Lithography machine light source pose optimization method, lithography machine and storage medium

Abstract

The invention provides a photoetching machine light source pose optimization method, a photoetching machine and a computer readable storage medium. The photoetching machine comprises a light source assembly, a workpiece table and a detection module, the optimization method comprises the following steps: driving the light source assembly to move to a test pose; driving the workpiece table to execute light field scanning so as to obtain light field distribution data corresponding to the test pose; determining an evaluation index corresponding to the test pose according to the light field distribution data; judging whether the evaluation index meets a preset convergence condition or not; if the evaluation index meets a convergence condition, determining the test pose as a target pose; and if the evaluation index does not meet the convergence condition, updating the test pose according to the evaluation index, and returning to execute the step of driving the light source assembly to move to the test pose. According to the invention, by adjusting the spatial pose of the light source assembly, the wafer on the workpiece table obtains better light intensity distribution.

Description

Technical Field

[0001] This application relates to the field of semiconductor manufacturing equipment technology, specifically to a method for optimizing the pose of a lithography machine light source, a lithography machine, and a computer-readable storage medium. Background Technology

[0002] In photolithography, the quality of the light field distribution on the wafer surface directly affects the accuracy and consistency of the exposed pattern. Related technologies primarily improve the light field distribution by optimizing the optical components within the illumination path.

[0003] However, during long-term operation of a lithography machine, the light source assembly itself may shift position due to thermal deformation or mechanical loosening. Related technologies typically employ fixed mounting methods for the light source assembly or only support manual coarse adjustments, making it difficult to automatically correct positional deviations. When the light source assembly deviates from its ideal light-emitting posture, it leads to a decrease in the uniformity of light intensity distribution on the wafer surface, thereby affecting the yield of the lithography process. Summary of the Invention

[0004] This application aims to solve the technical problem in the related art where the positional deviation of the light source component is difficult to correct in a timely manner, resulting in a decrease in the quality of light intensity distribution on the wafer surface.

[0005] The first aspect of this application provides a method for optimizing the pose of a light source in a lithography machine, applicable to a lithography machine including a light source assembly, a workpiece stage, and a detection module. The optimization method includes: Drive the light source assembly to move to the test pose; Drive the workpiece stage to perform light field scanning in order to obtain light field distribution data corresponding to the test pose; Based on the light field distribution data, determine the evaluation index corresponding to the test pose; Determine whether the evaluation indicators meet the preset convergence conditions; If the evaluation index meets the convergence condition, the test pose is determined as the target pose. If the evaluation metric does not meet the convergence condition, the test pose is updated according to the evaluation metric, and the process returns to the step of moving the driving light source component to the test pose.

[0006] In one embodiment, the test pose includes: position coordinates and angle orientation.

[0007] In one embodiment, driving the workpiece stage to perform optical field scanning includes: driving the workpiece stage to move along a grating-type scanning path or a concentric circle scanning path.

[0008] In one embodiment, when the workpiece stage is driven to perform light field scanning, the detection module collects light intensity signals at multiple sampling points according to a preset sampling frequency or spatial step size.

[0009] In one embodiment, the evaluation index includes light field uniformity; determining the evaluation index corresponding to the test pose based on light field distribution data includes: determining light field uniformity based on multiple light intensity signals.

[0010] In one embodiment, the evaluation index includes average light intensity; determining the evaluation index corresponding to the test pose based on light field distribution data includes: determining the average light intensity based on multiple light intensity signals.

[0011] In one embodiment, the convergence condition includes: the evaluation index is better than a preset threshold, or the rate of change of the evaluation index obtained by continuous iteration is within a preset convergence interval.

[0012] In one embodiment, updating the test pose according to the evaluation index includes: processing the evaluation index based on the optimization strategy to obtain the next test pose; updating the test pose to the next test pose; wherein the optimization strategy includes at least one of the following algorithms: swarm intelligence algorithm, Bayesian optimization algorithm, and gradient descent algorithm.

[0013] In one embodiment, after the test pose is determined to be the target pose, the method further includes: associating and storing the target pose with the current process parameters.

[0014] In one embodiment, the optimization method is configured to be triggered in the following scenarios: periodic maintenance mode of the lithography machine, or calibration period between the start of adjacent batch exposure processes.

[0015] A second aspect of this application provides a lithography machine, comprising: Light source assembly, used to provide a light source; The drive mechanism, connected to the light source assembly, is used to adjust the spatial pose of the light source assembly; The workpiece stage is equipped with a detection module; the workpiece stage is configured to drive the detection module to perform light field scanning in order to obtain light field distribution data. The controller is communicatively connected to the drive mechanism, the workpiece stage, and the light source assembly, respectively; the controller is configured to execute the optimization method as described in any of the first aspects.

[0016] A third aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the optimization method as described in any of the first aspects.

[0017] This application automatically finds the optimal pose of the light source component by driving the light source component to move in space and iteratively testing, thereby enabling the wafer on the workpiece stage to obtain a better light intensity distribution. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating the method for optimizing the pose of a lithography machine light source provided in an embodiment of this application. Figure 2 This is a schematic diagram of the process of performing optical field scanning on the workpiece stage according to an embodiment of this application; Figure 3 This is a schematic diagram of the target pose storage process provided in an embodiment of this application; Figure 4 This is a schematic diagram of the test pose update process provided in the embodiments of this application; Figure 5 This is a schematic structural block diagram of the lithography machine provided in the embodiments of this application; Figure 6 This is a schematic diagram of a computer-readable storage medium provided in an embodiment of this application.

[0020] Figure label: 10. Photolithography machine; 20. Computer-readable storage medium; 100. Light source assembly; 200. Drive mechanism; 300. Workpiece stage; 400. Controller; 500. Computer program. Detailed Implementation

[0021] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be particularly noted that the following embodiments are for illustrative purposes only and do not limit the scope of the application. Similarly, the following embodiments are only some, not all, embodiments of the present application, and all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of the present application.

[0022] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0023] The directional terms used in this description, such as "up," "down," "left," "right," "inner," and "outer," are only for reference to the directions shown in the attached diagram. These directional terms should be changed if the directions in the attached diagram change.

[0024] Please see Figures 1 to 4 , Figure 1 This is a flowchart illustrating a method for optimizing the pose of a lithography machine's light source, as provided in an embodiment of this application. This application provides a method for optimizing the pose of a lithography machine's light source, applicable to lithography machines. The lithography machine includes a light source assembly, a workpiece stage, and a detection module. The optimization method includes the following steps: Step S100: Drive the light source assembly to move to the test pose.

[0025] In this step, the light source assembly is controlled by the drive mechanism of the lithography machine to move or rotate in space so that it reaches the current test pose.

[0026] Step S200: Drive the workpiece stage to perform light field scanning to obtain light field distribution data corresponding to the test pose.

[0027] In this step, the workpiece stage moves the detection module within the exposure field of view. During this movement, the detection module acquires light intensity signals, thereby generating light field distribution data that reflects the quality of the light field under the current test pose.

[0028] Step S300: Determine the evaluation index corresponding to the test pose based on the light field distribution data.

[0029] In this step, evaluation indicators for quantitatively characterizing the quality of the light field are obtained by calculating the light field distribution data.

[0030] Step S400: Determine whether the evaluation index meets the preset convergence conditions.

[0031] In this step, the calculated evaluation index is compared with the preset convergence conditions to determine whether the current position of the light source component has met the preset conditions.

[0032] If the evaluation index meets the convergence condition, then proceed to step S410: determine the test pose as the target pose.

[0033] This indicates that the current test pose is the best pose found, and the optimization process ends.

[0034] If the evaluation index does not meet the convergence condition, then proceed to step S420: update the test pose according to the evaluation index, and return to the step of moving the driving light source component to the test pose (i.e., return to step S100).

[0035] In step S420, a new test pose is calculated using the current evaluation index, and the light source component is moved to the new test pose, thereby entering the next optimization steps from step S100 to step S400 until the evaluation index meets the convergence condition.

[0036] The optimization method provided in this application embodiment, by driving the light source component to move in space and combining feedback from the workpiece stage for iterative optimization, can automatically find the optimal pose of the light source component, thereby enabling the wafer on the workpiece stage to obtain a better light intensity distribution, solving the problem of reduced light intensity distribution quality on the wafer surface due to positional deviation of the light source component in related technologies.

[0037] In this embodiment, the test pose includes position coordinates and angular orientation. Specifically, the position coordinates define the translational position of the light source component in three-dimensional space, specifically represented by the X-axis, Y-axis, and Z-axis coordinates in a Cartesian coordinate system. The angular orientation defines the rotational state of the light source component in space, specifically represented by the tilt angle around the X-axis, the pitch angle around the Y-axis, and the yaw angle around the Z-axis. By comprehensively adjusting the position coordinates and angular orientation, the lithography machine's drive mechanism can achieve accurate control of the six degrees of freedom of the light source component, thereby covering all possible light emission postures of the light source component.

[0038] Please see Figure 2 , Figure 2 This is a schematic flowchart illustrating the process of performing light field scanning on a workpiece stage according to an embodiment of this application. In one embodiment, the step of driving the workpiece stage to perform light field scanning (i.e., step S200) includes steps S210 and S220, specifically: Step S210: Drive the workpiece stage to move along the grating scanning path or the concentric circle scanning path.

[0039] In this step, the controller sends motion commands to the workpiece stage. The workpiece stage responds to these commands, driving the detection module to traverse the exposure area along a preset trajectory. It can be understood that a raster-style scanning path allows the workpiece stage to perform row-by-row or column-by-column reciprocating motion, suitable for full-coverage detection of rectangular fields of view. A concentric circle scanning path allows the workpiece stage to perform circular motion with gradually changing radii, suitable for centrally symmetrical detection of circular fields of view. By selecting an appropriate scanning path, it can be ensured that the detection module provides complete and uniform coverage of the light field area, avoiding detection blind spots.

[0040] Step S220: The detection module collects light intensity signals at multiple sampling points according to a preset sampling frequency or spatial step size to obtain light field distribution data.

[0041] As the workpiece stage moves along the scanning path, a detection module mounted on the workpiece stage performs data acquisition. The detection module samples at a preset sampling frequency, such as 1000 times per second, or at a preset spatial step size, such as once per millimeter of movement. These preset values ​​can be adaptively adjusted according to actual usage. The detection module senses light energy at multiple discrete sampling points along the scanning path and converts it into electrical signals, thus obtaining light intensity signals corresponding to multiple sampling points. These light intensity signals, each corresponding to a position, together form the light field distribution data, used to characterize the light received by the wafer on the workpiece stage and for subsequent parameter calculations.

[0042] After acquiring the light field distribution data corresponding to the current test pose, the optimization method provided in this application embodiment further includes step S300, which involves determining the evaluation index corresponding to the current test pose based on the light field distribution data. The evaluation index is used to quantitatively assess the quality of the light field under this pose and is an important basis for guiding how the light source component adjusts its pose.

[0043] In one embodiment, the evaluation metric includes light field uniformity. Light field uniformity reflects the consistency of light energy distribution within the exposure field of view and is a key parameter for measuring the quality of lithographic imaging. The process of determining light field uniformity is as follows: First, the processor extracts the light intensity signal values ​​corresponding to all sampling points from the light field distribution data. A common calculation method is for the processor to identify the maximum and minimum light intensity values ​​from these values, calculate the ratio of their difference to their sum, and use this ratio as the quantification result of light field uniformity. The closer this ratio is to zero, the smaller the difference in extreme light intensity values, and the more uniform the light field distribution. In another feasible calculation method, the processor directly calculates the statistical variance or standard deviation of the light intensity signals at all sampling points. The smaller the variance or standard deviation, the lower the dispersion of the light intensity data, which also means better light field uniformity.

[0044] In another embodiment, the evaluation metric includes average light intensity. Average light intensity reflects the overall intensity level of light energy within the exposure field of view and directly affects the exposure dose received by the photoresist. The process of determining the average light intensity is as follows: the processor performs an arithmetic mean calculation on the light intensity signals from multiple sampling points, that is, summing all light intensity values ​​and dividing by the total number of sampling points to obtain the arithmetic mean light intensity. Furthermore, considering that imaging in the central region of the field of view is usually more critical than in the edge regions during photolithography, a weighted average method can also be used. In this method, the processor pre-configures different weight coefficients for sampling points at different spatial locations; for example, assigning a larger weight to sampling points in the central region and a smaller weight to sampling points in the edge regions. Subsequently, the processor performs a weighted average calculation on all light intensity signals to obtain a weighted average light intensity that better characterizes the effective exposure energy.

[0045] After determining the evaluation index corresponding to the current test pose in step S300, the process also includes step S400, which determines whether the evaluation index meets the preset convergence condition. The convergence condition is the criterion for determining when the optimization method terminates and outputs the final optimization result (i.e., the target pose).

[0046] In one embodiment, the convergence condition is set to an evaluation metric that is better than a preset threshold. This threshold represents the minimum requirement or desired target for optical field performance. For example, if the evaluation metric is optical field uniformity, its threshold can be preset to 98%. In step S400, the processor compares the calculated current optical field uniformity (e.g., 97.5%) with the threshold (98%). If the current uniformity is greater than or equal to the threshold, the performance is determined to be up to standard, the evaluation metric meets the convergence condition, and step S410 is executed to determine the current test pose as the target pose and end the optimization. If the current uniformity is less than the threshold, the performance is determined to be down to standard, the evaluation metric does not meet the convergence condition, and step S420 is executed to update the test pose according to the current evaluation metric to continue searching for a better pose. This threshold comparison method has a clear objective and is suitable for application scenarios with clear quantitative requirements for optical field quality.

[0047] In another embodiment, the convergence condition is determined based on the rate of change of the evaluation index over multiple iterations. This convergence condition setting focuses more on the convergence trend of the optimization process and is suitable for scenarios where the optimal light source pose is sought. Specifically, the processor monitors the changes in the evaluation index after each iteration, for example, by calculating the relative rate of change between the index value of the current iteration and the index value of the previous iteration. The processor can preset a very small rate of change interval, such as one-thousandth, to indicate that the optimization has stabilized. If the rate of change of the evaluation index calculated in multiple iterations (e.g., three) is less than this preset value, it indicates that the room for improvement in adjusting the light source pose is not large, and the optimization process has fully converged. At this point, it can be determined that the pose of the current light source component is a local optimum. In this case, the processor determines that the evaluation index meets the convergence condition and then executes step S410 to determine the current test pose as the target pose. If the rate of change of the evaluation index calculated in multiple iterations is still greater than the preset interval, it indicates that the pose of the light source component still has room for optimization. The processor determines that the evaluation index does not meet the convergence condition and continues to execute step S420. The method described above, which uses the rate of change to determine the pose of the light source component, can adaptively determine whether the optimization of the pose has reached a local optimum.

[0048] Please see Figure 3 In one embodiment, step S411 is further included after step S410. Specifically, the current test pose is determined as the target pose, and then step S411 is executed to associate and store the target pose with the current process parameters.

[0049] In this field, the process parameters of a lithography machine are a set of configuration data that defines a specific exposure process, typically including but not limited to exposure dose, illumination mode (such as conventional illumination, off-axis illumination), information on the mask used, and focus bias. These parameters together constitute a complete process recipe used to guide the lithography machine in performing specific exposure tasks.

[0050] The specific implementation of step S411 is as follows: the processor writes the determined target pose data (including its position coordinates and angle orientation) into the configuration file or database record corresponding to the process recipe, and establishes the association between the two. This association storage operation saves the data in the controller's non-volatile memory to ensure its persistence.

[0051] This application achieves both ease of application and process stability through step S411. Specifically, when the lithography machine needs to run the same process recipe again, the processor can directly read the associated target pose from storage and drive the light source assembly to move to that target pose. This avoids unnecessary time consumption caused by re-executing the entire optimization process, significantly improving the preparation efficiency of the lithography machine. Furthermore, binding the optimized target pose to the process recipe ensures that the light source assembly is in a verified optimal state each time the same process is executed, fundamentally guaranteeing the consistency of light field quality (such as uniformity and light intensity) between different production batches, thus improving production reliability and product yield.

[0052] If, in step S400, it is determined that the evaluation index does not meet the convergence condition, the optimization method proceeds to the step of updating the light source pose. Please refer to [link to relevant documentation]. Figure 4 , Figure 4 This is a schematic diagram of the test pose update process provided in an embodiment of this application. In one embodiment, step S420 includes steps S421 and S422.

[0053] Step S421: Process the evaluation index based on the optimization strategy to obtain the next test pose. In this step, the processor calls a preset optimization strategy algorithm to analyze and process the current evaluation index to generate a new pose that is more likely to improve the light field performance, i.e., the next test pose. In this embodiment, the optimization strategy can be selected from one of the following algorithms: swarm intelligence algorithm, Bayesian optimization algorithm, and gradient descent algorithm.

[0054] To illustrate its working principle, two typical algorithms are used as examples. If the optimization strategy uses the gradient descent algorithm, the processor calculates the gradient of the evaluation metric (such as light field uniformity) relative to the parameters of each degree of freedom (position coordinates and angular orientation) of the light source component. The direction of this gradient indicates the direction in which the evaluation metric improves the fastest. Simultaneously, the processor dynamically determines the step size by referring to a preset convergence threshold. For example, if the current uniformity is 90%, which is significantly lower than the preset threshold of 98%, the processor sets a larger step size to encourage the light source component to move towards the performance improvement area. If the current uniformity is close to the threshold, such as 97%, the processor switches to a smaller step size to achieve more precise adjustments and avoid non-convergence.

[0055] If the optimization strategy employs a swarm intelligence algorithm (such as particle swarm optimization), the processor treats the current test pose as a "particle" in the search space. The algorithm tracks the particle's own historical best evaluation index and pose, as well as the global best evaluation index and pose found so far by the entire "particle swarm." By combining the relationship between the current pose, the individual's historical best pose, and the global best pose, the algorithm calculates the particle's velocity and direction at the next moment, thereby deducing the next test pose. This type of algorithm excels at global optimization in complex multidimensional spaces.

[0056] Step S422: Update the test pose to the next test pose. After calculating the specific parameters of the next test pose in step S421, the processor performs the following update operation: updates the variable value representing the current test pose to the calculated new parameters, and then generates corresponding control commands based on these new parameters, sends them to the drive mechanism, and drives the light source component to actually move to the new spatial pose. After completing the above physical movement, the optimization method returns to step S100, starting a new round of optimization loop with the new light source pose as the starting point, until the convergence condition is met.

[0057] By executing step S420, this application achieves automatic and directional updates of the light source pose. Based on evaluation index feedback and optimization strategy decisions, the system can automatically determine which direction and by what magnitude the light source should be adjusted, thereby guiding the entire optimization process to converge quickly and stably towards a region with better light field performance.

[0058] In the embodiments of this application, the optimization method of this application is applicable to at least the following two scenarios: the regular maintenance mode of the lithography machine, or the calibration period between the start-up of adjacent batch exposure processes.

[0059] Specifically, scheduled maintenance refers to the planned downtime maintenance phase when the lithography machine is in a non-production state. During this phase, maintenance personnel will perform a system check on the lithography machine. Optimization methods can be incorporated into the maintenance process, such as performing light source pose search during maintenance to avoid errors accumulated over long-term operation.

[0060] The calibration period refers to the process gap between the completion of exposure for one batch of wafers and the loading of the next batch. During this time, the lithography machine is ready but has not yet performed exposure. Optimization methods can be implemented during this gap to adjust the pose of the light source. This method can compensate for drift caused by factors such as changes in equipment status between batches in real time, ensuring the consistency of exposure light field quality between different production batches. Furthermore, since the optimization process is integrated into the existing production process, this optimization method will not affect the overall production efficiency.

[0061] The optimization method provided in this application actively adjusts the pose of the light source component through a driving mechanism and uses the light field scanning data of the workpiece stage as feedback to construct a technical solution for pose adjustment, effect measurement, and index evaluation. This solution can automatically update to the optimal working pose of the light source without manual intervention, effectively solving the technical problem of uneven exposure caused by fixed or difficult-to-optimize light source pose in related technologies.

[0062] Please see Figure 5 , Figure 5 This is a schematic structural block diagram of the lithography machine 10 provided in an embodiment of this application. This application also provides a lithography machine 10, including: a light source assembly 100, a driving mechanism 200, a workpiece stage 300, and a controller 400.

[0063] A light source assembly 100 provides a light source. A drive mechanism 200 is connected to the light source assembly 100 and is used to adjust the spatial pose of the light source assembly 100. A workpiece stage 300 is provided with a detection module. The workpiece stage 300 is configured to drive the detection module to perform a light field scan to acquire light field distribution data. A controller 400 is communicatively connected to the drive mechanism 200, the workpiece stage 300, and the light source assembly 100. The controller 400 is configured to execute the optimization method as described in any of the foregoing embodiments.

[0064] Please see Figure 6 , Figure 6 This is a schematic diagram of a computer-readable storage medium 20 provided in an embodiment of this application. An embodiment of this application also provides a computer-readable storage medium 20 storing a computer program 500. When executed by a processor, the computer program 500 implements the optimization method as described in any of the foregoing embodiments.

[0065] It should be noted that the terms "first," "second," and "third" in this application are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0066] The above description is only a part of the embodiments of this application and does not limit the scope of protection of this application. Any equivalent device or equivalent process transformation made based on the content of this application specification and drawings, or direct or indirect application in other related technical fields, are similarly included in the patent protection scope of this application.

Claims

1. A method for optimizing the pose of a light source in a lithography machine, the lithography machine comprising a light source assembly, a workpiece stage, and a detection module; the optimization method comprising: Drive the light source assembly to move to the test pose; The workpiece stage is driven to perform light field scanning to obtain light field distribution data corresponding to the test pose. Based on the light field distribution data, the evaluation index corresponding to the test pose is determined; Determine whether the evaluation index meets the preset convergence condition; If the evaluation index satisfies the convergence condition, then the test pose is determined as the target pose; If the evaluation metric does not meet the convergence condition, the test pose is updated according to the evaluation metric, and the process returns to the step of driving the light source component to move to the test pose.

2. The optimization method according to claim 1, characterized in that, The test pose includes: position coordinates and angle orientation.

3. The optimization method according to claim 1, characterized in that, The process of driving the workpiece stage to perform optical field scanning includes: The workpiece stage is driven to move along a grating-type scanning path or a concentric circle scanning path.

4. The optimization method according to claim 3, characterized in that, When driving the workpiece stage to perform light field scanning, the detection module collects light intensity signals at multiple sampling points according to a preset sampling frequency or spatial step size.

5. The optimization method according to claim 4, characterized in that, The evaluation indicators include optical field uniformity; The step of determining the evaluation index corresponding to the test pose based on the light field distribution data includes: The uniformity of the light field is determined based on multiple light intensity signals.

6. The optimization method according to claim 4, characterized in that, The evaluation indicators include average light intensity; The step of determining the evaluation index corresponding to the test pose based on the light field distribution data includes: The average light intensity is determined based on multiple light intensity signals.

7. The optimization method according to claim 1, characterized in that, The convergence conditions include: the evaluation index is better than a preset threshold, or the rate of change of the evaluation index obtained by continuous iteration is within a preset convergence interval.

8. The optimization method according to claim 1, characterized in that, Updating the test pose according to the evaluation metric includes: The evaluation index is processed based on the optimization strategy to obtain the next test pose; Update the test pose to the next test pose; The optimization strategy includes at least one of the following algorithms: swarm intelligence algorithm, Bayesian optimization algorithm, and gradient descent algorithm.

9. The optimization method according to claim 1, characterized in that, After the test pose is determined to be the target pose, the following steps are also included: The target pose is associated with and stored with the current process parameters.

10. The optimization method according to claim 1, characterized in that, The optimization method is configured to be triggered in the following scenarios: the periodic maintenance mode of the lithography machine, or the calibration period between the start-ups of adjacent batch exposure processes.

11. A lithography machine, characterized in that, include: Light source assembly, used to provide a light source; A drive mechanism, connected to the light source assembly, is used to adjust the spatial pose of the light source assembly; The workpiece stage is equipped with a detection module; the detection module is configured to perform light field scanning to obtain light field distribution data. The controller is communicatively connected to the drive mechanism, the workpiece stage, and the light source assembly, respectively; the controller is configured to perform the optimization method as described in any one of claims 1 to 10.

12. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the optimization method as described in any one of claims 1 to 10.

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