Process optimization and experience inheritance method and system

Abstract

The invention relates to the technical field of process optimization and experience inheritance, in particular to a process optimization and experience inheritance method and system, and the method comprises the following steps: A, importing a design drawing and a data file; b, identifying and analyzing a design drawing and a data file; c, according to the extracted key information, a preset process rule, a layout rule and a visualization algorithm, generating a process bubble graph; d, performing empirical data association on the empirical data and a process bubble graph; e, performing encryption processing on the associated empirical data and generating an operation guidance two-dimensional code; f, obtaining process parameters and operation guidance required by production by scanning the operation guidance two-dimensional code; according to the process optimization and experience inheritance method, the process information and the association relationship are visually presented through the bubble graph, and the key process experience data are encrypted and stored by using the two-dimensional code, so that accurate storage and convenient transmission of the experience technology are ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of process optimization and experience inheritance, and particularly relates to a process optimization and experience inheritance method and system. BACKGROUND

[0002] In the traditional precision mold manufacturing process, there are many drawbacks. On the one hand, process experience mainly depends on artificial inheritance, and new employees are difficult to quickly obtain comprehensive and accurate experience knowledge, resulting in a long learning cycle, and in actual operation, operation errors are easily caused by human understanding deviation and insufficient experience, thereby affecting mold quality and production efficiency. On the other hand, the recording and transmission of process information lack efficient and accurate means, and it is difficult to realize quick retrieval and sharing, which is not conducive to the improvement and continuous improvement of the overall process level of the enterprise. SUMMARY

[0003] The present application is aimed at the deficiencies of the prior art and provides a process optimization and experience inheritance method, which directly presents process information and associated relationships through a bubble chart, and encrypts and stores key process experience data using a two-dimensional code, ensuring accurate storage and convenient transmission of experience technology. This not only greatly reduces human error and makes up for the deficiencies of manual technology, but also significantly improves the efficiency and quality of process design and production, promotes internal knowledge sharing and inheritance in enterprises, and enhances the core competitiveness of enterprises.

[0004] To achieve the above purpose, the technical scheme adopted by the present application is as follows: a process optimization and experience inheritance method, comprising the following steps:

[0005] A, import design drawings and data files;

[0006] B, identify and analyze the design drawings and data files, and extract key information;

[0007] C, according to the extracted key information and the preset process rules, manually input or select the corresponding process data from the database and fill it into the process elements of the bubble chart, and generate a process bubble chart according to the layout rules and visualization algorithm;

[0008] D, retrieve experience data related to the current process from the experience database, and associate the experience data with the process bubble chart;

[0009] E, encrypt the associated experience data and generate an operation guidance two-dimensional code;

[0010] F, obtain the required process parameters and operation guidance by scanning the operation guidance two-dimensional code.

[0011] Further improvement of the above scheme is that the key information in steps B and C includes one or more of geometric shapes and sizes in design drawings, equipment parameters, material property data.

[0012] Further improvement of the above scheme is that the process bubble chart takes bubbles as carriers, displays each process element in the form of bubbles with different attributes in the chart, and clearly indicates the sequence, logical relationship and data flow direction between processes through lines and arrows.

[0013] Further improvement of the above scheme is that the process bubble chart includes one or more of processing procedures, process parameters, quality requirements, and equipment requirements.

[0014] Further improvement of the above scheme is that the experience data includes one or more of process parameter settings of successful cases, equipment operation state records, and quality detection results, and the association of the experience data with the process bubble chart in step D specifically includes: accurately matching and linking the experience data with the process elements in the bubble chart through a data association algorithm.

[0015] Further improvement of the above scheme is that the process optimization and experience inheritance method further includes step G, process optimization, which specifically includes the following steps:

[0016] G1, real-time collection of production data and quality detection results;

[0017] G2, comparative analysis of collected information and experience data;

[0018] G3, when deviation occurs, issue a warning and provide optimization suggestions.

[0019] Further improvement of the above scheme is that the information stored in the operation guidance two-dimensional code includes core process parameters, operation points and quality control key data from design to production process.

[0020] A process optimization and experience inheritance system includes a processor and a memory, the memory stores program modules, the program modules run on the processor to realize a process optimization and experience inheritance method according to any one of the above schemes.

[0021] The process optimization and experience inheritance method provided by the application has the following advantages:

[0022] A, import design drawings and data files;

[0023] B, identify and analyze the design drawings and data files, and extract key information;

[0024] C, according to the extracted key information and the preset process rules, manually input or select the corresponding process data from the database to fill into the process elements of the bubble chart, and generate a process bubble chart according to the layout rules and the visualization algorithm;

[0025] D, retrieve experience data related to the current process from the experience database, and associate the experience data with the process bubble chart;

[0026] E, encrypt the associated experience data and generate an operation guidance two-dimensional code;

[0027] F, obtain the required process parameters and operation guidance by scanning the operation guidance two-dimensional code;

[0028] The process optimization and experience inheritance method of the present application directly presents process information and associated relationships through a bubble chart, and uses a two-dimensional code to encrypt and store key process experience data, ensuring accurate storage and convenient transmission of experience technology, which not only greatly reduces human error and makes up for the shortcomings of manual technology, but also significantly improves the efficiency and quality of process design and production, promotes internal knowledge sharing and inheritance in enterprises, and enhances the core competitiveness of enterprises. DETAILED DESCRIPTION

[0029] The process optimization and experience inheritance method of the present application includes the following steps:

[0030] A, import design drawings and data files;

[0031] B, identify and analyze the design drawings and data files, and extract key information;

[0032] C, according to the extracted key information and the preset process rules, manually input or select the corresponding process data from the database to fill into the process elements of the bubble chart, and generate a process bubble chart according to the layout rules and the visualization algorithm;

[0033] D, retrieve experience data related to the current process from the experience database, and associate the experience data with the process bubble chart;

[0034] E, encrypt the associated experience data and generate an operation guidance two-dimensional code;

[0035] F, obtain the required process parameters and operation guidance by scanning the operation guidance two-dimensional code; in the production process, the operator obtains the process parameters and operation guidance by scanning the two-dimensional code, and directly operates according to the accurate information provided by the system, avoiding operation errors caused by manual misreading or misremembering process requirements.

[0036] The process optimization and experience inheritance method of the application directly presents process information and correlation through a bubble chart, and encrypts and stores key process experience data through a two-dimensional code, so that the accurate storage and convenient transmission of experience technology are ensured, which not only greatly reduces human error and makes up for the deficiency of manual technology, but also significantly improves the efficiency and quality of process design and production, promotes internal knowledge sharing and inheritance of enterprises, and enhances the core competitiveness of enterprises.

[0037] The key information in the steps B and C includes one or more of geometric shapes and sizes in design drawings, equipment parameters, and material characteristic data; by extracting key information such as geometric shapes and sizes in design drawings, and related production data such as equipment parameters and material characteristic data, and combining other imported data, a basis is provided for subsequent bubble chart construction.

[0038] The process bubble chart takes bubbles as carriers, displays each process element in the form of bubbles with different attributes in the chart, and clearly indicates the sequence, logical relationship and data flow direction between processes through lines and arrows.

[0039] The process bubble chart includes one or more of machining processes, process parameters, quality requirements, and equipment requirements; the machining processes are, for example, milling, electric spark machining, and grinding, the process parameters are, for example, cutting speed, feed rate, and discharge energy, and the quality requirements are, for example, dimensional tolerance and surface roughness.

[0040] The experience data includes one or more of process parameter settings of successful cases, equipment operation state records, and quality detection results, and the experience data association in the step D specifically includes: through a data association algorithm, the experience data is accurately matched and linked with process elements in the bubble chart; the bubble chart not only displays the current designed process situation, but also integrates rich historical experience.

[0041] The process optimization and experience inheritance method of the application further includes a step G, process optimization, which specifically includes the following steps:

[0042] G1, real-time collection of production data and quality detection results;

[0043] G2, comparative analysis of collected information and experience data;

[0044] G3, when deviation occurs, issuing a warning and providing optimization suggestions;

[0045] For example: self-adaptation of injection mold cavity surface finish not meeting standards

[0046] 1. Deviation detection

[0047] Monitoring object: Mold cavity surface finish (Target value: Ra 0.4 μm).

[0048] Data source: Real-time acquisition of surface roughness data by online detection equipment (white light interferometer). Preset parameters in process bubble chart: Polishing process node (bubble) associated parameters (sandpaper grit, polishing pressure, rotation speed).

[0049] Deviation trigger: The detection value of a batch of cavities is Ra 0.6 μm, which exceeds the tolerance range (Ra ≤ 0.5 μm).

[0050] 2. Early warning and visual feedback

[0051] Bubble chart dynamic response: Polishing process node (bubble) turns orange, labeled "finish deviation +0.2 μm". Highlight the associated nodes to prompt potential influencing factors.

[0052] Multi-end early warning push:

[0053] Operation interface pop-up window: "The surface finish of X-02 cavity of certain cavity exceeds the standard, it is recommended to check the polishing parameters". The MES system generates a work order and automatically associates the responsible person and historical cases.

[0054] 3. Optimization suggestion generation logic

[0055] Experience base matching and AI reasoning: The system calls historical data and filters out 3 related optimization schemes:

[0056] Scheme 1: Sandpaper grit from #1500 to #2000, polishing pressure from 5N to 3N.

[0057] Scheme 2: Add "deep cooling + secondary tempering" process to improve material microstructure (suitable for PD613 mold steel).

[0058] Scheme 3: Polishing time is extended by 20%, rotation speed is adjusted from 1200 rpm to 800 rpm.

[0059] Dynamic weight calculation: Combine the current working conditions (equipment load rate, sandpaper inventory status) to recommend the preferred option (comprehensive score).

[0060] 4. Self-adaptive adjustment and verification

[0061] One-key execution optimization: The operator clicks "apply optimization" in the bubble chart, and the system automatically issues instructions to the polishing equipment:

[0062] Sandpaper grit: #1500 → #2000

[0063] Polishing pressure: 5N → 3N

[0064] Real-time verification and feedback:

[0065] The adjusted processing sample detection value is Ra 0.45 μm, which meets the requirements, and the bubble recovers green.

[0066] The system records the optimization parameters to the experience library and marks "high priority solution".

[0067] Continuous learning and optimization suggestions:

[0068] If the same device triggers a warning for five times in a row due to sandpaper grit problem, the system automatically pushes a procurement suggestion: "Suggest increasing #2000 sandpaper inventory".

[0069] Technical advantages and effects

[0070] 1) Precise positioning: through the bubble chart associated with the process chain (material → equipment → parameter), quickly lock the deviation source (insufficient sandpaper grit).

[0071] 2) Dynamic decision-making: based on real-time equipment status and historical data weight, avoid manual trial and error, response speed is improved by 80%.

[0072] 3) Closed-loop improvement: optimization results feed back to the experience library, forming a complete chain of "deviation warning → optimization → prevention", and the recurrence rate of similar problems is reduced by 55%.

[0073] Further reduce the uncertainty of human judgment and adjustment, ensure that the production process always maintains the best state, effectively reduce the influence of human factors on process stability.

[0074] The information stored by the operation guidance two-dimensional code includes core process parameters, operation points and quality control key data from design to production process; ensure the integrity and safety of experience technology;

[0075] The process scheme generated by the present application is based on accurate data and rich experience, and is output in a standardized format, so workers only need to follow the scheme to execute. In the production execution stage, the control instructions of the system to the equipment are also based on accurate process parameter settings, which reduces the errors that may occur when manually setting equipment parameters. In the whole process, due to the application of bubble chart intelligent process, human intervention is minimized in each link from process design to production execution, thereby significantly reducing the workpiece processing loss caused by human factors, improving production efficiency and product quality.

[0076] A process optimization and experience inheritance system, comprising a processor and a memory, the memory storing program modules, the program modules running on the processor, realizing a process optimization and experience inheritance method as described above.

[0077] To further illustrate the practical application effect of the present application, the following will show the present application through a specific case, as follows:

[0078] I. Project background

[0079] A certain precision mold enterprise undertakes customer orders (project ID: 1685425165988) to produce cylindrical mold cores (roughness Ra2.0), material PD613, hardness HRC58-60, using vacuum heat treatment + titanium plating surface treatment.

[0080] II. Implementation steps

[0081] 1. Import and analyze drawings: Import 2D drawing file ID: 1804736093112131 and 3D model (R504-ed3_GJ001_WZ001.png)

[0082] Analyze key parameters: size 40.689±0.005mm, shape and position tolerance ∥0.002mm, surface finish Ra0.4

[0083] 2. Bubble chart generation

[0084] Process element configuration:

[0085] Process: EDM (no cavity)

[0086] Process parameters: discharge gap X / Y = 0.08mm, machining depth -11.3063mm

[0087] Equipment requirements: AL40GS EDM machine (tool size 12)

[0088] Quality requirements: roughness Ra0.4, position accuracy ±0.005mm

[0089] Layout rules: arrange bubbles according to processing order, mark process time (manual 56min / automatic 120min)

[0090] 3. Experience data association

[0091] Search historical successful cases (project ID: 1685092022500):

[0092] Best discharge parameter combination: C001 (pulse width 0.016ms, tool lifting height 25mm)

[0093] Equipment optimization suggestions: reference sphere coordinate system G759, measurement frequency 2 times Quality detection record: good product rate 98.7%, common problems are electrode wear 4. Production execution

[0094] Scan the code to get guidance:

[0095] Device parameter auto-loading (discharge gap 0.08mm)

[0096] Operation tips: "Electrode pre-positioning requires 2 measurements, reference ball height 379.98mm"

[0097] Quality warning: Trigger alarm when machining depth deviation > 0.003mm

[0098] Three, optimization case

[0099] 1. Real-time data collection:

[0100] - Actual processing time: manual 58min / automatic 122min (exceeding reference ±5%)

[0101] - Test results: roughness Ra0.45 (exceeding standard 0.05)

[0102] 2. Comparative analysis:

[0103] - Compared with historical data: discharge energy fluctuation 0.5%

[0104] - Suggestion for adjustment: increase discharge pulse width from 0.016ms to 0.018ms

[0105] 3. Optimization implementation:

[0106] - After modifying process parameters, roughness is stable at Ra0.38-0.42

[0107] - Work time is shortened to manual 55min / automatic 118min

[0108] Four, inheritance application

[0109] 1. New employee training:

[0110] - Get 3D operation demonstration (including electrode installation animation) by scanning two-dimensional code

[0111] - Simulate training system to automatically judge operation compliance

[0112] 2. Knowledge sedimentation:

[0113] - The optimization data is stored in the experience library (project ID: 1726468538186)

[0114] - Form a standard process template: "Cylindrical insert EDM V3.2"

[0115]

[0116] Certainly, the above-mentioned is only the preferred embodiment of the present application, therefore, equivalent changes or modifications made in the structure, features and principles described in the patent application scope of the present application are included in the patent application scope of the present application.

Claims

1. A process optimization and experience succession method, characterized by, The method comprises the following steps: A. Importing design drawings and data files; B. Identifying and analyzing the design drawings and data files to extract key information; C. According to the extracted key information and the preset process rules, manually input or select the corresponding process data from the database to fill into the process elements of the bubble chart, and generate a process bubble chart according to the layout rules and visualization algorithms; D. Retrieving experience data related to the current process from the experience database, and associating the experience data with the process bubble chart; E. Encrypting the associated experience data and generating an operation guidance QR code; F. Obtaining the required process parameters and operation guidance by scanning the operation guidance QR code.

2. The process optimization and experience inheritance method according to claim 1, characterized in that: The key information in steps B and C includes one or more of the geometric shapes and sizes in the design drawings, equipment parameters, and material property data.

3. The process optimization and experience inheritance method of claim 1, wherein: The process bubble chart uses bubbles as carriers to display each process element in the form of bubbles with different attributes, and clearly indicates the sequence, logical relationship and data flow direction between processes through lines and arrows.

4. The process optimization and experience inheritance method according to claim 3, characterized in that: The process bubble chart includes one or more of the following information: processing steps, process parameters, quality requirements, and equipment requirements.

5. The process optimization and experience inheritance method according to claim 1, characterized in that: The experience data includes one or more of the following: successful case process parameter settings, equipment operation state records, and quality detection results. In step D, the experience data is associated with the process bubble chart to implement experience data association, which specifically includes: through a data association algorithm, the experience data is accurately matched and linked with the process elements in the bubble chart.

6. The process optimization and experience inheritance method of claim 1, wherein: It also includes step G, process optimization, which specifically includes the following steps: G1. Real-time collection of production data and quality detection results; G2. Comparing and analyzing the collected information with the experience data; G3. When there is a deviation, issue a warning and provide optimization suggestions.

7. The process optimization and experience inheritance method according to claim 1, characterized in that: The information stored in the operation guidance QR code includes core process parameters, operation points, and quality control key data from the design to the production process.

8. A process optimization and experience transfer system comprising a processor and a memory storing program modules, characterized in that: The program module runs on the processor to implement the process optimization and experience inheritance method of any one of claims 1-7.

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