A large-screen visualization system for industrial production equipment and intelligent manufacturing environment

Abstract

This application provides a large-screen visualization system for industrial production equipment and intelligent manufacturing environments. It provides a specific system architecture design scheme for industrial production equipment and intelligent manufacturing environments, and introduces the application of a 3D visualization engine. The system has the advantages of lightweight deployment and convenient and efficient application, thus meeting the high-quality data visualization needs of industrial production environments.

Description

Technical Field

[0001] This application relates to the field of intelligent manufacturing, specifically to a large-screen visualization system for industrial production equipment and intelligent manufacturing environments. Background Technology

[0002] In the field of smart factories or smart manufacturing, data visualization has become one of the important means to improve production efficiency.

[0003] Traditional data visualization systems often lack effective binding and real-time update mechanisms for equipment data, resulting in lagging data display and impacting decision-making efficiency. Faced with massive amounts of data, managers and business personnel at different levels have different focuses on the system data. In industrial production environments, real-time monitoring of production data and effective data analysis are becoming increasingly important. In traditional software development, in order to display real-time or multi-dimensional data on the portal homepage, backend developers usually need to modify the code, while frontend engineers need to adjust the interface style. This process is not only cumbersome, but also comes with high time and economic costs.

[0004] Furthermore, while various reporting and Business Intelligence (BI) tools are available on the market capable of designing large-screen data visualizations, they often suffer from problems such as complex operation, slow response, and difficulty in maintenance, making it difficult to meet the high-efficiency demands of modern industrial production. The shortcomings include: 1. Most existing reporting and BI tools are bulky and not lightweight or flexible enough; 2. Large-screen visualization pages created using these tools often have poor performance, making it difficult to achieve a rapid response time of all pages within one second. This is because these pages are usually directly connected to the database and may contain complex logical operations, resulting in slow front-end loading speeds; 3. Large-screen visualization pages generated using reporting and BI tools have low modularity and are difficult to reuse.

[0005] In other words, in the face of industrial production environments, although there are already mature data visualization systems, as well as related reporting tools and BI tools on the market, there is still room for improvement in terms of implementation effects, making it difficult to meet the demand for lightweight, convenient, and efficient high-quality data visualization. Summary of the Invention

[0006] This application provides a large-screen visualization system for industrial production equipment and intelligent manufacturing environments. It provides a specific system architecture design scheme for industrial production equipment and intelligent manufacturing environments, and introduces the application of a 3D visualization engine. The system has the advantages of lightweight deployment and convenient and efficient application, thus meeting the high-quality data visualization needs of industrial production environments.

[0007] In the first aspect, this application provides a large-screen visualization system for industrial production equipment and intelligent manufacturing environment, which includes a data source layer, a data processing layer and a three-dimensional visualization layer.

[0008] The data source layer includes various industrial production equipment deployed on-site in the manufacturing environment, various sensors and databases deployed on various industrial production equipment, which are used to collect and record initial industrial data in real time and transmit the initial industrial data to the data processing layer.

[0009] The data processing layer includes a data receiving module, a data cleaning module, and a data conversion module, which are used to clean, convert, and preprocess the received initial industrial data, and transmit the processed target industrial data to the 3D visualization layer.

[0010] The 3D visualization layer includes a 3D visualization engine, which loads the received target industrial data into a 3D visualization model obtained from a digital twin model created from a physical factory. This model is then displayed on a large screen and combined with preset key indicators for comprehensive monitoring and analysis.

[0011] Secondly, this application provides a processing method for a large-screen visualization system for industrial production equipment and intelligent manufacturing environments. The large-screen visualization system for industrial production equipment and intelligent manufacturing environments includes a data source layer, a data processing layer, and a 3D visualization layer. The data source layer includes various industrial production equipment deployed on-site in the manufacturing environment, various sensors deployed on these industrial production equipment, and databases. The data processing layer includes a data receiving module, a data cleaning module, and a data conversion module. The 3D visualization layer includes a 3D visualization engine. The processing method for the large-screen visualization system for industrial production equipment and intelligent manufacturing environments includes:

[0012] The data source layer collects and records initial industrial data in real time and transmits the initial industrial data to the data processing layer;

[0013] The data processing layer cleans, transforms, and preprocesses the received initial industrial data, and then transmits the processed target industrial data to the 3D visualization layer.

[0014] The 3D visualization layer loads the received target industrial data into a 3D visualization model obtained from a pre-built digital twin model of the physical factory, displays it on a large screen, and conducts comprehensive monitoring and analysis in conjunction with preset key indicators.

[0015] Thirdly, this application provides a computer-readable storage medium storing a plurality of instructions adapted for loading by a processor to execute the method provided in the second aspect of this application.

[0016] From the above, it can be concluded that this application has the following beneficial effects:

[0017] This application develops a large-screen visualization system for industrial production equipment and intelligent manufacturing environments, providing a specific system architecture design scheme and introducing the application of a 3D visualization engine. The system is lightweight in terms of deployment and convenient and efficient in application, thus meeting the high-quality data visualization needs of industrial production environments. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of a large-screen visualization system for industrial production equipment and intelligent manufacturing environment, as described in this application.

[0020] Figure 2 This is a schematic diagram of an example of a large-screen visualization system for industrial production equipment and intelligent manufacturing environment, as described in this application.

[0021] Figure 3 This is another example of a large-screen visualization system for industrial production equipment and intelligent manufacturing environments, as described in this application. Detailed Implementation

[0022] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0023] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules is not necessarily limited to those explicitly listed, but may include other steps or modules not explicitly listed or inherent to such processes, methods, products, or devices. The naming or numbering of steps appearing in this application does not imply that the steps in the method flow must be performed in the chronological / logical order indicated by the naming or numbering. The execution order of named or numbered process steps can be changed according to the desired technical purpose, as long as the same or similar technical effect is achieved.

[0024] The module division described in this application is a logical division. In practical applications, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the coupling or direct coupling or communication connection between modules shown or discussed may be through some interfaces, and the indirect coupling or communication connection between modules may be electrical or other similar forms, none of which are limited in this application. Furthermore, the modules or sub-modules described as separate components may or may not be physically separated, may or may not be physical modules, or may be distributed in multiple circuit modules. Some or all of the modules may be selected to achieve the purpose of the solution in this application according to actual needs.

[0025] first, Figure 1 This paper presents a schematic diagram of a large-screen visualization system for industrial production equipment and intelligent manufacturing environments, based on the present application. Figure 1 As can be easily seen, the large-screen visualization system for industrial production equipment and intelligent manufacturing environments provided in this application can specifically include three major system components: the data source layer, the data processing layer, and the 3D visualization layer. The following core system workflow can be used to help understand the workings of these three parts:

[0026] (1) The data source layer includes various industrial production equipment deployed on the manufacturing environment site, various sensors and databases deployed on various industrial production equipment, which are used to collect and record initial industrial data in real time and transmit the initial industrial data to the data processing layer.

[0027] It is understandable that the main purpose of the data source layer is to collect industrial data from the field for the system. For ease of explanation, the industrial data collected in this stage, or the data source layer, will be referred to as the initial industrial data, which will be distinguished from the target industrial data for subsequent processing.

[0028] The specific quantity and type of industrial production equipment are obviously adjusted according to the specific manufacturing environment on-site where the application scheme is deployed. For these devices, it is necessary to collect the initial industrial data required by this application through corresponding sensors. This industrial data is used to indicate the equipment status, working status and environmental status of these devices.

[0029] It is worth noting that the sensors deployed on industrial production equipment mentioned here can be deployed directly on the industrial production equipment, deployed in the surrounding environment of the industrial production equipment, or be original sensors of the industrial production equipment itself or unit modules with built-in sensing functions. All of these are possible in actual situations.

[0030] After the sensor collects the initial industrial data, it can be directly transmitted or transmitted to the database for storage through the corresponding equipment / devices. The database or the sensor itself can then transmit the data to the back-end data processing layer for further processing.

[0031] (2) The data processing layer includes a data receiving module, a data cleaning module and a data conversion module, which are used to clean, convert and preprocess the received initial industrial data, and transmit the processed target industrial data to the three-dimensional visualization layer.

[0032] As for the data processing layer, it can be understood that its main purpose is to process the initial industrial data collected from the data source layer into target industrial data for subsequent 3D visualization operations. Therefore, its data processing can also be understood as secondary data processing.

[0033] In the architecture design of this application, the data processing layer may include a data receiving module responsible for receiving data, a data cleaning module responsible for cleaning data, and a data conversion module responsible for data conversion and data preprocessing. The three modules process the data in sequence and finally output the target industrial data in a preset data format that is easy to load / display in three dimensions.

[0034] (3) The three-dimensional visualization layer includes a three-dimensional visualization engine, which loads the received target industrial data into a three-dimensional visualization model obtained by a digital twin model created from a physical factory, displays it on a large screen, and conducts comprehensive monitoring and analysis in conjunction with preset key indicators.

[0035] Understandably, the 3D visualization layer designed in this application is equipped with the 3D visualization engine pre-set in this application, which can also be understood as a 3D visualization platform. It has already created a digital twin model based on the specific manufacturing environment / physical factory of the solution in this application through digital twin technology, thus obtaining a 3D visualization model. In this way, environmental and indicator displays can be displayed through the 3D visualization model. The data is updated according to the target industrial data collected in real time, reflecting the real-time situation of the production environment. Combined with the pre-set key indicators of factory assets, facilities, energy efficiency, security, etc., it provides a good foundation for comprehensive monitoring and analysis.

[0036] In terms of specific implementation, this application can design and customize hardware solutions for the 3D visualization layer according to specific application scenarios and needs. For example, high-performance graphics processing units (GPUs), multi-screen display controllers, touch interaction devices, etc. can be used to build customized large-screen data visualization systems. These hardware solutions can provide better performance and user experience.

[0037] In this way, the problems of poor real-time performance, slow response speed and insufficient data display flexibility in existing data visualization systems can be solved. The complex production data of the production environment can be displayed on the big screen in an intuitive and interactive way, realizing multi-dimensional analysis and comprehensive display, giving full play to the value of the data, and making it easier for relevant users (or managers) in front of the big screen to monitor the production environment in real time and make timely decision analysis.

[0038] Furthermore, by integrating modules for data acquisition, processing, analysis, and visualization, this application system achieves seamless connection from data source to end user, enabling real-time data acquisition, processing, binding, and display. This effectively improves system response speed and user experience, ensuring that users can obtain the latest production status information and make timely and accurate decisions by opening large-screen pages in seconds, thus greatly improving work efficiency.

[0039] Furthermore, it should be understood that, in practical situations, in addition to the three major system components mentioned above, the large-screen visualization system for industrial production equipment and intelligent manufacturing environments provided in this application may also include other system components, such as a power supply layer. These may involve structures necessary for maintaining normal system operation or structures related to additional system function services. Considering that these are not the focus of this application, this application will not elaborate on these other system components in detail here.

[0040] In short, regarding the above Figure 1In accordance with the corresponding embodiments, this application provides a large-screen visualization system for industrial production equipment and intelligent manufacturing environments. It offers a specific system architecture design scheme and introduces the application of a 3D visualization engine. The system is lightweight in terms of deployment and convenient and efficient in application, thus meeting the high-quality data visualization needs of industrial production environments.

[0041] Next, we will further introduce the specific solutions that can be adopted in practical applications of the large-screen visualization system for industrial production equipment and intelligent manufacturing environment provided in this application.

[0042] For the data source layer, as an exemplary embodiment, the various sensors involved may specifically include different types of sensors such as temperature sensors, pressure sensors, and flow sensors. Of course, the specific sensor types and their quantities can be adjusted according to the actual situation. The focus here is on listing some more practical sensors.

[0043] In addition, the data source layer can transmit initial industrial data to the data processing layer based on the pre-established industrial IoT through communication protocols such as MQTT, OPCUA, or SSL / TLS.

[0044] Among them, Message Queuing Telemetry Transport (MQTT) is a machine-to-machine (M2M) / Internet of Things (IoT) connectivity protocol. It is designed as an extremely lightweight publish / subscribe message transmission protocol, which is very useful for remote connections where small code footprint and / or network bandwidth are very precious. It is designed for constrained devices and low-bandwidth, high-latency or unreliable networks, and is well-suited for the lightweight use case of this application, providing data transmission, monitoring and control services.

[0045] The Open Platform Communications Unified Architecture (OPC UA) is a communication protocol used to realize data exchange and communication between devices in industrial automation systems. It provides a standardized, secure, and scalable communication mechanism that enables seamless data exchange and communication between different devices. It is also well-suited to the application scenario of this application, providing services for data transmission, monitoring, and control.

[0046] Secure Socket Layer / Transport Layer Security (SSL / TLS) is a protocol that provides secure communication, ensuring the confidentiality and integrity of data transmitted between two devices and verifying identity. In terms of security in this application system, it supports encrypted data transmission and access control mechanisms between the data source layer and the data processing layer, ensuring data security, preventing data interception or tampering during transmission, and authenticating users and assigning permissions to ensure system security and data confidentiality, ensuring that only authorized users can access sensitive data.

[0047] Of course, in practical applications, other types of communication protocols may also be involved, which can be adapted to meet actual needs.

[0048] Furthermore, continuing to focus on the 3D visualization layer, as an exemplary embodiment, the 3D visualization model constructed by the 3D visualization layer can have:

[0049] 1. Predefined mapping relationships between different types of industrial data sources and different visualization components, including text boxes, charts, and graphs;

[0050] It is understandable that defining a clear mapping relationship between data sources and visualization components (which may involve data types, data ranges, display formats, etc.) and establishing corresponding data mapping tables or rules will enable a one-to-one correspondence between data fields in the data processing layer and visualization components / elements (such as text boxes, charts, graphics, etc.) in the 3D visualization model during real-time applications, promoting efficient and convenient data update.

[0051] For example, data from a sensor can be bound to a specific dashboard component.

[0052] Thus, regarding the real-time performance of this application system, it can be seen from the settings here that this application helps ensure the accuracy and timeliness of data through real-time data binding and dynamic updates, and can process data streams from multiple data sources simultaneously, maintaining the real-time performance of data display even in cases of massive data volumes.

[0053] Furthermore, it can be seen here that in terms of the scalability of the system in this application, the system adopts a modular design (not only involving the visualization components here, but also the communication between other system components and between different modules belonging to the same system component). The functional modules can communicate with each other through standardized API interfaces. In practical applications, this approach is easy to expand and maintain, allowing the system to flexibly add, remove, update or maintain the corresponding functional modules according to needs.

[0054] 2. A caching mechanism is introduced during the data mapping process;

[0055] It is understandable that setting up a caching mechanism helps avoid frequent data requests, optimize performance, and at the same time optimize the data binding and rendering process, ensuring smooth operation under high data volume and complex scenarios.

[0056] 3. Use an event-driven or polling mechanism to update data;

[0057] It is understandable that an event-driven or polling mechanism can be used, along with a corresponding scripting language (such as C#), to implement dynamic data update logic, ensuring that changes in the data source layer are reflected in the 3D visualization model in real time and that its visualization components are updated immediately.

[0058] 4. Set up exception handling logic.

[0059] It is understandable that setting up or implementing exception handling logic / rules / strategies in a 3D visualization model helps ensure that the system can still operate stably in the event of network latency or data loss.

[0060] Furthermore, as an exemplary embodiment, the visualization interface of the 3D visualization model can be set up using diverse data visualization interfaces such as dashboards, line charts, bar charts, and heat maps to display corresponding numerical data, image data, or video data.

[0061] In practice, the display of one or more visualization interfaces is based on the graphics rendering capabilities of the 3D visualization engine, combined with the corresponding user interface (UI) design. The data input or data variables involved in these visualization interfaces can be numerical data, image data, or video data, etc., and can also be represented in the visualization interface in the form of numerical data, image data, or video data.

[0062] Thus, in terms of the flexibility of this application system, users can customize data views according to their needs. It not only supports common numerical data, but also processes various types of data such as images and videos, providing rich data display methods, which helps to improve the ease of use of the system and the user experience.

[0063] Furthermore, as an exemplary embodiment, the visualization interface of the 3D visualization model can be specifically configured with interactive functions / capabilities. Through screen touch operation (meaning the device itself has a touch screen) or operation commands entered by input device (other devices such as touch screen, mouse, keyboard, or voice, etc.), operations such as viewing, filtering, or zooming can be performed on the visualization components in the visualization interface to meet the business needs of switching views and viewing data of different dimensions.

[0064] Under this configuration, this application has designed a user-friendly interactive interface for the 3D visualization layer or 3D visualization model. In practical applications, users can obtain the required visualization information by viewing, filtering, or zooming. The 3D visualization model can capture user input through its corresponding input management system and update the data display in real time based on the captured user operations.

[0065] In addition, refer to Figure 2 and Figure 3 The schematic diagrams shown below illustrate examples of the large-screen visualization system for industrial production equipment and intelligent manufacturing environments, respectively, which specifically reveal a specific manufacturing environment in which the solution of this application is applicable.

[0066] Specifically, as an exemplary embodiment, this application can be applied to the specific manufacturing environment of the steel plant's quality inspection center work area (corresponding to...). Figure 2 (As shown in the scenario), based on this, the visualization interface of the 3D visualization model can specifically include a virtual factory environment image area, a processing information area corresponding to different processing lines, a monthly statistics area corresponding to different operators, an alarm information area corresponding to different equipment alarms, a daily processing volume statistics area corresponding to a week, and a process statistics area corresponding to different process outputs. The different processes specifically involve tensile, bending, impact, hardness, metallographic, magnetic measurement, hole enlargement, drop hammer, fracture surface, and sample preparation.

[0067] Among them, from Figure 2 It can be seen that the working area of ​​the quality inspection center in the steel plant may involve industrial production equipment such as measuring table, feeding hopper line scanner, feeding robot, waste hopper, scanning and marking, sorting platform, sorting robot, transfer platform, sorting trolley, machining center, laser marking, material frame and tensile testing machine.

[0068] from Figure 3 As can be seen, with the user-friendly interface design, the virtual factory environment image area is located in the upper middle of the overall interface, the processing information area is located in the lower left of the overall interface, the monthly statistics area is located in the lower middle of the overall interface next to the processing information area, the alarm information area is located in the lower middle of the overall interface next to the monthly statistics area, the processing volume statistics area is located in the lower middle of the overall interface next to the alarm information area, which is located in the lower right of the overall interface, and the process statistics areas are located in the upper middle of the left side and the upper middle of the right side of the overall interface, respectively.

[0069] For a range of areas excluding the virtual factory environment image area, numerical variables are typically used (mainly output), and additional variables such as time can also be identified.

[0070] It is understood that the embodiment here is the visualization interface setting involved in the solution of this application, which focuses on the specific manufacturing environment of the steel plant quality inspection center operation area. It provides a specific user-friendly interface design scheme, which has good adaptability to the specific application scenario and takes into account both visualization display effect and visualization operation effect, thus having good practical significance.

[0071] Furthermore, as an exemplary embodiment, a large-screen visualization system for industrial production equipment and intelligent manufacturing environments can specifically employ a cross-platform application framework to build the relevant applications.

[0072] It is understood that, in terms of cross-platform support, the system can specifically support multiple operating system platforms such as Windows, Linux, macOS, and mobile devices (smartphones, tablets, laptops, personal digital assistants (PDAs), etc.), and is also compatible with various industrial equipment, providing a unified development and deployment environment.

[0073] The cross-platform application framework adopted can specifically be a cross-platform application development framework such as Electron or Flutter, which allows developers of the system to use web technologies (such as HTML, CSS, JavaScript, etc.) or languages ​​such as Dart to build specific cross-platform applications. These frameworks can generate applications that run on Windows, macOS, Linux, and mobile devices, meeting the application requirements of data visualization solutions that support multiple platforms.

[0074] Furthermore, as an exemplary embodiment, the visualization interface of the 3D visualization engine of this application is specifically configured based on Unity, Unreal Engine, or CryEngine products, combined with Tableau, Power BI, QlikView, ECharts, Highcharts, or D3.js products.

[0075] 3D visualization engines such as Unity, Unreal Engine, and CryEngine possess high-performance rendering capabilities, rich component libraries, and flexible interactive design functions, thus meeting the complex data visualization needs of this application.

[0076] Business intelligence tools such as Tableau, Power BI, and QlikView offer powerful data visualization capabilities, supporting custom dashboards, interactive charts, and real-time data updates. These tools feature easy-to-use interfaces and rich component libraries, enabling the rapid construction of complex data visualization projects.

[0077] Open-source JavaScript libraries such as ECharts, Highcharts, and D3.js can create rich data visualizations on web pages. These libraries offer flexible APIs and a large number of chart types, making them suitable for building web service-based visualization solutions.

[0078] Furthermore, in specific software development work, Java (with Swing, JavaFX, etc.), C# (with WPF, WinForms, etc.) or other programming languages ​​and frameworks that support graphical interface development can be used to build visual interfaces or visual systems, which have higher customizability and flexibility.

[0079] In addition, for the 3D visualization layer, or 3D visualization model / system, cloud services such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform can be used to build and deploy specific application services. These cloud services provide rich data storage, computing, and analysis resources, as well as easy-to-integrate visualization tools and API interfaces.

[0080] In addition, you can choose to use Software as a Service (SaaS) solutions, such as online data analytics platforms like Looker and Mode Analytics. These services offer comprehensive data visualization capabilities and support multiple data sources and custom dashboards.

[0081] Furthermore, as an exemplary embodiment, the 3D visualization layer belongs to the front end and the data processing layer belongs to the back end. In this regard, this application can also design a scheme that separates data processing and visualization, specifically using Python (Pandas, NumPy, etc.), R language or other data analysis tools for back end data processing and cleaning. The processed data can be sent to the front end visualization system through API interface, database query or file transfer.

[0082] Furthermore, in terms of real-time data stream processing, message queue systems such as Apache Kafka and RabbitMQ can be used, or real-time data processing frameworks such as Apache Flink or Spark Streaming can be used to process real-time data streams. These real-time data stream mechanisms can handle high-concurrency data streams and push the processing results to the front-end visualization system in real time for visualization processing.

[0083] Furthermore, in practice, the above-mentioned solutions can be combined to form a hybrid solution based on actual needs. For example, Unity can be used as the main visualization engine, while WebGL technology can be combined to realize the web-side display; or native development technology can be used to process core data, and the Unity engine can be used for front-end display, etc.

[0084] The above is an introduction to the large-screen visualization system for industrial production equipment and intelligent manufacturing environments provided in this application. Correspondingly, this application also provides a processing method for the large-screen visualization system for industrial production equipment and intelligent manufacturing environments. This large-screen visualization system for industrial production equipment and intelligent manufacturing environments is applied to a large-screen visualization system for industrial production equipment and intelligent manufacturing environments. The large-screen visualization system for industrial production equipment and intelligent manufacturing environments includes a data source layer, a data processing layer, and a 3D visualization layer. The data source layer includes various industrial production equipment deployed on-site in the manufacturing environment, various sensors deployed on various industrial production equipment, and databases. The data processing layer includes a data receiving module, a data cleaning module, and a data conversion module. The 3D visualization layer includes a 3D visualization engine. Based on this, the processing method for the large-screen visualization system for industrial production equipment and intelligent manufacturing environments includes the following steps:

[0085] 1) The data source layer collects and records initial industrial data in real time, and transmits the initial industrial data to the data processing layer;

[0086] 2) The data processing layer cleans, transforms, and preprocesses the received initial industrial data, and transmits the processed target industrial data to the 3D visualization layer;

[0087] 3) The 3D visualization layer loads the received target industrial data into a 3D visualization model obtained from a digital twin model created from a physical factory, displays it on a large screen, and conducts comprehensive monitoring and analysis in conjunction with preset key indicators.

[0088] As an exemplary embodiment, various sensors include temperature sensors, pressure sensors, and flow sensors;

[0089] Specifically, the data source layer, based on the pre-established industrial IoT, transmits initial industrial data to the data processing layer via MQTT, OPC UA, or SSL / TLS protocols.

[0090] As yet another exemplary embodiment, for a 3D visualization model, we have:

[0091] There is a predefined mapping relationship between different types of industrial data sources and different visualization components, including text boxes, charts and graphs;

[0092] A caching mechanism is introduced during the data mapping process;

[0093] Data updates can be performed using either an event-driven or polling mechanism.

[0094] Configure exception handling logic.

[0095] As another exemplary embodiment, the visualization interface of the 3D visualization model is specifically set through dashboards, line charts, bar charts, and heatmaps to display corresponding numerical data, image data, or video data.

[0096] As another exemplary embodiment, the visualization interface of the 3D visualization model is configured with interactive functions. Through screen touch operation or operation commands entered by input device, viewing, filtering or zooming operations can be performed on the visualization components in the visualization interface to meet the business needs of switching views and viewing data of different dimensions.

[0097] As another exemplary embodiment, for the specific manufacturing environment of the steel plant quality inspection center operation area, the visualization interface of the three-dimensional visualization model includes a virtual factory environment image area, a processing information area corresponding to different processing lines, a monthly statistics area corresponding to different operators, an alarm information area corresponding to different equipment alarms, a daily processing volume statistics area corresponding to a week, and a process statistics area corresponding to different process outputs. The different processes specifically involve tensile, bending, impact, hardness, metallographic, magnetic measurement, hole enlargement, drop hammer, fracture surface, and sample preparation.

[0098] As another exemplary embodiment, the visualization interface of the 3D visualization engine is specifically configured based on Unity, Unreal Engine, or CryEngine products, combined with Tableau, Power BI, QlikView, ECharts, Highcharts, or D3.js products.

[0099] As another exemplary embodiment, the large-screen visualization system for industrial production equipment and intelligent manufacturing environments specifically adopts a cross-platform application framework to build the relevant applications.

[0100] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the processing method for large-screen visualization systems for industrial production equipment and intelligent manufacturing environments described above can be found in, for example... Figure 1 The description of the large-screen visualization system for industrial production equipment and intelligent manufacturing environment in the corresponding embodiments will not be repeated here.

[0101] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by instructions, or by instructions controlling related hardware. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0102] To this end, this application provides a computer-readable storage medium storing a plurality of instructions that can be loaded by a processor to execute the steps of the processing method of the large-screen visualization system for industrial production equipment and intelligent manufacturing environment of this application. For specific operations, please refer to the description of the processing method of the large-screen visualization system for industrial production equipment and intelligent manufacturing environment, which will not be repeated here.

[0103] The computer-readable storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0104] Since the instructions stored in the computer-readable storage medium can execute the steps of the processing method of the large-screen visualization system for industrial production equipment and intelligent manufacturing environment of this application, the beneficial effects that the processing method of the large-screen visualization system for industrial production equipment and intelligent manufacturing environment of this application can achieve can be realized, as detailed in the preceding description, and will not be repeated here.

[0105] The above provides a detailed description of the large-screen visualization system for industrial production equipment and intelligent manufacturing environment, the processing method of the large-screen visualization system for industrial production equipment and intelligent manufacturing environment, and the computer-readable storage medium provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A large screen visualization system for industrial production equipment and smart manufacturing environments, characterized in that, The large-screen visualization system for industrial production equipment and intelligent manufacturing environment includes a data source layer, a data processing layer, and a 3D visualization layer. The data source layer includes various industrial production equipment deployed on-site in the manufacturing environment, various sensors and databases deployed on the various industrial production equipment, which are used to collect and record initial industrial data in real time and transmit the initial industrial data to the data processing layer. The data processing layer includes a data receiving module, a data cleaning module, and a data conversion module, which are used to clean, convert, and preprocess the received initial industrial data, and transmit the processed target industrial data to the three-dimensional visualization layer. The three-dimensional visualization layer includes a three-dimensional visualization engine, which loads the received target industrial data into a three-dimensional visualization model obtained from a digital twin model created by a physical factory, displays it on a large screen, and performs comprehensive monitoring and analysis in conjunction with preset key indicators. For the aforementioned 3D visualization model: There is a predefined mapping relationship between different types of industrial data sources and standardized API interfaces of different visualization components, including text boxes, charts and graphs; A caching mechanism is introduced during the data mapping process; Data updates can be performed using either an event-driven or polling mechanism. Configure exception handling logic; The visualization interface of the three-dimensional visualization model is specifically set through dashboards, line charts, bar charts, and heat maps to display corresponding numerical data, image data, or video data; For the specific manufacturing environment of the steel plant quality inspection center operation area, the various industrial production equipment includes measuring table, feeding hopper line scanner, feeding robot, waste hopper, scanning and marking, sorting platform, sorting robot, transfer platform, sorting trolley, machining center, laser marking, material frame and tensile testing machine; The visualization interface of the three-dimensional visualization model includes a virtual factory environment image area, a processing information area corresponding to different processing lines, a monthly statistics area corresponding to different operators, an alarm information area corresponding to different equipment alarms, a daily processing volume statistics area corresponding to a week, and a process statistics area corresponding to different process outputs. The different processes include tensile, bending, impact, hardness, metallographic, magnetic measurement, hole enlargement, drop hammer, fracture surface, and sample preparation.

2. The large screen visualization system for industrial production equipment and smart manufacturing environment of claim 1, wherein, The various sensors include temperature sensors, pressure sensors, and flow sensors; Specifically, the data source layer transmits the initial industrial data to the data processing layer via MQTT, OPC UA, or SSL / TLS protocols, based on a pre-established industrial Internet of Things (IoT) network.

3. The large screen visualization system for industrial production equipment and smart manufacturing environment of claim 1, wherein, The visualization interface of the 3D visualization model is equipped with interactive functions. Users can perform viewing, filtering, or zooming operations on the visualization components in the visualization interface through screen touch operations or operation commands entered by input devices, so as to meet the business needs of switching views and viewing data of different dimensions.

4. The large-screen visualization system for industrial production equipment and intelligent manufacturing environments according to claim 1, characterized in that, The visualization interface of the 3D visualization engine is specifically configured based on Unity, Unreal Engine, or CryEngine products, combined with Tableau, Power BI, QlikView, ECharts, Highcharts, or D3.js products.

5. The large-screen visualization system for industrial production equipment and intelligent manufacturing environments according to claim 1, characterized in that, The large-screen visualization system for industrial production equipment and intelligent manufacturing environments specifically adopts a cross-platform application framework to build the applications involved.

6. A processing method for a large-screen visualization system for industrial production equipment and intelligent manufacturing environments, characterized in that, The large-screen visualization system for industrial production equipment and intelligent manufacturing environments includes a data source layer, a data processing layer, and a 3D visualization layer. The data source layer includes various industrial production equipment deployed on-site in the manufacturing environment, various sensors deployed on these equipment, and a database. The data processing layer includes a data receiving module, a data cleaning module, and a data conversion module. The 3D visualization layer includes a 3D visualization engine. The processing method of the large-screen visualization system for industrial production equipment and intelligent manufacturing environments includes: The data source layer collects and records initial industrial data in real time, and transmits the initial industrial data to the data processing layer; The data processing layer cleans, transforms, and preprocesses the received initial industrial data, and transmits the processed target industrial data to the three-dimensional visualization layer. The three-dimensional visualization layer loads the received target industrial data into a three-dimensional visualization model obtained from a digital twin model created from a physical factory, displays it on a large screen, and performs comprehensive monitoring and analysis in conjunction with preset key indicators. For the aforementioned 3D visualization model: There is a predefined mapping relationship between different types of industrial data sources and standardized API interfaces of different visualization components, including text boxes, charts and graphs; A caching mechanism is introduced during the data mapping process; Data updates can be performed using either an event-driven or polling mechanism. Configure exception handling logic; The visualization interface of the three-dimensional visualization model is specifically set through dashboards, line charts, bar charts, and heat maps to display corresponding numerical data, image data, or video data; For the specific manufacturing environment of the steel plant quality inspection center operation area, the various industrial production equipment includes measuring table, feeding hopper line scanner, feeding robot, waste hopper, scanning and marking, sorting platform, sorting robot, transfer platform, sorting trolley, machining center, laser marking, material frame and tensile testing machine; The visualization interface of the three-dimensional visualization model includes a virtual factory environment image area, a processing information area corresponding to different processing lines, a monthly statistics area corresponding to different operators, an alarm information area corresponding to different equipment alarms, a daily processing volume statistics area corresponding to a week, and a process statistics area corresponding to different process outputs. The different processes include tensile, bending, impact, hardness, metallographic, magnetic measurement, hole enlargement, drop hammer, fracture surface, and sample preparation.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a plurality of instructions adapted for loading by a processor to perform the method of claim 6.

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