A process simulation method and system for three-dimensional chip

Abstract

This invention relates to the field of process simulation technology, specifically disclosing a method and system for simulating the process of a three-dimensional chip, comprising the following steps: Step S1: Obtain the processing cycle, select several nodes according to a set time interval threshold, and obtain the physical parameters and environmental indicators at each node; associate the physical parameters with the corresponding environmental indicators to form processing data; Step S2: Collect all historical processing data, number each node, and generate processing change curves of physical parameters changing over time; calculate the average rate of change of these curves, and combine them with the associated environmental indicator values ​​in the historical data to generate parameter change curves; Step S3: Obtain the environmental indicators during the simulation process and compare them with the environmental indicators in the historical processing data; Step S4: Continuously monitor the physical parameters, obtain the current processing change curve and its average rate of change, and calculate the difference value.

Description

Technical Field

[0001] This invention relates to the field of process simulation technology, specifically to a method and system for process simulation of three-dimensional chips. Background Technology

[0002] Process simulation realistically reproduces specific technological processes in a three-dimensional virtual environment, allowing users to operate process equipment or modify relevant parameters in real time. It uses computer technology to generate realistic virtual environments that can simulate various processes in semiconductor manufacturing. This simulation technology can efficiently model and simulate the entire process, thereby helping engineers identify and solve potential problems during the design phase.

[0003] 3D chip process simulation is a computer-based simulation process used to predict and optimize various physical and chemical phenomena in semiconductor manufacturing. It utilizes a realistic virtual environment generated by computer technology to simulate various processes in semiconductor manufacturing.

[0004] In existing technologies, although 3D process simulation can provide a lot of valuable information, its results often differ from the actual chip performance in production. This is because simulation models are usually based on idealized assumptions and simplified physical models, while there may be more uncertainties and complexities in reality. For example, chemical or physical models cannot fully capture complex manufacturing processes and physical phenomena, such as uneven temperature distribution and changes in chemical reaction rates. These factors are ignored or simplified in the simulation, leading to deviations between the simulation results and the actual situation. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for simulating the process of three-dimensional chips, thereby solving the above-mentioned technical problems.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] A method for simulating the process of a three-dimensional chip includes the following steps:

[0008] Step S1: Obtain the time period from the start to the end of chip processing, and record it as the processing cycle; set a time interval threshold, and select several nodes within the processing cycle according to the time interval threshold; obtain the physical parameters at each node to obtain real-time physical parameters, including size and roughness; and obtain all environmental indicators within the processing cycle, including temperature and chemical reaction rate; associate each physical parameter with an environmental indicator, and record all real-time physical parameters and all environmental indicators within the processing cycle as processing data;

[0009] Step S2: Obtain all historical processing data, number each node in the historical processing data, and generate a processing change curve of physical parameters based on the physical parameters at each node;

[0010] Obtain the average rate of change of the processing change curve of the physical parameter, and obtain the values ​​of environmental indicators associated with the physical parameter in historical processing data. Generate the parameter change curve based on the values ​​of each environmental indicator and its corresponding average rate of change.

[0011] Step S3: Before performing process simulation on the chip, obtain various environmental indicators for the process simulation, and record them as simulation environment indicators; compare all simulation environment indicators with the environmental indicators in the historical processing data to obtain the similarity between the environmental indicators and the historical processing data. Where n is the total number of environmental indicators, Z i Z represents the i-th environmental indicator. i ′ represents the i-th simulation environment index, i∈[1,n]; select the environment index of the historical processing data with the highest similarity and record the historical processing data as the class processing data;

[0012] Step S4: When performing process simulation on the chip, the physical parameters being monitored are recorded as monitored physical parameters; the monitored physical parameters are acquired in real time to obtain a processing change curve, which is recorded as the current processing change curve; the average change rate of the current processing change curve is acquired in real time and recorded as the current change rate R; the simulation environment index associated with the real-time monitored physical parameters is acquired, and the value of the simulation environment index is acquired and recorded as Z′; the difference value Dv=|Rf(Z′)| is obtained in real time, where f(Z′) is the expression of the parameter change curve when the value of the environment index is Z′; if the difference value exceeds a preset difference threshold, the monitored physical parameters are corrected.

[0013] As a further aspect of the present invention, the process of associating each physical parameter with an environmental indicator includes:

[0014] Select any environmental indicator as the environmental indicator to be tested, and record the remaining environmental indicators as the remaining environmental indicators; in all historical processing data, select several historical processing data in which all other environmental indicators are consistent and only the environmental indicator to be tested is consistent, and record them as verification data; obtain the physical parameters of the verification data at the end of processing, and compare the physical parameters between the verification data.

[0015] As a further aspect of the present invention: the process of comparing the physical parameters between various verification data includes:

[0016] Arbitrarily select one validation data point from all validation data as the standard validation data. The physical parameters of the standard validation data are denoted as standard physical parameters P0, and the test environment index of the standard validation data is denoted as standard environmental index Z0. Obtain the index difference Cz = |Z-Z0| between the test environment index Z of the validation data and the standard environmental index, and obtain the parameter difference Cp = |P-P0| between the physical parameters P of the validation data and the standard physical parameters. Based on the parameter differences corresponding to each index difference, obtain the dataset, and obtain the correlation coefficient between the index differences and parameter differences within the dataset. Judge the correlation coefficient.

[0017] As a further aspect of the present invention, the process of determining the correlation coefficient includes:

[0018] A correlation coefficient threshold is set, and the threshold range is [0.8, 0.95]. The correlation coefficient r between the index difference and the parameter difference in the dataset is obtained. If |r|∈[0.8, 0.95], the physical parameter is associated with the environmental index to be tested; if |r| does not belong to [0.8, 0.95], the physical parameter is not associated with the environmental index to be tested.

[0019] As a further aspect of the present invention: the process of generating the processing change curve includes:

[0020] A rectangular coordinate system is established with the node number as the x-axis and the physical parameter value as the y-axis. The physical parameters under each node number are converted into coordinate points at corresponding positions on the rectangular coordinate system. The coordinate points are connected by a smooth curve, and the curve is recorded as the processing change curve.

[0021] As a further aspect of the present invention: the process of obtaining the average rate of change includes:

[0022] Based on all coordinate points, a fitted straight line is obtained in the rectangular coordinate system using the least squares method. The slope of the fitted straight line is then obtained and denoted as the average rate of change.

[0023] As a further aspect of the present invention, the process of correcting the monitored physical parameters includes adjusting the monitored physical parameters to f(Z′).

[0024] As a further aspect of the present invention: a three-dimensional chip process simulation system, comprising:

[0025] Processing data acquisition module: acquires the time period from the start to the end of chip processing, recorded as the processing cycle; sets a time interval threshold, and selects several nodes within the processing cycle according to the time interval threshold; acquires physical parameters at each node to obtain real-time physical parameters, including size and roughness; and acquires all environmental indicators within the processing cycle, including temperature and chemical reaction rate; associates each physical parameter with an environmental indicator, and records all real-time physical parameters and all environmental indicators within the processing cycle as processing data;

[0026] Processing data processing module: acquires all historical processing data, numbers each node in the historical processing data, and generates processing change curves of physical parameters based on the physical parameters at each node;

[0027] Obtain the average rate of change of the processing change curve of the physical parameter, and obtain the values ​​of environmental indicators associated with the physical parameter in historical processing data. Generate the parameter change curve based on the values ​​of each environmental indicator and its corresponding average rate of change.

[0028] Simulation data comparison module: Before performing process simulation on the chip, various environmental indicators for the process simulation are acquired and recorded as simulation environment indicators; all simulation environment indicators are compared with the environmental indicators in the historical processing data to obtain the similarity between the simulation environment indicators and the environmental indicators of each historical processing data. Where n is the total number of environmental indicators, Z i Z represents the i-th environmental indicator. i ′ represents the i-th simulation environment index, i∈[1,n]; select the environment index of the historical processing data with the highest similarity and record the historical processing data as the class processing data;

[0029] Simulation Correction Module: When performing process simulation on the chip, the physical parameters being monitored are recorded as monitored physical parameters; the monitored physical parameters are acquired in real time to obtain a processing change curve, which is recorded as the current processing change curve; the average change rate of the current processing change curve is acquired in real time, which is recorded as the current change rate R; the simulation environment index associated with the real-time monitored physical parameters is acquired, and the value of the simulation environment index is acquired, which is recorded as Z′; the difference value Dv=|Rf(Z′)| is obtained in real time, where f(Z′) is the expression of the parameter change curve when the value of the environment index is Z′; if the difference value exceeds a preset difference threshold, the monitored physical parameters are corrected.

[0030] The beneficial effects of this invention are:

[0031] This invention acquires real-time physical parameters and environmental indicators during the chip manufacturing cycle and correlates them to more accurately simulate the impact of environmental changes on physical parameters during actual manufacturing. This helps improve the accuracy of 3D chip process simulation, making the simulation results closer to reality. By analyzing and comparing historical processing data, the processing conditions most similar to the current simulation environment can be found, providing a basis for process optimization. This helps reduce trial-and-error costs and improve production efficiency and product quality. During chip process simulation, changes in physical parameters are monitored in real time, and deviations from expected changes are calculated. This helps to identify problems promptly and make adjustments, ensuring the stability and controllability of the production process. By collecting and analyzing a large amount of historical processing data and simulation data, strong data support can be provided for production decisions. This helps companies better understand how various factors in the production process affect product quality, thus making more informed decisions. In summary, the 3D chip process simulation method of this invention has beneficial effects such as improving simulation accuracy, optimizing production processes, real-time monitoring and adjustment, and data-driven decision support, contributing to improving the efficiency and quality of 3D chip production. Attached Figure Description

[0032] The invention will now be further described with reference to the accompanying drawings.

[0033] Figure 1 This is a flowchart illustrating a three-dimensional chip process simulation method according to the present invention. Detailed Implementation

[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0035] Please see Figure 1 As shown, this invention provides a method for simulating the process of a three-dimensional chip, comprising the following steps:

[0036] Step S1: Obtain the time period from the start to the end of chip processing, and record it as the processing cycle; set a time interval threshold, and select several nodes within the processing cycle according to the time interval threshold; obtain the physical parameters at each node to obtain real-time physical parameters, including size and roughness; and obtain all environmental indicators within the processing cycle, including temperature and chemical reaction rate; associate each physical parameter with an environmental indicator, and record all real-time physical parameters and all environmental indicators within the processing cycle as processing data;

[0037] Understandably, the first step is to determine the entire timeframe from the start to the end of chip processing, i.e., the processing cycle, which forms the foundational timeframe for the entire simulation. To capture key changes during processing, a time interval threshold is set, and several nodes are selected within the processing cycle based on this threshold. These nodes represent important moments in the processing. At each selected time node, the chip's physical parameters, such as dimensions and surface roughness, are measured and recorded. These parameters reflect the chip's physical state at different processing stages. Simultaneously, environmental indicators, such as temperature and chemical reaction rates, are collected throughout the entire processing cycle. Environmental factors have a significant impact on chip processing and therefore require detailed recording. By correlating the physical parameters at each time node with the corresponding environmental indicators, complete processing data is generated. This allows for analysis of how environmental factors affect changes in physical parameters.

[0038] In a preferred embodiment of the present invention, the process of associating each physical parameter with an environmental indicator includes:

[0039] Select any environmental indicator as the environmental indicator to be tested, and record the remaining environmental indicators as the remaining environmental indicators; in all historical processing data, select several historical processing data in which all other environmental indicators are consistent and only the environmental indicator to be tested is consistent, and record them as verification data; obtain the physical parameters of the verification data at the end of processing, and compare the physical parameters between each verification data.

[0040] The process of comparing the physical parameters between different validation data includes:

[0041] Arbitrarily select one validation data point from all validation data as the standard validation data. Denote the physical parameters of the standard validation data as standard physical parameters P0, and the test environment index of the standard validation data as standard environmental index Z0. Obtain the index difference Cz = |Z-Z0| between the test environment index Z of the validation data and the standard environmental index, and obtain the parameter difference Cp = |P-P0| between the physical parameters P of the validation data and the standard physical parameters. Based on the parameter differences corresponding to each index difference, obtain the dataset, and obtain the correlation coefficient between the index differences and parameter differences within the dataset. Judge the correlation coefficient.

[0042] The process of determining the correlation coefficient includes:

[0043] A correlation coefficient threshold is set, and the threshold range is [0.8, 0.95]. The correlation coefficient r between the index difference and the parameter difference in the dataset is obtained. If |r|∈[0.8, 0.95], the physical parameter is associated with the environmental index under test; if |r| does not belong to [0.8, 0.95], the physical parameter is not associated with the environmental index under test.

[0044] It should be noted that commonly used correlation coefficients include the Pearson correlation coefficient. The Pearson correlation coefficient is mainly used to measure the linear correlation between two variables X and Y, with values ​​ranging from -1 to 1. When r > 0, it indicates a positive correlation between the two variables; when r < 0, it indicates a negative correlation; when r = 0, it indicates no linear correlation; when |r| > 0.95, the two variables are significantly correlated, indicating a very strong linear relationship; when 0.8 ≤ |r| < 0.95, the two variables are highly correlated, indicating a relatively strong linear relationship; when 0.5 ≤ |r| < 0.8, the two variables are moderately correlated, indicating a certain linear relationship; when 0.3 ≤ |r| < 0.5, the two variables are poorly correlated, indicating a weak linear relationship; when |r| < 0.3, the two variables are weakly correlated or uncorrelated, indicating almost no linear relationship. Therefore, the threshold range for the correlation coefficient is [0.8, 0.95].

[0045] Step S2: Obtain all historical processing data, number each node in the historical processing data, and generate a processing change curve of physical parameters based on the physical parameters at each node;

[0046] Obtain the average rate of change of the processing change curve of the physical parameter, and obtain the values ​​of environmental indicators associated with the physical parameter in historical processing data. Generate the parameter change curve based on the values ​​of each environmental indicator and its corresponding average rate of change.

[0047] Understandably, numbering each node in the historical processing data and generating processing change curves based on physical parameters helps visualize the changing trends of physical parameters over time; obtaining the average rate of change of the physical parameter processing change curves reflects the general trend of physical parameter changes; and combining the environmental indicator values ​​associated with physical parameters in the historical processing data and their corresponding average rates of change to generate parameter change curves helps understand the changing patterns of physical parameters under different environmental conditions.

[0048] In a preferred embodiment of the present invention, the process of generating the processing change curve includes:

[0049] A rectangular coordinate system is established with the node number as the x-axis and the physical parameter value as the y-axis. The physical parameters under each node number are converted into coordinate points at corresponding positions on the rectangular coordinate system. The coordinate points are connected by a smooth curve, and the curve is recorded as the processing change curve.

[0050] The process of obtaining the average rate of change includes:

[0051] Based on all coordinate points, a fitted straight line is obtained in the rectangular coordinate system using the least squares method. The slope of the fitted straight line is then obtained and denoted as the average rate of change.

[0052] Understandably, based on all coordinate points, a fitted straight line is obtained in a Cartesian coordinate system using the least squares method. The least squares method is a mathematical optimization technique that finds the best function match for the data by minimizing the sum of squared errors. It is used to find the straight line that best represents all data points. The slope of the fitted straight line is obtained and denoted as the average rate of change. The slope represents the degree of inclination of the straight line, which is the rate of change of the physical parameters. It represents the average level of change of the physical parameters with the node number.

[0053] Step S3: Before performing process simulation on the chip, obtain various environmental indicators for the process simulation, and record them as simulation environment indicators; compare all simulation environment indicators with the environmental indicators in the historical processing data to obtain the similarity between the environmental indicators and the historical processing data. Where n is the total number of environmental indicators, Z i Z represents the i-th environmental indicator. i ′ represents the i-th simulation environment index, i∈[1,n]; select the environment index of the historical processing data with the highest similarity and record the historical processing data as the class processing data;

[0054] Understandably, selecting the set of historical processing data most similar to the simulation environment based on the similarity calculation results as the class processing data helps improve the accuracy of the simulation.

[0055] Step S4: When performing process simulation on the chip, the physical parameters being monitored are recorded as monitored physical parameters; the monitored physical parameters are acquired in real time to obtain a processing change curve, which is recorded as the current processing change curve; the average change rate of the current processing change curve is acquired in real time, which is recorded as the current change rate R; the simulation environment index associated with the real-time monitored physical parameters is acquired, and the value of the simulation environment index is acquired, which is recorded as Z′; the difference value Dv=|Rf(Z′)| is obtained in real time, where f(Z′) is the expression of the parameter change curve when the value of the environment index is Z′; if the difference value exceeds a preset difference threshold, the monitored physical parameters are corrected;

[0056] It is understood that f(Z′) is the expected rate of change calculated based on the simulation environment indicators, which helps to detect the deviation between the simulation and the actual situation in a timely manner; the difference value reflects the deviation between the actual rate of change and the expected rate of change; if the difference value exceeds the preset difference threshold, it indicates that there is a significant deviation between the simulation results and the actual situation, and adjustments are needed.

[0057] In a preferred embodiment of the present invention, the process of correcting the monitored physical parameters includes adjusting the monitored physical parameters to f(Z′);

[0058] Understandably, this step, which calculates the expected values ​​based on the simulation environment indicators, aims to make the simulation results closer to reality and improve the accuracy of the simulation.

[0059] A three-dimensional chip process simulation system, comprising:

[0060] Processing data acquisition module: acquires the time period from the start to the end of chip processing, recorded as the processing cycle; sets a time interval threshold, and selects several nodes within the processing cycle according to the time interval threshold; acquires physical parameters at each node to obtain real-time physical parameters, including size and roughness; and acquires all environmental indicators within the processing cycle, including temperature and chemical reaction rate; associates each physical parameter with an environmental indicator, and records all real-time physical parameters and all environmental indicators within the processing cycle as processing data;

[0061] Processing data processing module: acquires all historical processing data, numbers each node in the historical processing data, and generates processing change curves of physical parameters based on the physical parameters at each node;

[0062] Obtain the average rate of change of the processing change curve of the physical parameter, and obtain the values ​​of environmental indicators associated with the physical parameter in historical processing data. Generate the parameter change curve based on the values ​​of each environmental indicator and its corresponding average rate of change.

[0063] Simulation data comparison module: Before performing process simulation on the chip, various environmental indicators for the process simulation are acquired and recorded as simulation environment indicators; all simulation environment indicators are compared with the environmental indicators in the historical processing data to obtain the similarity between the simulation environment indicators and the environmental indicators of each historical processing data. Where n is the total number of environmental indicators, Z i Z represents the i-th environmental indicator. i ′ represents the i-th simulation environment index, i∈[1,n]; select the environment index of the historical processing data with the highest similarity and record the historical processing data as the class processing data;

[0064] Simulation Correction Module: When performing process simulation on the chip, the physical parameters being monitored are recorded as monitored physical parameters; the monitored physical parameters are acquired in real time to obtain a processing change curve, which is recorded as the current processing change curve; the average change rate of the current processing change curve is acquired in real time, which is recorded as the current change rate R; the simulation environment index associated with the real-time monitored physical parameters is acquired, and the value of the simulation environment index is acquired, which is recorded as Z′; the difference value Dv=|Rf(Z′)| is obtained in real time, where f(Z′) is the expression of the parameter change curve when the value of the environment index is Z′; if the difference value exceeds a preset difference threshold, the monitored physical parameters are corrected.

[0065] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A method for simulating the process of a three-dimensional chip, characterized in that, Includes the following steps: Step S1: Obtain the time period from the start to the end of chip processing, and record it as the processing cycle; set a time interval threshold, and select several nodes within the processing cycle according to the time interval threshold; obtain the physical parameters at each node to obtain real-time physical parameters, including size and roughness; and obtain all environmental indicators within the processing cycle, including temperature and chemical reaction rate; associate each physical parameter with an environmental indicator, and record all real-time physical parameters and all environmental indicators within the processing cycle as processing data; Step S2: Obtain all historical processing data, number each node in the historical processing data, and generate a processing change curve of physical parameters based on the physical parameters at each node; Obtain the average rate of change of the processing change curve of the physical parameter, and obtain the values ​​of environmental indicators associated with the physical parameter in historical processing data. Generate the parameter change curve based on the values ​​of each environmental indicator and its corresponding average rate of change. Step S3: Before performing process simulation on the chip, obtain various environmental indicators for the process simulation, and record them as simulation environment indicators; compare all simulation environment indicators with the environmental indicators in the historical processing data to obtain the similarity between the environmental indicators and the historical processing data. Where n is the total number of environmental indicators, Z i Z represents the i-th environmental indicator. i ´ represents the i-th simulation environment index, i∈[1,n]; select the environment index of the historical processing data with the highest similarity and record the historical processing data as the class processing data; Step S4: When performing process simulation on the chip, the physical parameters being monitored are recorded as monitored physical parameters; the monitored physical parameters are acquired in real time to obtain a processing change curve, which is recorded as the current processing change curve; the average change rate of the current processing change curve is acquired in real time, which is recorded as the current change rate R; the simulation environment index associated with the real-time monitored physical parameters is acquired, and the value of the simulation environment index is acquired, which is recorded as Z´; the difference value Dv=|Rf(Z´)| is obtained in real time, where f(Z´) is the expression of the parameter change curve when the value of the environment index is Z´; if the difference value exceeds a preset difference threshold, the monitored physical parameters are corrected; In step S1, the process of associating each physical parameter with an environmental indicator includes: Select any environmental indicator as the environmental indicator to be tested, and record the remaining environmental indicators as the remaining environmental indicators; in all historical processing data, select several historical processing data in which all other environmental indicators are consistent and only the environmental indicator to be tested is consistent, and record them as verification data; obtain the physical parameters of the verification data at the end of processing, and compare the physical parameters between each verification data. In step S1, the process of comparing the physical parameters between the various verification data includes: Arbitrarily select one validation data point from all validation data as the standard validation data. Denote the physical parameters of the standard validation data as standard physical parameters P0, and the test environment index of the standard validation data as standard environmental index Z0. Obtain the index difference Cz = |Z-Z0| between the test environment index Z of the validation data and the standard environmental index, and obtain the parameter difference Cp = |P-P0| between the physical parameters P of the validation data and the standard physical parameters. Based on the parameter differences corresponding to each index difference, obtain the dataset, and obtain the correlation coefficient between the index differences and parameter differences within the dataset. Judge the correlation coefficient.

2. The method for simulating the process of a three-dimensional chip according to claim 1, characterized in that, In step S1, the process of determining the correlation coefficient includes: A correlation coefficient threshold is set, and the threshold range is [0.8, 0.95]. The correlation coefficient r between the index difference and the parameter difference in the dataset is obtained. If |r|∈[0.8, 0.95], the physical parameter is associated with the environmental index to be tested; if |r| does not belong to [0.8, 0.95], the physical parameter is not associated with the environmental index to be tested.

3. The method for simulating the process of a three-dimensional chip according to claim 1, characterized in that, In step S2, the process of generating the processing change curve includes: A rectangular coordinate system is established with the node number as the x-axis and the physical parameter value as the y-axis. The physical parameters under each node number are converted into coordinate points at corresponding positions on the rectangular coordinate system. The coordinate points are connected by a smooth curve, and the curve is recorded as the processing change curve.

4. The method for simulating the process of a three-dimensional chip according to claim 3, characterized in that, In step S2, the process of obtaining the average rate of change includes: Based on all coordinate points, a fitted straight line is obtained in the rectangular coordinate system using the least squares method. The slope of the fitted straight line is then obtained and denoted as the average rate of change.

5. The method for simulating the process of a three-dimensional chip according to claim 1, characterized in that, In step S4, the process of correcting the monitored physical parameter includes adjusting the monitored physical parameter to f(Z´).

6. A three-dimensional chip process simulation system, characterized in that, include: Processing data acquisition module: acquires the time period from the start to the end of chip processing, recorded as the processing cycle; sets a time interval threshold, and selects several nodes within the processing cycle according to the time interval threshold; acquires physical parameters at each node to obtain real-time physical parameters, including size and roughness; and acquires all environmental indicators within the processing cycle, including temperature and chemical reaction rate; associates each physical parameter with an environmental indicator, and records all real-time physical parameters and all environmental indicators within the processing cycle as processing data; Processing data processing module: acquires all historical processing data, numbers each node in the historical processing data, and generates processing change curves of physical parameters based on the physical parameters at each node; Obtain the average rate of change of the processing change curve of the physical parameter, and obtain the values ​​of environmental indicators associated with the physical parameter in historical processing data. Generate the parameter change curve based on the values ​​of each environmental indicator and its corresponding average rate of change. Simulation data comparison module: Before performing process simulation on the chip, various environmental indicators for the process simulation are acquired and recorded as simulation environment indicators; all simulation environment indicators are compared with the environmental indicators in the historical processing data to obtain the similarity between the simulation environment indicators and the environmental indicators of each historical processing data. Where n is the total number of environmental indicators, Z i Z represents the i-th environmental indicator. i ´ represents the i-th simulation environment index, i∈[1,n]; select the environment index of the historical processing data with the highest similarity and record the historical processing data as the class processing data; Simulation Correction Module: When performing process simulation on the chip, the physical parameters being monitored are recorded as monitored physical parameters; the monitored physical parameters are acquired in real time to obtain a processing change curve, which is recorded as the current processing change curve; the average change rate of the current processing change curve is acquired in real time, which is recorded as the current change rate R; the simulation environment index associated with the real-time monitored physical parameters is acquired, and the value of the simulation environment index is acquired, which is recorded as Z´; the difference value Dv=|Rf(Z´)| is obtained in real time, where f(Z´) is the expression of the parameter change curve when the value of the environment index is Z´; if the difference value exceeds a preset difference threshold, the monitored physical parameters are corrected; The process of associating various physical parameters with an environmental indicator includes: Select any environmental indicator as the environmental indicator to be tested, and record the remaining environmental indicators as the remaining environmental indicators; in all historical processing data, select several historical processing data in which all other environmental indicators are consistent and only the environmental indicator to be tested is consistent, and record them as verification data; obtain the physical parameters of the verification data at the end of processing, and compare the physical parameters between each verification data. The process of comparing the physical parameters between different validation data includes: Arbitrarily select one validation data point from all validation data as the standard validation data. Denote the physical parameters of the standard validation data as standard physical parameters P0, and the test environment index of the standard validation data as standard environmental index Z0. Obtain the index difference Cz = |Z-Z0| between the test environment index Z of the validation data and the standard environmental index, and obtain the parameter difference Cp = |P-P0| between the physical parameters P of the validation data and the standard physical parameters. Based on the parameter differences corresponding to each index difference, obtain the dataset, and obtain the correlation coefficient between the index differences and parameter differences within the dataset. Judge the correlation coefficient.

Images