Production data analysis method, device and equipment based on combination of FDC system and SCADA system, and medium

Abstract

The invention provides a production data analysis method and device based on combination of an FDC system and an SCADA system, equipment and a medium. The method comprises the following steps: acquiring production equipment monitoring data through an FDC system, and extracting target monitoring data from the production equipment monitoring data; after the wafer production batch is completed, performing statistical calculation on the target monitoring data of the batch of production to obtain statistical result data; pushing the target monitoring data and the statistical result data to a data platform in which resource data collected by the SCADA system is stored under the condition that a pushing condition is met; and in the data platform, wafer production analysis is carried out based on the target monitoring data, the statistical result data and the resource data collected by the SCADA system as basic data. According to the technical scheme, the collected data of the FDC system and the collected data of the SCADA system can be combined, more comprehensive analysis and prediction are carried out on wafer generation based on the production monitoring data and the resource supply data, and the product quality and the production efficiency are improved.

Description

Technical Field

[0001] The present application relates to the technical field of data monitoring, and particularly relates to a production data analysis method, device, equipment and medium based on the combination of the FDC system and the SCADA system. Background Art

[0002] In recent years, with the rapid development of the technology level, the production and manufacturing of semiconductor chips have become the key factors for the development of various devices.

[0003] In the process of semiconductor chip production, the FDC (Fault Detection and Classification) system is usually used to monitor the real-time situation of the machine tools and external environment data, so as to monitor the stability of the machine tools and the production situation of the wafers (Wafers). By collecting and analyzing various parameter data, any potential faults or abnormal situations can be identified, so as to realize the real-time monitoring and analysis of the production process. At the same time, by monitoring the production situation of the wafers, engineers can also evaluate the quality and production efficiency of the wafers, and adjust the production process in time to improve the product quality and reduce the scrap rate. In the actual production process, the supply of various resources will also have a huge impact on the quality and production efficiency of the wafers. However, there is currently no good way to make good use of the resource supply data. Therefore, how to monitor and analyze based on more dimensional data to improve the product quality and production efficiency is a technical problem to be solved urgently. Summary of the Invention

[0004] An object of the present application is to provide a production data analysis method, device, equipment and medium based on the combination of the FDC system and the SCADA system, which is at least used to solve the problem that the data of the FDC system is single and does not consider the resource supply data. The purpose of the present application is to provide a new production data analysis method based on the combination of the FDC system and the SCADA system. This method obtains production equipment monitoring data through the FDC system, and extracts target monitoring data from the production equipment monitoring data; performs statistical calculations on the target monitoring data to obtain statistical result data; and pushes the target monitoring data and the statistical result data to the data platform where the resource data collected by the SCADA system is stored; in the data platform, based on the target monitoring data, the statistical result data and the resource data collected by the SCADA system as basic data, wafer production analysis is carried out. By adopting this solution, it is possible to combine the collected data of the FDC system with the collected data of the SCADA system, and based on the production monitoring data and the resource supply data, conduct a more comprehensive analysis and prediction of the wafer generation, so as to improve the product quality and production efficiency.

[0005] To achieve the above object, some embodiments of the present application provide the following aspects:

[0006] In a first aspect, some embodiments of the present application further provide a production data analysis method based on the combination of the FDC system and the SCADA system. The method includes:

[0007] Obtain production equipment monitoring data through the FDC system, and extract target monitoring data from the production equipment monitoring data;

[0008] After the completion of the wafer production batch, perform statistical calculations on the target monitoring data produced in this batch to obtain statistical result data;

[0009] Under the condition of meeting the push condition, push the target monitoring data and the statistical result data to the data platform where the resource data collected by the SCADA system is stored;

[0010] In the data platform, based on the target monitoring data, the statistical result data, and the resource data collected by the SCADA system as basic data, perform wafer production analysis.

[0011] In a second aspect, some embodiments of the present application further provide a production data analysis device based on the combination of the FDC system and the SCADA system. The device includes:

[0012] A target monitoring data extraction module, configured to obtain production equipment monitoring data through the FDC system, and extract target monitoring data from the production equipment monitoring data;

[0013] A statistical result data determination module, configured to perform statistical calculations on the target monitoring data produced in this batch after the completion of the wafer production batch to obtain statistical result data;

[0014] A push module, configured to push the target monitoring data and the statistical result data to the data platform where the resource data collected by the SCADA system is stored under the condition of meeting the push condition;

[0015] A joint analysis module, configured to perform wafer production analysis in the data platform based on the target monitoring data, the statistical result data, and the resource data collected by the SCADA system as basic data.

[0016] In a third aspect, some embodiments of the present application further provide a computer device, and the device includes:

[0017] One or more processors; and

[0018] A memory storing computer program instructions, which when executed cause the processor to execute the production data analysis method based on the combination of the FDC system and the SCADA system as described above.

[0019] In a fourth aspect, some embodiments of the present application further provide a computer-readable medium having computer program instructions stored thereon, which can be executed by a processor to implement the production data analysis method based on the combination of the FDC system and the SCADA system as described above.

[0020] Compared with the prior art, in the solution provided by the embodiments of the present application, production equipment monitoring data is obtained through the FDC system, and target monitoring data is extracted from the production equipment monitoring data; statistical calculations are performed on the target monitoring data to obtain statistical result data; and the target monitoring data and the statistical result data are pushed to the data platform storing the resource data collected by the SCADA system; in the data platform, wafer production analysis is performed based on the target monitoring data, the statistical result data, and the resource data collected by the SCADA system as basic data. By adopting this solution, it is possible to combine the collected data of the FDC system with the collected data of the SCADA system, and based on the production monitoring data and the resource supply data, perform a more comprehensive analysis and prediction on wafer generation, improving the product quality and production efficiency. Description of the Drawings

[0021] Figure 1 is a flowchart of the production data analysis method based on the combination of the FDC system and the SCADA system provided by Embodiment 1 of the present application;

[0022] Figure 2 is a schematic structural diagram of the production data analysis device based on the combination of the FDC system and the SCADA system provided by Embodiment 2 of the present application;

[0023] Figure 3 is a schematic structural diagram of the computer device provided by Embodiment 3 of the present application. Detailed Embodiments

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0025] The technical solutions provided by the embodiments of the present application will be described in detail below with reference to the accompanying drawings through specific embodiments and their application scenarios.

[0026] Example 1

[0027] Figure 1 It is a schematic flow chart of the production data analysis method based on the combination of the FDC system and the SCADA system provided by Example 1 of this application. As Figure 1 shown, it specifically includes the following steps:

[0028] Step S101, obtain production equipment monitoring data through the FDC system, and extract target monitoring data from the production equipment monitoring data;

[0029] Among them, the FDC (Fault Detection and Classification) system is usually used to collect and monitor real-time machine conditions and environmental data during the semiconductor production process to achieve the monitoring of machine stability and wafer production conditions. By collecting and analyzing various parameter data, the FDC system can help monitor the operating status and environmental conditions of the equipment, identify any potential faults or abnormal conditions, so as to achieve real-time monitoring and analysis of the production process. Through the data collection and analysis of the FDC system, engineers can timely understand the stability of the machine, ensure that the equipment runs in a reliable state, and timely detect and solve possible problems. In addition, by monitoring the production situation of wafers, engineers can evaluate the quality and production efficiency of wafers, and timely adjust the production process to improve product quality and reduce the scrap rate.

[0030] The production equipment can be a machine for producing wafers. The production equipment monitoring data can be various key data continuously collected during the wafer production process. For example, in terms of process parameters, it can include temperature, gas flow rate, and time parameters, etc. In terms of equipment operating status, it can include the status of mechanical moving parts, motor speed and torque, and equipment vibration conditions, etc. In terms of quality monitoring, it can include wafer thickness, surface flatness, and particle contamination conditions, etc.

[0031] In this technical solution, optionally, extracting target monitoring data from the production equipment monitoring data includes:

[0032] Extract at least one type of data of water, electricity, bulk gas, and special gas obtained by the FDC system based on the status value ID from the production equipment monitoring data.

[0033] Extracting target monitoring data from the production equipment monitoring data can be to extract some monitoring data therefrom, and the target monitoring data can be data associated with the plant SCADA system, such as data of water, electricity, bulk gas, and special gas, etc.

[0034] Among them, the FDC system collects data such as water, electricity, bulk gases, and special gases through the status variable ID (SVID).

[0035] With such a setting in this solution, the acquisition efficiency and extraction accuracy of the target monitoring data can be improved.

[0036] Step S102: After the wafer production batch is completed, perform statistical calculations on the target monitoring data produced in this batch to obtain statistical result data.

[0037] It can be known that when performing statistical calculations, a certain scale of data is often required. For example, it can be all the data collected after the completion of the wafer production of a certain batch.

[0038] In this embodiment, optionally, after the wafer production batch is completed, performing statistical calculations on the target monitoring data produced in this batch to obtain statistical result data includes:

[0039] After the wafer production batch is completed, perform cumulative calculations on the water data produced in this batch to obtain water data statistical result data.

[0040] And / or

[0041] After the wafer production batch is completed, perform cumulative calculations on the electricity data produced in this batch to obtain electricity data statistical result data.

[0042] And / or

[0043] After the wafer production batch is completed, perform cumulative calculations and rate calculations on bulk gases and / or special gases to obtain gas data statistical result data.

[0044] Statistical calculations on the target monitoring data can be that cumulative calculations can be performed on water or electricity. Cumulative and rate calculations can be performed on gases. The gases also include mixed gases. According to the mixing ratio, statistical calculations are performed on each gas separately. After all the data is statistically calculated, through unit conversion, it is converted into data that can be used for analysis and application with the supply volume in the factory SCADA to obtain statistical result data.

[0045] With such a setting in this solution, the relevant data in the equipment monitoring data related to water, electricity, bulk gases, and special gases can be statistically calculated and analyzed together with the supply volume in the SCADA, which can improve the accuracy of data analysis, better monitor the operating status of the machine tools, and at the same time make better predictions for the supply of each resource.

[0046] In this embodiment, optionally, after the completion of a wafer production batch, cumulative calculation and rate calculation are performed on bulk gases and / or special gases to obtain gas data statistical result data, including:

[0047] After the completion of a wafer production batch, for bulk gases, cumulative calculation and rate calculation are respectively performed on each gas according to the mixing ratio to obtain the statistical result data of each gas.

[0048] Among them, by performing cumulative calculation and rate calculation on each gas, the statistical data of each gas can be obtained, thereby providing more detailed data for subsequent quantitative analysis and equipment operation analysis, which is beneficial to the attribution analysis of faults and the accurate control of supply volume.

[0049] In this embodiment, optionally, after performing statistical calculation on the target monitoring data produced in this batch to obtain statistical result data, the method further includes:

[0050] Performing unit conversion on the statistical result data to convert it into a unit format corresponding to the resource data collected by the SCADA system.

[0051] Among them, the unit conversion can be to convert the current format of the statistical result data into the format of the resource data collected by the SCADA system. For example, the unit of water consumption can be converted from milliliters (mL) in the statistical result to liters (L) in the resource data.

[0052] With such a setting in this solution, subsequent joint analysis can be facilitated, and errors in joint analysis caused by inconsistent data units and data formats can be avoided.

[0053] Step S103, when the push condition is met, push the target monitoring data and the statistical result data to the data platform where the resource data collected by the SCADA system is stored;

[0054] In this embodiment, optionally, the push conditions include: completion of a single wafer production, completion of a batch of wafer production, and reaching a preset time interval.

[0055] Among them, the push condition can be when a single wafer production is completed or a whole batch of wafer production is completed, or when a certain time interval is reached, it is considered that the push condition is met.

[0056] With such a setting in this embodiment, the timeliness of information push can be ensured, facilitating subsequent calculations, and certain push conditions are set to avoid the computing power consumption caused by continuous data transmission.

[0057] This solution can push the original data and statistical calculation data to the data platform used by the SCADA system to store the collected data through the database.

[0058] Among them, the SCADA (Supervisory Control and Data Acquisition) system is usually used to monitor and control the supply of various resources in the factory, including the supply of gas, water, electricity, etc. to the machines. Through the SCADA system, factory operators can monitor the consumption of various resources in real time to ensure that the machines can obtain sufficient resources such as gas, water, and electricity to support production operations. The SCADA system can display the supply of resources such as gas, water, and electricity in real time, and can also record historical data and analyze the usage trends of resources, which is convenient for formulating resource management strategies and optimizing the production process. By monitoring the resource supply, the factory can ensure the normal operation of equipment and avoid production interruptions or quality problems caused by resource shortages.

[0059] The resource data collected by the SCADA system can be data on resources such as gas, water, and electricity, such as supply volume and historical usage volume.

[0060] Step S104, in the data platform, based on the target monitoring data, the statistical result data, and the resource data collected by the SCADA system as basic data, perform wafer production analysis.

[0061] The data from the FDC system and the SCADA system can be integrated to establish a unified data storage and management platform for subsequent analysis. The integration of the two types of data can perform predictive analysis on the future usage and supply of water, electricity, and gas.

[0062] In this solution, by integrating the data of the FDC system and the SCADA system, the factory facility system can more comprehensively understand the situation of the wafer production process, achieve more in-depth data analysis and optimization, improve production efficiency and product quality. At the same time, it also lays a foundation for future data mining and intelligent production management.

[0063] In the solution provided by the embodiment of this application, production equipment monitoring data is obtained through the FDC system, and target monitoring data is extracted from the production equipment monitoring data; statistical calculations are performed on the target monitoring data to obtain statistical result data; and the target monitoring data and the statistical result data are pushed to the data platform where the resource data collected by the SCADA system is stored; in the data platform, based on the target monitoring data, the statistical result data, and the resource data collected by the SCADA system as basic data, perform wafer production analysis. By adopting this solution, it is possible to combine the collected data of the FDC system and the SCADA system, and based on the production monitoring data and resource supply data, perform a more comprehensive analysis and prediction on wafer generation, improving product quality and production efficiency.

[0064] Based on the above embodiments, optionally, in the data platform, wafer production analysis is performed based on the target monitoring data, the statistical result data, and the resource data collected by the SCADA system as basic data, including:

[0065] In the data platform, the target monitoring data, the statistical result data, and the resource data collected by the SCADA system are integrated to obtain a basic data table;

[0066] According to the basic data table, resource usage analysis and resource supply prediction analysis are performed during the wafer production process.

[0067] Among them, in the basic data table, the rows and columns can be divided according to the data source, data type, etc., and the corresponding numerical values are filled into the basic table. After obtaining the basic data table, resource usage analysis and resource supply prediction analysis can be performed during the wafer production process. For example, supply situation prediction, fault prediction, and future data mining are carried out.

[0068] With such a setting in this embodiment, all data contents can be reflected in a basic data table, which is convenient for subsequent analysis and calculation and improves the efficiency of data analysis.

[0069] This embodiment comprehensively analyzes the data of the two systems, can better understand the reasons for abnormal equipment data during the production process, and has a good analysis and comparison of the consumption of various resource supplies, and can make a good prediction of the future plant service supply based on the consumption.

[0070] Embodiment 2

[0071] Figure 2 It is a schematic structural diagram of a production data analysis device based on the combination of the FDC system and the SCADA system provided by the second embodiment of the present application. As Figure 2 shown, it specifically includes the following:

[0072] A target monitoring data extraction module 210, configured to obtain production equipment monitoring data through the FDC system and extract target monitoring data from the production equipment monitoring data;

[0073] A statistical result data determination module 220, configured to perform statistical calculations on the target monitoring data produced in this batch after the wafer production batch is completed to obtain statistical result data;

[0074] A push module 230, configured to push the target monitoring data and the statistical result data to the data platform where the resource data collected by the SCADA system is stored when the push condition is met;

[0075] The conjoint analysis module 240 is configured to perform wafer production analysis in the data platform based on the target monitoring data, the statistical result data, and the resource data collected by the SCADA system as basic data.

[0076] The production data analysis device based on the combination of the FDC system and the SCADA system in the embodiments of the present application may be a device, or a component, an integrated circuit, or a chip in a terminal. The device may be a mobile electronic device or a non-mobile electronic device. Exemplarily, the mobile electronic device may be a mobile phone, a tablet computer, a laptop computer, a palmtop computer, an in-vehicle electronic device, a wearable device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (PDA), etc., and the non-mobile electronic device may be a server, a Network Attached Storage (NAS), a personal computer (PC), a television (TV), a teller machine, or a self-service machine, etc. The embodiments of the present application do not make specific limitations.

[0077] The production data analysis device based on the combination of the FDC system and the SCADA system in the embodiments of the present application may be a device with an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems. The embodiments of the present application do not make specific limitations.

[0078] The production data analysis device based on the combination of the FDC system and the SCADA system provided in the embodiments of the present application can implement each process implemented in the above method embodiments. To avoid repetition, it will not be elaborated here.

[0079] Embodiment III

[0080] In addition, the embodiments of the present application further provide a computer device. Figure 3 It is a schematic structural diagram of the computer device provided in Embodiment III of the present application. The structure of the device is as Figure 3 shown. The device includes a memory 31 for storing computer-readable instructions and a processor 32 for executing the computer-readable instructions. When the computer-readable instructions are executed by the processor, the processor is triggered to execute the above method.

[0081] The methods and / or embodiments in the embodiments of this application can be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the methods shown in the flowcharts. When the computer program is executed by a processing unit, the above functions defined in the methods of this application are executed.

[0082] It should be noted that the computer-readable medium described in this application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. The computer-readable medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium can 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 this application, the computer-readable medium can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device.

[0083] In this application, the computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries the computer-readable program code. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, and this computer-readable medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted by any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0084] Computer program code for performing the operations of this application can be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, by connecting through the Internet using an Internet service provider).

[0085] The flowcharts or block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of devices, methods, and computer program products according to various embodiments of this application. In this regard, each block in the flowchart or block diagram can represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks can occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown can actually be executed substantially in parallel, and they can sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0086] As another aspect, embodiments of this application also provide a computer-readable medium, which can be included in the devices described in the above embodiments; or it can exist separately and not be assembled into the device. The above computer-readable medium carries one or more computer-readable instructions, and the computer-readable instructions can be executed by a processor to implement the steps of the methods and / or technical solutions of the foregoing embodiments of this application.

[0087] In a typical configuration of this application, the terminal and the devices of the service network both include one or more processors (CPUs), an input / output interface, a network interface, and a memory.

[0088] The memory may include non-permanent memory in the form of computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. The memory is an example of computer-readable media.

[0089] Computer-readable media includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. The information can be computer-readable instructions, data structures, program modules, 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 technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information accessible by a computing device.

[0090] In addition, the embodiments of the present application also provide a computer program, which is stored in a computer device, enabling the computer device to execute the method executed by the control code.

[0091] It should be noted that the present application can be implemented in software and / or a combination of software and hardware. For example, it can be implemented using an application-specific integrated circuit (ASIC), a general-purpose computer, or any other similar hardware device. In some 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 related data structures) can be stored in a computer-readable recording medium, such as RAM memory, magnetic or optical drives, or floppy disks and similar devices. Additionally, some steps or functions of the present application can be implemented using hardware, for example, as a circuit that cooperates with a processor to execute each step or function.

[0092] For those skilled in the art, it is obvious that the present application is not limited to the details of the above-described exemplary embodiments, and the present application can be implemented in other specific forms without departing from the spirit or basic characteristics of the present application. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present application is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be encompassed within the present application. Any reference signs in the claims should not be construed as limiting the claims involved. In addition, it is obvious that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. The multiple units or devices stated in the apparatus claims can also be implemented by one unit or device through software or hardware. First, second, etc. are used to denote names and do not denote any particular order.

Claims

1. A production data analysis method based on the combination of FDC system and SCADA system, characterized in that: include: Acquire production equipment monitoring data through the FDC system, and extract target monitoring data from the production equipment monitoring data; After the wafer production batch is completed, statistical calculation is performed on the target monitoring data produced in this batch to obtain statistical result data; When the push conditions are met, the target monitoring data and the statistical result data are pushed to the data platform where the resource data collected by the SCADA system is stored; In the data platform, wafer production analysis is performed based on the target monitoring data, the statistical result data and the resource data collected by the SCADA system as basic data.

2. The method according to claim 1, characterized in that Extracting target monitoring data from the production equipment monitoring data includes: At least one of water, electricity, bulk gas and special gas data acquired by the FDC system based on the state value ID is extracted from the production equipment monitoring data.

3. The method according to claim 1, characterized in that After the wafer production batch is completed, the target monitoring data of the production batch is statistically calculated to obtain statistical result data, including: After the wafer production batch is completed, the water data of this batch is accumulated and calculated to obtain the water data statistical result data; and / or, After the wafer production batch is completed, the electrical data of this batch is accumulated and calculated to obtain the electrical data statistical result data; and / or, After the wafer production batch is completed, cumulative calculations and rate calculations are performed for bulk gases and / or special gases to obtain gas data statistical results.

4. The method according to claim 3, characterized in that After the wafer production batch is completed, cumulative calculations and rate calculations are performed for bulk gases and / or special gases to obtain gas data statistical results, including: After the wafer production batch is completed, the cumulative calculation and rate calculation are performed on each gas according to the mixing ratio of the bulk gas to obtain the statistical results of each gas data.

5. The method according to claim 1, characterized in that After performing statistical calculation on the target monitoring data of the current batch of production to obtain statistical result data, the method further includes: The statistical result data is converted into a unit format corresponding to the resource data collected by the SCADA system.

6. The method according to claim 1, characterized in that The push conditions include: completion of single wafer production, completion of batch wafer production, and reaching a preset time interval.

7. The method according to claim 1, characterized in that In the data platform, wafer production analysis is performed based on the target monitoring data, the statistical result data, and the resource data collected by the SCADA system as basic data, including: In the data platform, the target monitoring data, the statistical result data and the resource data collected by the SCADA system are integrated to obtain a basic data table; Based on the basic data table, resource usage analysis and resource supply forecast analysis are performed during the wafer production process.

8. A production data analysis device based on the combination of FDC system and SCADA system, characterized in that: include: A target monitoring data extraction module is used to obtain production equipment monitoring data through the FDC system and extract target monitoring data from the production equipment monitoring data; A statistical result data determination module is used to perform statistical calculations on the target monitoring data produced in this batch after the wafer production batch is completed to obtain statistical result data; A push module, used for pushing the target monitoring data and the statistical result data to the data platform where the resource data collected by the SCADA system is stored when the push conditions are met; The joint analysis module is used to perform wafer production analysis in the data platform based on the target monitoring data, the statistical result data and the resource data collected by the SCADA system as basic data.

9. A computer device, characterized in that: The device comprises: one or more processors; and A memory storing computer program instructions, wherein when the computer program instructions are executed, the processor executes the production data analysis method based on the combination of the FDC system and the SCADA system as claimed in any one of claims 1 to 7.

10. A computer-readable medium, characterized in that Computer program instructions are stored thereon, and the computer program instructions can be executed by a processor to implement the production data analysis method based on the combination of the FDC system and the SCADA system as described in any one of claims 1 to 7.

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