the focal length data, is the hole diameter data, is the uniformity data, is the thickness data, is the step coverage data, is the film forming rate data, , , , , , , , , , , and It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset storage and computing integrated chip yield improvement platform).

[0095] Among them, the preset process first yield influence model is a calculation model obtained by acquiring a large amount of historical production process data and then conducting model training. The process first yield influence data can be calculated based on the light source wavelength data, exposure measurement data, focal length data, hole diameter data, uniformity data, thickness data, step coverage data and film formation rate data. The process first yield influence data refers to the data on the degree of reaction influence obtained by comprehensively considering the effective lithography data and the effective thin film deposition data.

[0096] According to an embodiment of the present invention, the second process yield influencing data is calculated based on the effective ion implantation data, the effective annealing data and the effective pickling data, specifically including:

[0097] Input the dose Q data, energy KE data, temperature setting data, holding time data, cooling rate data, acid concentration data, pickling temperature data and pickling time data into a preset process second yield impact model for processing, and obtain process second yield impact data;

[0098] The calculation formula of the process second yield impact data in the process second yield impact model is:

[0099] ;

[0100] in, This is the process second yield impact data, is the dose Q data, is the energy KE data, is the acid concentration data, is the pickling temperature data, is the pickling time data, Set the data for temperature. is the holding time data, is the cooling rate data, , , , , , , , , , , , , , , , , , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset storage and computing integrated chip yield improvement platform).

[0101] Among them, the influencing factors of the production process are diverse. The effective ion implantation data, effective annealing data and effective pickling data also affect the yield of the storage and computing integrated chip. The second process yield influencing data can be calculated based on the dose Q data, energy KE data, temperature setting data, holding time data, cooling rate data, acid concentration data, pickling temperature data and pickling time data. The second process yield influencing data refers to the data on the degree of reaction influence obtained by comprehensively considering the effective ion implantation data, effective annealing data and effective pickling data; the preset second process yield influencing model is a calculation model obtained by model training after obtaining a large amount of historical production process data. The second process yield influencing data can be calculated based on the dose Q data, energy KE data, temperature setting data, holding time data, cooling rate data, acid concentration data, pickling temperature data and pickling time data.

[0102] Please refer to Figure 3 , Figure 3This is a flow chart of obtaining process environment yield influencing factors for improving the yield of a storage-computing integrated chip provided by an embodiment of the present application. According to an embodiment of the present invention, obtaining standard production environment data and real-time production environment data, and calculating and obtaining process environment yield influencing factors based on the standard production environment data and the real-time production environment data specifically include:

[0103] S31. Obtain standard production environment data, including standard temperature data, standard humidity data, and standard cleanliness data;

[0104] S32, obtaining real-time production environment data, including real-time temperature data, real-time humidity data and real-time cleanliness data;

[0105] S33, calculating and obtaining the process environment yield influencing factor according to the standard temperature data, standard humidity data, standard cleanliness data, real-time temperature data, real-time humidity data and real-time cleanliness data;

[0106] The calculation formula of the process environment yield influencing factor is:

[0107] ;

[0108] in, is the process environment yield influencing factor, , , They are real-time temperature data, real-time humidity data and real-time cleanliness data. , , They are standard temperature data, standard humidity data and standard cleanliness data. , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the platform for improving the yield of the storage-computing integrated chip).

[0109] Among them, the production of storage and computing integrated chips, in addition to the production process parameters, must also comprehensively consider the production environment, which includes standard production environment data and real-time production environment data. Standard production environment data refers to the environmental data when the standard yield is achieved when producing chips, and real-time production environment data refers to the real-time production environment data when producing storage and computing integrated chips. Since the real-time production environment data is changing and has an impact on the yield of storage and computing integrated chips, the process environment yield influencing factor is calculated after comprehensively considering the standard production environment data and the real-time production environment data. The process environment yield influencing factor refers to the data on the degree of influence of the environment in the process link on the yield in the production of storage and computing integrated chips.

[0110] According to an embodiment of the present invention, the process comprehensive yield impact parameter is calculated based on the first process yield impact data, the second process yield impact data and the process environment yield impact factor, specifically including:

[0111] Inputting the first process yield influencing data, the second process yield influencing data and the process environment yield influencing factor into a preset process comprehensive yield model for processing to obtain a process comprehensive yield influencing parameter;

[0112] The calculation formula of the process comprehensive yield influencing parameter in the process comprehensive yield model is:

[0113] ;

[0114] in, The parameters that affect the comprehensive process yield are: The first yield rate impact data for the process, This is the process second yield impact data, is the process environment yield influencing factor, , and It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset storage and computing integrated chip yield improvement platform).

[0115] Among them, the first process yield influencing data, the second process yield influencing data and the process environment yield influencing factors all affect the production yield of the storage and computing integrated chip. Therefore, they need to be considered comprehensively to calculate the process comprehensive yield influencing parameters. The process comprehensive yield influencing parameters refer to the data on the degree of influence of the production process on the production yield of the storage and computing integrated chip. The preset process comprehensive yield model is obtained by obtaining a large amount of historical production process data, and then training and analyzing the model.

[0116] According to an embodiment of the present invention, the step of comparing the process comprehensive yield influencing parameter with a preset process comprehensive yield influencing threshold to obtain process yield influencing status data specifically includes:

[0117] Comparing the process comprehensive yield impact parameter with a preset process comprehensive yield impact threshold to obtain process yield impact state data;

[0118] Extracting a first threshold and a second threshold according to the process comprehensive yield impact threshold, and the first threshold is greater than the second threshold;

[0119] Comparing the comprehensive process yield influencing parameter with the first threshold and the second threshold;

[0120] If the process comprehensive yield influencing parameter is greater than the first threshold, the process yield influencing state data is accurate operation data;

[0121] If the process comprehensive yield influencing parameter is greater than the second threshold and less than or equal to the first threshold, the process yield influencing state data is buffer state data;

[0122] If the comprehensive process yield influencing parameter is less than or equal to the second threshold, the process yield influencing status data is early warning adjustment status data.

[0123] Among them, the process comprehensive yield influencing parameters directly affect the yield of the storage and computing integrated chip. Therefore, by comparing the process comprehensive yield influencing parameters with the preset process comprehensive yield influencing threshold, the process yield influencing status data can be obtained. The process yield influencing status data includes precise operation data, buffer status data or early warning adjustment status data. The precise operation data means that the process comprehensive yield influencing parameters are reasonable. Under this condition, the production yield of the storage and computing integrated chip meets the standard; the buffer status data means that the process comprehensive yield influencing parameters are within the allowable range, but the data needs to be improved. Under this condition, although the production yield of the storage and computing integrated chip meets the standard, there is a risk of falling to unqualified; the early warning adjustment status data means that the process comprehensive yield influencing parameters are no longer reasonable, the production yield of the storage and computing integrated chip is low and does not meet the standard, and the production process data needs to be adjusted immediately; in this embodiment, the process comprehensive yield influencing threshold is set to: [0, 0.88), early warning adjustment status data; [0.88, 0.92), buffer status data; [0.92, 1], precise operation data; when the process comprehensive yield influencing parameter is calculated to be 0.89, the process yield influencing status data is buffer status data. In this embodiment, the precise operation data is 10, the buffer status data is 1, and the warning adjustment status data is 0.

[0124] According to an embodiment of the present invention, obtaining a production process processing scheme according to the process yield influencing state data matching specifically includes:

[0125] Obtaining a production process treatment plan according to the process yield impact status data, including a maintenance process, a load fine-tuning process or a no-load adjustment process;

[0126] If the process yield influencing state data is accurate operation data, the production process treatment plan is to maintain the process;

[0127] If the process yield influencing state data is buffer state data, the production process processing solution is a load fine-tuning process;

[0128] The process yield impact status data is early warning adjustment status data, and the production process processing solution is a no-load adjustment process.

[0129] Among them, the production process handling plan refers to the production status and process adjustment status obtained according to the process yield influencing status data; the maintenance process means that the production process data remains unchanged and the production proceeds normally; the load fine-tuning process means that the production of the storage and computing integrated chip continues, and the production process is optimized and adjusted at the same time; the no-load adjustment process means that due to the high chip production defect rate, in order to reduce production waste, the material supply of the storage and computing integrated chip production is suspended, and the production process data is immediately optimized.

[0130] The present invention also discloses a system for improving the yield of a storage-computing integrated chip, comprising a memory and a processor, wherein the memory comprises a method program for improving the yield of the storage-computing integrated chip, and when the method program for improving the yield of the storage-computing integrated chip is executed by the processor, the following steps are implemented:

[0131] Obtain a preset amount of production process data during the production process of the storage-computing integrated chip, and process and obtain effective production process data, including effective photolithography data, effective thin film deposition data, effective ion implantation data, effective annealing data, and effective pickling data;

[0132] Calculate and obtain the first process yield impact data according to the effective photolithography data and the effective thin film deposition data;

[0133] Calculate and obtain the second process yield impact data according to the effective ion implantation data, the effective annealing data and the effective pickling data;

[0134] Obtain standard production environment data and real-time production environment data, and calculate the process environment yield influencing factors based on the standard production environment data and the real-time production environment data;

[0135] Obtaining a comprehensive process yield influencing parameter by calculation according to the first process yield influencing data, the second process yield influencing data and the process environment yield influencing factor;

[0136] Comparing the process comprehensive yield impact parameter with a preset process comprehensive yield impact threshold to obtain process yield impact state data;

[0137] A production process treatment plan is obtained according to the matching of the process yield influencing status data.

[0138] Among them, the production of integrated storage and computing chips is a very complex process, so there are many influencing factors. In the production process, the process links involve many factors, which are crucial to the impact of integrated storage and computing chips. Therefore, the improvement and control of the process links can improve the yield of integrated storage and computing chips; obtain a preset number of production process data in the production process of integrated storage and computing chips, and then obtain effective production process data, including effective lithography data, effective thin film deposition data, effective ion implantation data, effective annealing data, and effective pickling data, and then calculate the process first yield impact data, process second yield impact data and process environment yield impact factor, and then process to obtain the process comprehensive yield impact parameters, compare the process comprehensive yield impact parameters with thresholds to obtain process yield impact status data, and finally obtain the production process processing plan; through the processing of different production process processing plans, the technology of improving the yield of integrated storage and computing chips is realized.

[0139] According to an embodiment of the present invention, the acquisition of a preset amount of production process data in the production process of the storage-computing integrated chip and processing to obtain effective production process data, including effective lithography data, effective thin film deposition data, effective ion implantation data, effective annealing data and effective pickling data, specifically includes:

[0140] Obtain a preset number of production process data in the production process of the storage-computing integrated chip, calculate the average value of the production process data, and obtain effective production process data;

[0141] The effective production process data includes effective photolithography data, effective thin film deposition data, effective ion implantation data, effective annealing data and effective pickling data;

[0142] Extract light source wavelength data, exposure measurement data, focal length data and hole diameter data according to effective lithography data;

[0143] Extracting uniformity data, thickness data, step coverage data and film forming rate data according to the effective thin film deposition data;

[0144] Extracting dose Q data and energy KE data according to the effective ion implantation data;

[0145] Extracting temperature setting data, holding time data and cooling rate data according to the effective annealing data;

[0146] Acid solution concentration data, pickling temperature data and pickling time data are extracted according to the effective pickling data.

[0147] Among them, the production process of the storage and computing integrated chip involves many influencing factors, and this is a dynamic process. In order to better reflect the production process data, it is necessary to obtain a preset number of production process data. The preset number can be customized according to user needs, and the method for obtaining the preset number of production process data can also be set according to user needs. In this example, a fixed time period interval sampling method is adopted; the obtained production process data are added respectively and divided by the number of data to obtain the average value, and then the effective production process data is obtained. The effective production process data refers to representative data that can stably reflect the production process data; the effective production process data includes effective lithography data, effective thin film deposition data, effective ion implantation data, effective annealing data and effective pickling data. Lithography is a major process in the production of planar transistors and integrated circuits. Effective lithography data refers to representative data that can effectively reflect the relevant data in the lithography process. Thin film deposition is a technology for preparing extremely thin material layers on the surface of a substrate. These films are usually at the micron or nanometer level and usually have a single crystal or polycrystalline structure. Effective thin film deposition data refers to data that can effectively reflect the thin film. Representative data of relevant data in the film deposition process. Similarly, the effective ion implantation data, effective annealing data and effective pickling data in the production process of the integrated computing chip can be known; the light source wavelength data, exposure measurement data, focal length data and hole diameter data are extracted based on the effective lithography data. The light source wavelength data, exposure measurement data, focal length data and hole diameter data are all commonly used parameters in the chip production process; similarly, the uniformity data, thickness data, step coverage data and film formation rate data are extracted based on the effective thin film deposition data. The step coverage data refers to the thickness of the thin film at the step ( The relative relationship between the thickness at the bottom or side wall and the thickness at the flat surface is an indicator to measure the thickness loss of the film when it crosses the surface steps (such as holes, uneven places); extract the dose Q data and energy KE data based on the effective ion implantation data; the dose Q data represents the number of ions injected per unit area of ​​the target surface, and the energy KE data is generally expressed as the product of the electron charge and the potential difference; extract the temperature setting data, the holding time data and the cooling rate data based on the effective annealing data; extract the acid concentration data, the pickling temperature data and the pickling time data based on the effective pickling data.

[0148] According to an embodiment of the present invention, the step of calculating and obtaining the first process yield influencing data according to the effective lithography data and the effective thin film deposition data specifically includes:

[0149] Inputting the light source wavelength data, exposure metering data, focal length data, hole diameter data, uniformity data, thickness data, step coverage data, and film forming rate data into a preset process first yield influence model for processing to obtain process first yield influence data;

[0150] The calculation formula of the process first yield impact data in the process first yield impact model is:

[0151] ;

[0152] in, The first yield rate impact data for the process, is the light source wavelength data, is the exposure metering data, is the focal length data, is the hole diameter data, is the uniformity data, is the thickness data, is the step coverage data, is the film forming rate data, , , , , , , , , , , and It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset storage and computing integrated chip yield improvement platform).

[0153] Among them, the preset process first yield influence model is a calculation model obtained by acquiring a large amount of historical production process data and then conducting model training. The process first yield influence data can be calculated based on the light source wavelength data, exposure measurement data, focal length data, hole diameter data, uniformity data, thickness data, step coverage data and film formation rate data. The process first yield influence data refers to the data on the degree of reaction influence obtained by comprehensively considering the effective lithography data and the effective thin film deposition data.

[0154] According to an embodiment of the present invention, the second process yield influencing data is calculated based on the effective ion implantation data, the effective annealing data and the effective pickling data, specifically including:

[0155] Input the dose Q data, energy KE data, temperature setting data, holding time data, cooling rate data, acid concentration data, pickling temperature data and pickling time data into a preset process second yield impact model for processing, and obtain process second yield impact data;

[0156] The calculation formula of the process second yield impact data in the process second yield impact model is:

[0157] ;

[0158] in, This is the process second yield impact data, is the dose Q data, is the energy KE data, is the acid concentration data, is the pickling temperature data, is the pickling time data, Set the data for temperature. is the holding time data, is the cooling rate data, , , , , , , , , , , , , , , , , , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset storage and computing integrated chip yield improvement platform).

[0159] Among them, the influencing factors of the production process are diverse. The effective ion implantation data, effective annealing data and effective pickling data also affect the yield of the storage and computing integrated chip. The second process yield influencing data can be calculated based on the dose Q data, energy KE data, temperature setting data, holding time data, cooling rate data, acid concentration data, pickling temperature data and pickling time data. The second process yield influencing data refers to the data on the degree of reaction influence obtained by comprehensively considering the effective ion implantation data, effective annealing data and effective pickling data; the preset second process yield influencing model is a calculation model obtained by model training after obtaining a large amount of historical production process data. The second process yield influencing data can be calculated based on the dose Q data, energy KE data, temperature setting data, holding time data, cooling rate data, acid concentration data, pickling temperature data and pickling time data.

[0160] According to an embodiment of the present invention, the acquiring of standard production environment data and real-time production environment data, and calculating the process environment yield influencing factor according to the standard production environment data and the real-time production environment data, specifically includes:

[0161] Obtain standard production environment data, including standard temperature data, standard humidity data and standard cleanliness data;

[0162] Obtain real-time production environment data, including real-time temperature data, real-time humidity data, and real-time cleanliness data;

[0163] Calculate and obtain the process environment yield influencing factor according to the standard temperature data, standard humidity data, standard cleanliness data, real-time temperature data, real-time humidity data and real-time cleanliness data;

[0164] The calculation formula of the process environment yield influencing factor is:

[0165] ;

[0166] in, is the process environment yield influencing factor, , , They are real-time temperature data, real-time humidity data and real-time cleanliness data. , , They are standard temperature data, standard humidity data and standard cleanliness data. , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the platform for improving the yield of the storage-computing integrated chip).

[0167] Among them, the production of storage and computing integrated chips, in addition to the production process parameters, must also comprehensively consider the production environment, which includes standard production environment data and real-time production environment data. Standard production environment data refers to the environmental data when the standard yield is achieved when producing chips, and real-time production environment data refers to the real-time production environment data when producing storage and computing integrated chips. Since the real-time production environment data is changing and has an impact on the yield of storage and computing integrated chips, the process environment yield influencing factor is calculated after comprehensively considering the standard production environment data and the real-time production environment data. The process environment yield influencing factor refers to the data on the degree of influence of the environment in the process link on the yield in the production of storage and computing integrated chips.

[0168] According to an embodiment of the present invention, the process comprehensive yield impact parameter is calculated based on the first process yield impact data, the second process yield impact data and the process environment yield impact factor, specifically including:

[0169] Inputting the first process yield influencing data, the second process yield influencing data and the process environment yield influencing factor into a preset process comprehensive yield model for processing to obtain a process comprehensive yield influencing parameter;

[0170] The calculation formula of the process comprehensive yield influencing parameter in the process comprehensive yield model is:

[0171] ;

[0172] in, The parameters that affect the comprehensive process yield are: The first yield rate impact data for the process, This is the process second yield impact data, is the process environment yield influencing factor, , and It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset storage and computing integrated chip yield improvement platform).

[0173] Among them, the first process yield influencing data, the second process yield influencing data and the process environment yield influencing factors all affect the production yield of the storage and computing integrated chip. Therefore, they need to be considered comprehensively to calculate the process comprehensive yield influencing parameters. The process comprehensive yield influencing parameters refer to the data on the degree of influence of the production process on the production yield of the storage and computing integrated chip. The preset process comprehensive yield model is obtained by obtaining a large amount of historical production process data, and then training and analyzing the model.

[0174] According to an embodiment of the present invention, the step of comparing the process comprehensive yield influencing parameter with a preset process comprehensive yield influencing threshold to obtain process yield influencing status data specifically includes:

[0175] Comparing the process comprehensive yield impact parameter with a preset process comprehensive yield impact threshold to obtain process yield impact state data;

[0176] Extracting a first threshold and a second threshold according to the process comprehensive yield impact threshold, and the first threshold is greater than the second threshold;

[0177] Comparing the comprehensive process yield influencing parameter with the first threshold and the second threshold;

[0178] If the process comprehensive yield influencing parameter is greater than the first threshold, the process yield influencing state data is accurate operation data;

[0179] If the process comprehensive yield influencing parameter is greater than the second threshold and less than or equal to the first threshold, the process yield influencing state data is buffer state data;

[0180] If the comprehensive process yield influencing parameter is less than or equal to the second threshold, the process yield influencing status data is early warning adjustment status data.

[0181] Among them, the process comprehensive yield influencing parameters directly affect the yield of the storage and computing integrated chip. Therefore, by comparing the process comprehensive yield influencing parameters with the preset process comprehensive yield influencing threshold, the process yield influencing status data can be obtained. The process yield influencing status data includes precise operation data, buffer status data or early warning adjustment status data. The precise operation data means that the process comprehensive yield influencing parameters are reasonable. Under this condition, the production yield of the storage and computing integrated chip meets the standard; the buffer status data means that the process comprehensive yield influencing parameters are within the allowable range, but the data needs to be improved. Under this condition, although the production yield of the storage and computing integrated chip meets the standard, there is a risk of falling to unqualified; the early warning adjustment status data means that the process comprehensive yield influencing parameters are no longer reasonable, the production yield of the storage and computing integrated chip is low and does not meet the standard, and the production process data needs to be adjusted immediately; in this embodiment, the process comprehensive yield influencing threshold is set to: [0, 0.88), early warning adjustment status data; [0.88, 0.92), buffer status data; [0.92, 1], precise operation data; when the process comprehensive yield influencing parameter is calculated to be 0.89, the process yield influencing status data is buffer status data. In this embodiment, the precise operation data is 10, the buffer status data is 1, and the warning adjustment status data is 0.

[0182] According to an embodiment of the present invention, obtaining a production process processing scheme according to the process yield influencing state data matching specifically includes:

[0183] Obtaining a production process treatment plan according to the process yield impact status data, including a maintenance process, a load fine-tuning process or a no-load adjustment process;

[0184] If the process yield influencing state data is accurate operation data, the production process treatment plan is to maintain the process;

[0185] If the process yield influencing state data is buffer state data, the production process processing solution is a load fine-tuning process;

[0186] The process yield impact status data is early warning adjustment status data, and the production process processing solution is a no-load adjustment process.

[0187] Among them, the production process handling plan refers to the production status and process adjustment status obtained according to the process yield influencing status data; the maintenance process means that the production process data remains unchanged and the production proceeds normally; the load fine-tuning process means that the production of the storage and computing integrated chip continues, and the production process is optimized and adjusted at the same time; the no-load adjustment process means that due to the high chip production defect rate, in order to reduce production waste, the material supply of the storage and computing integrated chip production is suspended, and the production process data is immediately optimized.

[0188] A third aspect of the present invention provides a readable storage medium, which includes a method program for improving the yield of a storage and computing integrated chip. When the method program for improving the yield of a storage and computing integrated chip is executed by a processor, the steps of the method for improving the yield of a storage and computing integrated chip as described in any one of the above items are implemented.

[0189] The method, system and medium for improving the yield of integrated storage and computing chips disclosed in the present invention process a preset number of production process data in the production process of the integrated storage and computing chips to obtain effective lithography data, effective thin film deposition data, effective ion implantation data, effective annealing data and effective pickling data, and respectively calculate the first process yield influencing data and the second process yield influencing data, obtain standard production environment data and real-time production environment data and calculate the process environment yield influencing factor, and then calculate the process comprehensive yield influencing parameters, and then obtain the process yield influencing status data and the production process processing plan through threshold comparison; thereby, through the calculation and analysis based on the comprehensive process yield influencing parameters, the technology for improving the yield of integrated storage and computing chips is further realized.

[0190] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0191] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0192] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0193] Those skilled in the art can understand that: all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, the aforementioned program can be stored in a readable storage medium, and when the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), disks or optical disks, and other media that can store program codes.

[0194] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

Claims

1. A method for improving the yield of a storage-computing integrated chip, characterized in that: include: Obtain a preset amount of production process data during the production process of the integrated storage and computing chip, and process and obtain effective production process data, including effective photolithography data, effective thin film deposition data, effective ion implantation data, effective annealing data, and effective pickling data; Calculate and obtain the first process yield impact data according to the effective photolithography data and the effective thin film deposition data; Calculate and obtain the second process yield impact data according to the effective ion implantation data, the effective annealing data and the effective pickling data; Obtain standard production environment data and real-time production environment data, and calculate the process environment yield influencing factors based on the standard production environment data and the real-time production environment data; Obtaining a comprehensive process yield influencing parameter by calculation according to the first process yield influencing data, the second process yield influencing data and the process environment yield influencing factor; Comparing the process comprehensive yield impact parameter with a preset process comprehensive yield impact threshold to obtain process yield impact state data; Obtaining a production process treatment plan according to the process yield influencing state data matching; Obtain a preset number of production process data in the production process of the storage-computing integrated chip, calculate the average value of the production process data, and obtain effective production process data; The effective production process data includes effective photolithography data, effective thin film deposition data, effective ion implantation data, effective annealing data and effective pickling data; Extract light source wavelength data, exposure measurement data, focal length data and hole diameter data according to effective lithography data; Extracting uniformity data, thickness data, step coverage data and film forming rate data according to the effective thin film deposition data; Extracting dose Q data and energy KE data according to the effective ion implantation data; Extracting temperature setting data, holding time data and cooling rate data according to the effective annealing data; Extracting acid concentration data, pickling temperature data and pickling time data according to the effective pickling data; Inputting the light source wavelength data, exposure metering data, focal length data, hole diameter data, uniformity data, thickness data, step coverage data, and film forming rate data into a preset process first yield impact model for processing to obtain process first yield impact data; The calculation formula of the process first yield impact data in the process first yield impact model is: ； in, The first yield rate impact data for the process, is the light source wavelength data, is the exposure metering data, is the focal length data, is the hole diameter data, is the uniformity data, is the thickness data, is the step coverage data, is the film forming rate data, , , , , , , , , , , , is the preset characteristic coefficient; Input the dose Q data, energy KE data, temperature setting data, holding time data, cooling rate data, acid concentration data, pickling temperature data and pickling time data into a preset process second yield impact model for processing, and obtain process second yield impact data; The calculation formula of the process second yield impact data in the process second yield impact model is: ； in, This is the process second yield impact data, is the dose Q data, is the energy KE data, is the acid concentration data, is the pickling temperature data, is the pickling time data, Set the data for temperature. is the holding time data, is the cooling rate data, , , , , , , , , , , , , , , , , , , is the preset characteristic coefficient.

2. The method for improving the yield of a storage-computing integrated chip according to claim 1, characterized in that: The obtaining of standard production environment data and real-time production environment data, and calculating the process environment yield influencing factor according to the standard production environment data and the real-time production environment data, specifically includes: Obtain standard production environment data, including standard temperature data, standard humidity data and standard cleanliness data; Obtain real-time production environment data, including real-time temperature data, real-time humidity data, and real-time cleanliness data; Calculate and obtain the process environment yield influencing factor according to the standard temperature data, standard humidity data, standard cleanliness data, real-time temperature data, real-time humidity data and real-time cleanliness data; The calculation formula of the process environment yield influencing factor is: ； in, is the process environment yield influencing factor, , , They are real-time temperature data, real-time humidity data and real-time cleanliness data. , , They are standard temperature data, standard humidity data and standard cleanliness data. , , is the preset characteristic coefficient.

3. The method for improving the yield of a storage-computing integrated chip according to claim 2, characterized in that: The process comprehensive yield impact parameter is calculated based on the first process yield impact data, the second process yield impact data and the process environment yield impact factor, specifically including: Inputting the first process yield influencing data, the second process yield influencing data and the process environment yield influencing factor into a preset process comprehensive yield model for processing to obtain a process comprehensive yield influencing parameter; The calculation formula of the process comprehensive yield influencing parameter in the process comprehensive yield model is: ； in, The parameters that affect the comprehensive process yield are: The first yield rate impact data for the process, This is the process second yield impact data, is the process environment yield influencing factor, , and is the preset characteristic coefficient.

4. The method for improving the yield of a storage-computing integrated chip according to claim 3, characterized in that: The step of comparing the process comprehensive yield impact parameter with a preset process comprehensive yield impact threshold to obtain process yield impact state data specifically includes: Comparing the process comprehensive yield impact parameter with a preset process comprehensive yield impact threshold to obtain process yield impact state data; Extracting a first threshold and a second threshold according to the process comprehensive yield impact threshold, and the first threshold is greater than the second threshold; Comparing the comprehensive process yield influencing parameter with the first threshold and the second threshold; If the process comprehensive yield influencing parameter is greater than the first threshold, the process yield influencing state data is accurate operation data; If the process comprehensive yield influencing parameter is greater than the second threshold and less than or equal to the first threshold, the process yield influencing state data is buffer state data; If the comprehensive process yield influencing parameter is less than or equal to the second threshold, the process yield influencing status data is early warning adjustment status data.

5. The method for improving the yield of a storage-computing integrated chip according to claim 4, characterized in that: The obtaining of a production process processing scheme according to the process yield impact state data matching specifically includes: Obtaining a production process treatment plan according to the process yield impact status data, including a maintenance process, a load fine-tuning process or a no-load adjustment process; If the process yield influencing state data is accurate operation data, the production process treatment plan is to maintain the process; If the process yield influencing state data is buffer state data, the production process processing solution is a load fine-tuning process; The process yield impact status data is early warning adjustment status data, and the production process processing solution is a no-load adjustment process.

6. A system for improving the yield of integrated storage and computing chips, characterized in that: The invention comprises a memory and a processor, wherein the memory comprises a method program for improving the yield of a storage-computing integrated chip, and the method program for improving the yield of a storage-computing integrated chip is executed by the processor to implement the following steps: Obtain a preset amount of production process data during the production process of the integrated storage and computing chip, and process and obtain effective production process data, including effective photolithography data, effective thin film deposition data, effective ion implantation data, effective annealing data, and effective pickling data; Calculate and obtain the first process yield impact data according to the effective photolithography data and the effective thin film deposition data; Calculate and obtain the second process yield impact data according to the effective ion implantation data, the effective annealing data and the effective pickling data; Obtain standard production environment data and real-time production environment data, and calculate the process environment yield influencing factors based on the standard production environment data and the real-time production environment data; Obtaining a comprehensive process yield influencing parameter by calculation according to the first process yield influencing data, the second process yield influencing data and the process environment yield influencing factor; Comparing the process comprehensive yield impact parameter with a preset process comprehensive yield impact threshold to obtain process yield impact state data; Obtaining a production process treatment plan according to the process yield influencing state data matching; Obtain a preset number of production process data in the production process of the storage-computing integrated chip, calculate the average value of the production process data, and obtain effective production process data; The effective production process data includes effective photolithography data, effective thin film deposition data, effective ion implantation data, effective annealing data and effective pickling data; Extract light source wavelength data, exposure measurement data, focal length data and hole diameter data according to effective lithography data; Extracting uniformity data, thickness data, step coverage data and film forming rate data according to the effective thin film deposition data; Extracting dose Q data and energy KE data according to the effective ion implantation data; Extracting temperature setting data, holding time data and cooling rate data according to the effective annealing data; Extracting acid concentration data, pickling temperature data and pickling time data according to the effective pickling data; Inputting the light source wavelength data, exposure metering data, focal length data, hole diameter data, uniformity data, thickness data, step coverage data, and film forming rate data into a preset process first yield impact model for processing to obtain process first yield impact data; The calculation formula of the process first yield impact data in the process first yield impact model is: ； in, The first yield rate impact data for the process, is the light source wavelength data, is the exposure metering data, is the focal length data, is the hole diameter data, is the uniformity data, is the thickness data, is the step coverage data, is the film forming rate data, , , , , , , , , , , , is the preset characteristic coefficient; Input the dose Q data, energy KE data, temperature setting data, holding time data, cooling rate data, acid concentration data, pickling temperature data and pickling time data into a preset process second yield impact model for processing, and obtain process second yield impact data; The calculation formula of the process second yield impact data in the process second yield impact model is: ； in, This is the process second yield impact data, is the dose Q data, is the energy KE data, is the acid concentration data, is the pickling temperature data, is the pickling time data, Set the data for temperature. is the holding time data, is the cooling rate data, , , , , , , , , , , , , , , , , , , is the preset characteristic coefficient.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a method program for improving the yield of a storage-computing integrated chip. When the method program for improving the yield of a storage-computing integrated chip is executed by a processor, the steps of the method for improving the yield of a storage-computing integrated chip as described in any one of claims 1 to 5 are implemented.

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