Intelligent factory affair management system and method, storage medium and equipment

Abstract

The invention provides an intelligent factory affair management system and method, a storage device and a medium, and the system comprises a data collection subsystem, a data management subsystem and a factory affair management subsystem, the data collection subsystem is used for collecting operation data of factory affair equipment; the data management subsystem is used for receiving the operation data sent by the data acquisition subsystem and storing and displaying the operation data; the factory affair management subsystem is used for receiving the operation data forwarded by the data management subsystem, obtaining the operation state of the factory affair equipment according to the operation data, and sending the operation state of the factory affair equipment to the data management subsystem for display. According to the invention, modeling is carried out on each piece of factory equipment in the micro-nano laboratory, and unified processing and analysis are carried out on the data of the operation state of the factory equipment, so that operation and maintenance personnel can intuitively and directly obtain the operation state and specific operation data of the factory equipment from a display interface, an integrated intelligent platform is formed, and intelligent management of the factory equipment is realized.

Description

Technical Field

[0001] The present invention relates to the field of factory management, and in particular to an intelligent factory management system, method, storage medium and equipment. Background Art

[0002] The factory management system of a semiconductor laboratory is a key component to ensure that the laboratory can operate efficiently and safely. It is an automated solution for managing and controlling various facility systems in a semiconductor laboratory. It involves the management of various infrastructure and services in the laboratory, including but not limited to power supply, water treatment, gas supply, exhaust gas emission, temperature and humidity control, clean room environment maintenance, etc.; and integrates various basic equipment and services to achieve comprehensive monitoring and management of the entire semiconductor laboratory. The stability and reliability of these systems directly affect the normal operation of the equipment in the laboratory.

[0003] However, the existing factory system architecture is limited and cannot integrate other subsystems. It is also impossible to centrally and uniformly manage and analyze the data between subsystems. The subsystems cannot be used across platforms and are not very flexible. In addition, the data of each subsystem in the existing factory system is mostly presented in the form of reports. The large amount of report data makes it more difficult for engineers to manage or analyze the factory environment. It takes a lot of time and energy to analyze the causes of equipment failures in the factory system, and the requirements for engineers are high. It is difficult to accumulate and pass on factory equipment management experience or failure analysis experience. Summary of the invention

[0004] Based on this, the present invention provides an intelligent factory management system, method, storage medium and equipment. By modeling each factory equipment in the micro-nano laboratory and uniformly processing and analyzing the data on the operating status of the factory equipment, operation and maintenance personnel can directly obtain the operating status and specific operating data of the factory equipment from the display interface, thereby forming an integrated intelligent platform to realize intelligent management of the factory equipment.

[0005] In a first aspect, the present invention provides an intelligent factory management system, including a data acquisition subsystem, a data management subsystem and a factory management subsystem, wherein:

[0006] The data acquisition subsystem is used to collect the operation data of factory equipment;

[0007] The data management subsystem is used to receive the operation data sent by the data acquisition subsystem, and store and display the operation data;

[0008] The plant affairs management subsystem is used to receive the operation data forwarded by the data management subsystem, obtain the operation status of the plant affairs equipment according to the operation data, and send the operation status of the plant affairs equipment to the data management subsystem for display.

[0009] Furthermore, the intelligent factory affairs management system also includes an inspection subsystem, which is used to receive and execute factory affairs equipment inspection instructions sent by the factory affairs management subsystem, and send the inspection results to the data management subsystem.

[0010] Furthermore, the data management subsystem is configured as a mode combining edge computing devices and data center devices.

[0011] In a second aspect, the present invention further provides an intelligent factory affairs management method, which is applied to the intelligent factory affairs management system of the first aspect, and comprises the following steps:

[0012] Obtain real-time data of each plant equipment;

[0013] Extracting the real-time data according to the data type of each plant equipment to obtain standard real-time data of each plant equipment;

[0014] Determine whether each plant equipment is in a normal operating state according to the plant equipment standard real-time data and the plant equipment historical information set;

[0015] If the plant equipment is in normal operation, the operation status and real-time data of the plant equipment are marked and displayed in the plant equipment model;

[0016] If the plant equipment is in an abnormal operating state, the operating state, real-time data and real-time fault cause of the plant equipment are marked and displayed in the plant equipment model.

[0017] Furthermore, the real-time data is extracted according to the data type of each factory equipment to obtain the standard real-time data of each factory equipment, specifically:

[0018] Obtain data model tags from real-time data of each plant equipment;

[0019] According to the data model tag, necessary information is extracted from the real-time data of each plant equipment in a preset manner, and the necessary information of each plant equipment is recorded as standard real-time data of each plant equipment in a unified format of the digital management subsystem.

[0020] Furthermore, judging whether each plant equipment is in a normal operating state according to the plant equipment standard real-time data and the plant equipment historical information set includes:

[0021] Construct a historical curve of the parameters of the plant equipment according to the historical information set of the plant equipment;

[0022] On the historical curve, an upper limit of a parameter of the device operation is set according to a first ratio, and a lower limit of a parameter of the device operation is set according to a second ratio, and the upper limit and the lower limit of the parameter are marked in the same coordinate system as the historical curve;

[0023] If the standard real-time data of the plant equipment exceeds the upper or lower parameter limit, the real-time operation status of the plant equipment is marked as abnormal operation; otherwise, the real-time operation status of the plant equipment is marked as normal operation.

[0024] Furthermore, the intelligent factory affairs management method also includes: obtaining Boolean variable parameters of factory affairs equipment to determine whether the factory affairs equipment is in a normal operating state.

[0025] Furthermore, the intelligent factory management method also includes:

[0026] Based on the historical information collection and standard real-time data of the plant equipment, it is determined whether the operating status of the plant equipment has a trend of potential abnormal operating status.

[0027] Furthermore, the intelligent factory management method also includes:

[0028] If the plant equipment is in an abnormal operating state, a maintenance work order is generated according to the standard real-time data of the plant equipment.

[0029] Furthermore, the intelligent factory management method also includes:

[0030] Obtain equipment information of each factory equipment;

[0031] A model of the plant equipment is constructed according to the equipment information of each plant equipment, and a first mapping relationship is constructed between the model and the equipment information.

[0032] In a third aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any one of the intelligent factory management methods in the second aspect.

[0033] In a fourth aspect, the present invention further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it executes any one of the intelligent factory management methods in the second aspect.

[0034] The beneficial effects of adopting the above technical solution are as follows: the intelligent factory management system and method provided by this embodiment has high integration, high scalability and data trend visualization, and integrates other systems through an integrated intelligent platform, an integrated data management architecture; through the visualization management of factory equipment models, real-time dynamic information and remote control are displayed, and management is more intuitive and convenient. Furthermore, the accumulation of data assets in the data center is conducive to further analysis of the operating status and operating trends of factory equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.

[0036] Figure 1 This is a schematic diagram of an intelligent factory management system in one embodiment of the present application;

[0037] Figure 2 This is a schematic diagram of an intelligent factory management method in one embodiment of the present application;

[0038] Figure 3 This is a schematic diagram showing the global display of the factory equipment model of the intelligent factory management system in one embodiment of the present application;

[0039] Figure 4 This is a partial schematic diagram showing a factory equipment model of an intelligent factory management system in one embodiment of the present application;

[0040] Figure 5 This is a schematic diagram of data source filtering of an intelligent factory management method in one embodiment of the present application;

[0041] Figure 6 This is a schematic diagram of data aggregation of an intelligent factory management method in one embodiment of the present application;

[0042] Figure 7 This is a schematic diagram of data deduplication of an intelligent factory management method in one embodiment of the present application;

[0043] Figure 8 This is a flat schematic diagram of data of an intelligent factory management method in one embodiment of the present application;

[0044] Fig. 9 A schematic diagram for creating a factory equipment ledger for an intelligent factory management method in an embodiment of the present application;

[0045] Fig.10 This is a schematic diagram of factory equipment information of an intelligent factory management method in one embodiment of the present application;

[0046] Fig.11 This is a schematic diagram of an overview of factory equipment monitoring of an intelligent factory management method in one embodiment of the present application;

[0047] Fig.12 This is a schematic diagram of factory equipment status monitoring of an intelligent factory management method in one embodiment of the present application;

[0048] Fig.13 A schematic diagram of a historical curve of factory equipment in an intelligent factory management method in one embodiment of the present application;

[0049] Fig.14 This is a schematic diagram of factory equipment trend analysis of an intelligent factory management method in one embodiment of the present application;

[0050] Fig.15 This is a schematic diagram of factory equipment report analysis of an intelligent factory management method in one embodiment of the present application;

[0051] Fig.16 This is a schematic diagram of factory equipment failure analysis of an intelligent factory management method in one embodiment of the present application;

[0052] Fig.17 This is a schematic diagram of a maintenance work order for the intelligent factory management method in one embodiment of the present application. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. In order to explain the present invention in more detail, the intelligent factory management system, method, storage medium and device provided by the present invention are specifically described below in combination with the drawings.

[0054] Unless otherwise defined, the technical terms or scientific terms used in the disclosure of this application should be understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. Similarly, similar words such as "one", "one" or "the" do not indicate a quantitative limit, but indicate that there is at least one. Similar words such as "include" or "include" mean that the elements or objects appearing in front of the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Similar words such as "connect" or "connected" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship can also change accordingly.

[0055] The Facility Management Control System of a semiconductor laboratory is a key component to ensure that the laboratory can operate efficiently and safely. It is an automated solution for managing and controlling various facility systems in a semiconductor laboratory. It involves the management of various infrastructure and services in the laboratory, including but not limited to power supply, water treatment, gas supply, exhaust gas emission, temperature and humidity control, clean room environment maintenance, etc.; and the careful integration of various basic equipment and services to achieve comprehensive monitoring and management of the entire semiconductor laboratory. The stability and reliability of these systems directly affect the normal operation of the equipment in the laboratory.

[0056] The main functions of the factory management system include real-time monitoring, automatic control, alarm and notification, data analysis and reporting, and safety management. Among them, real-time monitoring refers to the collection of information on key parameters such as power usage, gas flow, temperature, humidity, etc. through sensors and data acquisition devices, and real-time display on the central monitoring screen, so that managers can understand the status of the facilities at any time; automatic control refers to the automatic adjustment of the working mode of the equipment according to the preset standards or algorithms, such as adjusting the temperature setting value of the air-conditioning system to maintain a stable production environment; alarm and notification means that when an abnormal situation is detected, such as equipment failure or operating parameters beyond the safe range, the system will immediately trigger an alarm and send a notification to relevant personnel so that timely action can be taken; data analysis and reporting means that the collected historical data can be used for trend analysis, performance evaluation and fault prediction, helping to optimize maintenance plans and improve energy efficiency; safety management refers to the implementation of strict user authority management to ensure that only authorized personnel can access sensitive information or perform specific operations, thereby enhancing the security of the system.

[0057] The traditional plant management control system adopts the PLC distributed control system structure to manage and monitor the power facilities, environment, and energy of each building. As the core operation monitoring system of the semiconductor, the plant management control system realizes the monitoring and collection of process parameters of the entire system. On this basis, an integrated intelligent platform is built, and the data center realizes the combination of artificial intelligence and the Internet of Things, which is an effective way of digital transformation. In the traditional plant system, the software and hardware are tightly coupled, and the software only runs on specific types of PLCs and I / Os. Data development and utilization require a complete review of the code transfer and the redesign of the application.

[0058] In this regard, the present invention provides an intelligent factory management method, which collects data from multiple equipment subsystems of the factory system and transmits them to the factory system for management, manages the factory equipment data in a unified manner, and visually monitors and manages the operation of the equipment in combination with the factory equipment data, thereby improving the efficiency of micro-nano laboratory factory management and data readability. Figure 2 A schematic diagram of the intelligent factory management method is shown.

[0059] The embodiment of the present application provides an application scenario of the intelligent factory affairs management method, which includes the terminal device provided in the embodiment, and the terminal device includes but is not limited to a smart phone and a computer device, wherein the computer device can be at least one of a desktop computer, a portable computer, a laptop computer, a mainframe computer, a tablet computer, etc. The terminal device receives the device information collected by the factory affairs equipment subsystem and obtains the comprehensive operation status of the micro-nano laboratory factory affairs equipment. For the specific process, please refer to the embodiment of the intelligent factory affairs management method.

[0060] The intelligent factory management method of this embodiment is applied to an intelligent factory management system, as shown in the attached Figure 1 As shown, the intelligent factory management system includes a data acquisition subsystem, a data management subsystem, a factory management subsystem and an inspection subsystem.

[0061] Among them, the data acquisition subsystem includes data acquisition devices installed at various factory equipment. The data acquisition devices can be divided into multiple types of data acquisition devices according to the type of factory equipment, including but not limited to electrical data acquisition devices, temperature data acquisition devices, humidity data acquisition devices, gas data acquisition devices, pure water data acquisition devices, chemical data acquisition devices and wastewater data acquisition devices. Moreover, since the data formats obtained by each type of data acquisition device are different, each type of data acquisition device corresponds to a specific data processing subsystem.

[0062] The data management subsystem includes a data storage center and a data display unit. The data storage center is used to store the factory equipment information transmitted from the data acquisition subsystem to the data management subsystem. The data display unit is used to construct a 2D / 3D model of the micro-nano laboratory factory equipment and display specific factory equipment information on the 2D / 3D model of the factory equipment.

[0063] The plant management subsystem is used to analyze and manage the plant equipment information forwarded by the data management subsystem, determine whether the plant equipment is in normal operation, whether the plant equipment needs to be repaired, or analyze the plant equipment failure.

[0064] The inspection subsystem is used to receive the factory equipment inspection instructions sent by the factory management subsystem and return the inspection results. The inspection subsystem may include at least one inspection robot or equipment worn by engineers during inspections. For example, the inspection subsystem regularly inspects factory equipment, and when the data management subsystem determines that the factory equipment is abnormal or receives an alarm, the inspection subsystem may be called to record or photograph the factory equipment, and transmit the on-site data to the operation and maintenance personnel to shorten the processing time of emergencies.

[0065] Based on the above intelligent factory affairs management system, the intelligent factory affairs management method of this embodiment includes the following steps:

[0066] Step S101, obtaining real-time data of each factory equipment.

[0067] Specifically, the factory equipment of this embodiment is set in the micro-nano laboratory to maintain the normal operation of the equipment in the micro-nano laboratory. According to the type of the factory equipment, the factory equipment of this embodiment includes but is not limited to power auxiliary equipment, temperature auxiliary equipment, humidity auxiliary equipment, pure water auxiliary equipment, fresh air system equipment, gas supply equipment, waste gas treatment equipment, process cooling water supply equipment, wastewater treatment equipment and chemical supply equipment. According to the different types of factory equipment, different data acquisition equipment is selected to obtain the real-time data of each factory equipment. For example, the real-time electric energy data of the electric energy auxiliary equipment is collected by using an ammeter, an electric energy meter, etc., the gas flow rate data of the gas supply equipment is collected by using a flow meter, and the chemical storage amount of the chemical supply equipment is collected by using a weight sensor or a liquid level sensor. It should be noted that the above-mentioned different data acquisition devices correspond to different data formats, and even the same type of factory equipment may have different data formats due to the inconsistency of the selected data acquisition device models.

[0068] Step S102 , extracting the real-time data according to the data type of each factory equipment to obtain standard real-time data of each factory equipment.

[0069] Specifically, considering that the real-time data of each plant equipment acquired by the data acquisition subsystem are incompatible with each other in different formats and cannot exchange data, in order to efficiently and quickly manage all the plant equipment of the micro-nano laboratory, when the real-time data of each plant equipment is sent to the data management subsystem, the first thing to be solved is to unify the real-time data collected by all plant equipment obtained by the data management subsystem. It should be noted that in order to reduce the impact of data transmission on the data format received by the data management subsystem, this embodiment can adopt multiple types of protocols such as OPCUA protocol (OLE for ProfessControl Unified Architecture), MODBUS (Modicon Bus) protocol, MQTT (Message QueuingTelemetry Transport) protocol or combine with API interface to realize batch transmission of data.

[0070] Furthermore, in order to improve the processing efficiency of the data management subsystem for factory equipment data from different data sources, for real-time data from different data sources, necessary information is extracted from the real-time data of each factory equipment to meet the unified format requirements of the data management subsystem. The specific steps are as follows:

[0071] Step S201, obtaining data model tags in real-time data of each factory equipment.

[0072] Specifically, a data model tag is provided in the real-time data of each factory equipment, and the data model tag is used to indicate the source of the data and the associated equipment. The data management subsystem can identify and classify the real-time data according to the data model tag and determine the specific format of the real-time data.

[0073] Step S202, extracting necessary information from the real-time data of each plant equipment in a preset manner according to the data model tag, and recording the necessary information of each plant equipment as standard real-time data of each plant equipment in a unified format of the digital management subsystem.

[0074] It should be noted that the necessary information extracted from the real-time data of each plant equipment in a preset manner according to the data model tag can be parsed or extracted by a parser or converter according to the specific format indicated by the data model tag. For example, when the data management subsystem determines that the real-time data of the plant equipment A is in JSON format according to the data model tag, the necessary information is extracted according to the format of the JSON format; when the real-time data of the plant equipment B is determined to be in CSV format according to the data model tag, the necessary information is extracted according to the rules of the CSV format.

[0075] The necessary information of the plant equipment is mapped to fields according to the mapping rules and unified format preset by the digital management subsystem to obtain standard real-time data. The format of standard real-time data can be set as "plant equipment ID, plant equipment coordinates, data collection time, real-time data 1, real-time data 2". For example, the standard real-time data of power auxiliary equipment A is recorded as "power auxiliary equipment A, ( )、 , current parameters, power parameters", the format of standard real-time data can be set according to the collection requirements of each factory equipment.

[0076] The standard real-time data of each plant equipment can be collected into a plant equipment real-time data set for recording. Each plant equipment information set corresponds to the standard real-time data of all plant equipment in the micro-nano laboratory at a specific time. The factory equipment information collection at the moment is recorded as ,in For the Factory equipment in Standard real-time data at all times. The processed plant equipment information is stored in the data storage center of the data management subsystem and indexed for subsequent rapid retrieval or analysis.

[0077] Step S103 , judging whether each plant equipment is in a normal operating state according to the plant equipment standard real-time data and the plant equipment historical information set.

[0078] Specifically, the data management subsystem sends the standard real-time data of the factory equipment to the factory management subsystem to judge the operating status of the factory equipment. In this process, in order to reduce the burden of data transmission and reduce the impact of the network environment, this embodiment uses the OPCUA protocol, MQTT protocol or API interface to call the real-time information collection and historical information collection of the factory equipment in the data management subsystem. For example, the factory management subsystem obtains the real-time information and historical information of the factory equipment A from the data storage center of the data management subsystem through the MQTT protocol, queries the corresponding data through the data model tag corresponding to the factory equipment A, and transmits the data through the MQTT protocol.

[0079] There are many ways to determine whether each plant equipment is in normal operation based on the historical information set and real-time data of the plant equipment, including but not limited to: (1) constructing a historical curve of the parameters of the plant equipment based on the historical information set of the plant equipment, as shown in the attached figure. Fig.13 As shown, the upper limit of the parameter of the equipment operation is set on the historical curve according to the first ratio, the lower limit of the parameter of the equipment operation is set according to the second ratio, and the upper limit and lower limit of the parameter are marked in the same coordinate system as the historical curve. If the standard real-time data of the plant equipment exceeds the upper limit or the lower limit of the parameter, the real-time operation status of the plant equipment is marked as abnormal operation; otherwise, the real-time operation status of the plant equipment is marked as normal operation. (2) According to the historical information set of the plant equipment, the first threshold and the second threshold of the normal operation of the plant equipment are set. If the real-time data of the plant equipment exceeds the range defined by the first threshold and the second threshold, the real-time operation status of the plant equipment is marked as abnormal operation; otherwise, the real-time operation status of the plant equipment is marked as normal operation. In addition, it should be noted that the parameters of some plant equipment are represented in the form of Boolean logical variables, and the operation status of the plant equipment is judged as abnormal or normal by "0" or "1", and there is no need to compare with the historical information set.

[0080] Further, as attached Fig.14As shown, a trend analysis can also be performed on the operating status of the plant equipment based on the historical information set and the standard real-time data of the plant equipment. Specifically, the historical information of the standard real-time data of the plant equipment at the previous p moments is combined with the standard real-time data to obtain the real-time operating curve of the plant equipment, the real-time operating curve is compared with the historical operating curve of any time period in the historical information set to obtain the historical operating curve with the highest similarity, and a trend analysis is performed on the operating status of the plant equipment based on the historical operating curve at the next moment of the historical operating curve; if the operating status of the plant equipment of the historical operating curve at the next moment is an abnormal state, then the operating status of the plant equipment has a trend of potential abnormal operating state.

[0081] Further, as attached Fig.16 As shown, fault analysis can also be performed on the plant equipment based on the historical information set and standard real-time data of the plant equipment. Specifically, the historical information of the standard real-time data of the plant equipment at the previous s moments is combined with the standard real-time information to obtain the real-time operation curve of the plant equipment, and the real-time operation curve is compared with the historical operation curve of any time period in the historical information set to obtain the historical operation curve with the highest similarity, and the fault cause corresponding to the historical operation curve is marked as the real-time fault cause that may exist in the plant equipment.

[0082] Step S104: if the factory equipment is in a normal operating state, the operating state and real-time data of the factory equipment are marked and displayed in the factory equipment model.

[0083] Step S105: If the plant equipment is in an abnormal operating state, the operating state, real-time data and real-time fault cause of the plant equipment are marked and displayed in the plant equipment model.

[0084] It should be noted that after the plant management subsystem analyzes the operating status of the plant equipment, it marks the real-time data of the plant equipment and returns the marked real-time data to the data management subsystem. The data management subsystem displays the marked real-time data in the plant equipment model, as shown in the attached figure. Figure 3-4 The information shown includes but is not limited to the operation status, real-time data and real-time fault causes of the plant equipment. The operation status of the plant equipment includes normal operation, abnormal operation and abnormal trend.

[0085] Further, as attached Fig.17As shown, when the plant management subsystem determines that the plant equipment is in an abnormal operating state, a maintenance work order is generated and sent to the plant management mobile terminal to remind the operation and maintenance engineers of the plant equipment to promptly repair or troubleshoot the abnormal plant equipment. The maintenance work order includes but is not limited to the name, location, real-time operating status, abnormal operation duration, real-time fault cause, alarm record, maintenance record, historical curve, etc. of the plant equipment.

[0086] Further, based on the embodiment of the above-mentioned intelligent factory management method, the data management subsystem can also be set to a mode combining edge computing devices and data center devices, wherein the edge computing devices are respectively arranged at the data acquisition devices of each factory equipment, directly communicated with the data acquisition devices, and preprocessed and analyzed the real-time data acquired by the data acquisition devices; the edge computing devices are communicated with the data center devices, and send the preprocessed real-time data to the data center at a preset time interval. Among them, the edge computing device can perform real-time data processing and analysis, quickly respond to local events and anomalies, and support real-time decision-making and control; and by processing data at the edge and sending only necessary information to the data center, edge computing can effectively reduce bandwidth requirements and make network resources more efficiently utilized. The data center provides larger storage space and more complex data management functions, and can store historical data, perform data archiving and backup, etc. The data center has powerful computing capabilities, can process large-scale data sets, can perform in-depth analysis of large amounts of collected data, and support long-term trend analysis, comprehensive report generation, and business intelligent decision-making.

[0087] The edge computing device pre-processes the real-time data sent by the data acquisition device, including but not limited to filtering the real-time data (such as the attached Figure 5 ), aggregate real-time data (as shown in the attached Figure 6 ), de-duplication of real-time data (as shown in the attached Figure 7 as shown), flattening the real-time data (as shown in the attached Figure 8 as shown).

[0088] Among them, filtering the real-time data means setting a data trust range for a specific data acquisition device. If the real-time data exceeds the data trust range, the real-time data is removed; if the real-time data is within the data trust range, the real-time data is retained. Furthermore, when the real-time data sent by the data acquisition device exceeds the data trust range continuously for a preset number of times, the edge computing device determines that the data acquisition device is abnormal, sends an abnormal collection alarm to the data center, and adjusts the data collection frequency of the data acquisition device. For example, a data acquisition device Q is provided at factory equipment A, and an edge computing device Z is provided at the data acquisition device Q. If the data acquisition device Q sends data to the edge computing device Z, If the real-time data exceeds the trustworthy range, the factory equipment A will be removed. Real-time data at all times; and if the real-time data sent by the data acquisition device Q to the edge computing device Z is continuous The data exceeds the trustworthy range and reaches the preset number of thresholds (Right now ), the edge computing device Z needs to send a collection abnormality alarm to the data center to remind the operation and maintenance personnel to repair the data collection device and adjust the data collection frequency of the data collection device Q (for example, from the original frequency Adjust to frequency , ).

[0089] Aggregation processing of real-time data refers to performing aggregation calculations based on the attributes of the real-time data, including but not limited to maximum value calculations, minimum value calculations, sum calculations, and average value calculations.

[0090] Deduplication of real-time data refers to deduplication of real-time data when the real-time data is consistent with the data at the previous moment.

[0091] Flattening real-time data means converting nested JSON fields in the data stream into flattened JSON fields.

[0092] Furthermore, in the embodiment of the above-mentioned intelligent factory management method, the data display unit of the data management subsystem displays the factory equipment information in the following specific process:

[0093] Step S301, obtain the equipment information of each factory equipment in the micro-nano laboratory, as shown in the attached Figure 9-10 As shown, including but not limited to the name, model, equipment condition, alarm record, repair record, maintenance record, operating status, equipment location, and person in charge information of each factory equipment.

[0094] Step S302: construct a model of the factory equipment according to the equipment information of each factory equipment, and construct a first mapping relationship between the model and the equipment information. The model is a 2D model or a 3D model. Figure 3-4 shown.

[0095] Specifically, the operator can click on the model of the plant equipment on the display panel to retrieve the specific equipment information of the plant equipment, or the model of the plant equipment on the display panel is provided with a suspended accessory, and the operating status of the plant equipment is displayed by the color of the suspended accessory. For example, the suspended accessory is round. When the suspended accessory of the plant equipment is displayed in green, it indicates that the operating status of the plant equipment is normal. When the suspended accessory of the plant equipment is displayed in yellow, it indicates that there is an abnormal trend in the operating status of the plant equipment. When the suspended accessory of the plant equipment is displayed in red, it indicates that there is an abnormality in the operating status of the plant equipment and an alarm is required.

[0096] Furthermore, the equipment information of the factory equipment also includes equipment monitoring information. A second mapping relationship is established between the model and the equipment monitoring information. The operator can operate the model of the factory equipment on the display panel in a preset manner to retrieve the equipment monitoring information of the factory equipment, such as the attached Figure 11-12 shown.

[0097] Furthermore, the equipment information of the plant equipment also includes analytical data of the equipment, including but not limited to historical curves (such as attached Fig.13 ), operation trend curve (as shown in the attached Fig.14 ), analysis report (as shown in the attached Fig.15 shown) and fault analysis (as shown in Fig.16 A third mapping relationship is established between the model and the analysis data, and the operator can operate the model of the factory equipment on the display panel in a preset manner to retrieve the analysis data of the factory equipment.

[0098] It should be understood that although the Figure 2 The steps in the flowchart are shown in sequence as indicated by 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 restriction for the execution of these steps, and these steps can be executed in other orders. Figure 2 At least part of the steps may include multiple sub-steps or sub-stages. These sub-steps or stages are not necessarily executed 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 part of the sub-steps or stages of other steps.

[0099] In one embodiment, the present invention further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the above-mentioned intelligent factory management method are implemented.

[0100] The computer-readable storage medium may be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read-only memory), an EPROM (erasable programmable read-only memory), a hard disk or a ROM. Optionally, the computer-readable storage medium includes a non-transitory computer-readable storage medium. The computer-readable storage medium has a storage space for program codes for executing any method step of the above method. These program codes may be read from or written into one or more computer program products, and the program codes may be compressed in an appropriate form.

[0101] In one embodiment, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the above-mentioned intelligent factory management method when executing the computer program.

[0102] The computer device includes a memory, a processor, and one or more computer programs, wherein the one or more computer programs can be stored in the memory and configured to be executed by one or more processors, and the one or more application programs are configured to execute the above-mentioned intelligent factory management method.

[0103] The processor may include one or more processing cores. The processor uses various interfaces and lines to connect the various parts of the entire computer device, and executes various functions of the computer device and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory, and calling data stored in the memory. Optionally, the processor can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor can integrate one or more combinations of a central processing unit (Central Processing Unit, CPU), a reporting verifier (Graphics Processing Unit, GPU) for buried data, and a modem. Among them, the CPU mainly processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing display content; and the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor, but may be implemented separately through a communication chip.

[0104] The memory may include a random access memory (RAM) or a read-only memory (ROM). The memory may be used to store instructions, programs, codes, code sets or instruction sets. The memory may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc. The data storage area may also store data created by the terminal device during use, etc.

[0105] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. The present invention provides an intelligent factory management system, characterized in that: It includes data acquisition subsystem, data management subsystem and factory management subsystem, among which: The data acquisition subsystem is used to collect the operation data of factory equipment; The data management subsystem is used to receive the operation data sent by the data acquisition subsystem, and store and display the operation data; The plant affairs management subsystem is used to receive the operation data forwarded by the data management subsystem, obtain the operation status of the plant affairs equipment according to the operation data, and send the operation status of the plant affairs equipment to the data management subsystem for display.

2. The intelligent factory management system according to claim 1, characterized in that: Also includes: The inspection subsystem is used to receive and execute the factory equipment inspection instructions sent by the factory management subsystem, and send the inspection results to the data management subsystem.

3. The intelligent factory management system according to claim 2, characterized in that: The data management subsystem is configured as a mode combining edge computing devices and data center devices.

4. An intelligent factory affairs management method, the intelligent factory affairs management method is applied to the intelligent factory affairs management system according to any one of claims 1 to 3, characterized in that: include: Obtain real-time data of each plant equipment; Extracting the real-time data according to the data type of each plant equipment to obtain standard real-time data of each plant equipment; Determine whether each plant equipment is in a normal operating state according to the plant equipment standard real-time data and the plant equipment historical information set; If the plant equipment is in normal operation, the operation status and real-time data of the plant equipment are marked and displayed in the plant equipment model; If the plant equipment is in an abnormal operating state, the operating state, real-time data and real-time fault cause of the plant equipment are marked and displayed in the plant equipment model.

5. The intelligent factory management method according to claim 4, characterized in that: The real-time data is extracted according to the data type of each factory equipment to obtain the standard real-time data of each factory equipment, specifically: Obtain data model tags from real-time data of each plant equipment; According to the data model tag, necessary information is extracted from the real-time data of each plant equipment in a preset manner, and the necessary information of each plant equipment is recorded as standard real-time data of each plant equipment in a unified format of the digital management subsystem.

6. The intelligent factory management method according to claim 5, characterized in that: The determining whether each plant equipment is in a normal operating state according to the plant equipment standard real-time data and the plant equipment historical information set includes: Construct a historical curve of the parameters of the plant equipment according to the historical information set of the plant equipment; On the historical curve, an upper limit of a parameter of the device operation is set according to a first ratio, and a lower limit of a parameter of the device operation is set according to a second ratio, and the upper limit and the lower limit of the parameter are marked in the same coordinate system as the historical curve; If the standard real-time data of the plant equipment exceeds the upper or lower parameter limit, the real-time operation status of the plant equipment is marked as abnormal operation; otherwise, the real-time operation status of the plant equipment is marked as normal operation.

7. The intelligent factory management method according to claim 6, characterized in that: Also includes: Obtain a Boolean variable parameter of a factory equipment to determine whether the factory equipment is in a normal operating state.

8. The intelligent factory management method according to claim 7, characterized in that: Also includes: Based on the historical information collection and standard real-time data of the plant equipment, it is determined whether the operating status of the plant equipment has a trend of potential abnormal operating status.

9. The intelligent factory management method according to claim 8, characterized in that: Also includes: If the plant equipment is in an abnormal operating state, a maintenance work order is generated according to the standard real-time data of the plant equipment.

10. The intelligent factory management method according to claim 9, characterized in that: Also includes: Obtain equipment information of each factory equipment; A model of the plant equipment is constructed according to the equipment information of each plant equipment, and a first mapping relationship is constructed between the model and the equipment information.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of any one of the intelligent factory management methods of claims 4-10 are implemented.

12. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it executes any one of the intelligent factory management methods in claims 4-10.

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