Management system and management method for dry etching apparatus

Abstract

This invention provides a management system and method for dry etching equipment, including an RPA information capture module, an intelligent equipment management module, and an RPA equipment operation module. The RPA information capture module retrieves corresponding process formulation information, real-time equipment operating parameters, historical sample process flow information, and user permissions from the experimental platform based on the dry etching task. The intelligent equipment management module verifies the feasibility of the process formulation information and checks for sample cross-contamination based on the information fed back from the RPA information capture module. The RPA equipment operation module automates the software operation of the equipment. This invention verifies process formulation information, user permissions, and sample cross-contamination before the dry etching equipment is used, improving equipment management efficiency and safety. Simultaneously, by combining RPA with automated equipment operation, it reduces user errors.

Description

Technical Field

[0001] This invention relates to the field of equipment management, specifically to a management system and method for dry etching equipment. Background Technology

[0002] As the application scope of micro-nano fabrication gradually expands, the number of users of micro-nano fabrication equipment is also increasing. Taking dry etching equipment as an example, the existing user group is highly diverse, with varying technical capabilities among users, resulting in a high risk of operational errors. Equipment malfunctions (such as excessive reflection power, matching device damage, and helium leakage) are prone to occur due to incorrect operation sequence or improper parameter settings.

[0003] For dry etching equipment, common operational malfunctions include the wide variety of micro- and nano-fabrication processes involved, the difficulty in precisely controlling etching materials, and the potential for cross-contamination within the chamber. Furthermore, failure to complete cleaning procedures as required or shortening the cleaning time can also lead to chamber contamination. Additionally, dry etching equipment involves the use of various toxic gases, posing a high management risk for these special gases (such as chlorine). Moreover, current dry etching equipment maintenance lacks precise monitoring of the health status of equipment components, often relying on scheduled replacements. This results in components being replaced before they fail, increasing maintenance costs and wasting the effective lifespan of the components. Summary of the Invention

[0004] Based on this, the present invention provides a management system and method for dry etching equipment. By setting up a core software robot, it breaks down data silos between the dry etching equipment and various systems in the experimental platform (such as the work order system, equipment monitoring system, process knowledge base, and experimental logbook), achieving comprehensive awareness of equipment status and process context. Based on this, the present invention not only achieves accurate billing during actual equipment use, but also automates the entire process chain, including intelligent judgment of process formula parameters, reducing tedious manual operations on the equipment interface, handling equipment anomaly alarms, and providing maintenance reminders. This significantly improves equipment management efficiency, safety, and resource utilization.

[0005] In a first aspect, the present invention provides a management system for a dry etching equipment, including an RPA information capture module, an equipment intelligent management module, and an RPA equipment operation module, wherein the equipment intelligent management module is communicatively connected to the RPA information capture module and the RPA equipment operation module respectively.

[0006] The RPA information capture module is used to retrieve information capture instructions according to the dry etching task to be executed by the dry etching equipment. This enables the RPA robot to retrieve the process formula information, real-time operating parameters of the dry etching equipment, historical process flow information of sample processing, user permissions, and etching process knowledge base corresponding to the dry etching task to be executed from at least one system in the experimental platform according to the information capture instructions.

[0007] The intelligent equipment management module is used to verify the feasibility of the process formula information, real-time operating parameters of the dry etching equipment, historical process flow information of sample processing, user permissions, and the cross-contamination probability of the historical process flow of the dry etching task to be executed, based on the process formula information, real-time operating parameters of the dry etching equipment, historical process flow information of the sample processing, user permissions, and etching process knowledge base of the dry etching task to be executed. If the feasibility of the process formula information, user permissions, and cross-contamination probability of the historical process flow all pass the verification, the module generates the corresponding dry etching operation instruction in combination with the dry etching task to be executed and sends the dry etching operation instruction to the RPA equipment operation module.

[0008] The RPA device operation module is used to perform automated operations on the components or input boxes of the dry etching interactive interface according to the standardized operation procedures of the dry etching equipment and the received dry etching operation instructions.

[0009] Furthermore, the RPA information capture module includes an equipment status capture unit, a process capture unit, a user information capture unit, a material capture unit, an experimental record capture unit, a knowledge base capture unit, and an alarm record retrieval unit.

[0010] The equipment status capture unit is used to capture the real-time operating parameters of the dry etching equipment and the process formula information corresponding to the dry etching task to be executed from the equipment monitoring system of the experimental platform.

[0011] The process grabbing unit is used to grab the planned process flow information of the sample corresponding to the dry etching task to be executed from the work order system of the experimental platform.

[0012] The material grabbing unit is used to grab material information that is permitted to be used in dry etching equipment from the equipment management knowledge base of the experimental platform;

[0013] The user information capture unit is used to capture user permissions for the dry etching equipment from the equipment management knowledge base of the experimental platform.

[0014] The experimental record capture unit is used to capture historical real process flow information of sample processing from the experimental notebook system of the experimental platform;

[0015] The knowledge base crawling unit is used to crawl etching process knowledge from the process knowledge base of the experimental platform;

[0016] The alarm record retrieval unit is used to retrieve the equipment alarm handling process from the equipment management knowledge base of the experimental platform.

[0017] Furthermore, the intelligent equipment management module includes a cost calculation unit, an authorization management unit, a recipe parameter verification unit, an alarm processing unit, and an equipment maintenance unit;

[0018] The cost calculation unit is used to calculate the equipment operating cost by combining the real-time operating parameters and process flow information of the dry etching equipment.

[0019] The authorization management unit is used to determine the usage rights of process formulas and materials in dry etching equipment based on user permissions, process formula information, material information permitted for use in dry etching equipment, and historical real process flow information.

[0020] The formula parameter verification unit is used to determine whether the configured process formula parameters meet the process parameter requirements of the dry etching equipment based on etching process knowledge.

[0021] The alarm processing unit is used to retrieve the device alarm processing flow based on the alarm information.

[0022] The equipment maintenance unit is used to generate equipment maintenance work orders based on real-time operating parameters.

[0023] Secondly, the present invention also provides a management method for a dry etching apparatus, wherein the management method for the dry etching apparatus is applied to the intelligent management module of the management system for the dry etching apparatus as described in any of the first aspects, and the management method for the dry etching apparatus includes the following steps:

[0024] The equipment status capture unit is used to capture process formula information of dry etching equipment from the equipment monitoring system of the experimental platform, and the knowledge base capture unit captures etching process knowledge from the process knowledge base of the experimental platform.

[0025] For any process parameter in the process formula information, retrieve the corresponding parameter limit range from the etching process knowledge;

[0026] If all process parameters in the process formula information meet the corresponding parameter limit range, extract the key parameter combination from the process formula information;

[0027] Based on the combination of key parameters, traverse the historical process formula information. If the historical process formula information does not contain the combination of key parameters, compare the combination of key parameters with the equipment safety window in the etching process knowledge.

[0028] If the combination of key parameters is not within the equipment safety window of the etching process knowledge, the combination of key parameters is input into the Paschen curve model and impedance matching model of plasma initiation for simulation.

[0029] If the simulation results are in the normal ignition region and the impedance matching degree is lower than the preset threshold, input all process parameters in the process recipe information into the RPA equipment operation module.

[0030] If the simulation results are in an abnormal ignition region or the impedance matching degree exceeds the preset threshold, a recipe warning message will be generated.

[0031] Furthermore, the management method for the dry etching equipment also includes:

[0032] If any process in the process formula information does not meet the corresponding parameter limit range, a formula warning information is generated.

[0033] If the combination of key parameters is within the equipment safety window of the etching process knowledge, input all process parameters in the process formula information into the RPA equipment operation module.

[0034] Furthermore, the management method for the dry etching equipment also includes:

[0035] If the process formulation information for the sample processing includes special gases, retrieve the material information and user permissions for the dry etching equipment that are permitted to be used, which are fed back by the RPA information capture module.

[0036] If the material information permitted for use by the dry etching equipment includes the special gas, and the user permissions include the usage permission for the special gas, then update the special gas usage permission for the corresponding process formulation information.

[0037] Furthermore, before inputting all process parameters from the process recipe information into the RPA equipment operation module, the following steps are also included:

[0038] Obtain historical process flow information of sample processing from the experimental record capture unit in the RPA information capture module, and planned process flow information of the sample from the process capture unit.

[0039] If the historical actual process flow information of the sample processing is inconsistent with the planned process flow information of the sample, the probability of cross-contamination when the sample is processed on the dry etching equipment is determined by combining the historical actual process flow information of the sample processing with the corresponding process formula information of the sample processing.

[0040] If the probability of cross-contamination during the processing of the sample on a dry etching device is greater than a set threshold, a process flow alarm message will be issued.

[0041] Furthermore, the management method for the dry etching equipment also includes:

[0042] The equipment status capture unit captures real-time operating parameters and process formula information of the dry etching equipment from the equipment monitoring system of the experimental platform, and the process capture unit captures planned process flow information of sample processing from the work order system of the experimental platform.

[0043] Determine the time window corresponding to each step in the process formulation information;

[0044] Based on the time window, extract the various gas consumption, process temperature and corresponding RF activation time for each step from the real-time operating parameters of the dry etching equipment.

[0045] The gas cost is calculated based on the amount of each gas used in each step and the unit price of each gas.

[0046] The equipment time cost is obtained based on the time window corresponding to each step, the planned process flow information for sample processing, and the unit price of the dry etching equipment.

[0047] The equipment depreciation cost is calculated based on the process temperature and RF activation time for each step.

[0048] The total cost of using the dry etching equipment is calculated based on the gas cost, equipment operating time cost, and equipment depreciation cost.

[0049] Furthermore, the management method for the dry etching equipment also includes:

[0050] If an alarm message is received, the corresponding alarm processing procedure is scheduled from the standardized operating procedure of the dry etching equipment based on the real-time operating parameters of the dry etching equipment, and the alarm processing unit is sent to the RPA equipment operation module to handle the alarm message.

[0051] Furthermore, the management method for the dry etching equipment also includes:

[0052] Obtain real-time operating parameters of the dry etching equipment;

[0053] If any of the real-time operating parameters deviates from the equipment operating parameter reference range, an equipment maintenance work order is generated by combining the real-time operating parameters with the process flow information executed by the dry etching equipment.

[0054] The beneficial effects of adopting the above technical solution are as follows: This embodiment sets up a software robot that runs through the RPA information capture module, equipment intelligent management module, and RPA equipment operation module in the management system of the dry etching equipment. The RPA information capture module retrieves relevant information about various systems and the dry etching equipment within the experimental platform. The equipment intelligent management module integrates or judges the operating status of the dry etching equipment and determines the feasibility of the process flow information. The RPA equipment operation module executes the process flow information, thereby improving the automated management of the dry etching equipment, effectively monitoring the user's process flow steps, accurately monitoring the health status of special gases and equipment components, and improving the operating efficiency and maintenance efficiency of the dry etching equipment. Attached Figure Description

[0055] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below.

[0056] Figure 1 This is a schematic diagram of the management system of a dry etching apparatus in one embodiment of this application;

[0057] Figure 2 This is a schematic diagram of a management method for a dry etching apparatus in one embodiment of this application. Detailed Implementation

[0058] 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. To describe the present invention in more detail, the management system and management method of the dry etching equipment provided by the present invention will be specifically described below with reference to the accompanying drawings.

[0059] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Similarly, the terms "an," "a," or "the" do not indicate a quantity limitation, but rather indicate the presence of at least one. The terms "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. The terms "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up," "down," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0060] For dry etching equipment, the highly diverse user base and varying technical capabilities among users pose a significant risk of operational errors. Common operational malfunctions include the wide variety of micro- and nano-fabrication processes involved in dry etching, the difficulty in precisely controlling etching materials, and the potential for cross-contamination within the chamber. Furthermore, failure to complete cleaning procedures as required or shortening the cleaning time can easily lead to chamber contamination. Additionally, dry etching equipment involves the use of various toxic gases, posing a high management risk for these special gases (such as chlorine). Moreover, current dry etching equipment maintenance lacks precise monitoring of the health status of equipment components, often relying on scheduled replacements. This results in components being replaced before they fail, increasing maintenance costs and wasting the effective lifespan of the components.

[0061] To address the aforementioned issues, this invention proposes a management system and method for dry etching equipment. This system breaks down data silos between the dry etching equipment and various systems within the experimental platform (such as the work order system, equipment monitoring system, process knowledge base, and experimental logbook), enabling comprehensive awareness of equipment status and process context. This achieves accurate billing during actual equipment use and completes end-to-end automation of intelligent process parameter judgment, automated operation of the equipment interface, equipment anomaly alarm handling, and maintenance reminders, significantly improving equipment management efficiency, security, and resource utilization.

[0062] The management system for the dry etching equipment provided in this embodiment includes an RPA information capture module 100, an intelligent equipment management module 200, and an RPA equipment operation module 300.

[0063] The RPA information capture module 100 is used to retrieve information capture instructions based on the dry etching task to be executed by the dry etching equipment. This enables the RPA robot to retrieve the process formula information, real-time operating parameters of the dry etching equipment, historical process flow information of sample processing, user permissions, and etching process knowledge base corresponding to the dry etching task to be executed from at least one system in the experimental platform according to the information capture instructions.

[0064] Specifically, the RPA information capture module 100 includes an equipment status capture unit 101, a process capture unit 102, a user information capture unit 103, a material capture unit 104, an experiment record capture unit 105, a knowledge base capture unit 106, and an alarm record retrieval unit 107.

[0065] The equipment status capture unit 101 is used to capture real-time operating parameters of the dry etching equipment and process recipe information corresponding to the dry etching tasks to be executed from the equipment monitoring system of the experimental platform. The real-time operating parameters of the dry etching equipment include, but are not limited to, equipment reaction chamber pressure, back helium pressure, back helium flow rate, flow rates of various gases, electrostatic chuck temperature, adsorption voltage, upper RF power, upper RF reflected power, lower RF power, lower RF reflected power, matching capacitor parameters, self-bias voltage, and RF power supply ignition duration. In this embodiment, the dry etching equipment receives a sequence of dry etching tasks to be executed at fixed times each day. Each dry etching task corresponds to different process recipe information, which is stored in the equipment monitoring system of the experimental platform. The process recipe information includes, but is not limited to, substrate material, mask material, target etching material, key step descriptions, special gases, and contamination sensitivity. This process recipe information covers all process-related data of the sample during the dry etching process.

[0066] It should be noted that the device grabbing module in this embodiment can directly grab data by scheduling the device software robot through a pre-set data grabbing path and data grabbing frequency.

[0067] The process capture unit 102 is used to capture the planned process flow information of the sample corresponding to the dry etching task to be executed from the work order system of the experimental platform. In this embodiment, the planned process flow information of the sample represents all the processing process flow information that the sample is planned to execute in the experimental platform, including the specific processing operation performed by the sample in each processing process of the experimental platform, the planned execution time of each processing process, the processing formula, and the sample detection information after processing, etc.

[0068] The user information capture unit 103 is used to capture user permissions for the dry etching equipment from the equipment management knowledge base of the experimental platform. These user permissions include, but are not limited to, the operation permissions that the user can perform on the dry etching equipment, the material permissions that the user can use during the operation of the dry etching equipment, and the special gas permissions that the user can use during the operation of the dry etching equipment.

[0069] The material retrieval unit 104 is used to retrieve permitted material information for the dry etching equipment from the equipment management knowledge base of the experimental platform. To prevent damage to the dry etching equipment by special materials, the equipment management knowledge base records permitted and prohibited material information for the dry etching equipment.

[0070] The experimental record capture unit 105 is used to capture the historical real process flow information of sample processing from the experimental notebook system of the experimental platform. The experimental notebook records the process flow information of all processing equipment for each sample within the experimental platform, specifically the process flow information of all processing processes performed before the sample is processed by dry etching, including the specific processing operations performed on the sample in the preceding processing process, the processing formula, and the sample testing information after processing.

[0071] The knowledge base retrieval unit 106 is used to retrieve etching process knowledge from the experimental platform's process knowledge base. This embodiment combines historical process formulation information with the working principle of dry etching to establish safe parameter ranges for each process step in the dry etching process (such as etching SiO2, Si, SiC, GaAs, etc.). These safe parameter ranges are defined in the form of a "power-pressure-gas flow rate safety space" and a "ignition window." The "power-pressure-gas flow rate safety space" indicates that within this space, the reflected power is within a safe threshold and can stably ignite. The "ignition window" indicates the pressure and power range within which each gas combination can stably ignite the plasma.

[0072] The alarm record retrieval unit 107 is used to retrieve the equipment alarm handling process from the equipment management knowledge base of the experimental platform.

[0073] The equipment intelligent management module 200 is used to verify the feasibility of the process formula information, real-time operating parameters of the dry etching equipment, historical process flow information of sample processing, user permissions, and the cross-contamination probability of the historical process flow of the dry etching task to be executed, based on the process formula information, real-time operating parameters of the dry etching equipment, historical process flow information of the sample processing, user permissions, and etching process knowledge base of the dry etching task to be executed. If the feasibility of the process formula information, user permissions, and cross-contamination probability of the historical process flow all pass the verification, the module generates the corresponding dry etching operation instruction in combination with the dry etching task to be executed and sends the dry etching operation instruction to the RPA equipment operation module.

[0074] The equipment intelligent management module 200 includes a cost calculation unit 201, an authorization management unit 202, a formula parameter verification unit 203, an alarm processing unit 204, and an equipment maintenance unit 205.

[0075] The cost calculation unit 201 is used to calculate the equipment operating cost by combining the real-time operating parameters and process recipe information of the dry etching equipment. Specifically, the cost calculation unit dynamically calculates the cost by retrieving real-time operating parameters such as gas consumption, RF power usage time, and equipment operating temperature during the execution of the process recipe information. In this embodiment, the cost calculation unit can determine the time window corresponding to each step in the process recipe information through the equipment software robot; based on the time window, it extracts the various gas consumption, process temperature, and corresponding RF activation time for each step from the real-time operating parameters; it obtains the gas cost based on the various gas consumption and unit price of each gas for each step; it obtains the equipment time cost based on the time window corresponding to each step and the unit price of the dry etching equipment; it obtains the equipment depreciation cost based on the process temperature and corresponding RF activation time for each step; finally, it sums up the gas cost, equipment time cost, and equipment depreciation cost to obtain the dry etching equipment operating cost.

[0076] The authorization management unit 202 is used to determine the usage rights of process formulas and materials on the dry etching equipment based on user permissions, process formula information, material information permitted for use on the dry etching equipment, and historical real-time process flow information. The authorization management unit prevents the unauthorized use of special gases or process formula information that does not meet the operating requirements of the dry etching equipment.

[0077] The formula parameter verification unit 203 is used to determine whether the configured process formula parameters meet the process parameter requirements of the dry etching equipment based on etching process knowledge. In this embodiment, the formula parameter verification unit can quickly determine whether the process formula parameters are compliant based on the rules and models of the dry etching equipment, reducing equipment damage caused by improper formula parameter settings.

[0078] The alarm processing unit 204 is used to retrieve the device alarm processing flow based on the alarm information. In this embodiment, the alarm processing unit can match the alarm information from the device alarm processing system after receiving the alarm information. If the match is successful, the alarm information can be processed according to the set device alarm processing flow or a historical device alarm processing flow.

[0079] The equipment maintenance unit 205 is used to generate equipment maintenance work orders based on real-time operating parameters. The equipment maintenance unit can determine the operating status of equipment components through real-time operating parameters, perform predictive maintenance based on the specific operating status of equipment components, and link with the work order system to automatically generate maintenance work orders after predicting early warnings for equipment components.

[0080] The RPA device operation module 300 is used to perform automated operations on the components or input boxes of the dry etching interactive interface according to the standardized operating procedures of the dry etching equipment and the received dry etching operation instructions.

[0081] Specifically, the RPA device operation module in this embodiment is a processing module equipped with a Robotic Process Automation (RPA) technology architecture. Through integrated standard operation steps, after the user makes a simple confirmation from the interactive interface, the entire operation steps in the process flow information can be completed by the RPA robot, avoiding situations where the device alarms due to user misoperation or unfamiliar users may cause equipment to alarm due to incorrect operation sequence.

[0082] This embodiment utilizes an RPA robot to integrate the RPA information capture module, equipment intelligent management module, and RPA equipment operation module within the dry etching equipment management system. The RPA information capture module retrieves relevant information from various systems within the experimental platform and the dry etching equipment. The equipment intelligent management module integrates this information, assesses the operating status of the dry etching equipment, determines the feasibility of process formulations, and executes process flow information via the RPA equipment operation module. This improves the automated management of the dry etching equipment, effectively monitors user process steps, accurately monitors the health status of special gases and equipment components, and ultimately enhances the operating and maintenance efficiency of the dry etching equipment.

[0083] Based on the aforementioned management system for dry etching equipment, this embodiment of the invention also proposes a corresponding management method for dry etching equipment. This management method, when executed by the equipment intelligent management module within the management system for dry etching equipment, is combined with the appended... Figure 2 The diagram illustrating the management method for dry etching equipment explains the specific steps of the management method in conjunction with the specific process formula information executed by the dry etching equipment:

[0084] (1) Process formulation parameter management

[0085] First, before the dry etching equipment executes the specific process formulation information, the feasibility and compliance of the specific process formulation information need to be verified. In this embodiment, the process formulation parameter management process is divided into two parts: one part checks whether individual process formulation parameters are compliant, and the other part checks whether the combination of key parameters in the entire process formulation flow is compliant, including the following steps:

[0086] Step S401: The equipment status capture unit is used to capture the process formula information of the dry etching equipment from the equipment monitoring system of the experimental platform, and the etching process knowledge is captured by the knowledge base capture unit from the process knowledge base of the experimental platform.

[0087] Step S402: For any process parameter in the process formula information, retrieve the parameter limit range corresponding to that process parameter from the etching process knowledge.

[0088] Step S403: If the process parameter does not meet the corresponding parameter limit range, generate process formula warning information.

[0089] Specifically, for each process parameter, the parameter can be directly compared with the corresponding parameter limit range in the etching process knowledge during the user configuration process. If the user-configured parameter exceeds the parameter limit range, a process formula warning message will be issued to remind the user that the process formula parameter does not meet the limit range of the dry etching equipment for process formula parameters.

[0090] Step S404: If all process parameters in the process formula information meet the corresponding parameter limit range, extract the key parameter combination from the process formula information.

[0091] Specifically, considering that the process formula information contains key formula information and basic formula information, and in order to improve the efficiency of judging whether there are contradictions or dangerous combinations in the process formula information, only the relevant process parameters in all key formula information can be retrieved to construct key parameter combinations for judgment.

[0092] Step S405: Traverse the historical process formula information according to the key parameter combination. If the historical process formula information does not contain the key parameter combination, compare the key parameter combination with the equipment safety window in the etching process knowledge.

[0093] Specifically, when a combination of key parameters matches any historical process recipe record in the historical process recipe information, the safety of the combination of key parameters can be determined based on whether the historical process recipe record caused damage to the equipment. If the corresponding historical process recipe record did not cause damage to the equipment, the process flow can be directly executed using the combination of key parameters. If the corresponding historical process recipe record shows that the equipment was damaged, an alarm needs to be issued for the combination of key parameters or the equipment should be directly prohibited from being started based on the combination of key parameters.

[0094] Step S406: If the combination of key parameters is within the equipment safety window of the etching process knowledge, input all process parameters in the process formula information into the RPA equipment operation module.

[0095] Step S407: If the combination of key parameters is not within the equipment safety window of the etching process knowledge, input the combination of key parameters into the Paschen curve model and impedance matching model of plasma ignition for simulation.

[0096] Step S408: If the simulation result is in the normal ignition region and the impedance matching degree is lower than the preset threshold, input all process parameters in the process formula information to the RPA equipment operation module.

[0097] It should be noted that the equipment safety window in the etching process knowledge in this embodiment is a safety window determined for known process formulations of dry etching equipment. When the combination of key parameters is within the equipment safety window, it means that, based on the dry etching process knowledge, it can be deduced that the process formulation, which has not been verified by historical records, is safe and feasible and will not damage the equipment. However, if the combination of key parameters is not within the equipment safety window, it does not mean that the process formulation is necessarily infeasible or will necessarily damage the equipment. Rather, it is necessary to further verify the unknown process formulation by combining the Paschen curve model of plasma initiation and the impedance matching model.

[0098] Specifically, the purpose of simulating the Paschen curve model for plasma ignition by inputting key parameter combinations is to calculate the position of these key parameter combinations on the Paschen curve in real time. If it is in the "difficult to ignite" (i.e., abnormal ignition region) area, it indicates that the input gas pressure is too high or too low, and corresponding pressure warning information needs to be generated. The Paschen curve is used to represent the relationship between gas breakdown voltage and the product of electrode spacing and gas pressure, and is crucial for plasma generation and maintenance. During dry etching, plasma is generated by applying an electric field to a low-pressure gas. Gas molecules ionize to form ions, electrons, and free radicals, and these active species work together to remove materials.

[0099] The purpose of inputting key parameter combinations into the impedance matching model is to determine the plasma impedance under given process conditions and calculate the matching degree with the standard impedance of the RF power supply (typically 50Ω). If the estimated reflected power exceeds the set threshold, an impedance warning message is generated.

[0100] Step S409: If the simulation result is in an abnormal ignition region or the impedance matching degree exceeds a preset threshold, generate a recipe warning message.

[0101] When a user receives a recipe warning, they need to adjust the process recipe of the dry etching equipment according to the content of the recipe warning to achieve the condition that the simulation results are in the normal ignition region and the impedance matching degree is lower than the preset threshold.

[0102] (2) Special gas management procedures for equipment use

[0103] Once the feasibility and compliance of the process formulation information are verified, considering that dry etching equipment requires the use of special gases in almost all core etching operations—these special gases are the core media for plasma generation, material etching, sidewall protection, and surface modification—the selection and proportion of special gases are determined by the process objectives of different operations. However, the use of special gases can be corrosive, toxic, or flammable and explosive. To ensure the safety and standardization of special gas use, this embodiment also needs to verify the user's permissions and the materials permitted for use by the dry etching equipment when verifying the use of special gases. Specifically:

[0104] Step S501: If the process formula information for the sample processing includes a special gas, retrieve the material information and user permissions for the dry etching equipment as fed back by the RPA information capture module.

[0105] Step S502: If the material information permitted for use by the dry etching equipment includes the special gas, and the user permissions include the usage permission for the special gas, update the special gas usage permission of the corresponding process formula information.

[0106] Specifically, for the use of special gases, such as chlorine, there is a dedicated special gas authorization system. Only users with the necessary authorization can use this special gas during the dry etching process. This is manifested in the authorization management unit updating the process formulation information for the corresponding processed sample. This system allows for precise control over special gases, reducing the risks associated with their management.

[0107] (3) Management of sample contamination of equipment

[0108] In this embodiment, considering that there are preliminary sample processing steps (such as cleaning, deposition, photolithography, etc.) before the sample enters the dry etching equipment, there may be residual particulate matter, organic matter, metallic impurities, and chemical byproducts in the preliminary sample processing steps, which can easily contaminate the dry etching equipment during the dry etching process. To prevent cross-contamination of the dry etching equipment caused by the above situations, the following steps are set before inputting all process parameters in the process formula information into the RPA operation module:

[0109] Step S601: Obtain the historical real process flow information of sample processing fed back by the experimental record capture unit in the RPA information capture module, and the planned process flow information of the sample fed back by the process capture unit.

[0110] Specifically, in this embodiment, the historical real process flow information of sample processing refers to the historical process flow information of the same sample to be processed before it enters the dry etching equipment, which was executed by other processing equipment in the experimental platform. This includes the processing steps, processing formula, processing temperature, processing time, and evaluation information of the processed sample corresponding to each historical process flow.

[0111] Step S602: If the historical actual process flow information of the sample processing is inconsistent with the planned process flow information of the sample, the probability of cross-contamination during the processing of the sample on the dry etching equipment is determined by combining the historical actual process flow information of the sample processing with the corresponding process formula information.

[0112] Specifically, since the planned process flow information for the sample is verified by a knowledge base or formulated with reference to historical processing process flow information, the planned process flow information is relatively rigorous. When the historical actual process flow information for sample processing is inconsistent with the planned process flow information, there is a high probability that some steps (such as residue cleaning, sample cleaning, etc.) in the previous sample processing operation were omitted or the operation time was insufficient. If this occurs during the dry etching process, it is highly likely that cross-contamination will occur.

[0113] The determination of whether there is cross-contamination between the historical process flow information of sample processing and the process formulation information of dry etching mainly includes the following aspects: ① Whether the historical process flow information of sample processing meets the standards, such as whether the cleaning time in the cleaning step of the sample reaches the standard value, or whether there is a problem of excessive deposition time in the deposition process of the sample leading to reactant residue; ② Whether the sample processed by the historical process flow has the possibility of interacting with the process formulation information of dry etching to generate by-products, such as the organic matter remaining on the sample surface after the cleaning step, which can easily interact with one of the reactants in the dry etching process formulation to generate by-products and cause equipment contamination, or the presence of tiny metal media on the sample surface after the previous photolithography process, which can be easily sputtered into the equipment reaction chamber by high-energy ion beam during the dry etching process, leading to equipment contamination, etc.

[0114] Furthermore, in this embodiment, the determination of whether the historical process flow information of the sample processing and the dry etching process formula are contaminated can also be achieved using a trained neural network (such as an RNN neural network, LSTM neural network, etc.). The historical processing records of the dry etching equipment are used as the training dataset. Each historical processing record includes the preceding process flow information of the historical sample processing and the dry etching process formula. Each historical processing record is marked with whether it has caused contamination to the dry etching equipment. The above historical processing records can be expanded by combining the standards for samples entering the dry etching equipment. The training dataset is divided into positive samples and negative samples to train the selected neural network model. The relevant parameters of the neural network model are adjusted until the trained neural network model can accurately output the probability that the preceding process flow information of the historical sample processing and the dry etching process formula have caused contamination to the dry etching equipment.

[0115] Step S603: If the probability of cross-contamination between the historical process flow information of the sample processing and the process formula information of dry etching is greater than a set threshold, then a process flow information alarm message is issued.

[0116] When the probability of cross-contamination between the historical process flow information of sample processing and the process formula information of dry etching is greater than a set threshold (e.g., the probability of cross-contamination is greater than 50%), a process flow alarm message is generated to remind the user to adjust the process formula information of dry etching or replace the etching process and etching equipment.

[0117] (4) Equipment billing management process

[0118] Furthermore, after the RPA equipment operation module performs automated operations on the components or input boxes of the dry etching interface according to the specific process formula information, considering the differences between the actual gas usage and actual process operation time and the planned process flow information during the execution of the dry etching equipment, in order to improve the accuracy of billing during the user's use of the dry etching equipment, this embodiment also sets up the following steps to limit the billing management process of the dry etching equipment:

[0119] Step S701: Obtain the real-time operating parameters and process formula information of the dry etching equipment from the equipment monitoring system of the experimental platform by the equipment status capture unit, and the sample processing plan process flow information from the work order system of the experimental platform by the process capture unit.

[0120] Step S702: Determine the time window corresponding to each step in the process formula information.

[0121] Specifically, the time window for each step records the start and end times of each step.

[0122] Step S703: Extract the various gas consumption, process temperature and corresponding RF activation time corresponding to each step from the real-time operating parameters of the dry etching equipment according to the time window.

[0123] Step S704: Calculate the gas cost based on the gas usage and unit price of each gas in each step.

[0124] Step S705: Obtain the equipment time cost based on the time window corresponding to each step, the planned process flow information of the sample processing, and the unit price of the dry etching equipment.

[0125] Step S706: Calculate the equipment loss cost based on the process temperature and RF activation time corresponding to each step.

[0126] Specifically, the formula for equipment loss cost is: Equipment Loss Cost = Equipment Base Rate * RF Time Ratio * Temperature Coefficient. The equipment base rate refers to the basic loss cost during equipment use. The RF time ratio represents the ratio of RF activation time to the total duration of the process recipe information. The temperature coefficient needs to be found in the specific process temperature-temperature coefficient table. When the process temperature is 20℃, the temperature coefficient is 1; when the process temperature is 0℃, the temperature coefficient is 1.3; and when the process temperature is 40℃, the temperature coefficient is 1.2.

[0127] Step S707: Obtain the equipment operating cost of the dry etching equipment based on the gas cost, equipment time cost, and equipment wear and tear cost.

[0128] Specifically, equipment operating costs are determined by adding gas costs, equipment operating time costs, and equipment depreciation costs.

[0129] (5) Equipment alarm management

[0130] If an alarm message is received, the corresponding alarm handling process is scheduled from the standardized operating procedure of the dry etching equipment based on the real-time operating parameters of the dry etching equipment, and the alarm handling process is sent to the RPA equipment operation module to resolve the alarm message.

[0131] For example, when the first helium flow rate of the dry etching equipment exceeds the soft tolerance alarm, the software robot determines the specific equipment alarm handling process based on the equipment alarm handling procedure as follows: "Click the alarm interface → select the alarm information → click the alarm option to confirm → if the indicator light turns yellow → automatically select the Decchuck process in the manual process interface (it is necessary to check whether the ESC temperature in the Decchuck Recipe is consistent with the cooler temperature in the monitoring interface. If they are inconsistent, automatically modify the Decchuck temperature) → click the start process of the manual process → the indicator light turns yellow, click transmit."

[0132] (6) Equipment maintenance and management

[0133] Step S801: Obtain the real-time operating parameters of the dry etching equipment.

[0134] Step S802: If any of the real-time operating parameters deviates from the equipment operating parameter reference range, an equipment maintenance work order is generated by combining the real-time operating parameters and the process flow information executed by the dry etching equipment.

[0135] By analyzing the real-time operating parameters of the dry etching equipment, the operating status of each component within the equipment is determined. The dry etching equipment has a reference range for each operating parameter. When any operating parameter deviates from the reference range, it means that the operating parameter is abnormal and may cause the dry etching equipment to malfunction. To ensure the normal operation of the dry etching equipment, maintenance work orders are generated, which can effectively avoid the waste of resources or insufficient maintenance caused by timely replacement of equipment components.

[0136] The following explanation uses the maintenance prediction of radio frequency reflection power as an example:

[0137] The radio frequency reflected power is directly proportional to the degree of impedance mismatch, and the increase in radio frequency reflected power is a gradual process.

[0138] Under normal operating conditions of the dry etching equipment, the RF transmission power is less than 1% or less than 2% (e.g., at 1000W power, the RF transmission power is less than 10W or less than 20W); the matching time is less than 1 second or less than 2 seconds.

[0139] Therefore, if any of the following symptoms occur, a device maintenance reminder work order can be generated based on real-time operating parameters:

[0140] (1) The baseline value of the RF reflected power shows a slow but continuous increase under the same process (e.g., from 1% to 1.5%, and then to 2%).

[0141] (2) Matching time has started to increase, and occasionally there will be situations where "rematching" is required;

[0142] (3) The reflected power will have brief, occasional spikes.

[0143] If any of the following symptoms occur, a maintenance work order can be generated based on real-time operating parameters:

[0144] (1) The baseline value of radio frequency reflected power increases significantly (e.g., stabilizes at 5% or higher);

[0145] (2) The matching time has become significantly longer and unstable.

[0146] Furthermore, to improve the efficiency of early warning status judgment and equipment maintenance work order generation, this embodiment can also combine the XGBoost classification model to judge the early warning status of dry etching equipment, specifically as follows:

[0147] Step S1: Real-time acquisition of operating data of the dry etching equipment and corresponding process batch context information.

[0148] The real-time operating data includes forward power, reflected power, reflected power percentage, and cap position inside the matcher. The process batch context information includes the process recipe ID, chamber ID, process start timestamp, process end timestamp, and target power set for the process.

[0149] Step S2: Aggregate high-frequency data from the real-time operation data for each process batch.

[0150] This setting takes into account that different processes have different power settings, and the absolute value of the reflected power is not very meaningful. The ratio of reflected power to forward power is the key indicator.

[0151] Step S3: Obtain the characteristics of the process batch based on the real-time operating data after aggregation.

[0152] Specifically, the characteristics of each process batch include baseline level characteristics, stability and fluctuation characteristics, matching performance characteristics, trend characteristics, and contextual characteristics.

[0153] Among them, the baseline level features reflect the slow rise of real-time running data, including the average percentage of reflected power, denoted as ref_ratio_mean; the median of reflected power, denoted as ref_ratio_median, which is not sensitive to peaks and can better reflect the baseline; and the 90th percentile, denoted as ref_ratio_90percentile, which is used to reflect the overall level but excludes extreme peaks.

[0154] Stability and volatility characteristics reflect occasional spikes and instability, including the standard deviation of the percentage of reflected power, denoted as ref_ratio_std, used to measure volatility; the maximum value within a process batch, denoted as ref_ratio_max, used to capture significant spikes; and the number of spikes in reflected power exceeding a set threshold, denoted as peak_count, which can be three times the standard deviation of the normal baseline.

[0155] Matching performance characteristics reflect whether the matching time has increased, including matching time, denoted as tuning_time, which is the time required from the start of the process until the reflected power first drops to a stable low level; and matching count, denoted as retune_count, which is the number of times the system needs to rematch during the process.

[0156] Trend characteristics reflect the gradual process and are the most important features for measuring the operating status of dry etching equipment. It is necessary to calculate the moving statistics of the above baseline characteristics. Taking the most recent N (N=20) batches as an example, this includes the average of the N batches, denoted as rolling_mean_20, which represents the average of the ref_ratio_mean of the most recent 20 batches; the standard deviation of the N batches, denoted as rolling_std_20, which represents the standard deviation of the ref_ratio_mean of the most recent 20 batches; and the slope of the N batches, denoted as trend_slope, obtained by performing linear regression on the ref_ratio_mean of the most recent 20 batches. A continuously positive slope is a very strong early warning signal.

[0157] Contextual features include recipe ID and reaction chamber ID. Recipe ID, denoted as recipe_id, is used to distinguish the "normal" baseline for different processes; reaction chamber ID, denoted as chamber_id, is used to distinguish the aging degree of different equipment.

[0158] Step S4: Set labels for the historical dataset to distinguish between normal status, warning prompt status and warning status corresponding to the historical data patterns.

[0159] When the historical data pattern corresponds to the warning status, it means that within the next M batches (e.g., M=5), the dry etching equipment has experienced one of the following situations: the average reflected power ref_ratio_mean is continuously > 5% or the equipment alarms and shuts down due to excessive reflected power; at this time, the label is recorded as Label = 2.

[0160] When the historical data pattern corresponds to the warning prompt status, it means that within the next M batches, the "warning" standard has not been met, but the following trends have occurred: the trend slope of the moving average of the reflection power, trend_slope, is continuously positive and exceeds the threshold; or the moving average of tuning_time or peak_count is significantly higher than the historical normal baseline of the device; at this time, the label is recorded as Label = 1.

[0161] When the historical data pattern corresponds to the normal status, it means batches that do not meet either the pre-warning or warning conditions. At this time, the label is recorded as Label = 0.

[0162] It should be noted that the above labels are defined based on "future" information. During training, we use the features of the Nth batch to predict whether there will be problems in the N+Kth batch (K<M), which ensures the predictability of the model.

[0163] Step S5, train the XGBoost model based on the above-labeled historical dataset until the model output conditions are met.

[0164] In the data splitting stage, split the data in chronological order. For example, use the data of the first 80% of the time for training and the last 20% for testing; randomly shuffling is strictly prohibited.

[0165] In the training and evaluation stage, the input is the feature vector generated in feature engineering; the output is the probability belonging to three labels (Label = 0, 1, 2). The above evaluation metrics include accuracy, precision, recall, and F1 score, and focus on the recall rate for the "warning" and "pre-warning" categories.

[0166] The trained model service can return the prediction result (for example: {batch_id: 123, prediction: 1, confidence: 0.95}). The warning result is pushed to the message queue or database: when Prediction = 0, no operation is performed, or a log is recorded. When Prediction = 1, a warning prompt work order is automatically generated in the MES to notify the engineer to check during the planned downtime. When Prediction = 2, a high-level alarm is triggered, and a work order is automatically generated for the maintenance engineer, suggesting an immediate inspection to prevent unplanned downtime.

[0167] Furthermore, this embodiment can also set to continuously monitor the prediction accuracy and latency of the model. If the performance deteriorates (the data distribution changes, i.e., "concept drift"), model retraining needs to be triggered. And the actual maintenance results of the maintenance personnel (whether there is actually a fault) are fed back to the system as new labels for optimizing the next version of the model.

[0168] It should be understood that, although attached Figure 1 The steps in the flowchart are shown sequentially according to the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order requirement for the execution of these steps, and they can be executed in other orders. Furthermore, [the following is a list of steps]. Figure 1 At least some of the steps in the process may include multiple sub-steps or sub-stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0169] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A management system for a dry etching apparatus, characterized in that, It includes an RPA information capture module, an intelligent device management module, and an RPA device operation module, wherein the intelligent device management module is communicatively connected to the RPA information capture module and the RPA device operation module, respectively. The RPA information capture module is used to retrieve information capture instructions according to the dry etching task to be executed by the dry etching equipment. This enables the RPA robot to retrieve the process formula information, real-time operating parameters of the dry etching equipment, historical process flow information of sample processing, user permissions, and etching process knowledge base corresponding to the dry etching task to be executed from at least one system in the experimental platform according to the information capture instructions. The intelligent equipment management module is used to verify the feasibility of the process formula information, real-time operating parameters of the dry etching equipment, historical process flow information of sample processing, user permissions, and the cross-contamination probability of the historical process flow of the dry etching task to be executed, based on the process formula information, real-time operating parameters of the dry etching equipment, historical process flow information of the sample processing, user permissions, and etching process knowledge base of the dry etching task to be executed. If the feasibility of the process formula information, user permissions, and cross-contamination probability of the historical process flow all pass the verification, the module generates the corresponding dry etching operation instruction in combination with the dry etching task to be executed and sends the dry etching operation instruction to the RPA equipment operation module. The RPA device operation module is used to perform automated operations on the components or input boxes of the dry etching interactive interface according to the standardized operation procedures of the dry etching equipment and the received dry etching operation instructions.

2. The management system of the dry etching equipment as described in claim 1, characterized in that, The RPA information capture module includes an equipment status capture unit, a process capture unit, a user information capture unit, a material capture unit, an experimental record capture unit, a knowledge base capture unit, and an alarm record retrieval unit; The equipment status capture unit is used to capture the real-time operating parameters of the dry etching equipment and the process formula information corresponding to the dry etching task to be executed from the equipment monitoring system of the experimental platform. The process grabbing unit is used to grab the planned process flow information of the sample corresponding to the dry etching task to be executed from the work order system of the experimental platform. The user information capture unit is used to capture user permissions for the dry etching equipment from the equipment management knowledge base of the experimental platform. The material grabbing unit is used to grab material information that is permitted to be used in dry etching equipment from the equipment management knowledge base of the experimental platform; the experimental record grabbing unit is used to grab historical real process flow information of sample processing from the experimental notebook system of the experimental platform; The knowledge base crawling unit is used to crawl etching process knowledge from the process knowledge base of the experimental platform; The alarm record retrieval unit is used to retrieve the equipment alarm handling process from the equipment management knowledge base of the experimental platform.

3. The management system of the dry etching equipment as described in claim 2, characterized in that, The intelligent equipment management module includes a cost calculation unit, an authorization management unit, a formula parameter verification unit, an alarm processing unit, and an equipment maintenance unit. The cost calculation unit is used to calculate equipment wear and tear costs by combining the real-time operating parameters and process formula information of the dry etching equipment. The authorization management unit is used to determine the usage rights of process formulas and materials in dry etching equipment based on user permissions, process formula information, material information permitted for use in dry etching equipment, and historical real process flow information. The formula parameter verification unit is used to determine whether the configured process formula parameters meet the process parameter requirements of the dry etching equipment based on etching process knowledge. The alarm processing unit is used to retrieve the device alarm processing flow based on the alarm information. The equipment maintenance unit is used to generate equipment maintenance work orders based on real-time operating parameters.

4. A management method for a dry etching apparatus, wherein the management method for the dry etching apparatus is applied to the intelligent equipment management module of the management system for the dry etching apparatus as described in any one of claims 1-3, characterized in that, The RPA information capture module includes an equipment status capture unit, a process capture unit, and a knowledge base capture unit. The management method for the dry etching equipment includes the following steps: The equipment status capture unit is used to capture process formula information of dry etching equipment from the equipment monitoring system of the experimental platform, and the knowledge base capture unit captures etching process knowledge from the process knowledge base of the experimental platform. For any process parameter in the process formula information, retrieve the corresponding parameter limit range from the etching process knowledge; If all process parameters in the process formula information meet the corresponding parameter limit range, extract the key parameter combination from the process formula information; Based on the combination of key parameters, traverse the historical process formula information. If the historical process formula information does not contain the combination of key parameters, compare the combination of key parameters with the equipment safety window in the etching process knowledge. If the combination of key parameters is not within the equipment safety window of the etching process knowledge, the combination of key parameters is input into the Paschen curve model and impedance matching model of plasma initiation for simulation. If the simulation results are in the normal ignition region and the impedance matching degree is lower than the preset threshold, input all process parameters in the process recipe information into the RPA equipment operation module. If the simulation results are in an abnormal ignition region or the impedance matching degree exceeds the preset threshold, a recipe warning message will be generated.

5. The management method for the dry etching equipment as described in claim 4, characterized in that, Also includes: If any process in the process formula information does not meet the corresponding parameter limit range, a formula warning information is generated. If the combination of key parameters is within the equipment safety window of the etching process knowledge, input all process parameters in the process formula information into the RPA equipment operation module.

6. The management method for the dry etching equipment as described in claim 4, characterized in that, Also includes: If the process formulation information for the sample processing includes special gases, retrieve the material information and user permissions for the dry etching equipment that are permitted to be used, which are fed back by the RPA information capture module. If the material information permitted for use by the dry etching equipment includes the special gas, and the user permissions include the usage permission for the special gas, then update the special gas usage permission for the corresponding process formulation information.

7. The management method for the dry etching equipment as described in claim 4, characterized in that, Before inputting all process parameters from the process recipe information into the RPA equipment operation module, the following steps are also included: Obtain the historical real process flow information of sample processing fed back by the experimental record capture unit in the RPA information capture module, as well as the planned process flow information of the sample fed back by the process capture unit; If the historical actual process flow information of the sample processing is inconsistent with the planned process flow information of the sample, the probability of cross-contamination when the sample is processed on the dry etching equipment is determined by combining the historical actual process flow information of the sample processing with the corresponding process formula information of the sample processing. If the probability of cross-contamination during the processing of the sample on a dry etching device is greater than a set threshold, a process flow alarm message will be issued.

8. The management method for the dry etching equipment as described in claim 4, characterized in that, Also includes: The equipment status capture unit captures real-time operating parameters and process formula information of the dry etching equipment from the equipment monitoring system of the experimental platform, and the process capture unit captures planned process flow information of sample processing from the work order system of the experimental platform. Determine the time window corresponding to each step in the process formulation information; Based on the time window, extract the various gas consumption, process temperature and corresponding RF activation time for each step from the real-time operating parameters of the dry etching equipment. The gas cost is calculated based on the amount of each gas used in each step and the unit price of each gas. The equipment time cost is obtained based on the time window corresponding to each step, the planned process flow information for sample processing, and the unit price of the dry etching equipment. The equipment depreciation cost is calculated based on the process temperature and RF activation time for each step. The total cost of using the dry etching equipment is calculated based on the gas cost, equipment operating time cost, and equipment depreciation cost.

9. The management method for the dry etching equipment as described in claim 8, characterized in that, Also includes: If an alarm message is received, the corresponding alarm handling process is scheduled from the standardized operating procedure of the dry etching equipment based on the real-time operating parameters of the dry etching equipment, and the alarm handling process is sent to the RPA equipment operation module to resolve the alarm message.

10. The management method for the dry etching equipment as described in claim 9, characterized in that, Also includes: Obtain real-time operating parameters of the dry etching equipment; If any of the real-time operating parameters deviates from the equipment operating parameter reference range, an equipment maintenance work order is generated by combining the real-time operating parameters with the process flow information executed by the dry etching equipment.

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