Digital twinning system suitable for aircraft engine product production line and design method of digital twinning system
By designing a digital twin system suitable for aeroengine product production lines, the problem of insufficient intelligence level of aeroengine machining automation production lines is solved, real-time monitoring and optimization of the production lines are achieved, and production efficiency and intelligence level are improved.
Patent Information
- Application Number
- CN202411671533.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-21
- Publication Date
- 2025-02-28
AI Technical Summary
The automated production lines of aircraft engine mechanical processing parts are insufficient in terms of production environment monitoring, data analysis and production decision optimization.
A digital twin system was designed, including production equipment layer, network perception layer, twin data layer, twin model layer and twin application layer. Through real-time monitoring of data acquisition, data storage, environment and logic model construction, as well as production process monitoring, simulation and performance display of the application layer, all-round monitoring and optimization of the production line is achieved.
It realizes all-round and real-time monitoring of the parts production process, improves the intelligence level of the production line, and improves the production efficiency through data-driven production line operation, reduces operating costs, and ensures the stable operation of the production line.
Smart Images
Figure CN119536160A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of digital factories and relates to a digital twin system suitable for an aero-engine product production line and a design method thereof. Background Art
[0002] Aircraft engine machining parts are produced in a discrete production mode with multiple varieties and small batches. The automated production line can solve the problems of scattered processes and difficult to control production rhythm in the traditional human-based production mode. However, there is still room for improvement in production environment monitoring, production data analysis, production decision-making, and optimization of the production line. The intelligence level of the automated production line for aircraft engine machining parts needs to be further improved. Summary of the invention
[0003] In view of the need to further improve the intelligence level of the automated production line for aero-engine mechanical processing parts, the present invention provides a digital twin system and a design method suitable for an aero-engine product production line.
[0004] The present invention provides a digital twin system suitable for an aeroengine product production line, comprising: a production equipment layer, a network perception layer, a twin data layer, a twin model layer and a twin application layer;
[0005] The production equipment layer includes a variety of aircraft engine product production line equipment, which is the source of real-time monitoring data collection of the production line;
[0006] The network perception layer includes industrial control network sensors and a campus network system. The industrial control network sensors are used to collect real-time monitoring data of the production equipment layer;
[0007] The twin data layer is used to store real-time monitoring data collected by industrial control network sensors and production operation data and equipment maintenance data in the campus network system;
[0008] The twin model layer builds a twin environment, a business logic model, and an analysis model based on real-time monitoring data, production operation data, and equipment maintenance data;
[0009] The twin application layer performs production process monitoring, production process simulation and production line performance display based on the twin environment, business logic model and analysis results constructed by the twin model layer.
[0010] The present invention also provides a design method for a digital twin system applicable to an aeroengine product production line, comprising:
[0011] Step 1: Twin data acquisition: Use industrial control network sensors to collect data on the equipment and resources of the aviation engine product production line to obtain real-time monitoring data, and obtain the production operation data and equipment maintenance data of the campus network system through the interface protocol;
[0012] Step 2, Twin data transmission: Real-time monitoring data, production operation data and equipment maintenance data are transmitted to the twin data layer through the interface protocol to realize data interaction between the industrial control network, campus network system and the twin system, and ensure real-time synchronization of physical production line data and twin production line data;
[0013] Step 3: Twin data storage: Store real-time monitoring data, production operation data, and equipment maintenance data in the database of the twin data layer to facilitate subsequent modeling and simulation analysis;
[0014] Step 4: Twin environment construction: 3D modeling and rendering of the equipment on the production line of aero-engine products, setting the geometric properties, physical properties, behavioral properties and communication interface of the equipment, and completing the construction of the twin environment;
[0015] Step 5: Business logic modeling: Analyze the parts production process of the aero-engine product production line, make process layout for the equipment and resources in the twin production line, analyze the material flow and operation process to create a logical model of the twin production line;
[0016] Step 6: Twin data modeling: Based on the collected production line twin data, a statistical method is used to build an analysis model of the twin production line;
[0017] Step 7. Twin data application: Based on the twin environment, synchronize the physical production line equipment status, logistics status, and detection status online in the digital twin system to realize production process monitoring; realize production process simulation based on the business logic model; and realize production performance indicator display based on the analysis model.
[0018] The digital twin system and design method thereof applicable to an aeroengine product production line of the present invention have the following beneficial effects:
[0019] (1) Based on the digital twin system, the production process of parts can be monitored in real time from all angles in the twin scene, accurately and intuitively understanding the overall operation of the production line and achieving effective control of the parts production process.
[0020] (2) The digital twin system can realize the operation of data-driven twin production lines, map the production and processing process of the physical production line, and visualize the production information, warehousing status, product qualification rate, equipment utilization rate, production efficiency and key data of equipment.
[0021] (3) Based on the digital twin system, the production processes of parts clamping, processing, grinding and polishing, cleaning, measurement, marking, etc. can be simulated. The production capacity, production energy consumption, production rhythm and production bottleneck of the production line can be analyzed. The rationality of the production material distribution strategy and production plan can be verified, thereby improving the production efficiency of the production line and reducing the operating costs of the production line.
[0022] (4) Based on the digital twin system, the virtual and real synchronization of the twin production line and the physical production line can be achieved, and the production line can be fully monitored, fault detected and risk assessed. By storing, modeling and analyzing the data collected from the physical production line, the production line production data can be better mined, the stable operation of the production line can be guaranteed, and the intelligent level of the production line can be improved. BRIEF DESCRIPTION OF THE DRAWINGS
[0023] Figure 1 It is a structural block diagram of a digital twin system applicable to an aero-engine product production line of the present invention;
[0024] Figure 2 It is a design flow chart of a digital twin system suitable for an aero-engine product production line according to the present invention. DETAILED DESCRIPTION
[0025] like Figure 1 As shown, a digital twin system suitable for an aero-engine product production line of the present invention includes: a production equipment layer, a network perception layer, a twin data layer, a twin model layer and a twin application layer.
[0026] The production equipment layer includes a variety of aircraft engine product production line equipment and is the source of real-time monitoring data collection for the production line.
[0027] In specific implementation, the production equipment layer includes a machining center, a cleaning machine, a grinding and polishing robot, a loading and unloading station, a Samsung measuring machine, an AGV trolley, a marking machine and a tool pre-adjusting device, etc.
[0028] The network perception layer includes industrial control network sensors and a campus network system. The industrial control network sensors are used to collect real-time monitoring data of the production equipment layer.
[0029] In specific implementation, the industrial control network sensors include: PLC, force torque sensor, pressure sensor, temperature sensor, optical sensor and photoelectric sensor, etc. The campus network system includes: ERP system, MES system, PDM system, CAPP system, QMS system, WMS system, etc.
[0030] The twin data layer is used to store real-time monitoring data collected by industrial control network sensors and production operation data and equipment maintenance data in the campus network system.
[0031] During specific implementation, real-time monitoring data includes: personnel status, equipment status, material status, parts status, processing environment and quality inspection.
[0032] Personnel status includes waiting status, moving status, and fatigue status. Equipment status includes startup, shutdown, and operation. Material status includes raw materials, semi-finished products, and finished products. Part status includes pending processing, in processing, completed, and reworked. Quality inspection includes pending inspection, unqualified, and qualified. Processing environment includes temperature, vibration, and torque.
[0033] Production operation data includes: production plan, process data, quality data, logistics data, operation documents and inventory data.
[0034] Equipment maintenance data includes: maintenance plan, operation log, equipment abnormality, fault handling, fault tree and case library.
[0035] The twin model layer builds a twin environment, business logic model and analysis model based on real-time monitoring data, production operation data and equipment maintenance data.
[0036] Building a twin environment specifically involves: building a three-dimensional resource model and a twin scene model, setting geometric properties, physical properties and communication interfaces, performing human-computer interaction design, and then realizing real-time data interaction between physical production line and virtual production line equipment.
[0037] The business logic model includes: operation logic model, production planning model, process flow model, material management model, logistics logic model and quality management model; by building a business logic model, the execution logic of virtual production line logistics, production planning and process flow is realized.
[0038] The analysis models include: production cycle model, capacity model, energy consumption model, utilization model, overall efficiency model and production balance model; the analysis of performance evaluation indicators is achieved by constructing the analysis model.
[0039] The twin application layer performs production process monitoring, production process simulation and production line performance display based on the twin environment, business logic model and analysis results constructed by the twin model layer.
[0040] In specific implementation, production process monitoring includes ambient temperature monitoring, spindle speed monitoring, spindle torque monitoring, finishing vibration monitoring, workpiece size monitoring and material position monitoring.
[0041] Production process simulation includes: production cycle simulation, capacity simulation, production logistics simulation, energy consumption simulation, process flow simulation and utilization rate simulation.
[0042] Production line performance: production rhythm, production capacity, production balance, equipment energy consumption, equipment overall efficiency and equipment utilization.
[0043] like Figure 2 As shown, the present invention also provides a design method for a digital twin system applicable to an aeroengine product production line, comprising:
[0044] Step 1: Twin data acquisition: Use industrial control network sensors to collect data on the equipment and resources of the aero-engine product production line to obtain real-time monitoring data, and obtain the production operation data and equipment maintenance data of the campus network system through the interface protocol.
[0045] The real-time monitoring data includes: personnel status, equipment status, material status, parts status, processing environment and quality inspection. The production operation data includes: production plan, process data, quality data, logistics data, operation files and inventory data; the equipment maintenance data includes: maintenance plan, operation log, equipment anomaly, fault handling, fault tree and case library.
[0046] Step 2, Twin data transmission: Real-time monitoring data, production operation data and equipment maintenance data are transmitted to the twin data layer through the interface protocol to realize data interaction between the industrial control network, campus network system and the twin system, and ensure real-time synchronization of physical production line data and twin production line data.
[0047] The interface protocols include: OPC UA, PROFIBUS, RS-232, RS-485, XML, JSON, etc.
[0048] Step 3: Twin data storage: Store real-time monitoring data, production operation data, and equipment maintenance data in the database of the twin data layer to facilitate subsequent modeling and simulation analysis.
[0049] Step 4: Twin environment construction: 3D modeling and rendering of the production line equipment of aero-engine products, setting the geometric properties, physical properties, behavioral properties and communication interface of the equipment to complete the construction of the twin environment.
[0050] Step 5: Business logic modeling: Analyze the parts production process of the aero-engine product production line, make process layout for the equipment and resources in the twin production line, analyze the material flow and operation process to create a logical model of the twin production line.
[0051] The business logic model includes: an operation logic model, a production plan model, a process flow model, a material management model, a logistics logic model and a quality management model.
[0052] Step 6: Twin data modeling: Based on the collected production line twin data, use statistical methods to build an analysis model of the twin production line.
[0053] The analysis model includes: a production cycle model, a production capacity model, an energy consumption model, a utilization model, an overall efficiency model and a production balance model; and the analysis of performance evaluation indicators is achieved by constructing the analysis model.
[0054] Step 7. Twin data application: Based on the twin environment, synchronize the physical production line equipment status, logistics status, and detection status online in the digital twin system to realize production process monitoring; realize production process simulation based on the business logic model; and realize production performance indicator display based on the analysis model.
[0055] Production process monitoring includes ambient temperature monitoring, spindle speed monitoring, spindle torque monitoring, finishing vibration monitoring, workpiece size monitoring and material position monitoring.
[0056] Production process simulation includes: production cycle simulation, capacity simulation, production logistics simulation, energy consumption simulation, process flow simulation and utilization rate simulation.
[0057] Production line performance: production rhythm, production capacity, production balance, equipment energy consumption, equipment overall efficiency and equipment utilization.
[0058] The digital twin system suitable for an aero-engine product production line according to the present invention can realize real-time online monitoring, simulation, prediction and optimization, and improve the intelligence level of the aero-engine mechanical processing automation production line.
[0059] The above description is only a preferred embodiment of the present invention and is not intended to limit the concept of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims
1. A digital twin system suitable for an aircraft engine product production line, characterized in that: include: Production equipment layer, network perception layer, twin data layer, twin model layer and twin application layer; The production equipment layer includes a variety of aircraft engine product production line equipment, which is the source of real-time monitoring data collection of the production line; The network perception layer includes industrial control network sensors and a campus network system. The industrial control network sensors are used to collect real-time monitoring data of the production equipment layer; The twin data layer is used to store real-time monitoring data collected by industrial control network sensors and production operation data and equipment maintenance data in the campus network system; The twin model layer builds a twin environment, a business logic model, and an analysis model based on real-time monitoring data, production operation data, and equipment maintenance data; The twin application layer performs production process monitoring, production process simulation and production line performance display based on the twin environment, business logic model and analysis results constructed by the twin model layer.
2. The digital twin system applicable to an aeroengine product production line as claimed in claim 1, characterized in that: The industrial control network sensors include: PLC, force torque sensor, pressure sensor, temperature sensor, optical sensor and photoelectric sensor.
3. The digital twin system applicable to an aeroengine product production line as claimed in claim 1, characterized in that: The real-time monitoring data includes: personnel status, equipment status, material status, parts status, processing environment and quality inspection; The production operation data includes: production plan, process data, quality data, logistics data, operation documents and inventory data; The equipment maintenance data includes: maintenance plan, operation log, equipment abnormality, fault handling, fault tree and case library.
4. The digital twin system applicable to an aeroengine product production line according to claim 1, characterized in that: Constructing a twin environment specifically involves: constructing a three-dimensional resource model and a twin scene model, setting geometric properties, physical properties, and communication interfaces, and performing human-computer interaction design, thereby realizing real-time data interaction between physical production line and virtual production line equipment; The business logic model includes: operation logic model, production plan model, process flow model, material management model, logistics logic model and quality management model; by building the business logic model, the execution logic of virtual production line logistics, production plan and process flow is realized; The analysis models include: production cycle model, capacity model, energy consumption model, utilization model, overall efficiency model and production balance model; the analysis of performance evaluation indicators is achieved by constructing the analysis model.
5. The digital twin system applicable to an aeroengine product production line according to claim 1, characterized in that: The production process monitoring in step 6 includes ambient temperature monitoring, spindle speed monitoring, spindle torque monitoring, finishing vibration monitoring, workpiece size monitoring and material position monitoring; Production process simulation includes: production cycle simulation, capacity simulation, production logistics simulation, energy consumption simulation, process flow simulation and utilization rate simulation; Production line performance: production rhythm, production capacity, production balance, equipment energy consumption, equipment overall efficiency and equipment utilization.
6. A design method for a digital twin system suitable for an aeroengine product production line, characterized in that: include: Step 1: Twin data acquisition: Use industrial control network sensors to collect data on the equipment and resources of the aviation engine product production line to obtain real-time monitoring data, and obtain the production operation data and equipment maintenance data of the campus network system through the interface protocol; Step 2, Twin data transmission: Real-time monitoring data, production operation data and equipment maintenance data are transmitted to the twin data layer through the interface protocol to realize data interaction between the industrial control network, campus network system and the twin system, and ensure real-time synchronization of physical production line data and twin production line data; Step 3: Twin data storage: Store real-time monitoring data, production operation data, and equipment maintenance data in the database of the twin data layer to facilitate subsequent modeling and simulation analysis; Step 4: Twin environment construction: 3D modeling and rendering of the equipment on the production line of aero-engine products, setting the geometric properties, physical properties, behavioral properties and communication interface of the equipment, and completing the construction of the twin environment; Step 5: Business logic modeling: Analyze the parts production process of the aero-engine product production line, make process layout for the equipment and resources in the twin production line, analyze the material flow and operation process to create a logical model of the twin production line; Step 6: Twin data modeling: Based on the collected production line twin data, a statistical method is used to build an analysis model of the twin production line; Step 7: Twin data application: Based on the twin environment, synchronize the equipment status, logistics status, and detection status of the physical production line online in the digital twin system to realize production process monitoring; realize production process simulation based on the business logic model; Production performance indicators are displayed based on the analysis model.
7. The design method of a digital twin system applicable to an aeroengine product production line according to claim 6, characterized in that: The real-time monitoring data includes: personnel status, equipment status, material status, parts status, processing environment and quality inspection; The production operation data includes: production plan, process data, quality data, logistics data, operation documents and inventory data; The equipment maintenance data includes: maintenance plan, operation log, equipment anomaly, fault handling, fault tree and case library.
8. The design method of a digital twin system applicable to an aeroengine product production line according to claim 6, characterized in that: The business logic model includes: an operation logic model, a production plan model, a process flow model, a material management model, a logistics logic model and a quality management model.
9. The design method of a digital twin system applicable to an aeroengine product production line according to claim 6, characterized in that: The analysis model includes: a production cycle model, a production capacity model, an energy consumption model, a utilization model, an overall efficiency model and a production balance model; and the analysis of performance evaluation indicators is achieved by constructing the analysis model.
10. The design method of a digital twin system applicable to an aeroengine product production line according to claim 6, characterized in that: Production process monitoring includes ambient temperature monitoring, spindle speed monitoring, spindle torque monitoring, finishing vibration monitoring, workpiece size monitoring and material position monitoring; Production process simulation includes: production cycle simulation, capacity simulation, production logistics simulation, energy consumption simulation, process flow simulation and utilization rate simulation; Production line performance: production rhythm, production capacity, production balance, equipment energy consumption, equipment overall efficiency and equipment utilization.