Digital operation and maintenance method and system for semiconductor water system

Abstract

The invention relates to the field of operation and maintenance systems, in particular to a digital operation and maintenance method and system for a semiconductor water system, and the method comprises the following steps: obtaining related data of the semiconductor water system, and accessing the related data to an Internet of Things platform; the position of the related data on the Internet of Things platform is combined with the position in the building information model, and data interaction and control operation are carried out in the building information model; equipment and pipelines related to the equipment state monitoring data, and waterways and inspection routes and / or objects related to the water production statistical data are associated, so that the visualization of the equipment operation state and the waterway flow direction and the unmanned inspection process are realized; according to the method, a water system operation prediction model is constructed, the operation condition of the semiconductor water system is predicted, equipment maintenance, consumable replacement, medicament consumption and an inspection cycle in the semiconductor water system are planned according to a prediction result, and then an operation and maintenance work order is generated to realize planning.

Description

Technical Field

[0001] The present disclosure relates to the field of operation and maintenance systems, and in particular to a digital operation and maintenance method and system for a semiconductor water system. Background Art

[0002] Semiconductor water systems generally include various modules such as water production monitoring, equipment management, unmanned inspection, emergency fault management, etc., and usually need to be integrated and managed. Existing systems usually use conventional architectures for modular notifications, and the controls are relatively abstract and simple, making it difficult to get started with the system. Digital twins make full use of physical models, sensor updates, operation history and other data, integrate multi-disciplinary, multi-physical quantity, multi-scale, and multi-probability simulation processes, complete mapping in virtual space, and thus reflect the entire life cycle of the corresponding physical equipment. Digital twin technology has been applied in various fields.

[0003] However, since the semiconductor water system involves many modules, if it is to be used for visualization of data, equipment, management and other aspects, it is necessary to pre-process the data collection, transmission and analysis in advance. The monitoring, data calculation and management involved are relatively complex. The data must be pre-processed and converted into the digital twin module for visualization. The existing technology still has the following problems: (1) Only a single model can be visualized, such as only equipment monitoring or single monitoring of the water system can be realized, and all equipment monitoring involved in the entire system or the flow direction and flow of water in the water system cannot be simulated; (2) Operation and maintenance work orders still need to be issued using the original system and cannot be combined with the visualization model; (3) They can only handle emergencies when problems occur in the equipment or system, or can only use routine inspections to maintain system operation. They cannot predict possible problems in the system or situations that require maintenance, so as to deal with problems before they occur. Summary of the invention

[0004] The embodiment of the present disclosure provides a semiconductor water system digital operation and maintenance method and system thereof to solve the problems existing in the related technologies. The technical solution is as follows: In a first aspect, an embodiment of the present disclosure provides a semiconductor water system digital operation and maintenance method, comprising the following steps: Obtain relevant data of the semiconductor water system and connect the relevant data to the Internet of Things platform, wherein the relevant data includes equipment status monitoring data, water production statistics data and inspection information; Combining the location of relevant data on the IoT platform with the location in the building information model, and performing data interaction and control operations in the building information model; The equipment and pipelines involved in the equipment status monitoring data, the waterways and inspection routes and / or objects involved in the water production statistical data are associated to realize the visualization of the equipment operation status and waterway flow direction and the unmanned inspection process; Construct a water system operation prediction model to predict the operation of the semiconductor water system based on the expected water use and water treatment needs of the semiconductor water system, combined with historical inspection data, historical equipment operating status and historical water production. Based on the prediction results, plan the equipment maintenance, consumables replacement, agent consumption and inspection cycle in the semiconductor water system, and then generate operation and maintenance work orders to implement the plan.

[0005] Optionally, the Internet of Things platform is an IoT platform, and the equipment status monitoring data is obtained by connecting the equipment operation status sensor and camera for monitoring the equipment status to the IoT platform; the water production statistical data is obtained by connecting the water flow sensor and water pressure sensor in the water system pipeline to the IoT platform; the inspection information is obtained by the inspection personnel logging into the handheld inspection device and connecting to the IoT platform to upload, or the inspection information is obtained by connecting the equipment operation status or water quality data obtained by sampling with unmanned inspection equipment to the IoT platform.

[0006] Optionally, after the operation and maintenance work order is generated, it includes: Push the operation and maintenance work order to the operation and maintenance personnel system through the mobile management platform and the PC management platform; and displaying the equipment and operation and maintenance items involved in the operation and maintenance content in the operation and maintenance work order at corresponding positions in the building information model in a visual manner; The operation and maintenance personnel update the equipment operation status and consumables usage through the operation and maintenance personnel system or in the building information model; The updated equipment operation status and consumables usage are updated into the building information model.

[0007] Optionally, combining the location of the relevant data on the IoT platform with the location in the building information model includes: The device ID and / or location coordinates corresponding to the relevant data are mapped to the building information model, the device ID is bound to the corresponding position of the building information model, and controls are set in the building information model to realize data interaction and control operations on relevant devices connected to the Internet of Things platform.

[0008] Optionally, the equipment and pipelines involved in the equipment status monitoring data, the waterways and inspection routes and / or objects involved in the water production statistical data are associated to realize the visualization of the equipment operation status and waterway flow direction and the unmanned inspection process, including: Select a suitable 3D display driver engine to build a digital twin model, which includes equipment, waterway and building information; The device operation status sensors and cameras, water flow sensors and water pressure sensors, handheld inspection devices or unmanned inspection devices connected to the IoT platform are bound to the 3D display drive engine to realize data-driven device operation status, visualization of water flow direction and unmanned inspection process.

[0009] Optionally, based on the expected water consumption and water treatment requirements of the semiconductor water system, the operation status of the semiconductor water system is predicted in combination with historical inspection data, historical equipment operation status and historical water production conditions, including: Obtain historical water use and water treatment demand data for semiconductor water systems, including water quality standards, water usage, and wastewater treatment volumes; Collect historical water use data, including historical water consumption, water quality indicators, and historical wastewater treatment volume; Collect historical equipment operation status data, historical water production data and historical inspection data. The historical equipment operation status data includes operation time, operation parameters and energy consumption data. The inspection data includes equipment inspection records, maintenance logs and fault reports. The historical water use and water treatment demand data, historical water use data, historical equipment operation status data, historical water production data and historical inspection data are cleaned and normalized to obtain a data set, wherein the data cleaning includes processing missing values, outliers and noise; Dividing the data set into a training set and a validation set; The historical water use and water treatment demand data, historical water use data, and historical inspection data in the training set are used as input, and the historical equipment operation status data and historical water production data are used as output. The pre-built recurrent neural network is trained to obtain a water system operation prediction model that predicts in time sequence; the water system operation prediction model is then tuned with the data in the validation set to avoid overfitting. The expected water use and water treatment requirements are used as data, combined with the updated historical inspection data, historical equipment operating status and historical water production, and the water system operation prediction model is used to predict the operation of the semiconductor water system to obtain a prediction result, which includes the expected operating status of the equipment and the expected water production.

[0010] Optionally, when the relevant data on the IoT platform is judged to be abnormal, a fault work order is directly generated and pushed to the operation and maintenance personnel system.

[0011] In a second aspect, the present disclosure provides a semiconductor water system digital operation and maintenance system, including: An Internet of Things platform access unit, which obtains relevant data of the semiconductor water system and accesses the relevant data to the Internet of Things platform, wherein the relevant data includes equipment status monitoring data, water production statistics data and inspection information; A BIM docking unit that combines the location of relevant data on the IoT platform with the location in the building information model, and performs data interaction and control operations in the building information model; Digital twin unit, and associate the equipment and pipelines involved in the equipment status monitoring data, the waterways and inspection routes and / or objects involved in the water production statistical data, to achieve visualization of equipment operation status and waterway flow direction and unmanned inspection process; The water system operation prediction unit builds a water system operation prediction model. According to the expected water use and water treatment needs of the semiconductor water system, combined with historical inspection data, historical equipment operation status and historical water production, the operation status of the semiconductor water system is predicted. According to the prediction results, the equipment maintenance, consumables replacement, agent consumption and inspection cycle in the semiconductor water system are planned, and then an operation and maintenance work order is generated to implement the plan.

[0012] In a third aspect, an embodiment of the present disclosure provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the digital operation and maintenance method of the semiconductor water system when executing the computer program.

[0013] In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the digital operation and maintenance method of the semiconductor water system.

[0014] The advantages or beneficial effects of the above technical solution include at least: (1) The present disclosure connects all monitoring data related to the semiconductor water system to the BIM model through the Internet of Things platform, realizing the simulation of all equipment monitoring involved in the entire system or the flow direction and flow of water in the water system; (2) The equipment operation status and waterway flow direction can be visualized and the inspection process can be unmanned, which helps the staff to quickly get started with the maintenance and inspection of the entire system, and also helps to understand and execute the operation and maintenance work orders, as well as to understand the execution status of the operation and maintenance work orders and fault management. (3) Build a water system operation prediction model to predict possible system problems or maintenance requirements, and intelligently generate operation and maintenance work orders to resolve problems before they occur.

[0015] The above summary is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments and features described above, further aspects, embodiments and features of the present disclosure will be readily apparent by reference to the accompanying drawings and the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the multiple drawings represent the same or similar parts or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings only depict some embodiments according to the present disclosure and should not be regarded as limiting the scope of the present disclosure.

[0017] Figure 1 It is a flow chart of the digital operation and maintenance method of the semiconductor water system according to Embodiment 1 of the present disclosure; Figure 2 This is a visualization interface diagram of relevant data on the Internet of Things platform in Embodiment 1 of the present disclosure; Figure 3 This is a visualization display effect diagram of the 3D display driving engine in Embodiment 1 of the present disclosure; Figure 4 Detailed implementation step diagram of S40 in Embodiment 1 of the present disclosure; Figure 5 This is a diagram of the operation and maintenance work order update steps in Embodiment 1 of the present disclosure; Figure 6 This is a block diagram of the digital operation and maintenance system of the semiconductor water system in Embodiment 2 of the present disclosure; Figure 7 This is a block diagram of another semiconductor water system digital operation and maintenance system in Example 2 of the present disclosure. DETAILED DESCRIPTION

[0018] Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

[0019] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0020] In addition, in order to better illustrate the present disclosure, numerous specific details are given in the following specific embodiments. It should be understood by those skilled in the art that the present disclosure can also be implemented without certain specific details. In some examples, methods, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the subject matter of the present disclosure.

[0021] It can be understood that the above-mentioned various method embodiments mentioned in the present disclosure can be combined with each other to form a combined embodiment without violating the principle logic. Due to space limitations, the present disclosure will not go into details.

[0022] In addition, the present disclosure also provides a semiconductor water system digital operation and maintenance system, an electronic device, a computer-readable storage medium, and a program, all of which can be used to implement any semiconductor water system digital operation and maintenance method provided by the present disclosure. The corresponding technical solutions and descriptions are referred to the corresponding records in the method part and will not be repeated here.

[0023] The execution subject of the semiconductor water system digital operation and maintenance method may be a computer or other device capable of realizing the semiconductor water system digital operation and maintenance. For example, the method may be executed by a terminal device or a server or other processing device, wherein the terminal device may be a user equipment (UE), a mobile device, a user terminal, a personal digital assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, etc. In some possible implementations, the semiconductor water system digital operation and maintenance method may be implemented by a processor calling a computer-readable instruction stored in a memory.

[0024] Example 1 This embodiment provides a semiconductor water system digital operation and maintenance method, such as Figure 1 As shown, the following steps are included: S10, obtaining relevant data of the semiconductor water system, and connecting the relevant data to the Internet of Things platform, the relevant data including equipment status monitoring data, water production statistics data and inspection information; S20, combining the location of the relevant data on the Internet of Things platform with the location in the building information model, and performing data interaction and control operations in the building information model; S30, associating the equipment and pipelines involved in the equipment status monitoring data, the waterways and inspection routes and / or objects involved in the water production statistical data, to achieve visualization of the equipment operating status and waterway flow direction and unmanned inspection process; S40. Construct a water system operation prediction model to predict the operation of the semiconductor water system based on the expected water use and water treatment needs of the semiconductor water system, combined with historical inspection data, historical equipment operating status and historical water production. Plan equipment maintenance, consumables replacement, agent consumption and inspection cycles in the semiconductor water system based on the prediction results, and then generate an operation and maintenance work order to implement the plan.

[0025] Based on the above configuration, the disclosed embodiment of the present invention connects all monitoring data related to the semiconductor water system to the BIM model through the Internet of Things platform, realizing the simulation of all equipment monitoring involved in the entire system or the water flow direction and flow in the water system. The visualization of equipment operating status and water flow direction and unmanned inspection process are realized, which is conducive to the staff to quickly get started with the maintenance and inspection of the entire system, and is also conducive to the understanding and execution of operation and maintenance work orders, and it is also convenient to understand the execution status of operation and maintenance work orders, fault management, etc.; build a water system operation prediction model, predict possible problems or maintenance needs of the system, and intelligently generate operation and maintenance work orders to deal with problems before they occur.

[0026] The following describes in detail each step of the embodiment of the present disclosure.

[0027] S10, obtaining relevant data of the semiconductor water system, and connecting the relevant data to the Internet of Things platform, the relevant data including equipment status monitoring data, water production statistics data and inspection information; Preferably, the Internet of Things platform is an IoT platform, and the equipment status monitoring data is obtained by connecting the equipment operation status sensor and camera for equipment status monitoring to the IoT platform; the water production statistics are obtained by connecting the water flow sensor and water pressure sensor in the water system pipeline to the IoT platform; the inspection information is obtained by the inspection personnel logging in to the handheld inspection device to connect to the IoT platform and upload, or the inspection information is obtained by connecting the equipment operation status or water quality data obtained by sampling by unmanned inspection equipment to the IoT platform. Among them, the equipment operation status sensor is used to monitor the operation status of related equipment, such as the operation status monitoring sensor or water quality monitoring sensor of related equipment in ultrapure water (UPW) preparation equipment, wastewater treatment equipment, and reclaimed water treatment equipment. The camera is used to monitor potential leakage points in the water system, and leak monitoring is realized in combination with the water pressure sensor; water flow sensors and water pressure sensors are installed in the pipeline of the water system, such as installed at the water inlet, water outlet and circulation pipeline; they can be connected to the IoT gateway by wireless or wired means, and then the data is transmitted to the IoT platform; in addition, the handheld inspection device or unmanned inspection device can also be connected to the IoT gateway, and the IoT platform is configured with a unique identifier for each sensor or device connected to the IoT gateway, and it is associated with the corresponding data type. In this way, it is possible to obtain equipment status monitoring data, water production statistics and inspection information on the same IoT platform.

[0028] S20. Combining the location of the relevant data on the Internet of Things platform with the location in the building information model, and performing data interaction and control operations in the building information model.

[0029] Among them, the unique identifier corresponding to each relevant data on the Internet of Things platform can be uniquely matched with the location in the building information model to form a one-to-one mapping relationship, and the location of the relevant data on the Internet of Things platform is combined with the location in the building information model, including: In one embodiment, the device ID and / or location coordinates corresponding to the relevant data are mapped to the building information model, the device ID is bound to the corresponding position of the building information model, controls are set in the building information model to realize data interaction and control operations of the relevant devices connected to the Internet of Things platform, and display controls are set in the visual interface to display or form data interaction and control operations. Figure 2 As shown, this is a visualization interface diagram of relevant data on the Internet of Things platform. The visualization interface includes water production statistics, water production flow, data detected by sensors in the terminal water supply TOC, terminal water supply silica and other polishing systems, fault statistics, consumption costs, fault work order progress, etc.

[0030] S30, associating the equipment and pipelines involved in the equipment status monitoring data, the waterways and inspection routes and / or objects involved in the water production statistical data, to achieve visualization of the equipment operating status and waterway flow direction and unmanned inspection process.

[0031] In some embodiments, S30 includes: Select a suitable 3D display driver engine to build a digital twin model, which includes equipment, waterway and building information; the 3D display driver engine can be Unity 3D, Unreal Engine, etc.; Bind the device operation status sensors and cameras, water flow sensors and water pressure sensors, handheld inspection devices or unmanned inspection devices connected to the IoT platform to the 3D display driver engine to realize data-driven device operation status, visualization of waterway flow direction and unmanned inspection process. Display the real-time status of the equipment in the 3D model, such as operation, failure, etc., use the 3D model to display the flow direction and flow of the waterway, and provide an intuitive dynamic display of water flow; design a user interface to allow users to interact with the 3D model by clicking, dragging, etc. Figure 3 The figure shows the visual display effect diagram of the 3D display driving engine in this embodiment.

[0032] S40, constructing a water system operation prediction model, predicting the operation of the semiconductor water system according to the expected water use and water treatment needs of the semiconductor water system, combined with historical inspection data, historical equipment operation status and historical water production, and planning equipment maintenance, consumables replacement, agent consumption and inspection cycle in the semiconductor water system according to the prediction results, and then generating an operation and maintenance work order to implement the plan; In one embodiment, the operation of the semiconductor water system is predicted based on the expected water use and water treatment requirements of the semiconductor water system, combined with historical inspection data, historical equipment operation status, and historical water production conditions, such as Figure 4 As shown, including: S401. Obtain historical water use and water treatment demand data of semiconductor water systems, including water quality standards, water consumption, and wastewater treatment volume; S402. Collect historical water use data, including historical water consumption, water quality indicators and historical wastewater treatment volume; S403, collecting historical equipment operation status data, historical water production data and historical inspection data, the historical equipment operation status data includes operation time, operation parameters and energy consumption data, etc., the inspection data includes equipment inspection records, maintenance logs and fault reports, etc.; S404. Clean and normalize the historical water use and water treatment demand data, historical water use data, historical equipment operation status data, historical water production data and historical inspection data to obtain a data set, so as to obtain a standardized data set. The data cleaning includes processing missing values, outliers and noise to ensure the accuracy and reliability of the data.

[0033] S405, dividing the data set into a training set and a validation set to facilitate subsequent model training and validation; S406. Taking the historical water use and water treatment demand data, historical water use data and historical inspection data in the training set as input, and taking the historical equipment operation status data and historical water production data as output, the pre-built recurrent neural network is trained to obtain a water system operation prediction model that predicts in time sequence; the water system operation prediction model is then tuned with the data in the validation set to avoid overfitting; wherein the recurrent neural network (RNN) can adopt a long short-term memory network (LSTM) or a gated recurrent unit (GRU), wherein, for example, the long short-term memory network (LSTM) introduces three gating mechanisms: a forget gate, an input gate and an output gate. The forget gate is implemented by a sigmoid layer, whose output value is between 0 and 1, indicating the degree of information retention. The input gate consists of a sigmoid layer and a tanh layer. The sigmoid layer determines which values ​​will be updated, while the tanh layer creates a new vector of candidate values ​​that will be added to the state. The output gate determines which part of the cell state will be output through a sigmoid layer, and then the tanh layer is used to calculate the final hidden state output. This enables the network to effectively capture long-term dependencies in sequence data, so that accurate predictions can be made in time order.

[0034] S407, using the expected water use and water treatment requirements as data, combined with the updated historical inspection data, historical equipment operation status and historical water production, using the water system operation prediction model to predict the operation of the semiconductor water system to obtain a prediction result, the prediction result includes the expected equipment operation status and expected water production; and planning the equipment maintenance, consumables replacement, agent consumption and inspection cycle in the semiconductor water system based on the prediction result. By constructing the above method, a solid foundation can be laid for the intelligent management and maintenance of semiconductor water systems.

[0035] As another embodiment, in order to handle emergency faults, the IoT platform is prioritized to determine the anomaly and generate a corresponding fault ticket, that is, when the relevant data on the IoT platform is determined to be abnormal, a fault ticket is directly generated and pushed to the operation and maintenance personnel system.

[0036] In one embodiment, after the operation and maintenance work order is generated, Figure 5 The figure shows the steps for updating the operation and maintenance work order, which also includes the following steps: S501. Push the operation and maintenance work order to the operation and maintenance personnel system through the mobile management platform and the PC management platform; the operation and maintenance personnel system also has personnel management functions, including personnel scheduling, work order statistics, performance management, personnel training and assessment management, etc., to facilitate personnel management and the implementation of operation and maintenance work orders; S502, and displaying the equipment and operation and maintenance items involved in the operation and maintenance content in the operation and maintenance work order at corresponding positions in the building information model in a visual manner; S503, the operation and maintenance personnel updates the equipment operation status and consumables usage through the operation and maintenance personnel system or in the building information model; S504: Update the updated equipment operation status and consumables usage status into the building information model (BIM).

[0037] This allows the digital twin system to display the latest equipment operating status and consumables usage.

[0038] In one embodiment, the digital twin system is also used to display the predicted costs, wherein the cost analysis function can be implemented in step S40 and displayed in the digital twin system in S50. By predicting equipment maintenance, consumables replacement and drug consumption, the operating cost of the water system can be analyzed and predicted based on this. This indicator is a key indicator for water system management.

[0039] Example 2 This embodiment provides a semiconductor water system digital operation and maintenance system 100, such as Figure 6 As shown, including: The Internet of Things platform access unit 1 obtains relevant data of the semiconductor water system and accesses the relevant data to the Internet of Things platform, wherein the relevant data includes equipment status monitoring data, water production statistics data and inspection information; BIM docking unit 2, combining the location of relevant data on the IoT platform with the location in the building information model, and performing data interaction and control operations in the building information model; Digital twin unit 3, and associates the equipment and pipelines involved in the equipment status monitoring data, the waterways and inspection routes and / or objects involved in the water production statistical data, to achieve visualization of the equipment operation status and waterway flow direction and unmanned inspection process; The water system operation prediction unit 4 builds a water system operation prediction model, and predicts the operation of the semiconductor water system based on the expected water use and water treatment needs of the semiconductor water system, combined with historical inspection data, historical equipment operation status and historical water production. According to the prediction results, the equipment maintenance, consumables replacement, agent consumption and inspection cycle in the semiconductor water system are planned, and then an operation and maintenance work order is generated to implement the plan.

[0040] The semiconductor water system digital operation and maintenance system 100 in this embodiment 2 is a system corresponding to the corresponding method in embodiment 1. In the absence of contradiction, the Internet of Things platform access unit 1, BIM docking unit 2, digital twin unit 3 and water system operation prediction unit 4 in this embodiment 2 are used to implement the corresponding method steps in the above-mentioned embodiment 1.

[0041] In addition, as an optional implementation, Figure 7 As shown, it is another block diagram of the semiconductor water system digital operation and maintenance system in the embodiment 2 of the present disclosure. The semiconductor water system digital operation and maintenance system 200 also includes a visualization update unit 5, which realizes: pushing the operation and maintenance work order to the operation and maintenance personnel system through the mobile management platform and the PC management platform; and displaying the equipment and operation and maintenance items involved in the operation and maintenance content in the operation and maintenance work order in the corresponding position in the building information model in a visual way; the operation and maintenance personnel update the equipment operation status and consumables usage through the operation and maintenance personnel system or in the building information model; and update the updated equipment operation status and consumables usage to the building information model (BIM). In this way, the digital twin system displays the latest equipment operation status and consumables usage.

[0042] Example 3 An embodiment of the present disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the digital operation and maintenance method of the semiconductor water system in Embodiment 1 when executing the computer program.

[0043] Embodiment 3 of the present disclosure is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0044] The electronic device may be in the form of a general-purpose computing device, for example, it may be a server device. The components of the electronic device may include, but are not limited to: at least one processor, at least one memory, and a bus connecting different system components (including the memory and the processor).

[0045] The bus includes data bus, address bus and control bus.

[0046] The memory may include volatile memory, such as random access memory (RAM) and / or cache memory, and may further include read-only memory (ROM).

[0047] The memory may also include a program tool having a set (at least one) of program modules, such program modules including but not limited to: an operating system, one or more application programs, other program modules and program data, each of which or some combination may include the implementation of a network environment.

[0048] The processor executes various functional applications and data processing by running computer programs stored in the memory.

[0049] The electronic device may also communicate with one or more external devices (e.g., keyboards, pointing devices, etc.). Such communication may be performed through an input / output (I / O) interface. In addition, the electronic device may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) through a network adapter. The network adapter communicates with other modules of the electronic device through a bus. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems, etc.

[0050] It should be noted that although several units / modules or sub-units / modules of the electronic device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided into multiple units / modules to be embodied.

[0051] Example 4 The embodiment of the present disclosure also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the program is executed by a processor, the steps of the digital operation and maintenance method of the semiconductor water system in embodiment 1 are implemented.

[0052] The readable storage medium may include but is not limited to: a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device or any suitable combination of the above.

[0053] In a possible implementation, the present disclosure can also be implemented in the form of a program product, which includes a program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps of the semiconductor water system digital operation and maintenance method described in Example 1.

[0054] Among them, the program code for executing the present disclosure can be written in any combination of one or more programming languages, and the program code can be executed completely on the user device, partially on the user device, as an independent software package, partially on the user device and partially on a remote device, or completely on the remote device.

[0055] The above are only specific embodiments of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any technician familiar with the technical field can easily think of various changes or substitutions within the technical scope disclosed in the present disclosure, which should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A digital operation and maintenance method for a semiconductor water system, characterized in that: The steps include: Obtain relevant data of the semiconductor water system and connect the relevant data to the Internet of Things platform, wherein the relevant data includes equipment status monitoring data, water production statistics data and inspection information; Combining the location of relevant data on the IoT platform with the location in the building information model, and performing data interaction and control operations in the building information model; The equipment and pipelines involved in the equipment status monitoring data, the waterways and inspection routes and / or objects involved in the water production statistical data are associated to realize the visualization of the equipment operation status and waterway flow direction and the unmanned inspection process; Construct a water system operation prediction model to predict the operation of the semiconductor water system based on the expected water use and water treatment needs of the semiconductor water system, combined with historical inspection data, historical equipment operating status and historical water production. Based on the prediction results, plan the equipment maintenance, consumables replacement, agent consumption and inspection cycle in the semiconductor water system, and then generate operation and maintenance work orders to implement the plan.

2. The semiconductor water system digital operation and maintenance method according to claim 1, characterized in that: The Internet of Things platform is an IoT platform, and the equipment status monitoring data is obtained by connecting the equipment operation status sensor and camera that monitor the equipment status to the IoT platform; the water production statistical data is obtained by connecting the water flow sensor and water pressure sensor in the water system pipeline to the IoT platform; the inspection information is obtained by the inspection personnel logging into the handheld inspection device and connecting to the IoT platform to upload, or the inspection information is obtained by connecting the equipment operation status or water quality data obtained by sampling by unmanned inspection equipment to the IoT platform.

3. The digital operation and maintenance method of a semiconductor water system according to claim 1 or 2, characterized in that: After the operation and maintenance work order is generated, it includes: Push the operation and maintenance work order to the operation and maintenance personnel system through the mobile management platform and the PC management platform; and displaying the equipment and operation and maintenance items involved in the operation and maintenance content in the operation and maintenance work order at corresponding positions in the building information model in a visual manner; The operation and maintenance personnel update the equipment operation status and consumables usage through the operation and maintenance personnel system or in the building information model; The updated equipment operation status and consumables usage are updated into the building information model.

4. The digital operation and maintenance method of semiconductor water system according to claim 1, characterized in that: Combining the location of relevant data on the IoT platform with the location in the building information model, including: The device ID and / or location coordinates corresponding to the relevant data are mapped to the building information model, the device ID is bound to the corresponding position of the building information model, and controls are set in the building information model to realize data interaction and control operations on relevant devices connected to the Internet of Things platform.

5. The digital operation and maintenance method of semiconductor water system according to claim 2, characterized in that: The equipment and pipelines involved in the equipment status monitoring data, the waterways and inspection routes and / or objects involved in the water production statistical data are associated to realize the visualization of the equipment operation status and waterway flow direction and the unmanned inspection process, including: Select a suitable 3D display driver engine to build a digital twin model, which includes equipment, waterway and building information; The device operation status sensors and cameras, water flow sensors and water pressure sensors, handheld inspection devices or unmanned inspection devices connected to the IoT platform are bound to the 3D display drive engine to realize data-driven device operation status, visualization of water flow direction and unmanned inspection process.

6. The semiconductor water system digital operation and maintenance method according to claim 1 or 2, characterized in that: Based on the expected water use and water treatment needs of the semiconductor water system, combined with historical inspection data, historical equipment operating status and historical water production, the operation status of the semiconductor water system is predicted, including: Obtain historical water use and water treatment demand data for semiconductor water systems, including water quality standards, water usage, and wastewater treatment volumes; Collect historical water use data, including historical water consumption, water quality indicators, and historical wastewater treatment volume; Collect historical equipment operation status data, historical water production data and historical inspection data. The historical equipment operation status data includes operation time, operation parameters and energy consumption data. The inspection data includes equipment inspection records, maintenance logs and fault reports. The historical water use and water treatment demand data, historical water use data, historical equipment operation status data, historical water production data and historical inspection data are cleaned and normalized to obtain a data set, wherein the data cleaning includes processing missing values, outliers and noise; Dividing the data set into a training set and a validation set; The historical water use and water treatment demand data, historical water use data, and historical inspection data in the training set are used as input, and the historical equipment operation status data and historical water production data are used as output. The pre-built recurrent neural network is trained to obtain a water system operation prediction model that predicts in time sequence; the water system operation prediction model is then tuned with the data in the validation set to avoid overfitting. The expected water use and water treatment requirements are used as data, combined with the updated historical inspection data, historical equipment operating status and historical water production, and the water system operation prediction model is used to predict the operation of the semiconductor water system to obtain a prediction result, which includes the expected operating status of the equipment and the expected water production.

7. The digital operation and maintenance method of semiconductor water system according to claim 3, characterized in that: It also includes directly generating a fault ticket and pushing it to the operation and maintenance personnel system when the relevant data on the IoT platform is judged to be abnormal.

8. A semiconductor water system digital operation and maintenance system, characterized in that: include: An Internet of Things platform access unit, which obtains relevant data of the semiconductor water system and accesses the relevant data to the Internet of Things platform, wherein the relevant data includes equipment status monitoring data, water production statistics data and inspection information; A BIM docking unit that combines the location of relevant data on the IoT platform with the location in the building information model, and performs data interaction and control operations in the building information model; Digital twin unit, and associate the equipment and pipelines involved in the equipment status monitoring data, the waterways and inspection routes and / or objects involved in the water production statistical data, to achieve visualization of equipment operation status and waterway flow direction and unmanned inspection process; The water system operation prediction unit builds a water system operation prediction model. According to the expected water use and water treatment needs of the semiconductor water system, combined with historical inspection data, historical equipment operation status and historical water production, the operation status of the semiconductor water system is predicted. According to the prediction results, the equipment maintenance, consumables replacement, agent consumption and inspection cycle in the semiconductor water system are planned, and then an operation and maintenance work order is generated to implement the plan.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the digital operation and maintenance method of the semiconductor water system described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the digital operation and maintenance method of the semiconductor water system described in any one of claims 1 to 7 is implemented.

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