A real-time monitoring method and system for exposure parameters of edge exposure machine

Abstract

The present invention relates to the field of parameter monitoring, and in particular to a real-time monitoring method and system for exposure parameters of an edge exposure machine, the method comprising: obtaining various parameters of the edge exposure machine at each moment, constructing a parameter sequence using the same parameters at different moments; converting the parameter sequence to obtain a frequency sequence; calculating the consistency between each frequency value and the operating state of the edge exposure machine, the consistency indicating the operating state of the edge exposure machine at the corresponding frequency value, using the consistency to classify the frequency value into a normal frequency set and an abnormal frequency set; calculating the abnormal degree of various parameters at the current moment; calculating the abnormal degree of the edge exposure machine, the abnormal degree of the edge exposure machine is positively correlated with the abnormal degree of the parameter, and in response to the abnormal degree being greater than a preset abnormal threshold, issuing a prompt indicating the abnormality of the edge exposure machine. The present invention improves the accuracy of the monitoring results of the exposure parameters and working state of the edge exposure machine.

Description

Technical Field

[0001] The present invention relates to the field of parameter monitoring, and in particular to a method and system for real-time monitoring of exposure parameters of an edge exposure machine. Background Art

[0002] Edge exposure machine refers to equipment used in lithography, microelectronics manufacturing and semiconductor industry. It is mainly used to expose patterns or graphics in specific areas on the surface of semiconductor wafers. Through precise light irradiation and exposure process, this equipment helps to manufacture tiny circuits or patterns for the production of integrated circuits. In the semiconductor manufacturing process, lithography is a very important step. It involves transferring the design pattern to the wafer surface by means of light. This process is crucial to the performance, function and size control of electronic equipment.

[0003] The Chinese patent application document with publication number CN108388087A discloses an edge exposure machine and an edge exposure method. The edge exposure machine includes: a light source for exposing the edge of a substrate from above; a vacuum pad for fixing the substrate from below by vacuum adsorption and supporting the substrate upward; a reflective bottom plate located at the bottom of the chamber of the edge exposure machine for reflecting the downward light emitted by the light source below the substrate, when the edge exposure machine exposes a substrate edge, the reflective bottom plate generates a reflective range corresponding to the portion of the substrate edge; and a translation mechanism for adjusting the horizontal relative position between the vacuum pad adjacent to the substrate edge and the substrate edge, so that the vacuum pad adjacent to the substrate edge tends to leave the reflective range.

[0004] During the operation of the edge exposure machine, real-time monitoring of exposure parameters is of great significance for ensuring the accuracy of the exposure process, improving production efficiency and reducing equipment failures. As semiconductor process nodes continue to shrink, the requirements for exposure machines are getting higher and higher, and parameter fluctuations may directly affect the exposure quality. Therefore, real-time monitoring of electrical parameters has become crucial. Summary of the invention

[0005] In order to improve the accuracy of exposure parameter monitoring results, the present invention provides a method and system for real-time monitoring of exposure parameters of an edge exposure machine.

[0006] In a first aspect, the present invention provides a method for real-time monitoring of exposure parameters of an edge exposure machine, which adopts the following technical solution:

[0007] Obtain various parameters of the edge exposure machine at each moment, and construct a parameter sequence using the same parameters at different moments;

[0008] The parameter sequence is converted into a frequency sequence, and a plurality of frequency values ​​are obtained according to the frequency sequence;

[0009] Calculate the consistency between each frequency value and the operating state of the edge exposure machine. The consistency indicates the operating state of the edge exposure machine at the corresponding frequency value. Use the consistency to classify the frequency value into a normal frequency set and an abnormal frequency set.

[0010] Calculate the first distance between each parameter at the current moment and the corresponding abnormal frequency set, and the second distance between each parameter and the corresponding normal frequency set, and use the ratio of the first distance to the second distance as the distance ratio;

[0011] Calculate the abnormal degree of each parameter at the current moment. The abnormal degree of the parameter is negatively correlated with the distance ratio;

[0012] The abnormality degree of the edge exposure machine is calculated. The abnormality degree of the edge exposure machine is positively correlated with the abnormality degree of the parameter. In response to the abnormality degree being greater than a preset abnormality threshold, a prompt indicating the abnormality of the edge exposure machine is issued.

[0013] By analyzing the frequencies corresponding to various parameters of the historical edge exposure machine, the normal frequency set and the abnormal frequency set are obtained. The abnormal degree of each real-time parameter is calculated according to the frequency of the real-time parameter and the distance between the normal frequency set and the abnormal frequency set. According to the consistency of each parameter and the edge exposure machine, the abnormal degree of each parameter is integrated together to obtain the final result, which improves the accuracy of the exposure parameters and working status monitoring results of the edge exposure machine.

[0014] Preferably, the method for calculating the consistency between each frequency value and the operating state of the edge exposure machine is: setting a corresponding label for each frequency value, the label including normal operation and abnormal operation;

[0015] The expression for the consistency between the frequency value and the operating state of the edge exposure machine is:

[0016]

[0017] In the formula, Indicates the consistency between the i-th frequency value of the k-th parameter and the operating status of the edge exposure machine, The label corresponding to the i-th frequency value of the k-th parameter is working properly. Indicates that the label corresponding to the i-th frequency value of the k-th parameter is abnormal. Indicates quantity.

[0018] The frequency value calculated by the formula is consistent with the edge exposure machine, which improves the accuracy of the calculation result.

[0019] Preferably, the method further comprises: calculating the consistency of various parameters with the operating state of the edge exposure machine, and the expression is:

[0020]

[0021] In the formula, represents the consistency between the kth parameter and the operating status of the exposure machine, norm represents the normalization function, represents the mean value of all frequency values ​​of the kth parameter and the consistency of the edge exposure machine operation status, It represents the standard deviation of the consistency of all frequency values ​​of the kth parameter and the operating status of the edge exposure machine, and exp represents an exponential function with e as the base.

[0022] The consistency between various parameters and the operating status of the exposure machine is calculated by the mean and standard deviation of the consistency between each frequency value and the operating status of the edge exposure machine, and the accuracy of the calculation results is improved through multiple dimensions.

[0023] Preferably, the abnormal degree expression of each parameter at the current moment is:

[0024]

[0025] In the formula, Indicates the abnormality of the kth parameter at the current moment, Indicates the frequency value of the kth parameter at the current moment, represents the ath frequency value in the abnormal frequency set of the kth parameter, represents the bth frequency value in the normal frequency set of the kth parameter, L represents the distance, exp represents the exponential function with e as the base, Indicates the consistency between the ath frequency value in the abnormal frequency set of the kth parameter and the operating state of the edge exposure machine, Indicates the consistency between the bth frequency value in the normal frequency set of the kth parameter and the operating status of the edge exposure machine.

[0026] Preferably, the abnormal degree expression of each parameter at the current moment is:

[0027]

[0028] In the formula, Indicates the abnormality of the kth parameter at the current moment, Indicates the frequency value of the kth parameter at the current moment, represents the ath frequency value in the abnormal frequency set of the kth parameter, It represents the bth frequency value in the normal frequency set of the kth parameter, L represents the distance, and exp represents the exponential function with e as the base.

[0029] Preferably, the expression of the abnormality degree of the edge exposure machine is:

[0030]

[0031] Where U represents the abnormality of the edge exposure machine, Indicates the consistency between the kth parameter and the operating status of the exposure machine, Indicates the abnormality of the kth parameter at the current moment.

[0032] By referring to multiple parameters and performing weighted summation on the multiple parameters, the abnormality degree of the edge exposure machine is obtained, which is convenient for further understanding the working state of the edge exposure machine, thereby realizing monitoring of the working state of the edge exposure machine.

[0033] Preferably, the parameters include current, voltage, power and temperature.

[0034] The exposure machine can be monitored from multiple dimensions, achieving better monitoring effects.

[0035] In a second aspect, the present invention provides a real-time monitoring system for exposure parameters of an edge exposure machine, which adopts the following technical solution:

[0036] A real-time monitoring system for exposure parameters of an edge exposure machine includes: a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the real-time monitoring method for exposure parameters of an edge exposure machine is implemented.

[0037] The beneficial effect is that the above-mentioned method for real-time monitoring of exposure parameters of an edge exposure machine is generated into a computer program and stored in a memory so as to be loaded and executed by a processor, thereby making a system based on the memory and the processor for easy use.

[0038] The present invention has the following technical effects:

[0039] 1. By analyzing the frequencies corresponding to various parameters of the historical edge exposure machine, the normal frequency set and the abnormal frequency set are obtained. The abnormal degree of each real-time parameter is calculated according to the frequency of the real-time parameter and the distance between the normal frequency set and the abnormal frequency set. According to the consistency of each parameter and the edge exposure machine, the abnormal degree of each parameter is integrated together to obtain the final result, which improves the accuracy of the exposure parameters and working status monitoring results of the edge exposure machine.

[0040] 2. The frequency value of the kth parameter at the current moment is used to calculate the abnormality of the parameter by using the Euclidean distance between the normal frequency set and the abnormal frequency set. This method is intuitive and easy to implement, and has a more efficient response speed in the real-time monitoring process.

[0041] 3. Dynamically monitor the parameters of the edge exposure machine to make it more adaptable to the actual working conditions, which helps to understand the working conditions of the edge exposure machine and the abnormal conditions of the parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] By reading the detailed description below with reference to the accompanying drawings, the above and other purposes, features and advantages of the exemplary embodiments of the present invention will become readily understood. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-restrictive manner, and the same or corresponding reference numerals represent the same or corresponding parts.

[0043] Figure 1 The present invention is a flow chart of a method for real-time monitoring of exposure parameters of an edge exposure machine. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0045] It should be understood that when the terms "first", "second", etc. are used in the claims, descriptions, and drawings of the present invention, they are only used to distinguish different objects, rather than to describe a specific order. The terms "include" and "comprise" used in the description and claims of the present invention indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their collections.

[0046] The embodiment of the present invention discloses a method for real-time monitoring of exposure parameters of an edge exposure machine, referring to Figure 1 , including the following steps:

[0047] S1: Obtain various parameters of the edge exposure machine at each moment, use the same parameters at different moments to construct a parameter sequence, convert the parameter sequence to obtain a frequency sequence, and obtain multiple frequency values ​​according to the frequency sequence.

[0048] During the operation of the edge exposure machine, parameters are obtained at equal intervals at different times, and the parameters include the current, voltage, power and temperature of the edge exposure machine. For the same parameter, a parameter sequence is constructed using the same parameters at different times, and a corresponding label is set for each data point in the parameter sequence. The labels include normal operation and abnormal operation. Normal operation indicates that the corresponding parameter of the edge exposure machine is in a normal state at the corresponding moment. Similarly, abnormal operation indicates that the corresponding parameter of the edge exposure machine is in an abnormal state at the corresponding moment. The parameter sequence is subjected to wavelet transform to obtain a frequency sequence, which includes multiple frequency values. It can be understood that each data point in the frequency sequence also has a corresponding label.

[0049] For example, , , …, For the current at the moment, the corresponding parameter sequence is ( , , …, ), and then the frequency sequence is obtained after wavelet transformation ( , , …, ), where for the data point , , , The label is abnormal, then the data point obtained after conversion , , , The label of is also abnormal. If the frequency sequence ( , , …, ) is specifically (3, 5, 3, 5, 8, 9, 3, 3, 5, 8), then its frequency values ​​are 3, 5, 8, 9.

[0050] S2: Calculate the consistency between each frequency value and the operating status of the edge exposure machine, and use the consistency to classify the frequency values ​​into a normal frequency set and an abnormal frequency set.

[0051] The expression for the consistency between the frequency value and the operating state of the edge exposure machine is:

[0052]

[0053] In the formula, Indicates the consistency between the i-th frequency value of the k-th parameter and the operating status of the edge exposure machine, The label corresponding to the i-th frequency value of the k-th parameter is working properly. Indicates that the label corresponding to the i-th frequency value of the k-th parameter is abnormal. Indicates quantity. Consistency indicates the operating state of the edge exposure machine at the corresponding frequency value. The larger its value, the more normal the operating state of the edge exposure machine at the corresponding frequency value. Conversely, the more abnormal the operating state. It can be understood that each frequency value corresponds to a consistency.

[0054] The method of using consistency to classify frequency values ​​into normal frequency sets and abnormal frequency sets is as follows: setting a classification threshold, classifying frequency values ​​whose consistency is greater than the classification threshold into normal frequency sets, and classifying frequency values ​​whose consistency is less than or equal to the classification threshold into abnormal frequency sets.

[0055] Exemplarily, the classification threshold is 0.8, the consistency between the frequency value 3 and the operating state of the edge exposure machine is 0.83, the consistency between the frequency value 5 and the operating state of the edge exposure machine is 0.92, the consistency between the frequency value 8 and the operating state of the edge exposure machine is 0.87, and the consistency between the frequency value 9 and the operating state of the edge exposure machine is 0.76. Among them, the consistency of frequency values ​​3, 5, and 8 is greater than the classification threshold. Therefore, frequency values ​​3, 5, and 8 are divided into a normal frequency set, and frequency value 9 is divided into an abnormal frequency set.

[0056] S3: Calculate the consistency of various parameters with the operating status of the edge exposure machine.

[0057] The expression is:

[0058] In the formula, represents the consistency between the kth parameter and the operating status of the exposure machine, norm represents the normalization function, represents the mean value of all frequency values ​​of the kth parameter and the consistency of the edge exposure machine operation status, represents the standard deviation of the consistency of all frequency values ​​of the kth parameter and the operating status of the edge exposure machine, exp represents the exponential function with e as the base, Represents the set of all frequency values ​​of the kth parameter and the consistency of the edge exposure machine's operating state. The consistency of the parameter means that when the corresponding parameter is used to measure the operating state of the edge exposure machine, the larger the value, the more normal the operating state of the edge exposure machine is when the corresponding parameter is used to measure the operating state of the edge exposure machine. Conversely, the operating state is more abnormal.

[0059] S4: Calculate the abnormality degree of each parameter at the current moment.

[0060] In one embodiment, the calculation method is: calculate the first distance between each parameter at the current moment and the corresponding abnormal frequency set, and the second distance with the corresponding normal frequency set, and take the ratio of the first distance to the second distance as the distance ratio. The abnormal degree of each parameter at the current moment is negatively correlated with the distance ratio.

[0061] The abnormal degree expression of the parameter is:

[0062]

[0063] In the formula, Indicates the abnormality of the kth parameter at the current moment, Indicates the frequency value of the kth parameter at the current moment, represents the ath frequency value in the abnormal frequency set of the kth parameter, represents the bth frequency value in the normal frequency set of the kth parameter, L represents the distance, which refers to the Euclidean distance here, It can be understood as the Euclidean distance between the frequency value of the kth parameter at the current moment and the ath frequency value in the abnormal frequency set. Indicates the first distance between the frequency value of the kth parameter at the current moment and the abnormal frequency set. Similarly, It can be understood as the Euclidean distance between the frequency value of the kth parameter at the current moment and the bth frequency value in the normal frequency set. It represents the second distance between the frequency value of the kth parameter at the current moment and the normal frequency set, and exp represents an exponential function with e as the base.

[0064] The abnormality of the corresponding parameters of the edge exposure machine can be judged by the abnormality degree of the parameters. Specifically, the greater the abnormality degree, the greater the corresponding parameter is in an abnormal state, which further indicates that the possibility that the working state of the edge exposure machine is abnormal is greater; for example, for current, the greater the abnormality degree, the greater the current parameter of the edge exposure machine is in an abnormal state, which further indicates that the working state of the edge exposure machine is in an abnormal state.

[0065] In one embodiment, the abnormal degree expression of the parameter is:

[0066]

[0067] In the formula, Indicates the abnormality of the kth parameter at the current moment, Indicates the frequency value of the kth parameter at the current moment, represents the ath frequency value in the abnormal frequency set of the kth parameter, represents the bth frequency value in the normal frequency set of the kth parameter, L represents the distance, exp represents the exponential function with e as the base, Indicates the consistency between the ath frequency value in the abnormal frequency set of the kth parameter and the operating state of the edge exposure machine, Indicates the consistency between the bth frequency value in the normal frequency set of the kth parameter and the operating status of the edge exposure machine.

[0068] S5: Calculate the abnormality level of the edge exposure machine. The abnormality level of the edge exposure machine is positively correlated with the abnormality level of the parameter. In response to the abnormality level being greater than a preset abnormality threshold, issue a prompt indicating the abnormality of the edge exposure machine.

[0069] The expression of the abnormality degree of the edge exposure machine is:

[0070]

[0071] Where U represents the abnormality of the edge exposure machine, Indicates the consistency between the kth parameter and the operating status of the exposure machine, Indicates the abnormality of the kth parameter at the current moment.

[0072] In the formula, It represents the weight of the kth parameter when calculating the abnormality degree of the edge exposure machine. The abnormality degree of the edge exposure machine indicates the possibility that the edge exposure machine is abnormal. When the abnormality degree is greater than the abnormality threshold, it indicates that the working state of the edge exposure machine is abnormal and needs to be stopped in time for maintenance.

[0073] An embodiment of the present invention also discloses a real-time monitoring system for exposure parameters of an edge exposure machine, including a processor and a memory, wherein the memory stores computer program instructions. When the computer program instructions are executed by the processor, a real-time monitoring method for exposure parameters of an edge exposure machine according to the present invention is implemented.

[0074] The above system also includes other components well known to those skilled in the art, such as a communication bus and a communication interface, and their configuration and functions are known in the art, so they will not be described in detail here.

[0075] In the present invention, the aforementioned memory may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, apparatus or device. For example, a computer-readable storage medium may be any appropriate magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory RRAM (Resistive Random Access Memory), a dynamic random access memory DRAM (Dynamic Random Access Memory), a static random access memory SRAM (Static Random Access Memory), an enhanced dynamic random access memory EDRAM (Enhanced Dynamic Random Access Memory), a high bandwidth memory HBM (High Bandwidth Memory), a hybrid memory cube HMC (Hybrid Memory Cube), etc., or any other medium that can be used to store the required information and can be accessed by an application, a module or both. Any such computer storage medium may be part of a device or accessible or connectable to a device.

[0076] Although this specification has shown and described a number of embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will conceive of many modifications, changes and alternatives without departing from the ideas and spirit of the present invention. It should be understood that in the practice of the present invention, various alternatives to the embodiments of the present invention described herein may be employed.

[0077] The above are all preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A real-time monitoring method for exposure parameters of an edge exposure machine, characterized in that: Includes steps: Obtain various parameters of the edge exposure machine at each moment, and construct a parameter sequence using the same parameters at different moments; The parameter sequence is converted into a frequency sequence, and a plurality of frequency values ​​are obtained according to the frequency sequence; Calculate the consistency between each frequency value and the operating state of the edge exposure machine. The consistency indicates the operating state of the edge exposure machine at the corresponding frequency value. Use the consistency to classify the frequency value into a normal frequency set and an abnormal frequency set. Calculate the consistency of various parameters and the operating status of the edge exposure machine, the expression is: , represents the consistency between the kth parameter and the operating status of the exposure machine, norm represents the normalization function, represents the mean value of all frequency values ​​of the kth parameter and the consistency of the edge exposure machine operation status, represents the standard deviation of the consistency of all frequency values ​​of the kth parameter and the operating state of the edge exposure machine, and exp represents an exponential function with e as the base; Calculate the first distance between each parameter at the current moment and the corresponding abnormal frequency set, and the second distance between each parameter and the corresponding normal frequency set, and use the ratio of the first distance to the second distance as the distance ratio; Calculate the abnormal degree of each parameter at the current moment. The abnormal degree of the parameter is negatively correlated with the distance ratio; The abnormality degree of the edge exposure machine is calculated. The abnormality degree of the edge exposure machine is positively correlated with the abnormality degree of the parameter. In response to the abnormality degree being greater than a preset abnormality threshold, a prompt indicating the abnormality of the edge exposure machine is issued.

2. The method for real-time monitoring of exposure parameters of an edge exposure machine according to claim 1, characterized in that: The method for calculating the consistency of each frequency value with the operating state of the edge exposure machine is: Set a corresponding label for each frequency value, including normal operation and abnormal operation; The expression for the consistency between the frequency value and the operating state of the edge exposure machine is: In the formula, Indicates the consistency between the i-th frequency value of the k-th parameter and the operating status of the edge exposure machine, The label corresponding to the i-th frequency value of the k-th parameter is working properly. Indicates that the label corresponding to the i-th frequency value of the k-th parameter is abnormal. Indicates quantity.

3. The method for real-time monitoring of exposure parameters of an edge exposure machine according to claim 2, characterized in that: The abnormal degree expression of each parameter at the current moment is: In the formula, Indicates the abnormality of the kth parameter at the current moment, Indicates the frequency value of the kth parameter at the current moment, represents the ath frequency value in the abnormal frequency set of the kth parameter, represents the bth frequency value in the normal frequency set of the kth parameter, L represents the distance, exp represents the exponential function with e as the base, Indicates the consistency between the ath frequency value in the abnormal frequency set of the kth parameter and the operating state of the edge exposure machine, Indicates the consistency between the bth frequency value in the normal frequency set of the kth parameter and the operating status of the edge exposure machine.

4. The method for real-time monitoring of exposure parameters of an edge exposure machine according to claim 1, characterized in that: The abnormal degree expression of each parameter at the current moment is: In the formula, Indicates the abnormality of the kth parameter at the current moment, Indicates the frequency value of the kth parameter at the current moment, represents the ath frequency value in the abnormal frequency set of the kth parameter, It represents the bth frequency value in the normal frequency set of the kth parameter, L represents the distance, and exp represents the exponential function with e as the base.

5. The method for real-time monitoring of exposure parameters of an edge exposure machine according to claim 1, characterized in that: The expression of the abnormality degree of the edge exposure machine is: Where U represents the abnormality of the edge exposure machine, Indicates the consistency between the kth parameter and the operating status of the exposure machine, Indicates the abnormality of the kth parameter at the current moment.

6. The method for real-time monitoring of exposure parameters of an edge exposure machine according to claim 1, characterized in that: Parameters include current, voltage, power and temperature.

7. A real-time monitoring system for exposure parameters of an edge exposure machine, characterized in that: include: A processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, a method for real-time monitoring of exposure parameters of an edge exposure machine according to any one of claims 1 to 6 is implemented.

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