CN115203895A - Digital twinning system in cutter manufacturing process - Google Patents
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Abstract
The invention relates to a digital twinning system in the cutter manufacturing process, which comprises the following components: production equipment, digital twinning models and application interfaces; the digital twin model comprises a physical model, a simulation model and a data model; the physical model adopts three-dimensional modeling software to carry out equal-proportion modeling on the production equipment; the simulation model is obtained by rendering the physical model and has the structure and material characteristics consistent with those of production equipment; and the data model receives the operation state, operation action and process parameter data of the production equipment in the cutter manufacturing process, which are acquired by the data acquisition terminal, performs data processing, and forms action logic mapping on the simulation model. The invention can realize the unified management of the production equipment and the process in the manufacturing process of the cutter, acquire the working state of each production equipment and the quality condition of the product in real time, improve the process of the production equipment based on big data calculation and automatically process alarm abnormity, thereby reducing the defective rate of the product manufacturing and shortening the production period of the product.
Description
Technical Field
The invention relates to the field of intelligent manufacturing management of industrial equipment, in particular to a digital twinning system in a cutter manufacturing process.
Background
The powder pressing, sintering, grinding and coating are the most important 4 steps in the cutter manufacturing process, each process is closely related to the product quality, quality problems occur in any link, the processing of the subsequent process and the quality of the final product are affected, and each process in the existing production flow is separated, so that the following defects are mainly caused:
1. the existing cutter manufacturing equipment is large in size, the installation requirements of each equipment are different, and most of the equipment is installed in different workshops in a scattered manner; in the traditional cutter manufacturing process, powder is pressed and then flows to a sintering process workshop, then flows to a grinding workshop and finally flows to a coating workshop, the product flowing time is long, and the process dispersion is difficult to uniformly manage; in conclusion, due to the fact that production and process data of equipment are scattered, the condition of the whole manufacturing process can be observed only after all working procedure responsible persons are subjected to summary processing, and when a certain product has a problem, the problem source is not traced well;
2. manufacturing equipment in each process is precision equipment, particularly sintering and coating need to be operated in a closed environment, real-time working conditions in the equipment cannot be observed, and problems are difficult to find in the working process;
3. when problems occur in the production process of the equipment, the equipment alarms to wait for the treatment of technicians or directly stops the machine, so that abnormal conditions cannot be intelligently treated, the production efficiency is delayed, and even the product quality is influenced;
4. at present, the cutter manufacturing process can only manage and control the product specification and the production batch, and the state of each product cannot be traced, so that the situation that the source cannot be traced when a certain product has a problem can occur.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a digital twinning system for the cutter manufacturing process, which can realize the unified management of the production equipment and the process of the cutter manufacturing process, acquire the working state of each production equipment and the quality condition of a product in real time, improve the process of the production equipment based on big data calculation and automatically process alarm abnormity, thereby reducing the defective rate of the product manufacturing and shortening the production period of the product.
In order to realize the purpose, the technical scheme of the invention is as follows:
a tool manufacturing process digital twinning system comprising: production equipment, digital twinning models and application interfaces; the digital twin model and the application interface are realized on the terminal equipment;
the digital twin model comprises a physical model, a simulation model and a data model; the physical model adopts three-dimensional modeling software to carry out equal-proportion modeling on the production equipment; the simulation model is obtained by rendering the physical model and has the structure and material characteristics consistent with those of production equipment; the data model receives the operation state, operation action and process parameter data of the production equipment in the cutter manufacturing process, which are acquired by the data acquisition terminal, processes the data, changes the data into an executable action command, forms action logic mapping on the simulation model, enables the simulation model and the production equipment to have consistent action simulation effect, and reflects the internal and external states of the production equipment in a virtual environment;
the application interface is generated based on the data model and comprises one or more of an equipment operation display module, a detection data display module, a product quality control module, a process early warning setting module, an alarm processing and analyzing module, an information loading and exporting module and a human-computer interaction module.
Preferably, the production equipment comprises a press, a sintering furnace, a grinding machine and a coating furnace, and corresponds to the pressing, sintering, grinding and coating processes in the manufacturing process of the cutter.
Preferably, the three-dimensional modeling software comprises UG or solidworks and is used for carrying out equal-proportion modeling on a press, a sintering furnace, a grinding machine and a coating furnace; the simulation model uses 3Dmax software to render the model; and the data model adopts C + + programming language to process data and generate an application interface.
Preferably, the press process parameters collected by the data collection terminal include: single weight, female die correction position, pressure of each shaft, upper punch forming position, female die forming position, gas flow and gas pressure;
the technological parameters of the sintering furnace collected by the data collecting terminal comprise: pressure, vacuum degree, micro-pressure, partial pressure, dewaxing pressure, strong cooling pressure, gas flow and gas pressure of each part of the hearth;
the grinding machine technological parameters acquired by the data acquisition terminal comprise: total power, shaft current, grinding temperature and grinding time;
the coating furnace process parameters acquired by the data acquisition terminal comprise: coating temperature, target voltage, target current, field coil current, bias voltage, bias current, turntable speed, gas flow, and gas pressure;
the data model and the simulation model simulate the working action of each production device in real time, simulate the process parameters which cannot be directly observed in the closed space, and visually display the process parameters in the form of an application interface in one or more modes of animation, charts and curves.
Preferably, the digital twinning system for the cutter manufacturing process further comprises a scanning device; each production equipment is provided with a scanning device, and each product production transmission tray is provided with an identification code for recording production information and product position information; when a product on a material tray enters a first process link, a scanning device on production equipment scans the product, the material tray information is associated with production information, the finished product is placed on a vacant position of the material tray by the production equipment, meanwhile, the material tray information, the production information, the product information and the product position information are uploaded to a cloud data center in an associated mode, corresponding information is endowed to an identification code of the material tray again, each process is finished, the recording of the product information is finished, and the production state of each product is checked through an application interface.
The equipment operation display module has a scene switching function and is used for checking the operation state and the production data of each production equipment in real time; the detection data display module is used for checking the detection information of each production device in real time; the product quality control module is used for checking the quality condition of the product being produced in real time; the process early warning setting module is used for setting a threshold value capable of realizing stable production; the alarm processing and analyzing module is used for prompting and recording production abnormity alarms and intelligently processing alarm conditions by improving process parameters; the information loading and exporting module is used for uploading and downloading important data in the production process; and the human-computer interaction module is used for remotely controlling the field production equipment.
Preferably, the application interface further comprises a product quality prediction and alarm module, specifically configured to: and deducing a relational expression between the process parameters and the product quality based on the quality data of the historical production product, dynamically displaying the change of the product quality in the simulation model through the conversion of the data model, predicting the product quality according to the current production condition and the internal state of the production equipment, and generating an alarm when the product quality is predicted to be reduced.
Preferably, the application interface further comprises a process scheme optimization module, which is specifically configured to: the detection data of each production device in the production process is automatically recorded, a data access interface in a quality inspection link is provided, manually detected data is imported, a data model carries out real-time processing on the data, big data analysis is carried out through a deep learning algorithm, and a process scheme is automatically optimized.
Preferably, the application interface further includes a production process backtracking module, specifically configured to: the production process of the production equipment in the specified time period is selected to be played back in the simulation system so as to trace the past production condition in detail and achieve the product production process tracing function.
Preferably, the alarm processing and analyzing module is further configured to: when monitoring that an alarm occurs in the operation process of the production equipment, obtaining a processing mode based on an alarm processing mode and/or big data learning in the corresponding alarm processing database of the production equipment so as to ensure the normal operation of the production equipment.
After the scheme is adopted, the invention has the beneficial effects that:
(1) Before each process starts, the digital twin system scans and records production information of the product transmission material tray through the scanning device, gives the production information to the product at each position on the material tray and uploads the production information to the database, so that a user can trace the information of the whole manufacturing process of each product at any time, and places with quality problems are determined;
(2) The digital twin system collects all process information, production information and product quality information of 4 key procedures in the cutter manufacturing process and carries out unified real-time dynamic display, a user can directly derive all information of a certain product in the whole manufacturing process, and the user can remotely monitor the running state of equipment at a first visual angle;
(3) The simulation model of the digital twin system can realize the space action simulation and the process engineering simulation which are consistent with the actual production equipment, and through an empirical formula established by process data and product quality, a user can directly see animation changes and real-time data icons of the internal environment and the product quality of the closed equipment, and if the quality problem of the product in the production equipment exists, the animation changes and the real-time data icons can be immediately found and processed;
(4) The digital twin system disclosed by the invention is based on data acquisition, cleaning and learning, and can automatically and intelligently adjust process parameters when the product quality fluctuates in the production process, so that the product quality is improved; the alarm condition in the operation process of the equipment can be intelligently processed by combining the embedded alarm processing database and the big data learning function.
(5) The digital twin system can send instructions to actual production equipment through the man-machine interaction module, and operate physical actions such as door opening and closing of the production equipment.
The present invention will be described in further detail with reference to the accompanying drawings and examples, but the present invention is not limited to the examples.
Drawings
FIG. 1 is a block diagram of a digital twinning system in a tool manufacturing process according to the present invention;
FIG. 2 is a data transfer frame diagram of a digital twinning system for a tool manufacturing process according to the present invention;
FIG. 3 is a perspective view of a production transport tray of the digital twinning system of the present invention during the manufacturing process of a cutting tool;
FIG. 4 is a schematic diagram of a material conveying system of a digital twinning system in a tool manufacturing process according to the present invention;
FIG. 5 is a schematic flow chart of the present invention for obtaining an optimal process route through deep learning.
Detailed Description
The technical solutions in the embodiments of the present invention will be described and discussed in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
The invention relates to a digital twin system in the cutter manufacturing process, which can realize the unified management of production equipment and processes in the cutter manufacturing process, acquire the working state of each production equipment and the quality condition of a product in real time, improve the production equipment process based on big data calculation and automatically process alarm abnormity, thereby reducing the defective rate of product manufacturing and shortening the production period of the product.
Referring to fig. 1, a digital twinning system for a tool manufacturing process includes: production equipment 10, digital twinning model 20 and application interface 30; the digital twin model 20 and the application interface 30 are implemented on a terminal device;
the digital twin model 20 comprises a physical model 201, a simulation model 202 and a data model 203; the physical model 201 adopts three-dimensional modeling software to carry out equal-proportion modeling on the production equipment 10; the simulation model 202 is obtained by rendering the physical model 201 and has the structure and material characteristics consistent with those of the production equipment 10; the data model 203 receives the running state, running action and process parameter data of the production equipment 10 in the cutter manufacturing process collected by the data collection terminal, performs data processing, changes the data into executable action commands, forms action logic mapping on the simulation model 202, enables the simulation model 202 and the production equipment 10 to have consistent action simulation effect, and reflects the internal and external states of the production equipment 10 from a virtual environment;
the application interface 30, which is generated based on the data model 203, includes one or more of an equipment operation display module 300, a detection data display module 301, a product quality control module 302, a process early warning setting module 303, an alarm processing analysis module 304, an information loading and exporting module 305, and a human-computer interaction module 306.
In this embodiment, the production equipment 10 includes a press 101, a sintering furnace 102, a grinding machine 103, and a coating furnace 104, which correspond to the pressing, sintering, grinding, and coating processes in the manufacturing process of the cutting tool.
Specifically, referring to fig. 2, the digital twin system in the complex tool manufacturing process of the present invention collects the operation state, process parameters, production conditions, and product quality of each device through a data collection terminal, and further uploads the collected data to the cloud data center 80 through the industrial internet after cleaning and uniform expression. And the database accesses and distributes the data to each data processing module for real-time processing of the data. The collected device action instructions are mapped into the simulation model 202, so that the simulation model 202 can have the same operation state, space action and parameter information as the actual device. The user can observe the operation state, the internal operation condition and the product quality change condition of each device in real time in the system device operation display module 300.
In this embodiment, the three-dimensional modeling software includes UG or solidworks, and is used to perform equal-scale (1:1) modeling on the press 101, the sintering furnace 102, the grinding machine 103, and the coating furnace 104. The simulation model 202 performs model rendering using software such as 3 Dmax. The data model 203 performs data processing using programming languages such as C + + and the like, and generates the application interface 30.
Specifically, the press 101 process parameters acquired by the data acquisition terminal include: single weight, female die correction position, pressure of each shaft, upper punch forming position, female die forming position, gas flow and gas pressure;
the sintering furnace 102 process parameters collected by the data collection terminal include: pressure, vacuum degree, micro-pressure, partial pressure, dewaxing pressure, strong cooling pressure, gas flow and gas pressure of each part of the hearth;
the grinding machine 103 process parameters acquired by the data acquisition terminal include: total power, shaft current, grinding temperature and grinding time;
the process parameters of the coating furnace 104 acquired by the data acquisition terminal include: coating temperature, target voltage, target current, field coil current, bias voltage, bias current, turntable speed, gas flow, and gas pressure.
The system can simulate the working action of each equipment model in real time, simulate the process parameters which cannot be directly observed in the closed space, such as pressure, temperature, vacuum degree, gas flow and the like, and finally visually display the process parameters in the form of the application interface 30 in one or more modes of animation, charts and curves.
In this embodiment, referring to fig. 3 and 4, the digital twinning system for the tool manufacturing process further includes a scanning device 40; each production equipment 10 is provided with a scanning device 40, and each product production transmission tray 50 is provided with an identification code 60 for recording production information and product position information; when a product 70 on a tray enters a first process link, a scanning device 40 on the production equipment 10 scans the product, tray information is associated with production information, the finished product is placed on a vacant position of the tray by the production equipment 10, meanwhile, the tray information, the production information, the product information and the product position information are associated and uploaded to a cloud data center 80, corresponding information is endowed to an identification code of the tray again, recording of each product information is completed after each process is completed, the production state of each product is checked through an application interface 30, process parameters derived through a large amount of historical production data and product quality data and a product quality relation empirical formula are embedded into a data model 203, and a user can observe the change of product quality in real time at a product quality control module 302.
In this embodiment, the empirical formula of the relationship between the sintering process parameters and the product quality is as follows:
| quality of the product | Technological parameters | Empirical formula |
| Grain size Co% | Pressure P N1 | Co％＝0.0043*ln(P N1 )+0.0292 |
| Carbon content Ct% | Vacuum degree P | Ct％＝e(0.7092*P 0.0656 +6.8737)/4.3878 |
| Grain size dwc | Temperature T | dwc＝{2453.8272/[(2024.3504-T)*Co％ 0.58 ] 1.2987 } |
In this embodiment, the empirical formula of the relationship between the coating process parameters and the product quality is as follows:
the identification code 60 includes a two-dimensional code or a bar code.
In this embodiment, the device operation display module 300 has a scene switching function, and is configured to check the operation state and the production data of each production device 10 in real time; the detection data display module 301 is configured to view detection information of each production device 10 in real time; the product quality control module 302 is configured to check the quality condition of a product being produced in real time; the process early warning setting module 303 is configured to set a threshold value capable of stabilizing production; the alarm processing and analyzing module 304 is used for prompting and recording production abnormity alarms and intelligently processing alarm conditions by improving process parameters; the information loading and exporting module 305 is used for uploading and downloading important data of the production process; the human-computer interaction module 306 is used for remotely controlling the field production equipment 10.
Specifically, each production device 10 performs detection of different dimensions on a product in the operation process, the digital twin system automatically records detection data of each device in the production process, meanwhile, information is provided and loaded into the export module 305, a user can also import manually detected data, a visual chart is formed through real-time processing of the data model 203, and the user can observe the visual chart in the detection data display module 301 in real time.
Further, the application interface 30 further includes a product quality prediction and alarm module, which is specifically configured to: and deducing a relational expression between the process parameters and the product quality based on the quality data of the historical production product, dynamically displaying the change of the product quality in the simulation model 202 through the conversion of the data model 203, predicting the product quality according to the current production condition and the internal state of the production equipment 10, and generating an alarm when the product quality is predicted to be reduced.
The application interface 30 further comprises a process scheme optimization module, specifically configured to: the detection data of each production device 10 in the production process is automatically recorded, a data access interface in the quality inspection link is provided, the data detected manually is imported, the data is processed in real time by the data model 203, the big data is analyzed through a deep learning algorithm, and the process scheme is automatically optimized.
The application interface 30 further includes a production process backtracking module, which is specifically configured to: the production process of the production equipment 10 in the specified time period is selected to be played back in the simulation system so as to trace the past production condition in detail and achieve the product production process tracing function.
The alarm processing and analyzing module 304 is further configured to: when it is monitored that an alarm occurs in the operation process of the production equipment 10, a processing mode is obtained based on an alarm processing mode and/or big data learning in an alarm processing database corresponding to the production equipment 10, so that the normal operation of the production equipment 10 is ensured.
Through deep learning of collected data and big data analysis, the digital twin system recommends users to use an optimized process scheme or automatically compensate based on the human-computer interaction module 306, early warning setting is carried out on the process in the running process of the production equipment 10, the process is immediately and automatically adjusted when quality fluctuation occurs, and the product quality is guaranteed. Meanwhile, an alarm processing database of each equipment operation process is built in the system, and when an alarm occurs in the equipment operation process, a processing mode can be obtained based on an alarm processing mode or big data learning in the database, so that the normal operation of the production equipment 10 is ensured.
Fig. 5 is a schematic diagram illustrating the method for obtaining an optimal process route through the trained reinforcement learning model according to the embodiment. Specifically, the acquired data are imported into a database, and the reinforcement learning model is trained through the database. The process parameters are used as input, the product quality is used as reward and punishment conditions of the model, and the process route is used as output. And establishing a Q table according to corresponding process flows, wherein each process flow corresponds to a value in the Q table, the value of the value represents the accumulated value of the process flow according to the reward and punishment conditions, and the larger the accumulated value is, the larger the Q value is, the process flow accords with positive reward in the reward and punishment conditions. And the selection of an optimal process route is realized through reward and punishment conditions, namely the quality of the product is good and bad, and when the product quality is qualified, a positive reward is given to the reinforcement learning model, namely the model is encouraged to be biased to select a process route with high processing quality in the aspect of the selection of the process route. In the training process of the model, a Q-learning algorithm is adopted, and the Q value is mainly updated by the Q-learning algorithm. The technical process is comprehensively evaluated through the positive reward or the negative reward obtained in the technical process and the reward and punishment conditions of the next technical process, so that the updating of the Q table is realized. And finally, judging the parameter corresponding to the process route with the highest quality according to the updated Q value.
Furthermore, a user can set physical actions such as opening and closing a door of the device through the human-computer interaction module 306, so as to form further human-computer interaction.
The above is only one preferred embodiment of the present invention. However, the present invention is not limited to the above embodiments, and any equivalent changes and modifications made according to the present invention, which do not bring out the functional effects beyond the scope of the present invention, belong to the protection scope of the present invention.
Claims (10)
1. A tool manufacturing process digital twinning system, comprising: production equipment, digital twinning models and application interfaces; the digital twin model and the application interface are realized on the terminal equipment;
the digital twin model comprises a physical model, a simulation model and a data model; the physical model adopts three-dimensional modeling software to carry out equal-proportion modeling on the production equipment; the simulation model is obtained by rendering the physical model and has the structure and material characteristics consistent with those of production equipment; the data model receives the running state, running action and process parameter data of the production equipment in the cutter manufacturing process, which are acquired by the data acquisition terminal, performs data processing, changes the data into executable action commands, forms action logic mapping on the simulation model, enables the simulation model and the production equipment to have consistent action simulation effect, and reflects the internal and external states of the production equipment from a virtual environment;
the application interface is generated based on the data model and comprises one or more of an equipment operation display module, a detection data display module, a product quality control module, a process early warning setting module, an alarm processing and analyzing module, an information loading and exporting module and a human-computer interaction module.
2. The tool manufacturing process digital twinning system of claim 1, wherein said production equipment includes a press, a sintering furnace, a grinding machine and a coating furnace, corresponding to pressing, sintering, grinding and coating processes in the tool manufacturing process.
3. The tool making process digital twinning system of claim 2, wherein said three-dimensional modeling software includes UG or solidworks for equal-scale modeling of presses, sintering furnaces, grinding machines, and coating furnaces; the simulation model uses 3Dmax software to render the model; and the data model adopts C + + programming language to process data and generate an application interface.
4. The digital twinning system for cutter manufacturing process of claim 2, wherein the press process parameters collected by the data collection terminal include: single weight, female die correction position, pressure of each shaft, upper punch forming position, female die forming position, gas flow and gas pressure;
the technological parameters of the sintering furnace collected by the data collecting terminal comprise: pressure, vacuum degree, micro-pressure, partial pressure, dewaxing pressure, strong cooling pressure, gas flow and gas pressure of each part of the hearth;
the grinding machine technological parameters acquired by the data acquisition terminal comprise: total power, shaft current, grinding temperature and grinding time;
the coating furnace process parameters acquired by the data acquisition terminal comprise: coating temperature, target voltage, target current, field coil current, bias voltage, bias current, turntable speed, gas flow, and gas pressure;
the data model and the simulation model simulate the working action of each production device in real time, simulate the process parameters which cannot be directly observed in the closed space, and visually display the process parameters in the form of an application interface in one or more modes of animation, charts and curves.
5. The tool manufacturing process digital twinning system of claim 1, further comprising a scanning device; each production equipment is provided with a scanning device, and each product production transmission tray is provided with an identification code for recording production information and product position information; when a product on a material tray enters a first process link, a scanning device on production equipment scans the product, the material tray information is associated with production information, the finished product is placed on a vacant position of the material tray by the production equipment, meanwhile, the material tray information, the production information, the product information and the product position information are uploaded to a cloud data center in an associated mode, corresponding information is endowed to an identification code of the material tray again, each process is finished, the recording of the product information is finished, and the production state of each product is checked through an application interface.
6. The digital twinning system for cutter manufacturing process according to claim 1, wherein the equipment operation display module has a scene switching function for checking the operation state and production data of each production equipment in real time; the detection data display module is used for checking the detection information of each production device in real time; the product quality control module is used for checking the quality condition of the product being produced in real time; the process early warning setting module is used for setting a threshold value capable of realizing stable production; the alarm processing and analyzing module is used for prompting and recording production abnormity alarms and intelligently processing alarm conditions by improving process parameters; the information loading and exporting module is used for uploading and downloading important data in the production process; and the human-computer interaction module is used for remotely controlling the field production equipment.
7. The tool manufacturing process digital twinning system of claim 1, wherein said application interface further includes a product quality prediction and alarm module, specifically configured to: and deducing a relational expression between the process parameters and the product quality based on the quality data of the historical production product, dynamically displaying the change of the product quality in the simulation model through the conversion of the data model, predicting the product quality according to the current production condition and the internal state of the production equipment, and generating an alarm when the product quality is predicted to be reduced.
8. The tool manufacturing process digital twinning system of claim 1, wherein said application interface further includes a process recipe optimization module, specifically configured to: the detection data of each production device in the production process is automatically recorded, a data access interface in a quality inspection link is provided, manually detected data is imported, a data model carries out real-time processing on the data, big data analysis is carried out through a deep learning algorithm, and a process scheme is automatically optimized.
9. The tool manufacturing process digital twinning system of claim 1, wherein said application interface further comprises a production process backtracking module, specifically configured to: the production process of the production equipment in the specified time period is selected to be played back in the simulation system so as to trace the past production condition in detail and achieve the product production process tracing function.
10. The tool manufacturing process digital twinning system of claim 1, wherein said alarm processing analysis module is further configured to: when monitoring that an alarm occurs in the operation process of the production equipment, obtaining a processing mode based on an alarm processing mode and/or big data learning in the corresponding alarm processing database of the production equipment so as to ensure the normal operation of the production equipment.
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| CN117339985A (en) * | 2023-12-05 | 2024-01-05 | 滦南县兴凯盛科技有限公司 | Method for manufacturing sectional material by recycling rail materials |
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| CN117339985A (en) * | 2023-12-05 | 2024-01-05 | 滦南县兴凯盛科技有限公司 | Method for manufacturing sectional material by recycling rail materials |
| CN117339985B (en) * | 2023-12-05 | 2024-02-23 | 滦南县兴凯盛科技有限公司 | Method for manufacturing sectional material by recycling rail materials |
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