Mold process compiling method and system based on AI

Abstract

The invention discloses an AI-based mold process compiling method and system, and the method comprises the steps: obtaining a 3D drawing of a part contained in a to-be-processed mold, and storing the 3D drawing in a part design library; searching similar historical parts in the part design library through an AI technology on the basis of the corresponding 3D drawings for each part contained in a to-be-machined mold, and obtaining information of the similar historical parts; according to the information of the similar historical parts, similar machining processes of the similar historical parts are extracted from a part process library, and machining processes are compiled for the parts based on the similar machining processes; and extracting process suggestions and processing steps from the industry knowledge base through an AI technology on the basis of the characteristics of the to-be-processed mold and the parts thereof, and finishing the processing process compiling of the to-be-processed mold on the basis of the process suggestions and the processing steps. According to the invention, the precision and efficiency of mould processing technology compilation can be greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of mold manufacturing information systems, and in particular to an AI-based mold process compilation method and system. Background Art

[0002] The importance of technology in the mold manufacturing process is extremely high, because it directly affects the quality of the mold, production efficiency, cost control and the accuracy and performance of the final product. The mold manufacturing process not only involves mold design and the selection of processing methods, but also covers every detail of the production process, which determines the feasibility and benefits of the entire mold manufacturing. Through reasonable process design and optimization, technical and economic requirements can be met to ensure the long-term reliability and stability of the mold.

[0003] In the existing technology, there are many problems in the traditional process preparation in the mold manufacturing process: low efficiency and long preparation cycle. Traditional process preparation relies on manual operation, manual calculation and experience accumulation, which is not only time-consuming and labor-intensive, but also prone to errors. Especially when facing complex parts or high-precision molds, the time and energy required for manual preparation far exceeds that of the automated system; the process plan is not optimized enough and there is a lot of repetitive work. Traditional process preparation often relies on experienced process engineers and lacks systematic theoretical and data support. Many process preparation tasks are repetitive, such as preparing processes for similar parts many times, manually drawing drawings, etc., which not only wastes a lot of time, but also increases the probability of errors; lack of standardization leads to unstable process quality. Different companies and different process engineers use different process methods and standards, which may lead to different results of process preparation and lack of consistency. It is easy to bring about unstable process quality and affect the quality of the final product; the personnel dependence is strong, and it is difficult to achieve knowledge inheritance. Traditional process preparation often relies on experienced process engineers to make decisions, and the personal experience and knowledge level of engineers directly affect the quality of the process plan. Once these senior engineers leave or change, the technology and knowledge gaps faced by the company may lead to difficulties in process preparation.

[0004] Based on the defects in the prior art, the present invention proposes a mold process compilation method and system based on AI. Summary of the invention

[0005] The main purpose of the present invention is to provide an AI-based mold process compilation method and system, which can realize the automatic generation of process routes for all parts under the mold through intelligent means.

[0006] The technical solution adopted by the present invention is: a mold process compilation method based on AI, comprising:

[0007] Obtaining 3D drawings of parts included in the mold to be processed, and storing the 3D drawings in a parts design library, which is a database containing 3D drawings of all historical parts;

[0008] For each part included in the mold to be processed, based on the corresponding 3D drawings, similar historical parts are retrieved in the part design library through AI technology, and information of the similar historical parts is obtained; based on the information of the similar historical parts, similar processing techniques of the similar historical parts are extracted from the part process library, and processing techniques are compiled for the parts based on the similar processing techniques. The part process library is a database containing processing techniques of all historical parts;

[0009] Based on the characteristics of the mold to be processed and its parts, AI technology is used to extract process suggestions and processing steps from the industry knowledge base, and the processing technology of the mold to be processed is compiled based on the process suggestions and processing steps. The industry knowledge base is a database containing processing technologies of different industries.

[0010] According to the above technical solution, based on the 3D drawing, the method for retrieving similar historical parts in the part design library specifically includes:

[0011] Verify the file format of 3D drawings and perform deep recognition through AI technology to obtain information such as part shape, structure, and size contained in the 3D drawings;

[0012] Convert the part shape, structure, size and other information contained in the 3D drawing into feature parameters, and retrieve historical parts containing similar feature parameters in the part design library through AI technology;

[0013] Through AI technology, the similarity values ​​between the historical parts containing similar feature parameters and the corresponding parts of the current 3D drawing are analyzed and sorted. A preset number of historical parts containing similar feature parameters are selected as similar historical parts in descending order of similarity.

[0014] According to the above technical solution, the information of similar historical parts includes the name, part number and material of each similar historical part.

[0015] According to the above technical solution, when compiling a processing technology for a part based on the similar processing technology, AI technology is used to identify unreasonable processing technologies based on the characteristics of the parts and the processing difficulty, and improve the processing technology of the parts.

[0016] According to the above technical solution, based on the requirements of the processing technology of the parts and the processing technology of the mold, the most suitable processing equipment is matched for the processing technology of the parts and the processing technology of the mold through AI technology.

[0017] According to the above technical solution, when compiling a processing technology for a part based on the similar processing technology, AI technology is used to match the most appropriate processing technology and tool configuration for the processing technology of the part according to the material, historical data and process experience of the part.

[0018] According to the above technical scheme, before compiling the part processing technology, the similar historical parts retrieved by AI technology are confirmed and corrected; before compiling the processing technology of the mold to be processed, the similar processing technology extracted by AI technology is confirmed and corrected.

[0019] Another aspect of the present invention provides an AI-based mold process compilation system, which executes the above-mentioned AI-based mold process compilation method; including a data acquisition layer, a data processing and analysis layer, a process recommendation and optimization layer, a process generation and feedback layer, and a user interface layer;

[0020] Among them, the data acquisition layer includes a part design library, a part process library and an industry knowledge base, the part design library is a database containing 3D drawings of all historical parts, the part process library is a database containing the processing technology of all historical parts, and the industry knowledge base is a database containing the processing technology of different industries; the data processing and analysis layer is used to retrieve similar historical parts in the part design library through AI technology; the process recommendation and optimization layer is used to extract similar processing technologies of similar historical parts in the part process library through AI technology; the process generation and feedback layer is used to compile processing technologies for parts based on the similar processing technologies through AI technology, and complete the compilation of processing technologies for the mold to be processed based on the characteristics of the mold to be processed and its parts; the user interface layer is used to realize information interaction between the system and the user.

[0021] Another aspect of the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned AI-based mold process compilation method when executing the computer program.

[0022] Another aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the above-mentioned AI-based mold process compilation method are implemented.

[0023] The beneficial effects of the present invention are as follows: the present invention provides an AI-based mold process compilation method and system, which, based on the massive data of multiple databases, completes the retrieval of similar historical parts, the compilation of parts processing technology and the compilation of mold processing technology for processing molds and the parts contained therein through AI technology. The compilation of mold processing technology no longer relies solely on human experience, but is achieved through multi-dimensional intelligent analysis and big data learning, which greatly improves the accuracy and efficiency of mold processing technology compilation.

[0024] Furthermore, the present invention can automatically identify unreasonable process paths through AI technology and propose improvement suggestions, thereby improving the efficiency of mold processing;

[0025] Furthermore, the present invention uses AI technology to match the most suitable processing equipment for the processing technology of parts and molds, which can reasonably dispatch equipment resources, optimize the configuration of production lines, and avoid waste of resources;

[0026] Furthermore, the present invention matches the most suitable processing technology and tool configuration for the processing technology of the part through AI technology, which can improve the processing quality and processing efficiency of the part.

[0027] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0029] Figure 1 is a flow chart of a mold process compilation method based on AI according to an embodiment of the present invention;

[0030] Figure 2 It is a structural diagram of an AI-based mold process compilation system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solution 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. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0032] It should be noted that the illustrations provided in the embodiments of the present invention are only used to illustrate the basic concept of the present invention in a schematic manner. Therefore, the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout type may also be more complicated.

[0033] In the present invention, it is also necessary to explain that, if the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. appear, the orientation or position relationship indicated is based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present application and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application. In addition, if the terms "first" and "second" appear, they are only used for description and distinction purposes, and cannot be understood as indicating or implying relative importance.

[0034] Example 1

[0035] This embodiment provides a mold process compilation method based on AI, the process is as follows Figure 1 Shown, including

[0036] S1. Obtain 3D drawings of parts included in the mold to be processed, and store the 3D drawings in a part design library, which is a database containing 3D drawings of all historical parts.

[0037] S2. For each part included in the mold to be processed, based on the corresponding 3D drawings, similar historical parts are retrieved in the part design library through AI technology, and the information of the similar historical parts is obtained; based on the information of the similar historical parts, similar processing techniques of the similar historical parts are extracted from the part process library, and processing techniques are compiled for the parts based on the similar processing techniques. The part process library is a database containing the processing techniques of all historical parts. By implementing this step, we can draw on the proven successful experience and significantly improve the accuracy of part process compilation.

[0038] Furthermore, in step S2, the method for retrieving similar historical parts in the part design library specifically includes:

[0039] T1. Verify the file format of the 3D drawing and perform deep recognition through AI technology to obtain information such as part shape, structure, and size contained in the 3D drawing.

[0040] T2. Convert the part shape, structure, size and other information contained in the 3D drawing into feature parameters, and retrieve historical parts containing similar feature parameters in the part design library through AI technology;

[0041] T3. Using AI technology, analyze the similarity values ​​between the historical parts containing similar feature parameters and the corresponding parts of the current 3D drawing, and sort them. Select a preset number of historical parts containing similar feature parameters as similar historical parts in descending order of similarity.

[0042] Furthermore, in step S2, the information of the similar historical parts includes the name, part number and material of each similar historical part.

[0043] S3. Based on the characteristics of the mold to be processed and its parts, AI technology is used to extract process suggestions and processing steps from the industry knowledge base, and the processing technology of the mold to be processed is compiled based on the process suggestions and processing steps. The industry knowledge base is a database containing processing technologies of different industries. By implementing this step, the processing technology of the mold can be optimized by combining cross-industry knowledge to obtain the most appropriate process suggestions and the processing steps that best meet industry standards and best practices.

[0044] The AI ​​system can realize automated process generation based on a large amount of historical data and advanced algorithms, significantly improve production efficiency, reduce human errors, and enable enterprises to quickly respond to the process requirements of different types of molds and parts. This embodiment is based on the massive data of the part design library, part process library and industry knowledge base. For the processing molds and the parts they contain, the AI ​​technology is used to complete the retrieval of similar historical parts, the compilation of part processing technology and the compilation of mold processing technology.

[0045] Furthermore, when a processing technology is compiled for a part based on the similar processing technology, the unreasonable processing technology is identified and improved according to the characteristics and processing difficulty of the part through AI technology. Through AI technology, the process sequence can be adjusted according to the characteristics and processing difficulty of the part, reducing the equipment load or processing time, thereby improving production efficiency.

[0046] Furthermore, according to the requirements of the processing technology of the parts and the processing technology of the mold, the most suitable processing equipment is matched for the processing technology of the parts and the processing technology of the mold through AI technology. This completes the reasonable scheduling of equipment resources, optimizes the configuration of the production line, and avoids the waste of resources caused by possible equipment selection errors in the manual compilation process.

[0047] Furthermore, when a processing technology is compiled for a part based on the similar processing technology, the most suitable processing technology and tool configuration are matched for the processing technology of the part according to the material, historical data and process experience of the part through AI technology. For example, for high-hardness metal materials, AI technology can automatically select suitable tools, coolants and processing parameters based on historical processing data and processing experience to improve the efficiency and accuracy of the high-hardness metal material processing technology.

[0048] Furthermore, before the part processing technology is compiled, the similar historical parts retrieved by AI technology and the similar processing technology extracted are confirmed and corrected. That is, the user manually screens the data obtained by AI technology and completes the correction or recommendation of the data, which can further improve the accuracy of the process compilation process.

[0049] Example 2

[0050] This embodiment provides an AI-based mold process compilation system, which executes the AI-based mold process compilation method described in Example 1; Figure 2 As shown, it includes data collection layer, data processing and analysis layer, process recommendation and optimization layer, process generation and feedback layer and user interface layer.

[0051] Among them, the data acquisition layer includes a part design library, a part process library and an industry knowledge base. The part design library is a database containing 3D drawings of all historical parts, the part process library is a database containing the processing technology of all historical parts, and the industry knowledge base is a database containing the processing technology of different industries.

[0052] The data processing and analysis layer is used to retrieve similar historical parts in the part design library through AI technology.

[0053] The process recommendation and optimization layer is used to extract similar processing technologies of similar historical parts from the part process library through AI technology. This structural layer is also used to conduct cross-industry learning and optimization of mold processing technology based on the industry knowledge base, and provide the process generation and feedback layer with process suggestions and processing steps required for compiling mold processing technology.

[0054] The process generation and feedback layer is used to compile a processing process for parts based on the similar processing processes through AI technology, and to extract process suggestions and processing steps from the industry knowledge base based on the characteristics of the mold to be processed and its parts, so as to complete the compilation of the processing process for the mold to be processed.

[0055] The user interface layer is used to realize information interaction between the system and the user, including receiving instructions input by the user and displaying the data obtained through AI technology to the user for confirmation and correction.

[0056] Among them, the functions realized by each structural layer correspond to the composition of the method described in Example 1, and will not be repeated here.

[0057] In summary, the present invention provides an AI-based mold process compilation method and system. Based on massive data from multiple databases, for the processing molds and the parts contained therein, AI technology is used to complete the retrieval of similar historical parts, the compilation of parts processing technology and the compilation of mold processing technology, which greatly improves the accuracy and efficiency of mold processing technology compilation.

[0058] It should be pointed out that, according to the needs of implementation, the various steps / components described in this application can be split into more steps / components, and two or more steps / components or partial operations of steps / components can be combined into new steps / components to achieve the purpose of the present invention.

[0059] The order of execution of each step in the above embodiment does not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0060] It should be understood that those skilled in the art can make improvements or changes based on the above description, and all these improvements and changes should fall within the scope of protection of the appended claims of the present invention.

Claims

1. A mold process compilation method based on AI, characterized in that: include: Obtaining 3D drawings of parts included in the mold to be processed, and storing the 3D drawings in a parts design library, where the parts design library is a database containing 3D drawings of all historical parts; For each part included in the processing mold, based on the corresponding 3D drawings, similar historical parts are retrieved in the part design library through AI technology, and information of the similar historical parts is obtained; based on the information of the similar historical parts, similar processing techniques of the similar historical parts are extracted from the part process library, and processing techniques are compiled for the parts based on the similar processing techniques. The part process library is a database containing processing techniques of all historical parts; According to the characteristics of the mold to be processed and its parts, AI technology is used to extract process suggestions and processing steps from the industry knowledge base, and the processing technology of the mold to be processed is compiled based on the process suggestions and processing steps. The industry knowledge base is a database containing processing technologies of different industries.

2. The AI-based mold process compilation method according to claim 1 is characterized in that: The method for retrieving similar historical parts in the part design library specifically includes: Verify the file format of 3D drawings and perform deep recognition through AI technology to obtain information such as part shape, structure, and size contained in the 3D drawings; Convert the part shape, structure, size and other information contained in the 3D drawing into feature parameters, and retrieve historical parts containing similar feature parameters in the part design library through AI technology; Through AI technology, the similarity values ​​between the historical parts containing similar feature parameters and the corresponding parts of the current 3D drawing are analyzed and sorted. A preset number of historical parts containing similar feature parameters are selected as similar historical parts in descending order of similarity.

3. The AI-based mold process compilation method according to claim 1 is characterized in that: The information of the similar historical parts includes the name, part number and material of each similar historical part.

4. The AI-based mold process compilation method according to claim 1 is characterized in that: When compiling a processing technology for a part based on the similar processing technology, AI technology is used to identify unreasonable processing technologies and make improvements based on the characteristics of the parts and the difficulty of processing.

5. The AI-based mold process compilation method according to claim 1 is characterized in that: When compiling the processing technology of parts and molds, the most suitable processing equipment is matched for the processing technology of the parts and molds through AI technology according to the requirements of the processing technology of the parts and molds.

6. The AI-based mold process compilation method according to claim 1 is characterized in that: When compiling a processing technology for a part based on the similar processing technology, AI technology is used to match the most appropriate tool configuration for the processing technology of the part according to the material of the part, historical processing data and processing technology experience.

7. The AI-based mold process compilation method according to claim 1 is characterized in that: Before compiling the part processing technology, the similar historical parts retrieved by the AI ​​technology and the similar processing technologies extracted are confirmed and corrected.

8. An AI-based mold process compilation system, which executes the AI-based mold process compilation method according to any one of claims 1 to 7; characterized in that: It includes data collection layer, data processing and analysis layer, process recommendation and optimization layer, process generation and feedback layer and user interface layer; Among them, the data acquisition layer includes a part design library, a part process library and an industry knowledge base, the part design library is a database containing 3D drawings of all historical parts, the part process library is a database containing the processing technology of all historical parts, and the industry knowledge base is a database containing the processing technology of different industries; the data processing and analysis layer is used to retrieve similar historical parts in the part design library through AI technology; the process recommendation and optimization layer is used to extract similar processing technologies of similar historical parts in the part process library through AI technology, and extract process suggestions and processing steps of the mold in the industry knowledge base based on the characteristics of the mold to be processed and its parts; the process generation and feedback layer is used to compile a processing technology for the part based on the similar processing technology through AI technology, and complete the compilation of the processing technology of the mold to be processed based on the process suggestions and processing steps of the mold; the user interface layer is used to realize information interaction between the system and the user.

9. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the AI-based mold process compilation method as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the steps of the AI-based mold process compilation method described in any one of claims 1 to 7 are implemented.

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