Die full life cycle digital management method

Abstract

The invention discloses a die full life cycle digital management method, and relates to the technical field of thermal forming dies, and the method comprises the following steps: selecting a laser scanning device according to the type of a die; scanning a mold real object, and recording a deviation value between the real object and a design drawing; scanning the research-in data, comparing the data with a real object, and storing the data; scanning the surface of the service mold during maintenance, and comparing and recording difference value data; after the full life cycle of the mold is completed, previous scanning data are compared; and calling a full life cycle file of the mold, and optimizing a subsequent new mold according to the file. According to the die full-life-cycle digital management method, different abrasion losses in the die production and service full life cycle can be seen through digital comparison, so that an allowable difference value suitable for die abrasion changes is found out, direct CNC machining is facilitated through an accurate digital die difference chart, the die health state is conveniently and accurately recorded, and the die full-life-cycle digital management method is suitable for popularization and application. And shutdown accidents caused by die failure are avoided in advance.

Description

Technical Field

[0001] The invention relates to the technical field of thermoforming moulds, and in particular to a digital management method for the entire life cycle of a mould. Background Art

[0002] New molds in hot forming molds need to be manually matched by fitters before they can be put into service normally. In addition, the wear status of different parts of the above molds is inconsistent. When the wear exceeds the allowable tolerance, it causes abnormal springback of the parts and requires replacement of new inserts. At this time, the new inserts need to be matched again after the processing data comes out, which is time-consuming and labor-intensive. In order to reduce the degree of manual labor, reduce the number of matching times or even eliminate the need for fitters to match, it is now necessary to digitize the service wear process of the mold throughout its life cycle, so as to combine additive technology to keep the mold in the optimal state at all times and avoid multiple matching operations.

[0003] Based on this, a digital management method for the entire life cycle of molds is now provided, which can eliminate the drawbacks of existing technical solutions. Summary of the invention

[0004] The purpose of the present invention is to provide a digital management method for the entire life cycle of a mold, so as to solve the problem in the background technology that the mold wear state is different and the fitter needs to grind and match the mold multiple times.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A digital management method for the entire life cycle of a mold includes the following steps:

[0007] S1. Select laser scanning equipment with appropriate accuracy according to the mold type;

[0008] S2. After the mold is machined, scan the actual mold and compare it with the design drawing to get the difference value, and record the deviation value between the actual object and the design;

[0009] S3. After the mold is developed, the developed data is scanned and compared with the actual object processed by the mold machine to obtain the optimal mold data and save it as a mold file;

[0010] S4. Perform multiple maintenance operations on the mold, scan the surface of the mold in service during maintenance, compare it with the optimal drawing data to obtain the difference value, and record the data;

[0011] S5. When it is found that the mold wear exceeds the allowable tolerance of the part, analyze the wear condition, adjust the additive formula, and develop the mold to keep it in service;

[0012] S6. After the mold has completed 300,000 to 500,000 molds in its entire life cycle, compare the previous scan data and collect the above data to form a mold life cycle archive;

[0013] S7. Retrieve the mold's entire life cycle archive and optimize subsequent new molds based on the archive.

[0014] Preferably, the step S2 comprises:

[0015] S21, scanning the mold using a laser scanning device to obtain point cloud data at different positions on the mold surface;

[0016] S22, removing noise and redundant information from the point cloud data, simplifying the point cloud data while ensuring accuracy, performing a surface reconstruction operation based on multiple point cloud data, obtaining a three-dimensional model of the mold, and acquiring coordinate information of any position point of the mold model;

[0017] S23, comparing the coordinate information of the mold three-dimensional model with the coordinate information of the standard model, calculating the three-dimensional deviation, and selecting different color RGB values ​​for drawing, and displaying the deviation area color map through different colors.

[0018] Preferably, step S4 comprises:

[0019] S41. When the mold is maintained after 10,000 molds have been used, scan the mold and compare it with the optimal value after research and matching to obtain the difference value and save the wear data;

[0020] S42, when the mold is maintained after 30,000 molds have been used, scan the mold and compare it with the optimal value after research and matching, get the difference value, and save the wear data;

[0021] S43, when the mold is maintained after 100,000 molds have been used, scan the mold and compare it with the optimal value after research and matching, obtain the difference value, and save the wear data;

[0022] S44. When the mold is maintained after 200,000 molds have been used, scan the mold and compare it with the optimal value after research and matching to obtain the difference value and save the wear data.

[0023] Preferably, step S5 comprises:

[0024] S51. When it is found that the three-dimensional deviation of the mold exceeds the allowable tolerance of the part, the mold wear cause is analyzed through the analysis module, and the cause includes temperature, humidity, air density, and position, and the mold service environment is adjusted;

[0025] S52. Adjust the additive formula according to the three-dimensional deviation so that the above-mentioned mold can restore its geometric dimensions to the optimal value and continue to serve.

[0026] Preferably, the present invention further comprises a digital management system for the entire life cycle of a mold, the system comprising a laser scanning device and a data analysis device that communicate with each other via a network;

[0027] The laser scanning device is used to perform an all-round scan on the mold, obtain the position information of the mold surface, and construct a three-dimensional model after preprocessing the position information. The laser scanning device includes an image acquisition module, a monitoring module and a preprocessing module;

[0028] The image acquisition module is used to acquire image data of the scanned mold, and the image data includes the wear part, mold status, numbering information and surface point cloud data;

[0029] The monitoring module is used to detect changes in the surrounding environment of the mold;

[0030] The pre-processing module is used to perform image data enhancement, noise removal and simplification operations on the above image data;

[0031] The data analysis device is used to compare and analyze the scanned three-dimensional model with the mold of the optimal data, and design and optimize the additive formula based on the above comparison and analysis results. The data analysis device includes a data storage library, a processor, a comparison component and a display panel;

[0032] The data repository is used to collect, store and provide scanning history data and design drawing data of multiple molds, and divide a number of data corresponding to the mold into a number of groups according to the full life cycle of the mold to form a full life cycle archive of the mold;

[0033] The processor is used to receive and output data information of each module, data storage library and display panel;

[0034] The comparison component is used to perform comparative analysis on the mold and provide possible causes of wear and tear and an adjusted mold additive solution;

[0035] The display panel is used to receive data information transmitted by the processor, and update the display results in real time based on the data information.

[0036] Preferably, the monitoring module includes a temperature sensor unit, a humidity sensor unit, an air density sensor unit and a position sensor unit;

[0037] The temperature sensor unit is used to monitor the temperature of the mold service environment in real time;

[0038] The humidity sensor unit is used to monitor the humidity of the mold service environment in real time;

[0039] The air density sensor unit is used to monitor the air density of the mold service environment in real time;

[0040] The position sensor unit is used to monitor the position information of the mold service environment in real time.

[0041] Preferably, the preprocessing module includes a feature extraction unit, a data cleaning unit and a data simplification unit;

[0042] The feature extraction unit is used to extract point cloud data with representative geometric features from the scanned three-dimensional data of the mold, and the geometric features include the contour, curved surface, and hole of the mold;

[0043] The data cleaning unit is used to remove noise and redundant information in the point cloud data;

[0044] The data reduction unit is used to simplify point cloud data.

[0045] Preferably, the comparison component includes an acquisition module, a comparison module, an early warning module, a drawing module and an analysis module;

[0046] The acquisition module is used to construct a three-dimensional model of the mold according to the processed point cloud data, and obtain the coordinate information of any position point of the mold model;

[0047] The comparison module is used to compare the three-dimensional model of the mold with the standard model, evaluate the wear of the mold based on the comparison result and calculate the three-dimensional deviation, and select different color RGB values ​​for drawing, and display the deviation area color map through different colors;

[0048] The early warning module is used to determine whether the mold deviation reaches the early warning threshold, and to issue an early warning to the mold that reaches the early warning threshold. The upper limit threshold of the mold wear degree is set to I 阈值 ;

[0049] The drawing module is used to draw a deviation color map of the mold;

[0050] The analysis module is used to compare and analyze the changes in the surrounding environment of the mold that have reached a threshold with historical data, and provide reasons that affect the degree of wear based on the above data.

[0051] Preferably, one side of the laser scanning device and the data analysis device is provided with an information access port, and the information access port includes a wireless transmission port and a charging interface.

[0052] Preferably, the comparison component further comprises an alarm module electrically connected to the comparison module and the early warning module, and the alarm module is used for emitting an alarm sound after the mold reaches an early warning threshold.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] This digital management method for the entire life cycle of the mold scans the mold to obtain physical data before the new mold is put into service, and compares it with the design data to obtain the difference value and save it. When the mold is maintained, it is scanned again to record the wear of the mold under normal service. Through digital comparison, the different wear amounts of the mold in the entire life cycle of production and service can be seen, so as to find the allowable difference value suitable for the change of mold wear. The precise digitized mold difference map is convenient for direct CNC processing, which is convenient for providing on-site managers with accurate basis for production optimization. In addition, the digital management of the entire life cycle can accurately record the health status of the mold, avoid downtime accidents caused by mold failure in advance, and the use effect is good. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is a schematic diagram of the process of the present invention.

[0056] Figure 2 It is a schematic diagram of the process of step S2 of the present invention.

[0057] Figure 3 It is a schematic flow chart of step S4 of the present invention.

[0058] Figure 4 It is a schematic diagram of the process of step S5 of the present invention.

[0059] Figure 5 It is a schematic diagram of the overall structure of the management system of the present invention.

[0060] Figure 6 It is a schematic diagram of the structure of the laser scanning device and the data analysis device of the present invention.

[0061] Figure 7 It is a schematic diagram of the structure of the monitoring module and the preprocessing module of the present invention.

[0062] Figure 8 It is a structural schematic diagram of the data analysis device of the present invention.

[0063] Fig. 9 It is a schematic structural diagram of a comparative component of the present invention.

[0064] Fig.10 This is the mold deviation color diagram of the present invention.

[0065] Notes on the accompanying drawings: laser scanning device 100, image acquisition module 110, monitoring module 120, temperature sensor unit 121, humidity sensor unit 122, air density sensor unit 123, position sensor unit 124, preprocessing module 130, feature extraction unit 131, data cleaning unit 132, data simplification unit 133, data analysis device 200, data repository 210, processor 220, comparison component 230, acquisition module 231, comparison module 232, early warning module 233, drawing module 234, analysis module 235, alarm module 236, display panel 240, information access port 300. DETAILED DESCRIPTION

[0066] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0067] In this embodiment, if Figure 1-Figure 10 As shown, a digital management method for the entire life cycle of a mold includes the following steps:

[0068] S1. Select a laser scanning device 100 with appropriate accuracy according to the mold type;

[0069] The laser scanning device 100 includes but is not limited to a laser scanner and a structured light scanner, which is convenient for emitting light and receiving reflected light, and determining the three-dimensional coordinates of each point on the mold surface by calculating the time difference or angle change of the light;

[0070] S2. After the mold is machined, scan the actual mold and compare it with the design drawing to get the difference value, and record the deviation value between the actual object and the design;

[0071] The mold machine is a common structure in this field and is a prior art. Assuming that the mold object just processed is the first mold, after aligning the mold object with the design drawing, any point on the design drawing is set as A, and the corresponding point A on the first mold model is set as point B. The position coordinate of point A is a=(X a ,Y a ,Z a ), the position coordinate of B is b=(X b ,Y b ,Z b ), calculate the deviation of these two points in each coordinate axis direction: ΔX = X b -X a , ΔX=X b -X a ,ΔX=X b -X a , and then according to the three-dimensional deviation formula Calculate the deviation Δd between point A and point BAB According to the above method, the design deviation values ​​between other points on the design drawing and the first mold can be obtained;

[0072] S3. After the mold is developed, the developed data is scanned and compared with the actual object processed by the mold machine to obtain the optimal mold data and save it as a mold file;

[0073] Assume that the mold just developed is the second mold. After aligning the scanned second mold with the first mold model, set the point corresponding to point B on the second mold as point C. The position coordinate of point C is c=(X c ,Y c ,Z c ), calculate the deviation between point C and point B in each coordinate axis direction: ΔX = X c -X b , ΔX=X c -X b ,ΔX=X c -X b , and then the deviation value between point C and point B can be calculated. According to the above method, the design deviation values ​​between other points on the second mold and the first mold can be obtained, so as to find the optimal data of the mold, set the optimal mold as the third mold, and set the corresponding point on the third mold as point D. The position coordinate d=(X d ,Y d ,Z d ), which is convenient for calculating the deviation between point D and points A, B, and C;

[0074] S4. Perform multiple maintenance operations on the mold, scan the surface of the mold in service during maintenance, compare it with the optimal drawing data to obtain the difference value, and record the data;

[0075] Assuming that the mold just maintained is the fourth mold, after aligning the scanned fourth mold with the third mold model, find the corresponding point E on the fourth mold, and then use the point cloud data of the target point E = (X e ,Y e ,Z e ) obtains the deviation in each coordinate axis direction, and then calculates the deviation value between the target points;

[0076] S5. When it is found that the mold wear exceeds the allowable tolerance of the part, analyze the wear condition, adjust the additive formula, and develop the mold to keep it in service;

[0077] Set the upper limit of mold wear to I 阈值 , when Δd is greater than I 阈值When the mold is damaged, the user is prompted through the early warning module 233 and the alarm module 236 that the mold has reached the maximum wear level and needs to be repaired immediately. The data can also be transmitted to the analysis module 235 to analyze the cause of the mold damage, such as whether it is caused by wear metal friction or mold overheating.

[0078] S6. After the mold has completed 300,000 to 500,000 molds in its entire life cycle, compare the previous scan data and collect the above data to form a mold life cycle archive;

[0079] It is convenient to record the wear amount of the mold under normal service. Through digital comparison, the different wear amounts of the mold in the whole life cycle of production and service can be seen, so as to find the allowable difference value suitable for the change of mold wear;

[0080] S7. Retrieve the mold's full life cycle archive and optimize subsequent new molds based on the archive;

[0081] Digital mold archives can record the service performance of different molds and provide a benchmark for mold iteration.

[0082] Among them Figure 1 and Figure 2 As shown, step S2 includes:

[0083] S21, scanning the mold using a laser scanning device 100 to obtain point cloud data at different positions on the mold surface;

[0084] S22, removing noise and redundant information from the point cloud data, simplifying the point cloud data while ensuring accuracy, performing a surface reconstruction operation based on multiple point cloud data, obtaining a three-dimensional model of the mold, and acquiring coordinate information of any position point of the mold model;

[0085] S23, comparing the coordinate information of the mold three-dimensional model with the coordinate information of the standard model, calculating the three-dimensional deviation, and selecting different color RGB values ​​for drawing, and displaying the deviation area color map through different colors;

[0086] The scanned 3D data is processed and analyzed, including data denoising, cleaning and registration, to improve the accuracy and reliability of the data. The deviation area color map can be used to quickly observe whether the deviation is within the threshold range.

[0087] Among them Figure 1 and Figure 3 As shown, step S4 includes:

[0088] S41. When the mold is maintained after 10,000 molds have been used, scan the mold and compare it with the optimal value after research and matching to obtain the difference value and save the wear data;

[0089] S42, when the mold is maintained after 30,000 molds have been used, scan the mold and compare it with the optimal value after research and matching, get the difference value, and save the wear data;

[0090] S43, when the mold is maintained after 100,000 molds have been used, scan the mold and compare it with the optimal value after research and matching, obtain the difference value, and save the wear data;

[0091] S44, when the mold is maintained after 200,000 molds have been used, scan the mold and compare it with the optimal value after research and matching, get the difference value, and save the wear data;

[0092] During the service life of the mold, it is necessary to perform multiple maintenance operations on it to extend its service life and facilitate timely detection of its wear degree to see if it meets the normal changes in the mold's life cycle.

[0093] Among them Figure 1 and Figure 4 As shown, step S5 includes:

[0094] S51, when it is found that the three-dimensional deviation of the mold exceeds the allowable tolerance of the part, the mold wear cause is analyzed by the analysis module 235, the cause includes temperature, humidity, air density, position, and the mold service environment is adjusted;

[0095] S52. Adjust the additive formula according to the three-dimensional deviation so that the above-mentioned mold can restore its geometric dimensions to the optimal value and continue to serve.

[0096] Among them Figure 5-Figure 9 As shown, it also includes a digital management system for the entire life cycle of a mold, which includes a laser scanning device 100 and a data analysis device 200 that communicate with each other through a network;

[0097] The laser scanning device 100 is used to perform an all-round scan on the mold, obtain the position information of the mold surface, and construct a three-dimensional model after pre-processing the position information. The laser scanning device 100 includes an image acquisition module 110, a monitoring module 120 and a pre-processing module 130;

[0098] The image acquisition module 110 is used to acquire image data of the scanned mold, which includes the worn parts, mold status, number information and surface point cloud data, so as to be responsible for emitting laser beams and receiving reflected light, thereby obtaining mold surface information;

[0099] The monitoring module 120 is used to detect changes in the surrounding environment of the mold so as to promptly detect and handle any abnormal situation;

[0100] The pre-processing module 130 is used to enhance, remove noise and simplify the above image data, remove noise points irrelevant to the mold surface through algorithms, reduce the amount of data and improve processing efficiency while maintaining data accuracy;

[0101] The data analysis device 200 is used to compare and analyze the scanned three-dimensional model with the mold of the optimal data, and design and optimize the additive formula based on the above comparison and analysis results. The data analysis device 200 includes a data storage library 210, a processor 220, a comparison component 230 and a display panel 240;

[0102] The data repository 210 is used to collect, store and provide scanning history data and design drawing data of multiple molds, and divide the corresponding mold data into several groups according to the full life cycle of the mold to form a mold full life cycle archive, so as to provide data management and retrieval functions so as to efficiently access and use the stored data;

[0103] The processor 220 is used to receive and output data information from each module, the data repository 210 and the display panel 240, and supports operations such as data import, conversion, and merging to ensure the quality and accuracy of the data. The algorithm includes statistical methods and machine learning methods;

[0104] The comparison component 230 is used to compare and analyze the mold, and provide possible causes of wear and tear and an adjusted mold additive solution, compare the scanned three-dimensional model with the mold of the optimal data, analyze the difference and similarity between the two, output a detailed analysis report according to the comparison results, and then improve the mold based on the comparison analysis results;

[0105] The display panel 240 is used to receive the data information transmitted by the processor 220, and to update the display results in real time based on the above data information, so as to display the analysis results in an intuitive manner.

[0106] Among them Figure 6 and Figure 7 As shown, the monitoring module 120 includes a temperature sensor unit 121, a humidity sensor unit 122, an air density sensor unit 123 and a position sensor unit 124;

[0107] The temperature sensor unit 121 is used to monitor the temperature of the mold service environment in real time;

[0108] The humidity sensor unit 122 is used to monitor the humidity of the mold service environment in real time;

[0109] The air density sensor unit 123 is used to monitor the air density of the mold service environment in real time;

[0110] The position sensor unit 124 is used to monitor the position information of the mold service environment in real time;

[0111] The temperature sensor unit 121, the humidity sensor unit 122, the air density sensor unit 123 and the position sensor unit 124 are electrically connected to each other, and the surrounding environment of the mold is monitored by a number of sensor units, including but not limited to temperature, humidity, air density and position information, so as to timely discover the impact of the environment on the mold and take corresponding measures to adjust it to ensure its normal operation.

[0112] Among them Figure 6 and Figure 7 As shown, the preprocessing module 130 includes a feature extraction unit 131, a data cleaning unit 132 and a data simplification unit 133;

[0113] The feature extraction unit 131 is used to extract point cloud data with representative geometric features from the scanned three-dimensional data of the mold, and the geometric features include the contour, curved surface, and hole of the mold, and extract features useful for subsequent analysis or modeling from the original data. The feature extraction methods include principal component analysis (PCA), linear discriminant analysis (LDA), etc.

[0114] The data cleaning unit 132 is used to remove noise and redundant information in the point cloud data, including but not limited to missing value processing, outlier processing, data smoothing, etc., so as to facilitate the processing of impurities and noise in the original data to ensure the accuracy and reliability of subsequent analysis;

[0115] The data simplification unit 133 is used to simplify the point cloud data. On the premise of ensuring accuracy, the point cloud data is simplified to reduce the data volume and improve processing efficiency. The simplification methods include but are not limited to quantity reduction, data compression, etc.

[0116] Among them Figure 6-Figure 9 As shown, the comparison component 230 includes an acquisition module 231, a comparison module 232, an early warning module 233, a drawing module 234 and an analysis module 235;

[0117] The acquisition module 231 is used to construct a three-dimensional model of the mold according to the processed point cloud data, and obtain the coordinate information of any position point of the mold model, providing a reliable data basis for subsequent comparison work;

[0118] The comparison module 232 is used to compare the three-dimensional model of the mold with the standard model, evaluate the wear of the mold based on the comparison result and calculate the three-dimensional deviation, and select different color RGB values ​​for drawing, and use different colors to display the deviation area color map. Using advanced comparison algorithms and technologies, the scanned three-dimensional model is accurately compared with the optimal data mold. The module can identify the differences in shape, size, position, etc. between the two and generate detailed comparison results;

[0119] The early warning module 233 is used to determine whether the mold deviation has reached the early warning threshold, and to issue an early warning to the mold that has reached the early warning threshold. The upper limit threshold of the mold wear degree is set to I 阈值 , the threshold can be adjusted according to the actual wear of the mold, so as to find the allowable difference value suitable for the change of mold wear;

[0120] The drawing module 234 is used to draw a deviation color map of the mold, so as to display the comparison result to the user in an intuitive manner, so that the user can clearly see the difference between the scanned three-dimensional model and the optimal data mold;

[0121] The analysis module 235 is used to compare and analyze the changes in the surrounding environment of the mold that has reached the threshold with historical data, and provide reasons that affect the degree of wear based on the above data, so as to improve the efficiency of mold optimization.

[0122] Among them Figure 5 As shown, an information access port 300 is provided on one side of the laser scanning device 100 and the data analysis device 200. The information access port 300 includes a wireless transmission port and a charging interface, which is connected to other power storage devices through the charging interface to provide power to the electrical components of the system, facilitating network connection and transportation operations.

[0123] Among them Figure 6-Figure 9 As shown, the comparison component 230 also includes an alarm module 236 electrically connected to the comparison module 232 and the warning module 233. The alarm module 236 is used to emit a warning sound after the mold reaches the warning threshold. The alarm module 236 includes but is not limited to an audible and visual alarm. When the parameters of the mold data exceed the preset threshold, a sound and light are emitted, and a warning signal is automatically sent to the user, and its information is transmitted to the display panel 240, so as to remind the user to pay attention to and deal with the problems found in the comparison.

[0124] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A digital management method for the entire life cycle of a mold, characterized in that: The following steps are involved: S1. Selecting a laser scanning device (100) with appropriate accuracy according to the type of mold; S2. After the mold is machined, scan the actual mold and compare it with the design drawing to get the difference value, and record the deviation value between the actual object and the design; S3. After the mold is developed, the developed data is scanned and compared with the actual object processed by the mold machine to obtain the optimal mold data and save it as a mold file; S4. Perform multiple maintenance operations on the mold, scan the surface of the mold in service during maintenance, compare it with the optimal drawing data to obtain the difference value, and record the data; S5. When it is found that the mold wear exceeds the allowable tolerance of the part, analyze the wear condition, adjust the additive formula, and develop the mold to keep it in service; S6. After the mold has completed 300,000 to 500,000 molds in its entire life cycle, compare the previous scan data and collect the above data to form a mold life cycle archive; S7. Retrieve the mold's entire life cycle archive and optimize subsequent new molds based on the archive.

2. The method for digital management of the entire mold life cycle according to claim 1 is characterized in that: The step S2 comprises: S21, scanning the mold using a laser scanning device (100) to obtain point cloud data at different positions on the mold surface; S22, removing noise and redundant information from the point cloud data, simplifying the point cloud data while ensuring accuracy, performing a surface reconstruction operation based on multiple point cloud data, obtaining a three-dimensional model of the mold, and acquiring coordinate information of any position point of the mold model; S23, comparing the coordinate information of the mold three-dimensional model with the coordinate information of the standard model, calculating the three-dimensional deviation, and selecting different color RGB values ​​for drawing, and displaying the deviation area color map through different colors.

3. The method for digital management of the entire mold life cycle according to claim 1 is characterized in that: The step S4 comprises: S41. When the mold is maintained after 10,000 molds have been used, scan the mold and compare it with the optimal value after research and matching to obtain the difference value and save the wear data; S42, when the mold is maintained after 30,000 molds have been used, scan the mold and compare it with the optimal value after research and matching, get the difference value, and save the wear data; S43, when the mold is maintained after 100,000 molds have been used, scan the mold and compare it with the optimal value after research and matching, obtain the difference value, and save the wear data; S44. When the mold is maintained after 200,000 molds have been used, scan the mold and compare it with the optimal value after research and matching to obtain the difference value and save the wear data.

4. The method for digital management of the entire mold life cycle according to claim 1 is characterized in that: The step S5 comprises: S51, when it is found that the three-dimensional deviation of the mold exceeds the allowable tolerance of the part, the mold wear cause is analyzed by the analysis module (235), the cause includes temperature, humidity, air density, position, and the mold service environment is adjusted; S52. Adjust the additive formula according to the three-dimensional deviation so that the above-mentioned mold can restore its geometric dimensions to the optimal value and continue to serve.

5. The method for digital management of the entire mold life cycle according to claim 1 is characterized in that: Also included is a digital management system for the entire life cycle of a mold, the system comprising a laser scanning device (100) and a data analysis device (200) communicating with each other via a network; The laser scanning device (100) is used to perform an all-round scan on the mold, obtain position information of the mold surface, and construct a three-dimensional model after pre-processing the position information. The laser scanning device (100) comprises an image acquisition module (110), a monitoring module (120) and a pre-processing module (130); The image acquisition module (110) is used to acquire image data of a scanned mold, wherein the image data includes wear parts, mold status, numbering information, and surface point cloud data; The monitoring module (120) is used to detect changes in the surrounding environment of the mold; The pre-processing module (130) is used to perform image data enhancement, noise removal and simplification operations on the above-mentioned image data; The data analysis device (200) is used to compare and analyze the scanned three-dimensional model with the mold of the optimal data, and to design and optimize the additive formulation based on the comparison and analysis results. The data analysis device (200) comprises a data storage library (210), a processor (220), a comparison component (230) and a display panel (240); The data repository (210) is used to collect, store and provide scanning history data and design drawing data of multiple molds, and divide a number of data corresponding to the molds into a number of groups according to the full life cycle of the molds to form a full life cycle archive of the molds; The processor (220) is used to receive and output data information of each module, a data storage library (210) and a display panel (240); The comparison component (230) is used to perform a comparison analysis operation on the mold and provide possible causes of wear and tear and an adjusted mold additive solution; The display panel (240) is used to receive data information transmitted by the processor (220), and to update the display result in real time based on the data information.

6. The method for digital management of the entire life cycle of molds according to claim 5 is characterized in that: The monitoring module (120) comprises a temperature sensor unit (121), a humidity sensor unit (122), an air density sensor unit (123) and a position sensor unit (124); The temperature sensor unit (121) is used to monitor the temperature of the mold service environment in real time; The humidity sensor unit (122) is used to monitor the humidity of the mold service environment in real time; The air density sensor unit (123) is used to monitor the air density of the mold service environment in real time; The position sensor unit (124) is used to monitor the position information of the mold service environment in real time.

7. The method for digital management of the entire life cycle of molds according to claim 5 is characterized in that: The preprocessing module (130) comprises a feature extraction unit (131), a data cleaning unit (132) and a data simplification unit (133); The feature extraction unit (131) is used to extract point cloud data with representative geometric features from the three-dimensional data of the mold obtained by scanning, and the geometric features include the contour, curved surface and hole of the mold; The data cleaning unit (132) is used to remove noise and redundant information in the point cloud data; The data simplification unit (133) is used to simplify point cloud data.

8. The method for digital management of the entire life cycle of molds according to claim 5 is characterized in that: The comparison component (230) includes an acquisition module (231), a comparison module (232), an early warning module (233), a drawing module (234) and an analysis module (235); The acquisition module (231) is used to construct a three-dimensional model of the mold according to the processed point cloud data, and to obtain coordinate information of any position point of the mold model; The comparison module (232) is used to compare the three-dimensional model of the mold with the standard model, evaluate the wear condition of the mold based on the comparison result and calculate the three-dimensional deviation, and select different color RGB values ​​for drawing, and display the deviation area color map through different colors; The early warning module (233) is used to determine whether the mold deviation has reached the early warning threshold, and to issue an early warning to the mold that has reached the early warning threshold. The upper limit threshold of the mold wear degree is set to I 阈值 ; The drawing module (234) is used to draw a deviation color map of the mold; The analysis module (235) is used to compare and analyze the changes in the surrounding environment of the mold that have reached a threshold with historical data, and provide reasons that affect the degree of wear based on the above data.

9. The method for digital management of the entire life cycle of molds according to claim 5 is characterized in that: An information access port (300) is provided on one side of each of the laser scanning device (100) and the data analysis device (200), and the information access port (300) comprises a wireless transmission port and a charging interface.

10. The method for digital management of the entire life cycle of molds according to claim 8, characterized in that: The comparison component (230) further comprises an alarm module (236) electrically connected to the comparison module (232) and the warning module (233), wherein the alarm module (236) is used to emit a warning sound after the mold reaches a warning threshold.

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