Semiconductor-based exception handling method and device, medium and product

Abstract

The embodiment of the invention relates to the technical field of semiconductor manufacturing, and discloses a semiconductor-based exception handling method and device, a medium and a product. The method is applied to a virtual measurement system. The method comprises the following steps: acquiring parameter information of equipment; determining whether the equipment is abnormal or not according to the parameter information; if the equipment is abnormal, maintaining the abnormal equipment; and if the equipment is not abnormal, triggering an equipment measurement function, and counting target information of the wafer yield. The technical problem of low wafer production efficiency caused by defective product detection in the prior art can be at least solved.

Description

Technical Field

[0001] The present application relates to the field of semiconductor manufacturing technology, and in particular to a semiconductor-based exception handling method, device, medium and product. Background Art

[0002] Etching and processing wafers are crucial steps in the semiconductor manufacturing process. These steps form micron or even nanometer-level circuit patterns on the surface of the wafer, thereby building the microelectronic components required for electronic devices. During the etching and processing of wafers, detecting defective products (or unqualified products) is the key to ensuring product quality and yield.

[0003] In the related art, in order to detect defective products, some methods involve manually measuring wafers during etching and processing; some methods involve monitoring production data and manually intervening and adjusting based on the monitored production data.

[0004] The inventors have discovered that there are at least the following technical problems in the related technology: before manually measuring the wafers during the etching and processing process, the machine needs to be stopped for inspection, which greatly affects the production efficiency of the wafers; and in the solution where manual intervention and adjustment is performed based on the monitored production data, the time cost is high, resulting in the wafer production efficiency still being unsatisfactory. Summary of the invention

[0005] One purpose of the present application is to provide a semiconductor-based exception handling method, device, medium and product, at least to solve the technical problem in the related art that the production efficiency of wafers is low due to the detection of defective products.

[0006] To achieve the above objectives, some embodiments of the present application provide the following aspects:

[0007] In the first aspect, some embodiments of the present application also provide a semiconductor exception handling method, which is applied to a virtual measurement system; the method includes: obtaining parameter information of a device; determining whether the device has an abnormality based on the parameter information; if the device has an abnormality, maintaining the abnormal device; if the device has no abnormality, triggering the device measurement function, and statistically calculating target information of wafer yield.

[0008] In a second aspect, some embodiments of the present application further provide an electronic device, comprising: one or more processors; and a memory storing computer program instructions, wherein the computer program instructions, when executed, cause the processor to perform the steps of the method described above.

[0009] In a third aspect, some embodiments of the present application further provide a computer-readable medium having computer program instructions stored thereon, wherein the computer program instructions can be executed by a processor to implement the method as described above.

[0010] In a fourth aspect, some embodiments of the present application further provide a computer program product, comprising a computer program / instruction, which implements the steps of the method described above when executed by a processor.

[0011] Compared with the related art, the solution provided in the embodiment of the present application provides a semiconductor abnormality handling method, which is applied to a virtual measurement system to obtain parameter information of the device; determine whether the device is abnormal according to the parameter information; if the device is abnormal, maintain the abnormal device; if the device is not abnormal, trigger the device measurement function, and count the target information of the wafer yield. Due to the solution provided by the embodiment of the present application, before manually measuring the wafer in the etching and processing process, there is no need to stop the machine for inspection, so it will not affect the production efficiency of the wafer; because the dependence on manual intervention is reduced, the time cost can be reduced, and the purpose of improving the production efficiency of the wafer is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] One or more embodiments are exemplarily described by pictures in the corresponding drawings, and these exemplified descriptions do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0013] Figure 1 An exemplary flow chart of a semiconductor-based exception handling method provided according to some embodiments of the present application;

[0014] Figure 2 An exemplary flow chart of a semiconductor-based abnormality processing method according to some embodiments of the present application, after determining whether the device is abnormal according to the parameter information;

[0015] Figure 3 An exemplary flow chart of an application example of a semiconductor-based exception handling method provided according to some embodiments of the present application;

[0016] Figure 4 This is an exemplary structural diagram of an electronic device provided according to some embodiments of the present application. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0018] The following terms are used in this article.

[0019] Virtual Measurement System, or VMS for short, is a measurement system based on computer simulation and virtual technology. It can simulate and analyze various physical quantities of wafers without actual physical measurement equipment.

[0020] The factory process management system, the full English name is Fab Flow System, or FFS for short. It is a system designed for wafer fab factories that runs through all systems in the factory and provides a full range of interactive workflows for production purposes.

[0021] Fault Detection and Classification System, or FDC for short, is a key technology system used in the semiconductor manufacturing field to improve equipment efficiency, stability, and process consistency.

[0022] PMS system, which refers to preventive maintenance system, is a tool used to plan and execute equipment maintenance activities, with the aim of reducing equipment failures and extending equipment life.

[0023] PTS system, which refers to the Parts Tracking System, is a system used to manage equipment parts. It can track the inventory, procurement and use of parts.

[0024] DMS system, the full name of which is Semiconductor Device Manufacturing System, is an automation system used in the semiconductor device manufacturing process. The system combines semiconductor equipment, control software and automation technology to improve the efficiency, quality and reliability of the semiconductor manufacturing process.

[0025] YMS system refers to the yield management system.

[0026] First embodiment

[0027] The first embodiment of the present application relates to a semiconductor-based abnormality processing method. Figure 1As shown, the method is applied to a virtual measurement system, and the method may include the following steps:

[0028] Step S101, obtaining parameter information of the device;

[0029] Step S102, determining whether the device is abnormal according to the parameter information;

[0030] Step S103, if the device is abnormal, then maintain the abnormal device;

[0031] Step S104: If the device does not have any abnormality, the device measurement function is triggered, and target information of the Lot yield is counted.

[0032] The following is a detailed description of each of the above steps.

[0033] Regarding step S101, specifically, in some examples, the parameter information of the device can be obtained through the FDC system. The device can be a machine used to produce the semiconductor; the parameter information can include but is not limited to: type information of the device, performance indicator information of the device, and key parameter information of the device during operation. Furthermore, the key parameter information can include but is not limited to: parameter information such as temperature, pressure, time, and speed.

[0034] Regarding step S102, specifically, in some examples, it can be determined whether the device is abnormal based on whether the parameter information is within a preset normal working threshold range. For example, if there is parameter information that is not within the preset normal working threshold range, it can be determined that the device is abnormal, otherwise, it can be determined that the device is not abnormal.

[0035] Regarding step S103, specifically, in some examples, if the device is abnormal, the PMS system can be used to maintain the abnormal device to achieve the purpose of maintenance. For example, it can include inspection, repair, replacement of parts, etc. of the abnormal device. Among them, during the maintenance process, the PTS system can be used to determine the type, quantity and source of the required parts to ensure the smooth progress of the above maintenance work. In addition, the status of the abnormal device can be tracked to continuously monitor the performance and operating status of the abnormal device, so as to timely discover and solve potential problems.

[0036] For step S104, specifically, in some examples, if the device does not have an abnormality, the DMS system can be used to trigger the device measurement function to automatically start the measurement and test procedures for the device to ensure the performance and accuracy of the device. In addition, the YMS system can be used to count the target information of the Lot yield, and the target information includes: arc breakdown yield and defect yield. Among them, the arc breakdown yield refers to the ratio of the number of defective products caused by arc breakdown to the total production quantity during the production process. The defect yield refers to the ratio of the number of defective products caused by various defects (such as material defects, process defects, etc.) to the total production quantity during the production process.

[0037] It should be noted that since the virtual measurement system can simulate and evaluate the performance and characteristics of the design during the design stage of semiconductor devices, by simulating the impact of different process parameters and structural changes on the device, design engineers can verify design choices in advance and optimize the design to meet requirements.

[0038] Considering that actual measurement and testing of semiconductor devices requires expensive equipment and long experimental cycles. The embodiments of the present application can reduce the number and time of experiments, save costs and resources by using a virtual measurement system. Design engineers can guide experimental design and testing strategies through simulation and prediction, thereby achieving design goals more efficiently and reducing experimental cycles and costs.

[0039] Considering that the virtual measurement system can simulate the impact of process parameters on device performance, it helps process engineers optimize the manufacturing process. By simulating the device characteristics and performance under different process conditions, process engineers can adjust process parameters to increase yield, reduce defect rate, and ensure device consistency and reliability.

[0040] Considering that virtual measurement systems can also be used to predict the reliability of semiconductor devices, by simulating the behavior and performance of devices under different stress conditions, their life and reliability can be evaluated, and design and process improvements can be guided to improve the life and reliability of products.

[0041] It is not difficult to find that, compared with the related art, the solution provided in the embodiment of the present application provides a semiconductor abnormality handling method, which is applied to a virtual measurement system to obtain parameter information of the device; determine whether the device is abnormal according to the parameter information; if the device is abnormal, maintain the abnormal device; if the device is not abnormal, trigger the device measurement function, and count the target information of the wafer yield. Due to the solution provided by the embodiment of the present application, there is no need to stop the machine for inspection before manually measuring the wafer during etching and processing, so it will not affect the production efficiency of the wafer; because the dependence on manual intervention is reduced, the time cost can be reduced, and the purpose of improving the production efficiency of the wafer is achieved.

[0042] Second embodiment

[0043] The second embodiment of the present application relates to a semiconductor-based abnormality processing method. The second implementation is an improvement on the first embodiment, and the specific improvement is that after determining whether the device is abnormal according to the parameter information, the method further includes the following steps: Figure 2 As shown:

[0044] Step S201, analyzing the production data of the equipment through a data model; the data model is trained according to the type and characteristics of the production data to obtain:

[0045] Step S202: locating the fault according to the analysis result.

[0046] Specifically, in some examples, the production data may be obtained based on daily data generated by a virtual measurement system in actual factory production collected during the semiconductor manufacturing process.

[0047] Exemplarily, different training schemes can be formed according to the type and characteristics of the production data, and different data models can be obtained according to different training schemes. Specifically, the type of production data may include, but are not limited to: equipment performance data, quality control data, production efficiency data, energy consumption data, etc. The characteristics of the production data may include, but are not limited to: the distribution, range, correlation, periodicity, etc. of the production data. In an embodiment of the present application, a variety of different data models can be developed and applied according to the type and characteristics of the production data in combination with different training schemes to meet different analysis needs and objectives. Then, the data model is loaded into the virtual measurement system, and fault location and analysis are performed through the data model in the virtual measurement system.

[0048] It should be noted that the type, characteristics and factory requirements of the generated data can be customized to obtain the training scheme to meet flexible and diverse requirements. Therefore, the training scheme is not specifically limited in the embodiments of the present application.

[0049] Exemplarily, new production data may be continuously acquired, and the data model may be updated and improved based on the new production data to ensure that the data model can accurately locate and analyze faults.

[0050] Exemplarily, the present application utilizes the production data collected by the virtual measurement system, analyzes and classifies the generated data through the data model, and transmits the analysis and classification results to the FFS system. Specifically, when the FFS system dynamically receives the results of the analysis and classification of the production data according to the data model transmitted back by the virtual measurement system, the FFS system makes a judgment based on the analysis and classification results. If a defect occurs, the FFS system alarm is triggered, and the FFS system automatically processes or manually intervenes to improve the efficiency of the entire production process. Among them, the relationship between the data model and the FFS system is a conditional provision relationship. The FFS system will form a corresponding processing flow for the analysis and classification results based on the training scheme of the data model and its corresponding logic.

[0051] Specifically, in some examples, if a detection failure occurs, an alarm is triggered and automatic processing or manual intervention is performed.

[0052] Optionally, in some embodiments, locating the fault according to the analysis result includes: generating a first result for characterizing the abnormal fault of the machine and / or a second result for characterizing the production fault.

[0053] Specifically, in some examples, during the process of fault location and analysis, the fault detection results can be divided into machine abnormal failures and production failures. The specific scope of the problem in the production process of the problem machine can be located based on the data model formed by the virtual measurement system, which is convenient for engineers to correct and repair the problem in a timely manner.

[0054] It is not difficult to find that in the embodiment of the present application, by first judging whether it is in an abnormal state and distinguishing whether the machine has an abnormality, the production data of the equipment is analyzed through the data model, and then the fault is located based on the analysis results; since the data model is trained according to the type and characteristics of the production data, it is conducive to quickly locating the problem.

[0055] Third embodiment

[0056] The third embodiment of the present application relates to an application example of a semiconductor-based abnormality processing method, such as Figure 3As shown, the method comprises the following steps:

[0057] 1. Data collection;

[0058] 2. Data transmission;

[0059] 3. Data analysis;

[0060] 4. Fault detection and classification;

[0061] 5. Data reporting;

[0062] 6.FFS system processing;

[0063] 7. Feedback and adjustment;

[0064] Among them, data acquisition here refers to obtaining the parameter information of the equipment, and then transmitting the data to input the parameter information of the equipment into the virtual measurement system. The virtual measurement system performs data analysis based on the parameter information to determine whether the equipment is abnormal. If the equipment is abnormal, the abnormal equipment is maintained; if the equipment is not abnormal, the equipment measurement function is triggered, and the target information of the wafer yield is statistically calculated. At the same time, after determining whether the equipment is abnormal based on the parameter information, data reporting is performed. The production data of the equipment is analyzed through a data model; the data model is trained according to the type and characteristics of the production data, and fault location is performed based on the analysis results. The FFS system then processes the analysis results and provides feedback and adjustments.

[0065] Among them, the FFS system can automatically adjust the process parameters by real-time monitoring and analyzing data to maintain the stability and consistency of the production process. Combining the virtual measurement system and the FFS system, the automation and intelligence of the production process can be realized. The virtual measurement system provides a basis for automatic control by simulating and predicting the optimization of design and process parameters. The FFS system can monitor and control the entire production process in real time and realize automated data analysis and processing. This can reduce manual intervention and improve the stability, consistency and reliability of production.

[0066] This application uses a virtual measurement system to monitor the entire production process, which can give an early warning and connect to the FFS system. The system can handle the warning level set by the FFS system accordingly, saving time and cost and improving production efficiency.

[0067] It can be seen that in the above-mentioned application embodiments, the virtual measurement system is cleverly combined with the FFS, DMS, and YMS systems for process optimization and adjustment.

[0068] The step division of the above methods is only for the purpose of clear description. When implemented, they can be combined into one step or some steps can be split and decomposed into multiple steps. As long as they include the same logical relationship, they are all within the scope of protection of this patent; adding insignificant modifications to the algorithm or process or introducing insignificant designs without changing the core design of the algorithm and process are all within the scope of protection of this patent.

[0069] In addition, some embodiments of the present application also provide an electronic device. The electronic device may be a digital computer in various forms, such as a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, etc. The electronic device may also be a mobile device in various forms, such as a personal digital processing, a cellular phone, a smart phone, a wearable device, and other similar computing devices.

[0070] The electronic device includes: one or more processors; and a memory storing computer program instructions, wherein when the computer program instructions are executed, the processor executes the steps of the method provided in any one or more of the above embodiments. Figure 4 An exemplary structural diagram of the electronic device is disclosed. Figure 4 As shown, the electronic device includes: one or more processors 1101, memory 1102, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the electronic device, including instructions stored in or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some other embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple electronic devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Among them, the components shown in this article, their connections and relationships, and their functions are only used as examples, and are not intended to limit the implementation of the present application described and / or required herein.

[0071] The electronic device may further include: an input device 1103 and an output device 1104. The processor 1101, the memory 1102, the input device 1103 and the output device 1104 may be connected via a bus or other means. Figure 4 The example of connecting through bus is taken in the following.

[0072] The input device 1103 can receive input digital or character information, and generate key signal input related to the user settings and function control of the electronic device, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, an indicator bar, one or more mouse buttons, a trackball, a joystick and other input devices. The output device 1104 may include a display device, an auxiliary lighting device (e.g., an LED) and a tactile feedback device (e.g., a vibration motor), etc. The display device may include, but is not limited to, a liquid crystal display (LCD), a light emitting diode (LED) display and a plasma display. In some embodiments, the display device may be a touch screen.

[0073] To provide interaction with a user, the electronic device may be a computer. The computer has: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball), through which the user can provide input to the computer. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0074] In the embodiments of the present application, a computer program / instruction is stored on a computer-readable medium, and when the computer program / instruction is executed by a processor, the steps of the method provided by any one or more of the above embodiments are implemented. The computer-readable medium may be included in the electronic device described in the above embodiments; or it may exist independently without being assembled into the device. The above computer-readable medium carries one or more computer-readable instructions.

[0075] The memory 1102 can be used as a non-transient computer-readable storage medium, which can be used to store non-transient software programs, non-transient computer executable programs and modules. The processor 1101 executes various functional applications and data processing of the server by running the non-transient software programs, instructions and modules stored in the memory 1102, so as to implement the program instructions / modules corresponding to the method provided by any one or more embodiments in the embodiments of the present application.

[0076] The memory 1102 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 1102 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory 1102 may optionally include a memory remotely arranged relative to the processor 1101, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0077] It should be noted that the computer-readable medium described in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device.

[0078] Computer readable media include permanent and non-permanent, removable and non-removable media, and can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, modules of programs or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission medium that can be used to store information that can be accessed by a computing device.

[0079] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0080] In the above-described embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. For example, it can be implemented by using an application specific integrated circuit (ASIC), a general-purpose computer or any other similar hardware device. In certain embodiments, the software program of the present application can be executed by a processor to implement the above steps or functions. Similarly, the software program of the present application (including relevant data structures) can be stored in a computer-readable recording medium, for example, a RAM memory, a magnetic or optical drive or a floppy disk and similar devices. In addition, some steps or functions of the present application can be implemented by hardware, for example, as a circuit that cooperates with a processor to perform each step or function.

[0081] The computer program product provided in the embodiment of the present application includes one or more computer programs / instructions, and when the computer program / instructions are executed by the processor, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium, or transmitted from a computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or a data center that includes one or more available media integrations. The available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state disk (SSD)), etc.

[0082] The flow chart or block diagram in the accompanying drawings shows the possible architecture, function and operation of the equipment, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated system for hardware that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0083] The scope of the present application is defined by the appended claims rather than the above description, and it is intended that all changes that fall within the meaning and scope of the equivalent elements of the claims are included in the present application. Any figure mark in the claims should not be regarded as limiting the claims involved. In addition, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in the device claim may also be implemented by one unit or device through software or hardware. The words "first", "second", etc. are only used to distinguish the description, and do not indicate any particular order, nor can they be understood as indicating or implying relative importance.

[0084] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily mention changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims, and the above embodiments should be regarded as exemplary and non-restrictive.

Claims

1. A semiconductor-based abnormality processing method, characterized in that: The method is applied to a virtual measurement system, and the method comprises: Get the parameter information of the device; Determine whether the device is abnormal according to the parameter information; If the equipment is abnormal, maintain the abnormal equipment; If the device does not have any abnormality, the device measurement function is triggered, and the target information of the wafer yield is counted.

2. The method according to claim 1, characterized in that The obtaining of parameter information of the device includes: obtaining parameter information of the device through an FDC system.

3. The method according to claim 1, characterized in that If the device is abnormal, maintaining the abnormal device includes: if the device is abnormal, using the PMS system to maintain the abnormal device.

4. The method according to claim 1, characterized in that: If the device does not have any abnormality, the device measurement function is triggered, and the target information of the Lot yield rate statistics includes: If the device does not have any abnormality, the DMS system is used to trigger the device measurement function, and the YMS system is used to count the target information of the Lot yield, wherein the target information includes: arc breakdown yield and defect yield.

5. The method according to claim 1, characterized in that After determining whether the device is abnormal according to the parameter information, the method further includes: The production data of the equipment is analyzed by a data model; the data model is trained according to the type and characteristics of the production data to obtain: Based on the analysis results, locate the fault.

6. The method according to claim 5, characterized in that The fault location according to the analysis result includes: According to the analysis result, a first result for characterizing the abnormal fault of the machine and / or a second result for characterizing the production fault is generated.

7. An electronic device, characterized in that: The electronic device comprises: one or more processors; and A memory storing computer program instructions, which, when executed, cause the processor to perform the steps of the method as claimed in any one of claims 1 to 6.

8. A computer readable medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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