Intelligent management system for injection mold production

Abstract

The invention discloses an intelligent management system for injection mold production, and belongs to the field of intelligent management systems.Product production data in the injection mold production process are imported into a production quality analysis strategy for production quality analysis, and injection mold deformation data are imported into a mold defect analysis strategy for mold defect analysis; the production quality analysis result and the mold defect analysis result are integrated to carry out matching analysis of the mold and the production process, and mold replacement early warning is carried out according to the matching analysis result of the mold and the production process. The matching condition of the mold and the production process is accurately obtained, so that the mismatching condition of the mold and the production process is found in advance, and the production quality of subsequent products is improved.

Description

Technical Field

[0001] The invention belongs to the field of intelligent management systems, in particular to an intelligent management system for injection mold production. Background Art

[0002] An injection mold is a tool used to produce plastic products. It is a tool that injects molten plastic material into a mold and forms a product of the desired shape through pressurization and cooling. An injection mold is usually composed of a mold base, a mold core, a mold cavity, a cooling system, a discharge system, and other parts. The working principle of an injection mold is to first feed the plastic particles into the screw barrel of the injection molding machine through a feeding system, and then heat and melt them into a molten state. Next, the screw rotates to push the molten plastic forward so that it enters the nozzle of the injection mold. The molten plastic enters the mold cavity in the mold, fills the entire mold cavity and contacts the inner wall of the mold. At the same time, the cooling system in the mold absorbs heat from the mold, causing the plastic to cool and solidify rapidly. When the plastic is fully solidified, the mold separates and pushes out the molded part, and then the screw of the injection molding machine rotates and the injection process is repeated again. The working process of the entire injection mold is cyclically repeated to continuously produce plastic parts. However, the injection mold in the prior art is unable to match the mold and the production process through comprehensive production quality analysis results and mold defect analysis results during product production, which leads to the inability to accurately obtain the matching situation between the mold and the production process, and the inability to discover the mismatch between the mold and the production process in advance. The above problems exist in the prior art; in order to solve these problems, the present application designs an intelligent management system for injection mold production. Summary of the invention

[0003] In view of the deficiencies in the prior art, the present invention proposes an intelligent management system for injection mold production. The present invention obtains product production data and injection mold deformation data in the injection mold production process, imports the product production data in the injection mold production process into the production quality analysis strategy for production quality analysis, imports the injection mold deformation data into the mold defect analysis strategy for mold defect analysis, and performs matching analysis between the mold and the production process based on the comprehensive production quality analysis results and the mold defect analysis results. According to the matching analysis results between the mold and the production process, a mold replacement warning is issued. The present invention matches the mold and the production process by comprehensively analyzing the production quality analysis results and the mold defect analysis results, accurately obtains the matching situation of the mold and the production process, and discovers the mismatch between the mold and the production process in advance, thereby improving the subsequent product production quality.

[0004] To achieve the above object, the present invention provides the following technical solution: an intelligent management system for injection mold production, which includes a data acquisition module, a production quality analysis module, a mold defect analysis module, a mold matching analysis module, a mold replacement warning module and a control module:

[0005] Wherein, the data acquisition module is used to acquire product production data and injection mold deformation data during the injection mold production process;

[0006] The production quality analysis module is used to import product production data in the injection mold production process into the production quality analysis strategy to perform production quality analysis;

[0007] The mold defect analysis module is used to import the injection mold deformation data into the mold defect analysis strategy to perform mold defect analysis;

[0008] The mold matching analysis module is used to comprehensively analyze the production quality analysis results and the mold defect analysis results to perform matching analysis between the mold and the production process;

[0009] The mold replacement warning module is used to issue a mold replacement warning based on the matching analysis results between the mold and the production process;

[0010] The control module is used to control the operation of the data acquisition module, the production quality analysis module, the mold defect analysis module, the mold matching analysis module and the mold replacement early warning module.

[0011] As a preferred technical solution for an intelligent management system for injection mold production, the data acquisition module includes a product production data acquisition unit and an injection mold deformation data acquisition unit. The product production data acquisition unit is used to collect surface images of the produced products and dimensional data of each monitoring position, and at the same time collects bubble size and burr density data at each position on the surface of the produced products. The injection mold deformation data acquisition unit is used to collect dimensional deformation data and mold surface crack data during the mold operation process;

[0012] As a preferred technical solution for an intelligent management system for injection mold production, the production quality analysis strategy includes the following specific steps:

[0013] S11, obtaining a surface image of the product and dimension data of each monitoring position, and importing the obtained surface image of the product into an image analysis software to obtain pixel value data of each pixel point;

[0014] S12, importing the obtained pixel value data of each pixel point and the pixel value data of each pixel point corresponding to the standard production product into a pixel abnormal value calculation formula to calculate the pixel abnormal value, wherein the pixel abnormal value calculation formula is: Wherein, m is the number of pixels on the product, ci is the pixel value of the i-th pixel on the production product, and ciz is the pixel value data of the corresponding i-th pixel of the standard production product;

[0015] S13, importing the acquired dimension data of each monitoring position of the production product and the dimension data of each monitoring position of the standard production product into the dimension abnormality value calculation formula to calculate the dimension abnormality value, wherein the dimension abnormality value calculation formula is: Where n is the number of monitoring positions, xj is the distance from the jth monitoring position to the center point of the production product, yj is the dimensional data of the jth monitoring position of the production product, and yjz is the dimensional data of the jth monitoring position of the standard production product;

[0016] Through this step, the dimensional data of each monitoring position of the production product is compared with the dimensional data of each monitoring position of the standard production product to analyze the dimensional difference of each monitoring position. At the same time, the distance from the monitoring position to the center point of the production product is used as a weight to further improve the effect of the abnormal analysis of the production product size.

[0017] As an optimal technical solution for an intelligent management system for injection mold production, the production quality analysis strategy also includes the following specific steps:

[0018] S14, collecting bubble size and burr density data at various positions on the surface of the production product, importing the bubble size and burr density data at various positions on the surface of the production product into the production product defect abnormal value calculation formula to calculate the production product defect abnormal value, wherein the production product defect abnormal value calculation formula is: Wherein, a is the bubble ratio, N is the number of bubbles, Sv is the area of ​​the vth bubble, Dv is the distance from the vth bubble to the center of the product, Sm is the maximum area of ​​the safety bubble, ρm is the burr density data, and ρmz is the maximum value of the safety range of the burr density data;

[0019] Through this step, the bubble size and burr density data at various locations on the surface of the product are comprehensively analyzed, and then the surface abnormalities of the product are accurately analyzed;

[0020] S15, substituting the calculated pixel abnormal value, size abnormal value and production product defect abnormal value into the production quality abnormal value calculation formula to calculate the production quality abnormal value, wherein the production quality abnormal value calculation formula is: Hs=b1Xs+b2Qs+Ns, wherein b1 is the pixel abnormality ratio coefficient, and b2 is the size abnormality ratio coefficient;

[0021] As an optimal technical solution for an intelligent management system for injection mold production, the mold defect analysis strategy includes the following specific steps:

[0022] S21, obtaining dimensional deformation data and mold surface crack data during the mold operation process;

[0023] S22, importing the dimensional deformation data of the mold operation process into the mold dimensional defect analysis value calculation formula to calculate the mold dimensional defect analysis value, wherein the mold dimensional defect analysis value calculation formula is: Wherein, V() is the volume of the three-dimensional figure in the brackets, Ac is the three-dimensional shape data of the mold when it is initially used, Bc is the real-time three-dimensional shape data of the mold during operation, ∪ is the union of the three-dimensional shapes of two molds in the same direction, and ∩ is the intersection of the three-dimensional shapes of two molds in the same direction;

[0024] S23, obtaining real-time surface crack data of the mold during operation, and importing the obtained real-time surface crack data of the mold during operation into a mold crack defect analysis value calculation formula to calculate the mold crack defect analysis value, wherein the mold crack defect analysis value calculation formula is: Where C is the standard value of crack distance, Cx is the average distance between surface cracks, R is the number of cracks, lr is the length of the rth crack, dr is the width of the rth crack, is the safe length of the crack, is the safe width of the crack;

[0025] S24. Obtain the calculated mold size defect analysis value and mold crack defect analysis value and substitute them into the mold defect abnormality analysis value calculation formula to calculate the mold defect abnormality analysis value, wherein the mold defect abnormality analysis value calculation formula is: Dc=χHc+(1-χ)Lc, wherein χ is the size defect ratio coefficient.

[0026] As an optimal technical solution for an intelligent management system for injection mold production, the matching analysis between the mold and the production process based on the comprehensive production quality analysis results and the mold defect analysis results includes the following specific steps:

[0027] S31, obtaining the calculated production quality abnormality value and mold defect abnormality analysis value;

[0028] S32, substituting the obtained production quality abnormal value and mold defect abnormal analysis value into the matching abnormal value calculation formula to calculate the matching abnormal value, wherein the matching abnormal value calculation formula is: J=θHs+(1-θ)Dc, wherein θ is the production quality ratio coefficient;

[0029] S33. Compare the calculated matching anomaly value with the set matching anomaly threshold. If the calculated matching anomaly value is greater than or equal to the set matching anomaly threshold, it means that the mold does not match the production process. If the calculated matching anomaly value is less than the set matching anomaly threshold, it means that the mold matches the production process.

[0030] As an optimal technical solution for an intelligent management system for injection mold production, the specific content of the mold replacement warning based on the matching analysis results of the mold and the production process is: if the mold and the production process are judged to be mismatched, the staff will be reminded to replace the mold; if the mold and the production process are judged to be matched, the staff will not be reminded to replace the mold.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] The present invention obtains product production data and injection mold deformation data in the injection mold production process, imports the product production data in the injection mold production process into a production quality analysis strategy for production quality analysis, imports the injection mold deformation data into a mold defect analysis strategy for mold defect analysis, comprehensively analyzes the matching of the mold and the production process based on the production quality analysis results and the mold defect analysis results, and issues a mold replacement warning based on the matching analysis results of the mold and the production process. The present invention matches the mold and the production process by comprehensively analyzing the production quality analysis results and the mold defect analysis results, accurately obtains the matching situation of the mold and the production process, and discovers the mismatch between the mold and the production process in advance, thereby improving the subsequent product production quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a schematic diagram of the overall framework of an intelligent management system for injection mold production according to the present invention;

[0034] Figure 2 This is a schematic diagram of a data acquisition module framework of an intelligent management system for injection mold production according to the present invention;

[0035] Figure 3 It is a schematic diagram of the production quality analysis strategy flow in an intelligent management system for injection mold production of the present invention;

[0036] Figure 4 The present invention is a schematic diagram of the mold defect analysis strategy flow in an intelligent management system for injection mold production. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present invention will be described clearly and completely 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, rather than all the embodiments.

[0038] Example 1

[0039] The technical problem solved by this embodiment is that the injection mold in the prior art cannot perform matching analysis between the mold and the production process by integrating the production quality analysis results and the mold defect analysis results during the product production process, thereby failing to accurately obtain the matching situation between the mold and the production process, and failing to discover the mismatch between the mold and the production process in advance;

[0040] To solve the above problems, please refer to Figure 1 The present invention provides a preferred embodiment: Figure 1 As shown, an intelligent management system for injection mold production includes a data acquisition module, a production quality analysis module, a mold defect analysis module, a mold matching analysis module, a mold replacement warning module and a control module:

[0041] Among them, the data acquisition module is used to obtain product production data and injection mold deformation data during the injection mold production process;

[0042] Production quality analysis module, used to import product production data in the injection mold production process into the production quality analysis strategy for production quality analysis;

[0043] Mold defect analysis module, used to import the injection mold deformation data into the mold defect analysis strategy for mold defect analysis;

[0044] Mold matching analysis module, used to conduct matching analysis between mold and production process based on comprehensive production quality analysis results;

[0045] The mold replacement warning module is used to issue mold replacement warnings based on the matching analysis results between the mold and the production process;

[0046] A control module, used to control the operation of a data acquisition module, a production quality analysis module, a mold defect analysis module, a mold matching analysis module, and a mold replacement early warning module;

[0047] A further improvement in this embodiment is that Figure 2 As shown, the data acquisition module includes a product production data acquisition unit and an injection mold deformation data acquisition unit. The product production data acquisition unit is used to collect the surface image of the product and the size data of each monitoring position, and at the same time collect the bubble size and burr density data of each position on the surface of the product. The injection mold deformation data acquisition unit is used to collect the size deformation data of the mold operation process and the mold surface crack data;

[0048] It should be noted here that the specific steps for the image acquisition terminal to collect the surface image of the injection molded product and the dimensional data of each monitoring position can be as follows: Set up the image acquisition device: According to actual needs, select a suitable image acquisition device, such as a camera, scanner, etc. Place the device in a suitable position so that the surface image of the injection molded product can be clearly captured; Adjust acquisition parameters: According to the characteristics and requirements of the injection molded product, adjust the parameters of the image acquisition device, such as exposure time, focal length, aperture, etc., to ensure that the quality and clarity of the collected image meet the requirements; Collect surface images: Start the image acquisition device to collect images of the surface of the injection molded product, ensure that the collected image contains the entire surface of the product, and minimize the impact of factors such as light and shadow on the image quality; Extract dimensional data: In the collected image, use image processing and analysis technology to extract the dimensional data of each monitoring position. This can be achieved through edge detection, region growing, threshold segmentation and other methods;

[0049] At the same time, the specific steps of collecting the bubble size and burr density data at various positions on the surface of the production product can be as follows: converting the collected image information into digital signals and transmitting them to a dedicated image processing system, performing denoising, enhancement, segmentation and other processing on the digital signals to extract characteristic information on the product surface, such as bubbles and burrs, extracting these features from the enhanced image based on the characteristics of the bubbles and burrs (such as size, shape, color, etc.), comparing and identifying the processed images through a preset algorithm and a defect feature library, thereby determining whether bubbles exist on the product surface and the size of the bubbles, and evaluating the density of the burrs, recording the detected bubble size and burr density data, and performing statistical analysis on these data to understand their distribution at various positions on the product surface;

[0050] A further improvement in this embodiment is that Figure 3 As shown, the production quality analysis strategy includes the following specific steps:

[0051] S11, obtaining a surface image of the product and dimension data of each monitoring position, and importing the obtained surface image of the product into an image analysis software to obtain pixel value data of each pixel point;

[0052] S12, importing the obtained pixel value data of each pixel point and the pixel value data of each pixel point corresponding to the standard production product into a pixel abnormal value calculation formula to calculate the pixel abnormal value, wherein the pixel abnormal value calculation formula is: Wherein, m is the number of pixels on the product, ci is the pixel value of the i-th pixel on the production product, and ciz is the pixel value data of the corresponding i-th pixel of the standard production product;

[0053] Through this step, the difference between each pixel of the product and the corresponding pixel of the standard production product is analyzed and evaluated for product anomalies;

[0054] S13, importing the acquired dimension data of each monitoring position of the production product and the dimension data of each monitoring position of the standard production product into the dimension abnormality value calculation formula to calculate the dimension abnormality value, wherein the dimension abnormality value calculation formula is: Where n is the number of monitoring positions, xj is the distance from the jth monitoring position to the center point of the production product, yj is the dimensional data of the jth monitoring position of the production product, and yjz is the dimensional data of the jth monitoring position of the standard production product;

[0055] Through this step, the dimensional data of each monitoring position of the production product is compared with the dimensional data of each monitoring position of the standard production product to analyze the dimensional difference of each monitoring position. At the same time, the distance from the monitoring position to the center point of the production product is used as a weight to further improve the effect of the abnormal analysis of the production product size.

[0056] The production quality analysis strategy also includes the following specific steps:

[0057] S14, collecting bubble size and burr density data at various positions on the surface of the production product, importing the bubble size and burr density data at various positions on the surface of the production product into the production product defect abnormal value calculation formula to calculate the production product defect abnormal value, wherein the production product defect abnormal value calculation formula is: Wherein, a is the bubble ratio, N is the number of bubbles, Sv is the area of ​​the vth bubble, Dv is the distance from the vth bubble to the center of the product, Sm is the maximum area of ​​the safety bubble, ρm is the burr density data, and ρmz is the maximum value of the safety range of the burr density data;

[0058] Through this step, the bubble size and burr density data at various locations on the surface of the product are comprehensively analyzed, and then the surface abnormalities of the product are accurately analyzed;

[0059] S15, substituting the calculated pixel abnormal value, size abnormal value and production product defect abnormal value into the production quality abnormal value calculation formula to calculate the production quality abnormal value, wherein the production quality abnormal value calculation formula is: Hs=b1Xs+b2Qs+Ns, wherein b1 is the pixel abnormality ratio coefficient, and b2 is the size abnormality ratio coefficient;

[0060] In this embodiment, the production quality abnormal value is used as the matching abnormal value, and the calculated matching abnormal value is compared with the set matching abnormal threshold. If the calculated matching abnormal value is greater than or equal to the set matching abnormal threshold, it means that the mold does not match the production process. If the calculated matching abnormal value is less than the set matching abnormal threshold, it means that the mold matches the production process. If the judgment result that the mold does not match the production process is obtained, the staff is reminded to replace the mold. If the judgment result that the mold matches the production process is obtained, the staff is not reminded to replace the mold.

[0061] It should be noted that in this embodiment, the advantage of this embodiment over the prior art is that in this embodiment, product production data in the injection mold production process is used as a reference indicator to perform a matching analysis of the mold and the production process, and the matching situation of the mold and the production process is accurately obtained, so as to discover the mismatch between the mold and the production process in advance.

[0062] Example 2

[0063] This embodiment adds a mold defect analysis strategy implementation method based on the embodiment 1. The specific content of this embodiment is as follows: Figure 1 As shown, an intelligent management system for injection mold production includes a data acquisition module, a production quality analysis module, a mold defect analysis module, a mold matching analysis module, a mold replacement warning module and a control module:

[0064] Among them, the data acquisition module is used to obtain product production data and injection mold deformation data during the injection mold production process;

[0065] Production quality analysis module, used to import product production data in the injection mold production process into the production quality analysis strategy for production quality analysis;

[0066] Mold defect analysis module, used to import the injection mold deformation data into the mold defect analysis strategy for mold defect analysis;

[0067] Mold matching analysis module, used to analyze the matching between mold and production process by integrating production quality analysis results and mold defect analysis results;

[0068] The mold replacement warning module is used to issue mold replacement warnings based on the matching analysis results between the mold and the production process;

[0069] A control module, used to control the operation of a data acquisition module, a production quality analysis module, a mold defect analysis module, a mold matching analysis module, and a mold replacement early warning module;

[0070] A further improvement in this embodiment is that Figure 2As shown, the data acquisition module includes a product production data acquisition unit and an injection mold deformation data acquisition unit. The product production data acquisition unit is used to collect the surface image of the product and the size data of each monitoring position, and at the same time collect the bubble size and burr density data of each position on the surface of the product. The injection mold deformation data acquisition unit is used to collect the size deformation data of the mold operation process and the mold surface crack data;

[0071] It should be noted here that the specific steps for the image acquisition terminal to collect the surface image of the injection molded product and the dimensional data of each monitoring position can be as follows: Set up the image acquisition device: According to actual needs, select a suitable image acquisition device, such as a camera, scanner, etc. Place the device in a suitable position so that the surface image of the injection molded product can be clearly captured; Adjust acquisition parameters: According to the characteristics and requirements of the injection molded product, adjust the parameters of the image acquisition device, such as exposure time, focal length, aperture, etc., to ensure that the quality and clarity of the collected image meet the requirements; Collect surface images: Start the image acquisition device to collect images of the surface of the injection molded product, ensure that the collected image contains the entire surface of the product, and minimize the impact of factors such as light and shadow on the image quality; Extract dimensional data: In the collected image, use image processing and analysis technology to extract the dimensional data of each monitoring position. This can be achieved through edge detection, region growing, threshold segmentation and other methods;

[0072] At the same time, the specific steps of collecting the bubble size and burr density data at various positions on the surface of the production product can be as follows: converting the collected image information into digital signals and transmitting them to a dedicated image processing system, performing denoising, enhancement, segmentation and other processing on the digital signals to extract characteristic information on the product surface, such as bubbles and burrs, extracting these features from the enhanced image based on the characteristics of the bubbles and burrs (such as size, shape, color, etc.), comparing and identifying the processed images through a preset algorithm and a defect feature library, thereby determining whether bubbles exist on the product surface and the size of the bubbles, and evaluating the density of the burrs, recording the detected bubble size and burr density data, and performing statistical analysis on these data to understand their distribution at various positions on the product surface;

[0073] A further improvement in this embodiment is that Figure 3 As shown, the production quality analysis strategy includes the following specific steps:

[0074] S11, obtaining a surface image of the product and dimension data of each monitoring position, and importing the obtained surface image of the product into an image analysis software to obtain pixel value data of each pixel point;

[0075] S12, importing the obtained pixel value data of each pixel point and the pixel value data of each pixel point corresponding to the standard production product into a pixel abnormal value calculation formula to calculate the pixel abnormal value, wherein the pixel abnormal value calculation formula is: Wherein, m is the number of pixels on the product, ci is the pixel value of the i-th pixel on the production product, and ciz is the pixel value data of the corresponding i-th pixel of the standard production product;

[0076] Through this step, the difference between each pixel of the product and the corresponding pixel of the standard production product is analyzed and evaluated for product anomalies;

[0077] S13, importing the acquired dimension data of each monitoring position of the production product and the dimension data of each monitoring position of the standard production product into the dimension abnormality value calculation formula to calculate the dimension abnormality value, wherein the dimension abnormality value calculation formula is: Where n is the number of monitoring positions, xj is the distance from the jth monitoring position to the center point of the production product, yj is the dimensional data of the jth monitoring position of the production product, and yjz is the dimensional data of the jth monitoring position of the standard production product;

[0078] Through this step, the dimensional data of each monitoring position of the production product is compared with the dimensional data of each monitoring position of the standard production product to analyze the dimensional difference of each monitoring position. At the same time, the distance from the monitoring position to the center point of the production product is used as a weight to further improve the effect of the abnormal analysis of the production product size.

[0079] The production quality analysis strategy also includes the following specific steps:

[0080] S14, collecting bubble size and burr density data at various positions on the surface of the production product, importing the bubble size and burr density data at various positions on the surface of the production product into the production product defect abnormal value calculation formula to calculate the production product defect abnormal value, wherein the production product defect abnormal value calculation formula is: Wherein, a is the bubble ratio, N is the number of bubbles, Sv is the area of ​​the vth bubble, Dv is the distance from the vth bubble to the center of the product, Sm is the maximum area of ​​the safety bubble, ρm is the burr density data, and ρmz is the maximum value of the safety range of the burr density data;

[0081] Through this step, the bubble size and burr density data at various locations on the surface of the product are comprehensively analyzed, and then the surface abnormalities of the product are accurately analyzed;

[0082] S15, substituting the calculated pixel abnormal value, size abnormal value and production product defect abnormal value into the production quality abnormal value calculation formula to calculate the production quality abnormal value, wherein the production quality abnormal value calculation formula is: Hs=b1Xs+b2Qs+Ns, wherein b1 is the pixel abnormality ratio coefficient, and b2 is the size abnormality ratio coefficient;

[0083] In this embodiment, if Figure 4 As shown, the mold defect analysis strategy includes the following specific steps:

[0084] S21, obtaining dimensional deformation data and mold surface crack data during the mold operation process;

[0085] S22, importing the dimensional deformation data of the mold operation process into the mold dimensional defect analysis value calculation formula to calculate the mold dimensional defect analysis value, wherein the mold dimensional defect analysis value calculation formula is: Wherein, V() is the volume of the three-dimensional figure in the brackets, Ac is the three-dimensional shape data of the mold when it is initially used, Bc is the real-time three-dimensional shape data of the mold during operation, ∪ is the union of the three-dimensional shapes of two molds in the same direction, and ∩ is the intersection of the three-dimensional shapes of two molds in the same direction;

[0086] S23, obtaining real-time surface crack data of the mold during operation, and importing the obtained real-time surface crack data of the mold during operation into a mold crack defect analysis value calculation formula to calculate the mold crack defect analysis value, wherein the mold crack defect analysis value calculation formula is: Where C is the standard value of crack distance, Cx is the average distance between surface cracks, R is the number of cracks, lr is the length of the rth crack, dr is the width of the rth crack, is the safe length of the crack, is the safe width of the crack;

[0087] S24, obtaining the calculated mold size defect analysis value and mold crack defect analysis value, and substituting them into the mold defect abnormality analysis value calculation formula to calculate the mold defect abnormality analysis value, wherein the mold defect abnormality analysis value calculation formula is: Dc=χHc+(1-χ)Lc, wherein χ is the size defect ratio coefficient;

[0088] In this embodiment, the matching analysis between the mold and the production process based on the comprehensive production quality analysis results and the mold defect analysis results includes the following specific steps:

[0089] S31, obtaining the calculated production quality abnormality value and mold defect abnormality analysis value;

[0090] S32, substituting the obtained production quality abnormal value and mold defect abnormal analysis value into the matching abnormal value calculation formula to calculate the matching abnormal value, wherein the matching abnormal value calculation formula is: J=θHs+(1-θ)Dc, wherein θ is the production quality ratio coefficient;

[0091] S33, comparing the calculated matching abnormality value with the set matching abnormality threshold, if the calculated matching abnormality value is greater than or equal to the set matching abnormality threshold, it means that the mold does not match the production process, if the calculated matching abnormality value is less than the set matching abnormality threshold, it means that the mold matches the production process;

[0092] The specific content of the mold replacement warning based on the matching analysis results of the mold and the production process is: if the mold and the production process are judged to be mismatched, the staff will be reminded to replace the mold; if the mold and the production process are judged to be matched, the staff will not be reminded to replace the mold.

[0093] The advantages of this embodiment over the first embodiment are as follows: obtaining product production data and injection mold deformation data during the injection mold production process, importing the product production data during the injection mold production process into the production quality analysis strategy for production quality analysis, importing the injection mold deformation data into the mold defect analysis strategy for mold defect analysis, performing matching analysis between the mold and the production process based on the comprehensive production quality analysis results and the mold defect analysis results, and issuing a mold replacement warning based on the matching analysis results between the mold and the production process. The present invention matches the mold and the production process by comprehensively analyzing the production quality analysis results and the mold defect analysis results, accurately obtaining the matching situation between the mold and the production process, so as to detect the mismatch between the mold and the production process in advance, thereby improving the subsequent product production quality.

[0094] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An intelligent management system for injection mold production, characterized in that: It includes data acquisition module, production quality analysis module, mold defect analysis module, mold matching analysis module, mold replacement warning module and control module: Wherein, the data acquisition module is used to acquire product production data and injection mold deformation data during the injection mold production process; The production quality analysis module is used to import product production data in the injection mold production process into the production quality analysis strategy to perform production quality analysis; The mold defect analysis module is used to import the injection mold deformation data into the mold defect analysis strategy to perform mold defect analysis; The mold matching analysis module is used to comprehensively analyze the production quality analysis results and the mold defect analysis results to perform matching analysis between the mold and the production process; The mold replacement warning module is used to issue a mold replacement warning based on the matching analysis results between the mold and the production process; The control module is used to control the operation of the data acquisition module, the production quality analysis module, the mold defect analysis module, the mold matching analysis module and the mold replacement early warning module.

2. An intelligent management system for injection mold production as claimed in claim 1, characterized in that: The data acquisition module includes a product production data acquisition unit and an injection mold deformation data acquisition unit. The product production data acquisition unit is used to collect surface images of the products and dimensional data of each monitoring position, and at the same time collect bubble size and burr density data at each position on the surface of the products. The injection mold deformation data acquisition unit is used to collect dimensional deformation data and mold surface crack data during the mold operation process.

3. An intelligent management system for injection mold production as claimed in claim 2, characterized in that: The production quality analysis strategy includes the following specific steps: S11, obtaining a surface image of the product and dimension data of each monitoring position, and importing the obtained surface image of the product into an image analysis software to obtain pixel value data of each pixel point; S12, importing the obtained pixel value data of each pixel point and the pixel value data of each pixel point corresponding to the standard production product into a pixel abnormal value calculation formula to calculate the pixel abnormal value, wherein the pixel abnormal value calculation formula is: Wherein, m is the number of pixels on the product, ci is the pixel value of the i-th pixel on the production product, and ciz is the pixel value data of the corresponding i-th pixel of the standard production product; S13, importing the acquired dimension data of each monitoring position of the production product and the dimension data of each monitoring position of the standard production product into the dimension abnormality value calculation formula to calculate the dimension abnormality value, wherein the dimension abnormality value calculation formula is: Wherein, n is the number of monitoring positions, xj is the distance from the jth monitoring position to the center point of the production product, yj is the dimensional data of the jth monitoring position of the production product, and yjz is the dimensional data of the jth monitoring position of the standard production product.

4. An intelligent management system for injection mold production as claimed in claim 3, characterized in that: The production quality analysis strategy also includes the following specific steps: S14, collecting bubble size and burr density data at various positions on the surface of the production product, importing the bubble size and burr density data at various positions on the surface of the production product into the production product defect abnormal value calculation formula to calculate the production product defect abnormal value, wherein the production product defect abnormal value calculation formula is: Wherein, a is the bubble ratio, N is the number of bubbles, Sv is the area of ​​the vth bubble, Dv is the distance from the vth bubble to the center of the product, Sm is the maximum area of ​​the safety bubble, ρm is the burr density data, and ρmz is the maximum value of the safety range of the burr density data; S15. Substitute the calculated pixel abnormality value, size abnormality value and production product defect abnormality value into the production quality abnormality value calculation formula to calculate the production quality abnormality value, where the production quality abnormality value calculation formula is: Hs=b1Xs+b2Qs+Ns, where b1 is the pixel abnormality ratio coefficient, and b2 is the size abnormality ratio coefficient.

5. An intelligent management system for injection mold production as claimed in claim 4, characterized in that: The mold defect analysis strategy includes the following specific steps: S21, obtaining dimensional deformation data and mold surface crack data during the mold operation process; S22, importing the dimensional deformation data of the mold operation process into the mold dimensional defect analysis value calculation formula to calculate the mold dimensional defect analysis value, wherein the mold dimensional defect analysis value calculation formula is: Wherein, V() is the volume of the three-dimensional figure in the brackets, Ac is the three-dimensional shape data of the mold when it is initially used, Bc is the real-time three-dimensional shape data of the mold during operation, ∪ is the union of the three-dimensional shapes of two molds in the same direction, and ∩ is the intersection of the three-dimensional shapes of two molds in the same direction; S23, obtaining real-time surface crack data of the mold during operation, and importing the obtained real-time surface crack data of the mold during operation into a mold crack defect analysis value calculation formula to calculate the mold crack defect analysis value, wherein the mold crack defect analysis value calculation formula is: Where C is the standard value of crack distance, Cx is the average distance between surface cracks, R is the number of cracks, lr is the length of the rth crack, dr is the width of the rth crack, is the safe length of the crack, is the safe width of the crack; S24. Obtain the calculated mold size defect analysis value and mold crack defect analysis value and substitute them into the mold defect abnormality analysis value calculation formula to calculate the mold defect abnormality analysis value, wherein the mold defect abnormality analysis value calculation formula is: Dc=χHc+(1-χ)Lc, wherein χ is the size defect ratio coefficient.

6. An intelligent management system for injection mold production as claimed in claim 5, characterized in that: The comprehensive production quality analysis results and mold defect analysis results are used to perform matching analysis between the mold and the production process, including the following specific steps: S31, obtaining the calculated production quality abnormality value and mold defect abnormality analysis value; S32. Substitute the obtained production quality abnormality value and mold defect abnormality analysis value into the matching abnormality value calculation formula to calculate the matching abnormality value, wherein the matching abnormality value calculation formula is: J=θHs+(1-θ)Dc, wherein θ is the production quality ratio coefficient.

7. An intelligent management system for injection mold production as claimed in claim 6, characterized in that: The comprehensive production quality analysis results and mold defect analysis results are used to perform matching analysis on the mold and the production process, and the following specific steps are also included: comparing the calculated matching anomaly value with the set matching anomaly threshold; if the calculated matching anomaly value is greater than or equal to the set matching anomaly threshold, it indicates that the mold and the production process do not match; if the calculated matching anomaly value is less than the set matching anomaly threshold, it indicates that the mold and the production process match.

8. An intelligent management system for injection mold production as claimed in claim 7, characterized in that: The specific content of the mold replacement warning based on the matching analysis result of the mold and the production process is: if the mold and the production process are judged not to match, the staff will be reminded to replace the mold; if the mold and the production process are judged to match, the staff will not be reminded to replace the mold.

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