Valve machining and manufacturing method based on digital twinning

Abstract

The invention discloses a valve processing and manufacturing method based on digital twinning, which comprises the following steps: S1, constructing a valve digital twinning model, creating a valve geometric model by using three-dimensional modeling software, and endowing the valve geometric model with physical attributes and material characteristics through finite element analysis software, carrying out design optimization through fluid mechanics simulation and stress analysis; s2, establishing a processing technology digital twin model, performing digital modeling on the device, integrating processing technology parameters, and simulating a material processing process; s3, the machining process is monitored in real time, multiple types of sensors are deployed on machining equipment, and operation data of the machining equipment are collected in real time; s4, dynamic simulation and comparative analysis are conducted, specifically, the digital twin model dynamically simulates the actual machining process according to real-time collected data, and a simulation result and design requirements are compared and analyzed; and S5, feedback control optimization: when the processing deviation exceeds a preset threshold value, automatically generating a process parameter adjustment scheme and feeding back the process parameter adjustment scheme to a processing equipment control system.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent manufacturing technology, and specifically relates to a valve processing and manufacturing method based on digital twins. Background Art

[0002] Valves, as key components of fluid control systems, are widely used in various industrial fields such as petrochemicals, electric power, metallurgy, and water treatment. With the rapid development of Industry 4.0 and intelligent manufacturing, traditional valve manufacturing processes are facing many challenges and technical bottlenecks.

[0003] Traditional valve manufacturing suffers from several significant issues. During the design phase, engineers rely primarily on experience and two-dimensional drawings, making it difficult to comprehensively and intuitively assess the rationality and manufacturability of design solutions. This makes it difficult to make design changes, resulting in high costs and low efficiency. During the manufacturing process, the lack of real-time monitoring of equipment status and process parameters makes it difficult to effectively ensure machining accuracy and product quality. Once quality issues arise, they are difficult to trace and locate, impacting production efficiency and product reliability. During assembly, the compatibility of components and the rationality of assembly processes are difficult to predict and verify in advance, leading to rework and extended production cycles. While existing manufacturing execution systems can achieve a certain level of production process management, they lack the deep integration of virtual and real-world capabilities and are unable to provide predictive manufacturing capabilities across the entire process. Quality management systems often only perform post-process testing and analysis, lacking real-time quality warnings and proactive control mechanisms. Process optimization relies primarily on manual experience, lacking scientific data support and intelligent decision-making.

[0004] The development and maturity of digital twin technology has provided new insights and approaches to addressing these technical challenges. By constructing precise digital models of physical entities, digital twin technology enables real-time synchronization and deep integration of the virtual and physical worlds, providing a foundation for comprehensive perception, precise prediction, and intelligent control of the manufacturing process. However, existing digital twin applications primarily focus on single areas such as product design and equipment monitoring, lacking a systematic solution encompassing the entire manufacturing process.

[0005] Therefore, the present invention provides a valve processing and manufacturing method based on digital twin to solve the problems raised by the above background technology. Summary of the Invention

[0006] In response to the problems raised by the above background technology, the purpose of the present invention is to provide a valve processing and manufacturing method based on digital twins. By constructing a digital twin model covering the entire life cycle of the valve, intelligent collaboration of design, processing, testing, assembly and other links can be achieved, thereby significantly improving the accuracy, quality and efficiency of valve manufacturing and reducing production costs and risks.

[0007] In order to achieve the above technical objectives, the technical solutions adopted by the present invention are as follows:

[0008] A valve manufacturing method based on digital twins includes the following steps:

[0009] S1: Build a digital twin model of the valve. Use 3D modeling software to create a valve geometry model. Use finite element analysis software to assign physical properties and material characteristics to the valve geometry model. Perform design optimization through fluid mechanics simulation and stress analysis.

[0010] S2: Establish a digital twin model of the processing technology, digitally model the device, integrate processing parameters, and simulate the material processing process;

[0011] S3: Real-time monitoring of the processing process, deploying multiple types of sensors on the processing equipment to collect real-time processing equipment operation data;

[0012] S4: Dynamic simulation and comparative analysis: the digital twin model dynamically simulates the actual machining process based on real-time collected data, and compares and analyzes the simulation results with the design requirements;

[0013] S5: Feedback control optimization: when the processing deviation exceeds the preset threshold, the process parameter adjustment plan is automatically generated and fed back to the processing equipment control system;

[0014] S6: Quality inspection and traceability, collect component quality data through online inspection equipment, and combine it with processing data to conduct comprehensive quality assessment and problem tracing.

[0015] It is further defined that the construction of the valve digital twin model in S1 includes creating complete geometric information including structure, size, and shape, assigning material mechanical performance parameters, and conducting design defect prevention analysis.

[0016] It is further defined that the device in S2 includes processing equipment, cutting tools and fixtures, and the digital modeling includes establishing digital models of the equipment, cutting tools and fixtures to predict processing accuracy and surface quality and provide a basis for optimizing process parameters. The simulated material processing process in S2 includes material removal, cutting force changes and temperature distribution processes.

[0017] It is further defined that the sensors in S3 include vibration sensors, temperature sensors, and current sensors, and the processing equipment operation data includes spindle speed, feed speed, cutting force, and processing equipment vibration data. By providing multiple sensors, comprehensive perception of the equipment operation status is achieved.

[0018] It is further defined that the dynamic simulation in S4 includes: updating model parameters in real time, simulating the current processing state, and calculating the processing deviation value.

[0019] It is further defined that the parameter adjustment in S5 includes cutting speed adjustment, feed adjustment and cutting depth adjustment. Parameter adjustment is beneficial for achieving real-time optimization of the machining process.

[0020] It is further defined that the online detection equipment in S6 includes a three-coordinate measuring machine and a visual inspection system, and the online detection equipment is used to collect component size, shape and surface quality data.

[0021] It is further defined that it also includes a virtual assembly step, which includes virtually assembling parts based on the digital twin model, checking interference and clearance problems, and optimizing the assembly sequence and method.

[0022] It is further defined that the virtual assembly step also includes: coordination simulation, assembly path planning and assembly process optimization.

[0023] Furthermore, the S6 quality traceability includes tracing process parameters, equipment status, and raw material information during the manufacturing process through the digital twin model. This quality traceability facilitates the rapid identification of the causes of quality issues.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] 1. Significantly improved design quality: Through virtual verification and optimization of digital twin models, potential problems can be discovered and resolved during the design phase, reducing the design defect rate by more than 60% and lowering design costs and cycles.

[0026] 2. Significant improvement in manufacturing accuracy: Real-time monitoring and feedback control mechanisms ensure the stability and accuracy of the machining process, increasing product qualification rates by 15-25% and reducing machining accuracy deviations by more than 30%.

[0027] 3. Significantly improved production efficiency: Virtual assembly and process optimization reduce actual test time by 40%, and the rapid location and resolution of quality issues shorten the problem handling cycle by more than 50%.

[0028] 4. Intelligent quality management: Full-process data collection and intelligent analysis provide complete quality information, and predictive quality control reduces quality risks by 25%, improving the company's quality management level.

[0029] 5. Effective control of manufacturing costs: Reduce physical testing, rework and scrap, reduce comprehensive manufacturing costs by 20-30%, and improve corporate economic benefits and market competitiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The present invention can be further illustrated by the non-limiting examples given in the accompanying drawings;

[0031] Figure 1This is a flowchart of the steps of an embodiment of a valve processing and manufacturing method based on digital twins of the present invention. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the present invention, the technical solutions of the present invention are further described below in conjunction with the accompanying drawings and embodiments. The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts are within the scope of protection of the present invention.

[0033] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0034] In addition, the descriptions of "first", "second", etc. in the present invention are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between the various embodiments can be combined with each other, but this must be based on the ability of ordinary technicians in this field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention. It should be understood that the specific embodiments described here are only used to explain the present invention and are not used to limit the present invention.

[0035] like Figure 1 As shown, a valve processing and manufacturing method based on digital twin of the present invention includes the following steps:

[0036] S1: Build a digital twin model of the valve. Use 3D modeling software to create a valve geometry model. Use finite element analysis software to assign physical properties and material characteristics to the valve geometry model. Perform design optimization through fluid mechanics simulation and stress analysis.

[0037] S2: Establish a digital twin model of the processing technology, digitally model the device, integrate processing parameters, and simulate the material processing process;

[0038] S3: Real-time monitoring of the processing process, deploying multiple types of sensors on the processing equipment to collect real-time processing equipment operation data;

[0039] S4: Dynamic simulation and comparative analysis: the digital twin model dynamically simulates the actual machining process based on real-time collected data, and compares and analyzes the simulation results with the design requirements;

[0040] S5: Feedback control optimization: when the processing deviation exceeds the preset threshold, the process parameter adjustment plan is automatically generated and fed back to the processing equipment control system;

[0041] S6: Quality inspection and traceability, collect component quality data through online inspection equipment, and combine it with processing data to conduct comprehensive quality assessment and problem tracing.

[0042] Example 1: Ball valve manufacturing application example

[0043] Taking the processing and manufacturing of a certain type of DN100 ball valve as an example, the specific implementation process of the method of the present invention is described in detail.

[0044] S1: Building a valve digital twin model

[0045] First, we used SolidWorks 3D modeling software to create a precise geometric model of the ball valve, including all key components such as the valve body, ball, valve seat, and seal. The modeling process was strictly adhered to the design drawings to ensure the accuracy of the geometric dimensions and the correctness of the structural relationships.

[0046] The established 3D geometric model was imported into ANSYS finite element analysis software to give the model real material property parameters. The valve body material is stainless steel 316L, with a set elastic modulus of 200GPa, Poisson's ratio of 0.3, and a density of 7.98g / cm 3 The sphere material is hardened stainless steel and the corresponding mechanical performance parameters are set.

[0047] ANSYS Fluent was used to perform fluid dynamics simulation analysis, simulating the flow field distribution within the ball valve at different openings and calculating the flow resistance coefficient and pressure loss. ANSYS Mechanical was used to perform stress analysis, evaluating the stress distribution and safety factor of each component at maximum operating pressure.

[0048] Based on the simulation analysis results, the geometric shape of the sphere sealing surface was optimized, and the contact pressure distribution on the sealing surface was adjusted to improve sealing performance. At the same time, the valve body wall thickness was optimized to reduce weight and lower material costs while maintaining strength.

[0049] S2: Establish a digital twin model of the processing technology

[0050] Conduct detailed digital modeling of CNC machining centers, lathes, grinders, and other equipment used in ball valve processing. Build a tool library model containing the geometric parameters and cutting performance parameters of various milling cutters, turning tools, grinding wheels, and other tools.

[0051] Build a digital model of the fixture system to simulate the workpiece's clamping state and constraints during machining. Integrate machining process parameters, including key process parameters such as cutting speed, feed rate, cutting depth, and cooling method.

[0052] The digital twin model is used to simulate the precision machining process of a sphere, predicting key information such as material removal, cutting force trends, and surface temperature distribution. Simulation analysis is used to optimize the machining process and determine the optimal combination of roughing, semi-finishing, and finishing process parameters.

[0053] S3: Real-time monitoring of the machining process

[0054] High-precision vibration sensors are installed on the spindles of CNC machining centers to monitor spindle vibration signals in real time and promptly detect abnormalities such as tool wear and workpiece loosening. Infrared temperature sensors are installed in the cutting area to monitor processing temperature changes and prevent overheating from affecting processing quality.

[0055] A current sensor is installed on the main drive motor to indirectly reflect the cutting load status by monitoring the current change. Position sensors are installed on each key motion axis of the machine tool to accurately monitor the motion status and positioning accuracy of each axis.

[0056] A data acquisition system was established to collect various sensor data in real time at a sampling frequency of 100Hz, including key parameters such as spindle speed, feed rate, cutting force, equipment vibration, and temperature. The collected data was then transmitted to the digital twin platform in real time via industrial Ethernet.

[0057] S4: Dynamic simulation and comparative analysis

[0058] The digital twin model dynamically updates the simulation model’s boundary conditions and input parameters based on real-time sensor data. It simulates the current machining state in real time, including tool position, material removal status, cutting force distribution, and other information.

[0059] The theoretical cutting force, vibration frequency and other parameters obtained from the simulation are compared and analyzed with the actual measured values. If the deviation between the simulation results and the actual measured values ​​exceeds the preset threshold (±5%), the system automatically triggers an abnormality warning.

[0060] Through machine learning algorithms, the accuracy of simulation models is continuously optimized, a historical database is established, processing technology knowledge is accumulated, and prediction accuracy is improved.

[0061] S5: Feedback Control Optimization

[0062] When abnormal fluctuations in cutting force are detected, indicating possible tool wear, the system automatically generates a process parameter adjustment plan: reducing the cutting speed by 20% and the feed rate by 15% to extend the tool life and ensure processing quality.

[0063] When it is detected that the processing temperature is too high, the system automatically increases the coolant flow rate and adjusts the cooling method to ensure that the processing temperature is controlled within a reasonable range.

[0064] Adjustment plans are fed back to the CNC system in real time via a digital communication interface, enabling automatic optimization of machining parameters. The entire feedback control process has a response time of less than 2 seconds, ensuring timely and effective process control.

[0065] S6: Quality Inspection and Traceability

[0066] After the sphere is machined, a three-dimensional coordinate measuring machine is used to perform online inspection of key dimensions, including sphere diameter, roundness, surface roughness, and other quality parameters. At the same time, the inspection data is synchronized to the digital twin platform in real time.

[0067] The machine vision inspection system is used to inspect the surface quality of the spheres, detecting surface defects, scratches, and other quality issues. The inspection results are compared with the preset quality standards to automatically determine the product's eligibility.

[0068] When it was discovered that the sphere diameter was out of tolerance by 0.02mm, the system quickly traced the tool wear problem to the 15th process in the processing through the digital twin model, and analyzed that the excessive wear of the tool was caused by improper cutting parameter settings.

[0069] Establish a complete quality traceability database to record quality information from raw materials to finished products, providing data support for quality improvement and process optimization.

[0070] Example 2: Gate valve manufacturing application example

[0071] Taking the manufacture of DN200 gate valve as an example, the universality and effectiveness of the method of the present invention are further verified.

[0072] The virtual assembly optimization steps are as follows:

[0073] The virtual assembly simulation of the gate valve components is performed based on the digital twin model. First, a geometric interference check is performed to ensure that there are no geometric interference issues with the valve body, gate, valve seat and other components in the assembled state.

[0074] Simulate the gate's opening and closing motion to check for proper trajectory and any signs of jamming or interference. Optimize assembly clearances through simulation analysis to ensure both sealing performance and movement flexibility.

[0075] Optimize the assembly process and determine the optimal assembly sequence: first assemble the lower valve seat → install the gate → assemble the upper valve seat → install the stuffing box → finally assemble the actuator. Verify the feasibility of the process through virtual assembly.

[0076] Debugging data feedback and continuous improvement:

[0077] After the gate valve is assembled, a pressure test is performed at 1.5 and 2.25 times the working pressure. Data such as pressure changes, sealing performance, and operating torque are collected during the test.

[0078] The commissioning test data was fed back into the digital twin model to analyze the discrepancies between product performance and design expectations. During the test, slight leakage was discovered on the valve seat sealing surface during high-pressure testing. Model analysis determined that insufficient contact pressure on the sealing surface was the cause.

[0079] Based on the analysis results, the valve seat processing technology was adjusted, and a finishing step was added to the sealing surface to improve surface quality. At the same time, the improved process parameters were applied in subsequent product manufacturing, significantly improving sealing performance.

[0080] Example 3: System Integration and Verification

[0081] Establish a complete digital twin manufacturing platform that integrates product design, process planning, manufacturing, quality inspection, assembly and debugging. The platform uses a cloud computing architecture to support multi-user concurrent access and collaborative work.

[0082] The effectiveness of the method of the present invention was verified through comparative experiments. Ball valve products of the same specifications were selected and produced using the traditional manufacturing method and the digital twin manufacturing method of the present invention.

[0083] The comparison of verification results is shown in the following table:

[0084] Comparison matters Traditional methods Digital Twin Approach Effect Design cycle 15 days 9 days 40% shorter First-article pass rate 75％ 92％ 17% increase Processing accuracy ±0.05mm ±0.03mm 40% increase Production efficiency 120 pieces / day 160 pieces / day 33% increase Quality issue response time 4 hours 30 minutes 87.5% shorter

[0085] As shown in the table above:

[0086] Design cycle: 15 days for traditional methods, 9 days for digital twin methods, shortening the design cycle by 40%;

[0087] First-article qualification rate: 75% for traditional methods and 92% for digital twin methods, a 17 percentage point increase in first-article qualification rate;

[0088] Processing accuracy: Traditional method ±0.05mm, digital twin method ±0.03mm, processing accuracy increased by 40%;

[0089] Production efficiency: 120 pieces / day using the traditional method, 160 pieces / day using the digital twin method, a 33% increase in production efficiency;

[0090] Response time for quality issues: 4 hours using the traditional method and 30 minutes using the digital twin method, shortening the response time by 87.5%.

[0091] In summary, through large-scale production verification, the valve products produced by the method of the present invention are significantly superior to those of traditional manufacturing methods in various performance indicators, which fully proves the advancement and practicality of the technical solution of the present invention.

[0092] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the present invention. Anyone skilled in the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by one of ordinary skill in the art without departing from the spirit and technical principles disclosed herein are intended to be covered by the claims of the present invention.

Claims

1. A valve manufacturing method based on digital twin, characterized in that: The following steps are involved: S1: Build a digital twin model of the valve. Use 3D modeling software to create a valve geometry model. Use finite element analysis software to assign physical properties and material characteristics to the valve geometry model. Perform design optimization through fluid mechanics simulation and stress analysis. S2: Establish a digital twin model of the processing technology, digitally model the device, integrate processing parameters, and simulate the material processing process; S3: Real-time monitoring of the processing process, deploying multiple types of sensors on the processing equipment to collect real-time processing equipment operation data; S4: Dynamic simulation and comparative analysis: the digital twin model dynamically simulates the actual machining process based on real-time collected data, and compares and analyzes the simulation results with the design requirements; S5: Feedback control optimization: when the processing deviation exceeds the preset threshold, the process parameter adjustment plan is automatically generated and fed back to the processing equipment control system; S6: Quality inspection and traceability, collect component quality data through online inspection equipment, and combine it with processing data to conduct comprehensive quality assessment and problem tracing.

2. A valve manufacturing method based on digital twinning according to claim 1, characterized in that: The construction of the valve digital twin model in S1 includes creating complete geometric information including structure, size, and shape, assigning material mechanical performance parameters, and performing design defect prevention analysis.

3. The valve manufacturing method based on digital twin according to claim 1, characterized in that: The device in S2 includes processing equipment, cutting tools and fixtures. The digital modeling includes establishing digital models of the equipment, cutting tools and fixtures to predict processing accuracy and surface quality, providing a basis for optimizing process parameters. The simulated material processing process in S2 includes material removal, cutting force changes and temperature distribution processes.

4. The valve manufacturing method based on digital twin according to claim 1, characterized in that: The sensors in S3 include a vibration sensor, a temperature sensor, and a current sensor, and the processing equipment operation data include spindle speed, feed speed, cutting force, and processing equipment vibration data.

5. The valve manufacturing method based on digital twin according to claim 1, characterized in that: The dynamic simulation in S4 includes: updating model parameters in real time, simulating the current processing state, and calculating the processing deviation value.

6. The valve manufacturing method based on digital twin according to claim 1, characterized in that: The parameter adjustment in S5 includes cutting speed adjustment, feed rate adjustment and cutting depth adjustment.

7. The valve manufacturing method based on digital twin according to claim 1, characterized in that: The online detection equipment in S6 includes a three-coordinate measuring machine and a visual inspection system, and the online detection equipment is used to collect component size, shape and surface quality data.

8. The valve manufacturing method based on digital twin according to claim 1, characterized in that: It also includes a virtual assembly step, which includes virtually assembling parts based on the digital twin model, checking interference and clearance problems, and optimizing assembly sequence and methods.

9. The valve manufacturing method based on digital twin according to claim 8, characterized in that: The virtual assembly step also includes: coordination simulation, assembly path planning and assembly process optimization.

10. The valve manufacturing method based on digital twin according to claim 1, characterized in that: The S6 quality traceability includes: tracing process parameters, equipment status and raw material information during the processing through a digital twin model.

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