Intelligent three-dimensional design generation method and system for forming mold

Abstract

The invention relates to the technical field of forming mold design and manufacturing, in particular to an intelligent three-dimensional design generation method and system for a forming mold. The method comprises the following steps: reading an initial three-dimensional design model of a forming mold, identifying dynamic contact pairing in the forming mold, defining a monitoring area, and obtaining parameters of the forming mold; standard working condition simulation calculation is executed based on the monitoring area and the forming mold parameters, technological parameters and structural parameters are adjusted through a preset interactive interface, wear rate distribution of the mold contact surface is calculated and displayed in real time, and a wear prediction cloud picture is obtained; performing color homogenization on the wear prediction cloud picture to generate an optimized wear rate picture and an optimized working condition configuration file; and accumulated wear depth calculation is carried out according to the optimized wear rate diagram and a preset optimal performance point. The die is regarded as a dynamically evolved whole, and wear is uniformly distributed, so that the effective life of the die is prolonged, the maintenance cost is reduced, and the production efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of molding die design and manufacturing technology, and in particular to an intelligent three-dimensional design generation method and system for molding dies. Background Technology

[0002] Traditional mold design employs a static design mindset, focusing solely on the geometric accuracy and assembly fit of the initial mold state. However, it neglects the inevitable wear and tear process that molds undergo during actual production. This results in molds only maintaining optimal performance briefly at the beginning of their lifespan, after which their performance rapidly deteriorates, failing to achieve optimal performance throughout their entire lifespan. Traditional wear control methods primarily rely on material upgrades (such as using high-hardness steel), surface treatments (such as nitriding and hard chrome plating), and coating technologies (such as PVD and CVD coatings). These methods not only significantly increase mold manufacturing costs but also only delay wear rather than fundamentally solve the problem. Once the coating is damaged, the wear rate actually accelerates. The uneven stress distribution problem commonly found in mold structural design, especially in the parting surface sealing area and the chamfered areas at structural transitions, often becomes a wear hotspot due to stress concentration. This uneven wear limits the overall lifespan of the mold to its weakest point, leading to significant material scrap and frequent maintenance downtime.

[0003] In summary, existing technologies suffer from problems such as a disconnect between static design and dynamic use, limited effectiveness of passive wear resistance, and uneven wear distribution leading to early failure, which urgently need to be addressed. Summary of the Invention

[0004] Therefore, it is necessary to provide an intelligent three-dimensional design generation method and system for molding dies to solve at least one of the above-mentioned technical problems.

[0005] To achieve the above objectives, an intelligent 3D design generation method for molding dies includes the following steps: Step S1: Read the initial 3D design model of the molding die, identify the dynamic contact pairing in the molding die, define the monitoring area, and obtain the molding die parameters; Step S2: Perform standard working condition simulation calculations based on the monitoring area and molding die parameters. Adjust process parameters and structural parameters through a preset interactive interface, calculate and display the wear rate distribution of the mold contact surface in real time, and obtain a wear prediction cloud map. Perform color uniformization on the wear prediction cloud map to generate an optimized wear rate map and an optimized working condition configuration file. Step S3: Calculate the cumulative wear depth based on the optimized wear rate map and the preset optimal performance point, and perform model surface offset compensation on the initial three-dimensional design model to obtain the pre-compensated three-dimensional model; Step S4: Bind the pre-compensated 3D model to the optimized working condition configuration file, and generate a molding die intelligent design data package based on the pre-compensated 3D model and the optimized working condition configuration file.

[0006] This invention achieves proactive management and utilization of the mold wear process by introducing a dynamic evolution perspective throughout the entire lifecycle. Firstly, through simulation analysis and interactive parameter optimization, this method can accurately identify and eliminate wear hotspots caused by stress concentration, achieving a uniform distribution of wear rates on the contact surfaces. This allows all mold components to age collaboratively, avoiding the scrapping of the entire mold due to premature local failure and fundamentally solving the problem of uneven wear. Crucially, this method intentionally introduces geometric deviations matching the expected wear depth through precise reverse pre-compensation of the initial 3D model. This ensures that the mold does not fail from its optimal state during production and use, but rather gradually "breaks in" to its designed optimal performance point through natural wear. This ensures that the mold can maintain a highly efficient and stable working state over a longer lifecycle. The resulting intelligent design data package deeply integrates optimized design schemes, optimal process parameters, and lifecycle maintenance strategies, providing unprecedented scientific guidance for mold manufacturing and use. This significantly extends the effective service life of the mold, greatly reduces maintenance costs and downtime, and comprehensively improves production efficiency and product quality stability.

[0007] Preferably, the present invention also provides an intelligent three-dimensional design generation system for molding dies, used to execute the intelligent three-dimensional design generation method for molding dies as described above, the intelligent three-dimensional design generation system for molding dies comprising: The model parameter acquisition module is used to read the initial three-dimensional design model of the molding die, identify dynamic contact pairings in the molding die, define the monitoring area, and obtain the molding die parameters. The wear optimization analysis module is used to perform standard working condition simulation calculations based on the monitoring area and molding die parameters. Through an interactive interface, process parameters and structural parameters are adjusted, and the wear rate distribution of the mold contact surface is calculated and displayed in real time to obtain a wear prediction cloud map. The wear prediction cloud map is then color-uniformed to generate an optimized wear rate map and an optimized working condition configuration file. The reverse compensation design module is used to calculate the cumulative wear depth based on the optimized wear rate map and the preset optimal performance point, perform non-uniform surface offset operation on the initial three-dimensional design model, perform assembly verification and fit relationship check on the model after offset operation, and generate a pre-compensated three-dimensional model. The intelligent data integration module is used to bind the pre-compensated 3D model with the optimized working condition configuration file, and generate a molding die intelligent design data package based on the pre-compensated 3D model and the optimized working condition configuration file.

[0008] This system achieves comprehensive and efficient acquisition of mold geometry, material, and working condition data through a model parameter acquisition module, laying a precise foundation for subsequent design. Through a wear optimization analysis module, the system can simulate and optimize the wear rate distribution of the mold contact surface in real time, achieving wear uniformity through interactive control. This effectively solves the problem of early failure caused by uneven wear distribution in traditional mold design, significantly extending mold life. The reverse compensation design module, based on accurate cumulative wear depth calculation, performs intelligent non-uniform surface offset compensation on the initial design model, enabling the mold to gradually reach its optimal fit during production, fundamentally improving the mold's performance throughout its entire lifecycle. Finally, the intelligent data integration module binds and encapsulates all design results and optimization schemes, generating a comprehensive intelligent design data package. This achieves fully digital management of mold design, manufacturing, use, and maintenance, thereby significantly reducing manufacturing costs and maintenance expenses, and comprehensively improving production efficiency and product quality. Attached Figure Description

[0009] Figure 1 This is a schematic diagram illustrating the steps of an intelligent 3D design generation method for molding dies. Figure 2 This is a schematic diagram of the initial model of the molding die and dynamic contact pairing recognition in this invention; Figure 3 This is a schematic diagram of the clamping force-strain curve in this invention. Detailed Implementation

[0010] The technical method of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0011] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0012] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0013] To achieve the above objectives, please refer to Figures 1 to 3 This invention provides an intelligent three-dimensional design generation method for molding dies, comprising the following steps: Step S1: Read the initial 3D design model of the molding die, identify the dynamic contact pairing in the molding die, define the monitoring area, and obtain the molding die parameters; In this embodiment of the invention, the system first reads the initial 3D design model in STEP format and simultaneously loads an XML parameter file containing data such as rated clamping force, injection pressure, and the elastic modulus of P20 mold steel. Subsequently, through geometric proximity and kinematic constraint analysis, the system automatically identifies all dynamic contact pairs in the mold assembly that exhibit relative sliding during mold opening and closing. The system records the geometric topology, relative motion characteristics, and contact area of ​​these pairs, constructing a contact pair database. All contact surfaces involved in this database are then aggregated and defined as the monitoring area for subsequent simulation and optimization.

[0014] Step S2: Perform standard working condition simulation calculations based on the monitoring area and molding die parameters. Adjust process parameters and structural parameters through a preset interactive interface, calculate and display the wear rate distribution of the mold contact surface in real time, and obtain a wear prediction cloud map. Perform color uniformization on the wear prediction cloud map to generate an optimized wear rate map and an optimized working condition configuration file. In this embodiment of the invention, based on the monitoring area and molding die parameters, the system performs finite element simulation under standard working conditions and calibrates it using physical measurement data such as pressure-sensitive paper to generate a benchmark contact state diagram containing pressure and stress distribution. In the interactive interface, the system provides adjustment sliders associated with key parameters such as clamping force and chamfer radius. The response characteristics of these sliders are pre-calibrated based on strain gauge testing and a stress concentration factor database. By adjusting the sliders, the operator can call a reduced-order model to calculate and update the wear rate distribution cloud map of the die contact surface in real time until the color distribution of the cloud map reaches a preset uniformity index, i.e., the rate ratio of high and low wear areas is less than 3.0. At this point, the system saves the final parameter combination as an optimized working condition configuration file and the corresponding wear rate distribution map as an optimized wear rate map.

[0015] Step S3: Calculate the cumulative wear depth based on the optimized wear rate map and the preset optimal performance point, and perform model surface offset compensation on the initial three-dimensional design model to obtain the pre-compensated three-dimensional model; In this embodiment of the invention, the system receives 80,000 cycles set by the user as the optimal performance point. Based on the optimized wear rate map, it calculates the cumulative total wear depth of each grid point on the mold when reaching this performance point. This calculation process is calibrated using physical grinding test data, ultimately generating a target cycle wear depth map. Next, the system performs non-uniform surface offset compensation on the contact surface of the initial 3D design model, that is, offsets the surface outward along the normal direction of each point to its corresponding wear depth value. The offset surface is then reconstructed using Poisson to generate a continuous solid, and local feature preservation processing is performed on key geometric features such as chamfers and sharp edges to restore their accurate shape. Finally, the generated model undergoes virtual assembly inspection, and excessive interference or excessive gaps are eliminated by iteratively adjusting the local offset, ultimately obtaining a qualified pre-compensated 3D model.

[0016] Step S4: Bind the pre-compensated 3D model to the optimized working condition configuration file, and generate a molding die intelligent design data package based on the pre-compensated 3D model and the optimized working condition configuration file; In this embodiment of the invention, the final pre-compensated 3D model is exported as a STEP AP242 format file containing machining process annotations and geometric tolerance information. Based on the model's initial interference state and wear prediction throughout its entire life cycle, the system automatically generates two guidance documents: one is a mold break-in period guidance scheme specifying initial low-pressure operating parameters, and the other is a life cycle maintenance plan that divides the model into three stages—break-in, stabilization, and degradation—and provides corresponding parameter adjustment suggestions. Finally, the system encapsulates the exported 3D model file, optimized operating condition configuration file, and the two guidance scheme files to generate a ZIP format intelligent design data package for molding dies.

[0017] Of particular importance, step S1 includes: Read the initial 3D design model of the molding die and extract the key structural geometric data from the model; Read the molding die parameters, which include working condition parameters and material property parameters; The system automatically identifies all dynamic contact pairs in the mold, records the geometric topology, relative motion characteristics, and contact area data of each pair of contact surfaces, constructs a contact pair database, and defines the contact surfaces in the contact pair database as monitoring areas.

[0018] In one embodiment, the system reads a pre-edited XML format parameter file containing operating condition parameters and material property parameters; It should be noted that the working condition parameters include the rated clamping force, which is 2500kN, and the peak injection pressure, which is 100MPa; the material property parameters include the elastic modulus of the mold steel (grade P20) of 210GPa, Poisson's ratio of 0.3, and Brinell hardness of 300HBW, as well as the melt index and shrinkage of the molding plastic (grade ABS).

[0019] In one implementation of this embodiment, the operation of automatically identifying all dynamic contact pairs in the mold and building a contact pair database specifically involves: The system pairs all parts in the mold assembly and performs close-range detection on each pair. When the surfaces of two parts are parallel or nearly parallel within a tolerance of 0.01 mm, the system determines that they constitute a potential contact pair. For each potential contact pair, the system further analyzes its assembly constraints to determine whether there is relative sliding, rolling, or impact during mold opening, closing, or ejection. If so, it is confirmed as a dynamic contact pair. The system creates a record for each dynamic contact pair, which includes the ID of the paired parts, the geometric topology information of the contact surfaces, the degrees of freedom of relative motion (e.g., translation along the Z-axis), and the contact area calculated by mesh integration. All these records are integrated and stored to form a contact pair database, and all contact surfaces recorded in this database are uniformly set and collectively defined as the monitoring area for subsequent simulation analysis.

[0020] Please see Figure 2 This diagram illustrates the initial model of the molding die and the dynamic contact pairing identification in this invention. It showcases the key structures and dynamic contact pairing distribution of the initial 3D model of the molding die, visually presenting the basic geometric relationships and core contact areas of the die assembly. The diagram marks key reference surfaces such as the "upper die positioning reference surface" and the "lower die support plane," and delineates the dynamic contact pairing areas—i.e., the contact surfaces that slide / fit during die opening and closing and ejection (such as parting surfaces, guide pillar and guide sleeve mating surfaces, etc.). These contact pairs are the core objects for subsequent wear monitoring and simulation calculations. The diagram clearly reflects the geometric topological relationships and spatial positions of each contact surface. This provides a visual basis for "constructing the contact pair database" and "defining the monitoring area" in step S1.

[0021] Please see Figure 3This is a schematic diagram of the clamping force-strain curve in this invention, showing the relationship between clamping force and the strain value of the mold parting surface. The horizontal axis represents clamping force, and the vertical axis represents the strain value of the parting surface (reflecting the degree of material deformation). The curve shows a positive correlation trend: as the clamping force increases, the strain value gradually increases, and the strain increases rapidly in the low clamping force stage, while it tends to level off in the high clamping force stage (consistent with the elastic deformation law of materials). This curve is the key basis for "parameter adjustment slider configuration" and "lightweight wear calculation" in step S2. By establishing the correlation between clamping force and stress through measured data, it helps to accurately control process parameters to eliminate high-stress areas and achieve uniform wear.

[0022] Preferably, step S2, which involves performing standard operating condition simulation calculations based on the monitoring area and molding die parameters, includes: Static and quasi-static simulation calculations based on standard operating condition parameters are performed in the monitoring area to extract the pressure distribution, shear stress distribution, and stress concentration points at the initial contact instant. Attach pressure-sensitive paper to the mold parting surface, apply the rated clamping force to close the mold, and record the actual contact pressure distribution on the parting surface. Use an R-angle gauge to measure the actual chamfer radius of the mold corner transition area, and mark the sharp areas with a radius less than 0.5mm; The pressure and stress distributions are overlaid on the corresponding contact surfaces of the initial 3D design model in the form of color cloud maps to form a reference contact state diagram.

[0023] In one embodiment, the initial three-dimensional design model is imported into the finite element analysis system, and the contact pairings within the monitoring area are meshed to generate a finite element model; It should be noted that the standard operating parameters include rated clamping force, peak injection pressure, and mold operating temperature; the rated clamping force is set to 2000kN to 3000kN, and the peak injection pressure is set to 80MPa to 120MPa. The above standard working parameters are applied as loads and boundary conditions on the finite element model, and static simulation calculations are performed to extract the pressure data matrix of the contact surface nodes after the mold is closed and stabilized. Then, quasi-static simulation calculations are performed to simulate the pressure changes during the injection molding process and extract the shear stress data matrix at the initial contact moment. At the same time, the system automatically retrieves nodes whose stress values ​​exceed the preset stress benchmark and marks them as stress concentration points.

[0024] In another embodiment, the operation of recording the actual contact pressure distribution at the parting surface specifically involves: A 100μm thick ultra-low pressure pressure-sensitive paper was cut into a shape that matched the monitoring area of ​​the mold parting surface. It was then attached to the parting surface of one side of the mold without wrinkles using special fixing tape. The mold was installed on an injection molding machine, a rated clamping force of 2500kN was applied and held for 30 seconds before the mold was opened. The colored pressure-sensitive paper was removed, and its color image was acquired using a high-precision image scanner. Based on the pressure-color depth calibration curve of the pressure-sensitive paper, the grayscale value of the image was converted into quantified pressure distribution data for subsequent calibration of the simulation model.

[0025] In one implementation of this embodiment, the operation of measuring the actual chamfer radius of the mold corner transition area is specifically as follows: Using a 0.1mm precision R-angle gauge, its measuring edge is placed tightly against the curved surface of all corner transition areas on the mold; the radius value corresponding to the R-angle gauge edge that is completely in contact with the curved surface is read and recorded, and the measured value is correlated with the corresponding geometric features on the initial three-dimensional design model; It should be noted that areas with a radius of less than 0.5 mm are defined as sharp areas because they are prone to stress concentration when subjected to force, and the system will highlight such areas.

[0026] In another embodiment, the operation of forming the reference contact state diagram specifically includes: The extracted nodal pressure data matrix and nodal shear stress data matrix are assigned to the mesh vertices of the corresponding contact surfaces in the initial 3D design model using a coordinate mapping algorithm. The numerical values ​​are converted into a color gradient from blue (low value) to red (high value) using a preset color map, thereby generating a visual pressure distribution cloud map and stress distribution cloud map on the surface of the 3D model. Finally, the two cloud maps are overlaid on the surface of the initial 3D design model with 50% transparency to form a reference contact state diagram containing pressure, stress, and stress concentration point markers.

[0027] Preferably, adjusting process parameters and structural parameters through a preset interactive interface in step S2 includes: High-stress areas with stress values ​​exceeding a preset stress threshold are identified from the baseline contact condition diagram; Install resistance strain gauges on the mold, connect a strain tester, record the strain values ​​of the parting surface under different clamping forces, and plot the clamping force-strain curve; Three sets of test blocks were fabricated, and the stress concentration factor at each chamfer radius was measured. Based on the clamping force-strain curve and stress concentration factor, the high-stress area is associated with the clamping force and the chamfer radius of the contact surface, and the parameter adjustment slider is configured. Each time a parameter slider is adjusted, a lightweight wear calculation is performed.

[0028] In one embodiment, the system automatically traverses all grid nodes in the reference contact state diagram and reads the stress value of each node; the read stress value is compared with 70% of the preset material yield strength as a stress threshold; It should be noted that the stress threshold is set to 350 MPa; any continuous area formed by nodes with stress values ​​higher than 350 MPa is automatically identified by the system and highlighted with a red border, and defined as a high-stress area.

[0029] In another embodiment, the operation of plotting the clamping force-strain curve is as follows: At the actual mold location corresponding to the high-stress zone, a resistance strain gauge with a resistance of 120Ω and a sensitivity coefficient of 2.0 is attached along the direction of the maximum principal stress. The strain gauge is connected to a strain gauge tester via a bridge circuit. The clamping force is gradually increased from 1000kN to 3000kN in 500kN increments, and held for 10 seconds at each clamping force level while recording stable strain values. The recorded multiple sets of (clamping force, strain value) data are subjected to linear regression fitting to generate the clamping force-strain relationship curve for the high-stress zone.

[0030] In one implementation of this embodiment, the operation of measuring the stress concentration factor specifically involves: Using the same P20 steel as the mold body, three sets of test blocks were manufactured through precision machining. Each set of test blocks contained corner structures with chamfer radii of 0.5mm, 1.0mm, 1.5mm, 2.0mm, and 2.5mm, respectively. Micro-strain gauges were attached to the root of each chamfer radius, and a known tensile load was applied to the test blocks. The local strain at each point was recorded using a strain gauge. Through the formula: ; Calculate the stress concentration factor, where Stress concentration factor The maximum nominal stress at the chamfer root is calculated using the measured local strain and the material's elastic modulus. The nominal stress at a uniform cross-section far from the chamfer; the calculated stress corresponding to each chamfer radius. The values ​​are stored to form a chamfer radius-stress concentration factor database.

[0031] In another embodiment, the operation of configuring the parameter adjustment slider is specifically as follows: On the interactive interface, a set of related parameter adjustment sliders are generated for each identified high-stress area; specifically, a "clamping force" slider is generated, whose adjustment range is set from 1500kN to 2800kN based on the clamping force-strain curve; at the same time, a "chamfer radius" slider is generated to affect the structural rotation angle of the high-stress area, whose adjustment range is set from 0.5mm to 2.5mm based on the chamfer radius-stress concentration factor database. It should be noted that the adjustment of the slider and the stress value of the high-stress area are mapped to each other through the above curve and the database, so that each movement of the slider corresponds to a specific parameter input.

[0032] In one implementation of this embodiment, the operation of performing lightweight wear calculation specifically involves: When the user drags any parameter slider (e.g., adjusting the clamping force slider from 2500kN to 2400kN), the system immediately obtains the new parameter value represented by the slider; the system calls a pre-built reduced-order model (ROM), which is constructed based on the full-size finite element analysis results and can quickly estimate the contact pressure changes in the high-stress zone and its adjacent areas under the new parameters; based on the updated contact pressure, a simplified Arcard wear model is used. The system performs rapid calculations of instantaneous wear rates and feeds the results back to the interface, enabling real-time response to parameter adjustments. This refers to the amount of wear. The wear coefficient is... To contact pressure, The relative sliding speed, For time.

[0033] Preferably, the real-time calculation and display of the wear rate distribution of the mold contact surface in step S2 includes: The contact surface pressure distribution is recalculated based on the adjusted parameters to generate updated contact surface pressure data. Substitute the updated contact surface pressure data into the preset wear model to calculate the wear rate value for each contact point; A wear prediction cloud map is generated based on the wear rate value and updated and displayed on the interface in real time. Calculate the regional wear uniformity index of the wear prediction cloud map.

[0034] In one embodiment, when the position of a parameter slider (such as "clamping force" or "chamfer radius") in the interactive interface changes, the system uses the adjusted parameter value as a new boundary condition or geometric input; it calls a pre-compiled response surface model (RSM) or reduced-order model (ROM) for rapid solution. This model is pre-calculated and fitted through a large number of full-size finite element simulations, and can recalculate the contact pressure of all grid nodes in the entire monitoring area within milliseconds; the calculation result is stored in the form of an N×1 dimensional vector, where N is the total number of grid nodes in the monitoring area, and this vector is the updated contact surface pressure data.

[0035] In another embodiment, the operation of calculating the wear rate value for each contact point specifically involves: The system iterates through each pressure value in the updated contact surface pressure data vector. ; each Substitute into the preset Archard wear model Calculate the corresponding grid nodes unit cycle wear rate ; It should be noted that the meanings of the parameters in the formula are as follows: For the first The wear rate of each node (unit: mm / cycle), where K is a dimensionless wear coefficient, the value of which is determined to be 1.5 × 10⁻ based on the pairing test of mold steel P20 and molding material ABS. 5 s is the relative sliding distance of each mold opening and closing, set to 0.2mm, and H is the Brinell hardness of the mold steel, set to 300HBW.

[0036] In one implementation of this embodiment, the operation of real-time updating and displaying the wear prediction cloud map specifically involves: The calculated wear rate value for each node The coordinates are assigned to the corresponding mesh nodes on the surface of the 3D model; the same color mapping table as the reference contact state diagram is used to map the wear rate value from low to high to a gradient color from blue to red; the system's graphics rendering engine uses the updated node color data to redraw the mold contact surface on the interactive interface, thereby realizing real-time refreshing of the wear prediction cloud map, with a refresh rate of no less than 30 frames per second.

[0037] In another embodiment, the operation of calculating the regional wear uniformity index of the wear prediction cloud map is specifically as follows: After each update of the wear prediction cloud map, the system automatically calculates the standard deviation of the wear rate for the entire monitoring area. and average wear rate ; Through the formula: ; Calculate the wear uniformity index of the area It should be pointed out that, The value range is from 0 to 1. The closer the value is to 1, the more uniform the wear rate distribution. This index, as a quantitative indicator, will be displayed in a prominent position on the interactive interface in real time to guide the user's parameter adjustment operations.

[0038] Preferably, the color homogenization of the wear prediction cloud map in step S2 includes: By repeatedly adjusting multiple parameter sliders, the color distribution of the wear prediction cloud map tends to be uniform. The uniformity evaluation standard is that the ratio of the wear rate of the high wear area to the low wear area does not exceed the preset wear threshold. Each parameter adjustment is recorded to form parameter-uniformity relationship data; When the wear distribution reaches the preset wear uniformity, record the specific values ​​of all current parameter sliders and generate an optimized working condition configuration file; at the same time, save the current wear prediction results as an optimized wear rate map in the form of a three-dimensional data matrix.

[0039] In one embodiment, the operator repeatedly adjusts multiple parameter sliders such as "clamping force" and "chamfer radius" on an interactive interface; each adjustment generates a real-time calculation and update of the wear prediction cloud map; it should be noted that the uniformity evaluation standard is quantified as the ratio of the wear rate of high-wear areas to low-wear areas. The calculation method is as follows: ; in This represents the average value of the top 5% of nodes with the highest wear rate in the cloud map. This is the average value of the last 5% of nodes with the lowest wear rate in the cloud map; the goal of adjustment is to make... The wear threshold is not exceeded 3.0.

[0040] In another embodiment, the operation of forming parameter-uniformity relationship data specifically involves: The system backend records every adjustment of the parameter sliders; specifically, when any slider position changes and stabilizes for 0.5 seconds, the system automatically captures the values ​​of all current parameter sliders (e.g., clamping force). chamfer radius (and simultaneously record the area wear uniformity index calculated at this moment) Each captured data point is treated as a separate data point. , ,..., The data is stored in a data table, thus forming a multidimensional mapping relationship between parameter combinations and wear uniformity.

[0041] In one implementation of this embodiment, the operation of generating the optimized operating condition configuration file and the optimized wear rate map specifically involves: When the operator adjusts the interface to make the area wear uniformity index U reach or exceed the preset value of 0.95 for the first time, and the wear rate ratio... When the stability value is less than 3.0, the system determines that the wear uniformity target has been achieved; the system immediately locks and records the final values ​​of all parameter sliders at this moment, such as clamping force of 2450kN and relevant chamfer radius of 1.8mm; and records these parameters in key-value pairs (e.g., ...). <parameter Name="LockingForce" Value="2450kN" / > Save it as an optimized working condition configuration file in XML format; at the same time, save the final wear prediction result displayed on the current interface, that is, the wear rate value of each grid node, as an N×M three-dimensional data matrix, which is the optimized wear rate map, where N and M are the dimensions of the model surface grid.

[0042] Preferably, step S3, which calculates the cumulative wear depth based on the optimized wear rate map and the preset optimal performance point, includes: Receive the number of production cycles expected by the user to achieve the best fit of the mold, and set this number as the optimal performance point; By controlling the wear amount of the grinding wheel, the wear state of different cycles is simulated, and the dimensional deviation under each state is measured; Measure the actual clearance change of the parting surface under different clamping forces, and calibrate the predicted wear depth value; Based on the optimized wear rate map, the cumulative total wear depth at each contact surface grid point of the mold is calculated during the number of cycles from the first cycle to the optimal performance point. The cumulative total wear depth is stored in the form of three-dimensional mesh data to generate the target cycle wear depth map. The target periodic wear depth map is smoothed to eliminate outliers and discontinuous areas.

[0043] In one embodiment, the operation of setting the optimal performance point specifically involves: The input box on the interactive interface receives the number of production cycles expected by the operator to achieve optimal mold fit. It should be noted that, The typical value range is from 50,000 to 100,000 times. In this embodiment, it is set to... The number of cycles is 80,000; the system uses this value of 80,000 as the target cycle endpoint for calculating the cumulative wear depth, i.e., the optimal performance point.

[0044] In another embodiment, the operation of calibrating the wear depth prediction value specifically involves: On a P20 steel test block made of the same material as the mold, controlled grinding was performed using a precision surface grinder. The wear depth of different cycle counts was simulated by controlling the total feed rate of the grinding wheel, for example, grinding away 0.01mm, 0.02mm, and 0.03mm of material layers. The actual dimensional deviation of the test block after each grinding state was measured using a coordinate measuring machine (CMM) to establish the correspondence between the grinding amount and the dimensional deviation. In addition, the actual mold was placed on a press, and a feeler gauge was placed at the parting surface gap to measure the change in the actual closed gap of the parting surface under clamping forces of 1500kN, 2000kN, and 2500kN. The above two sets of measured data were input into the system, and the system fine-tuned the wear coefficient K in the theoretical wear calculation model accordingly to calibrate the absolute accuracy of the wear depth prediction.

[0045] In one implementation of this embodiment, the operation of generating the target periodic wear depth map specifically involves: The system iterates through each grid node in the optimized wear rate map. Read its unit cycle wear rate ; Through the formula: ; Calculate the total cumulative wear depth of the node when it reaches its optimal performance point. ; in, For nodes Total wear depth, For nodes The wear rate per unit cycle (mm / cycle). The number of loops for the optimal performance point; The total cumulative wear depth of all nodes The data is stored in the form of a three-dimensional mesh, forming a target periodic wear depth map that is consistent with the geometric topology of the mold surface.

[0046] In another embodiment, the operation of smoothing the target periodic wear depth map specifically involves: The system calculates the depth value of each node in the target periodic wear depth map. Apply a Gaussian smoothing filter; Specifically, the new depth value for each node. The depth values ​​of the node itself and its eight neighboring nodes are used to calculate a weighted average, with the weights distributed according to a Gaussian function. It should be noted that this processing aims to eliminate isolated depth abruptness points caused by computational errors or mesh singularities, and to make the transition of areas with discontinuous depth changes (such as the boundary between different materials) more natural, thereby ensuring the continuity and smoothness of subsequent surface offsets.

[0047] Preferably, step S3, which involves compensating for surface offset in the initial 3D design model, includes: The contact surface of the initial 3D design model is discretized into a high-density grid lattice; The actual mold parting surface is rapidly scanned to capture the surface micro-morphology and compared with the theoretical model using point cloud analysis. Scan the chamfered section of the mold along the set path and extract the actual chamfer curve data; For each point in the grid, read the depth value corresponding to that point in the target periodic wear depth map, and calculate the offset vector based on that depth value; Offset each grid point spatially along the offset vector to construct an offset point cloud; Adaptive reconstruction of the offset point cloud is performed to generate a continuous surface; Perform local feature preservation processing on continuous surfaces; Perform assembly verification and fit relationship check on the model after offset operation.

[0048] In one embodiment, the operation of discretizing the contact surface of the initial three-dimensional design model into a high-density grid lattice specifically involves: All contact surfaces in the initial 3D design model are extracted and then meshed using a surface reconstruction algorithm. It should be noted that the mesh is generated using triangular elements, and the average side length of the mesh is set to 0.2mm to ensure the geometric accuracy of subsequent offset compensation.

[0049] In another embodiment, the operation of rapidly scanning the actual mold parting surface specifically involves: A white light scanner is used to scan the parting surface of a newly processed, unused mold insert, with a point cloud density of 100 points per square millimeter. The actual surface point cloud obtained from the scan is compared with the theoretical smooth surface of the initial 3D design model. The system automatically calculates the distribution of micro-morphological deviations caused by factors such as machining tool marks, and this deviation data will be used as the correction benchmark for offset compensation.

[0050] In one implementation of this embodiment, the operation of calculating the offset vector is specifically as follows: For each point in the high-density grid lattice First, calculate the normal vector at that point. ; Then, read the cumulative total wear depth value corresponding to that point from the target cycle wear depth map. ; offset vector Through the formula: ; Calculations show that the direction of this vector is the outward normal direction of the surface, and its magnitude is equal to the total wear depth at that point.

[0051] In another embodiment, the operations of constructing the offset point cloud and generating the continuous surface are as follows: The system traverses every point in the high-density grid. , and its coordinates with the corresponding offset vector Add them together to get the new coordinates of the point in space. The set of all new coordinate points constitutes the offset point cloud. The offset point cloud is processed by the Poisson Surface Reconstruction algorithm, which fits an implicit function that best approximates all offset points by solving a Poisson equation, and finally generates a continuous, smooth and hole-free NURBS surface.

[0052] In another implementation of this embodiment, the operation of performing local feature preservation processing on the continuous surface is specifically as follows: The system first automatically identifies key geometric features such as sharp edges, chamfers, and round holes on the original surface. After performing surface offset, it performs local topological comparison and geometric correction on these feature areas. For example, for a chamfer feature, the system ensures that the chamfer radius after offset is consistent with the original design value, and ensures the G2 level continuity transition between the chamfer and the adjacent offset surface through surface blending technology.

[0053] In one operation step of this embodiment, the specific operation of performing assembly verification and mating relationship check on the model after the offset operation is as follows: All generated pre-compensated surfaces are virtually reassembled with other fixed components of the mold; clearance and interference analysis are performed, and the system automatically detects the minimum distance between all mating surfaces; if an interference area is detected, it is determined that the pre-compensation is excessive; if a clearance is detected that is greater than the preset tolerance of 0.02mm, it is determined that the pre-compensation is insufficient; the system will highlight these unqualified areas and provide suggestions for local offset adjustment until all mating relationships meet the initial design requirements. The final model is the pre-compensated 3D model.

[0054] Preferably, performing local feature preservation processing on continuous surfaces includes: Identify the geometric features of the mold surface. Local coordinate mapping is performed on the geometric features of the mold surface to establish a topological correspondence between the original features and the offset features; Based on the topological correspondence, the offset surface is locally adjusted to maintain the shape characteristics of the geometric features; Hybrid interpolation is performed in the feature transition region.

[0055] In one embodiment, the operation of identifying the geometric features of the mold surface specifically includes: The system automatically performs geometric analysis on the surfaces in the initial 3D design model, calculating the principal curvature of each grid point. and and its gradient to identify features; It should be noted that areas with a curvature change rate exceeding a preset threshold of 10 mm⁻² are identified as edges or sharp edges; cylindrical or toroidal surfaces with constant curvature are identified as holes or chamfers; the system classifies all identified geometries, such as fillets with a radius of 2.0 mm and positioning holes with a depth of 5.0 mm, and establishes a feature list.

[0056] In another embodiment, the operation of establishing the topological correspondence is specifically as follows: For each geometric feature in the feature list, the system establishes a local parametric coordinate system for it. Taking a chamfer feature as an example, the system extracts its center trajectory line (ridge line) and cross-sectional contour as its parametric definition. Then, on the surface after global offset, the system searches for and determines the mapping position of the original ridge line and contour line according to the nearest point principle, thereby establishing a point-to-point topological correspondence between the original feature and the offset surface region.

[0057] In one implementation of this embodiment, the operation of local surface adjustment specifically involves: Based on the established topological correspondence, the system first performs logical cut-off on the continuous surface after global offset, removing the distorted region corresponding to the original feature. Then, the system calls the parameterized definition of the original feature, such as a chamfer with a radius of 2.0 mm, and regenerates a new chamfered surface with accurate geometry (i.e., the radius is still 2.0 mm) at the new mapped position. This operation ensures that the geometric accuracy of the key functional features is not changed due to global offset compensation.

[0058] In another embodiment, the operation of performing hybrid interpolation is specifically as follows: A transition zone with a width of 0.5 mm is defined between the regenerated feature surface and the surrounding global offset surface. Within this transition zone, the system applies a quintic polynomial blending function to interpolate the two surfaces, generating a completely new connecting surface. It should be noted that this hybrid interpolation process ensures that the curvature at the joint reaches the G2 level, meaning that not only is the position and tangent continuous at the joint, but the curvature also changes continuously, thus ensuring that the surface of the final pre-compensated 3D model is smooth and without any sharp transition marks.

[0059] Preferably, the assembly verification and mating relationship check of the model after the offset operation includes: Perform interference detection on all mating surfaces, mark the interference regions, and calculate the interference volume; For the region where interference is detected, calculate the expected number of interference elimination loops and determine whether the expected number of interference elimination loops is less than the preset loop ratio of the number of loops at the optimal performance point; If the expected number of interference elimination loops is greater than a preset loop ratio of the number of loops at the optimal performance point, then a curvature-based local offset adjustment is performed on the region. For areas where excessive gaps are detected, predict the gap size at the optimal performance point. If the gap exceeds the tolerance requirement, increase the offset of that area. Update all locally adjusted offsets, rebuild the 3D model, and generate a pre-compensated 3D model.

[0060] In one embodiment, the operation of performing interference detection on all mating surfaces specifically involves: In the virtual assembly environment, the offset-compensated mold core and cavity model are positioned according to the actual assembly position; the system automatically performs the intersection operation in Boolean operation on all mating surfaces of the two models. If the operation result generates a solid with a non-zero volume, it is determined that there is interference. It should be noted that the system will highlight the interfering entity in red and calculate its volume (unit: mm³). This interfering area is the marked interfering area.

[0061] In another embodiment, the operation of calculating the expected number of interference elimination cycles specifically involves: For each detected interference region, the system extracts its interference volume. And query the average wear rate per unit cycle for that region from the optimized wear rate map. ; Through the formula: ; Calculate the expected number of interference elimination cycles ,in The contact area of ​​the interference region; the system will calculate The result is compared to a preset threshold, which represents the number of loops required to achieve the optimal performance. 10%; if If the number of judgments is 80,000, then the judgment threshold is 8,000.

[0062] In one implementation of this embodiment, the operation of performing local offset adjustment on the interference region specifically involves: If calculated If the number of iterations exceeds 8000, the system determines that the initial interference is too large. The system will then adjust the original surface offset within this interference region by reducing it. It should be noted that the reduction in offset is not uniformly distributed, but rather proportional to the local surface curvature of the region. That is, more offset is reduced at locations with greater curvature to ensure a smooth transition of the adjusted surface. The goal of this adjustment is to make the recalculated surface... It is exactly less than 8000 times.

[0063] In another embodiment, the operation of adjusting the area with excessively large gaps specifically involves: The system detects the initial clearance between all mating surfaces. ,like If the value is greater than zero, it indicates a gap region; the system predicts that it will reach its optimal performance point. The final gap in this area The calculation method is as follows: ; in This represents the cumulative wear depth of the opposite part in this area; if the calculated... If the offset exceeds the preset tolerance requirement by 0.01mm, the system determines that the initial compensation is insufficient and will increase the original offset of that area by an amount that makes the initial compensation insufficient. The goal is to converge to 0.01 mm.

[0064] In one operation step of this embodiment, the operation of generating the pre-compensated 3D model specifically includes: The system updates all local offsets that have been adjusted (reduced or increased) through the above steps to the original target periodic wear depth map; based on the updated final wear depth map, the entire process of model surface offset compensation is re-executed, including constructing the offset point cloud and generating a continuous smooth surface; the final 3D model generated after this round of verification and correction is the qualified pre-compensated 3D model.

[0065] Of particular importance, step S4 includes: Convert the pre-compensated 3D model into an industry-standard data format and add machining process annotations and dimensional tolerance information; Based on the initial fit state of the pre-compensated 3D model, suggestions for adjusting process parameters in the early stage of mold use are formulated to form a mold break-in period guidance plan; Based on the optimized wear rate map, the performance change curve of the whole life cycle is predicted. The mold service cycle is divided into the break-in period, the stable period and the decline period. Parameter adjustment strategies are formulated for each period to form a whole life cycle maintenance plan. The pre-compensated 3D model, optimized working condition configuration file, mold break-in period guidance plan, and full life cycle maintenance plan are encapsulated to generate a molding die intelligent design data package.

[0066] In one embodiment, the operation of converting the pre-compensated 3D model into an industry-standard data format and adding annotations specifically involves: The final pre-compensated 3D model is exported as a STEP AP242 format file, which contains precise geometry and additional Product and Manufacturing Information (PMI). In this model file, machining process annotations are added to key functional surfaces. For example, the cavity surface is marked with "Requires EDM finishing, surface roughness Ra0.8μm". At the same time, the geometric dimensions and tolerances (GD&T) information of key mating dimensions are marked. For example, the positioning tolerance of the guide post and guide sleeve is marked as 0.01mm.

[0067] In another embodiment, the specific steps for creating a mold break-in period guidance plan are as follows: Based on the initial interference state of the pre-compensated 3D model, the system automatically generates recommended process parameters for the break-in period. It should be noted that this is intended to allow the initial interference area to break in smoothly under controlled low-pressure conditions. Specifically, the recommendations are: within the first 8000 production cycles (i.e., the expected interference elimination cycle), set the clamping force to 90% of the optimized operating value, i.e., 2205kN, and reduce the injection speed to 80% of the normal speed. These recommendations are recorded in text form to form a mold break-in period guidance document.

[0068] In one implementation of this embodiment, the operation of forming a full life-cycle maintenance plan specifically includes: Based on the optimized wear rate map, the system predicts the change curve of the product flash amount with the number of production cycles through cumulative calculation; according to the change of the slope of the curve, the entire life cycle of the mold is automatically divided into three stages: the break-in period from 0 to 8000 cycles, the stabilization period from 8001 to 80000 cycles, and the decline period after 80001 cycles. Parameter adjustment strategies are formulated for each phase: during the stable phase, the parameters in the optimized working condition configuration file are strictly implemented; when entering the decline phase and the predicted flash exceeds 0.05mm, the system recommends increasing the clamping force by 2% to 5% based on the optimized value to compensate for wear clearance; these strategies together constitute the full life cycle maintenance plan.

[0069] In another embodiment, the operation of generating the intelligent design data package for molding dies specifically involves: Use data compression and archiving technology to encapsulate the following four files: 1. A pre-compensated 3D model file in STEP AP242 format containing machining process annotations and tolerance information; 2. Optimized operating condition configuration file in XML format; 3. A mold break-in period guidance plan in PDF format; 4. A full lifecycle maintenance plan in PDF format; The above files are packaged into a ZIP compressed file with a version number and generation timestamp. This file is the final delivered intelligent design data package for the molding die.

[0070] Therefore, the embodiments should be considered as exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalents of the application are intended to be included within the invention.

[0071] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A method for intelligent three-dimensional design and generation of molding dies, characterized in that, The method includes the following steps: Step S1: Read the initial 3D design model of the molding die, identify the dynamic contact pairing in the molding die, define the monitoring area, and obtain the molding die parameters; Step S2: Perform standard working condition simulation calculations based on the monitoring area and molding die parameters. Adjust process parameters and structural parameters through a preset interactive interface, calculate and display the wear rate distribution of the mold contact surface in real time, and obtain a wear prediction cloud map. Perform color uniformization on the wear prediction cloud map to generate an optimized wear rate map and an optimized working condition configuration file. Step S3: Calculate the cumulative wear depth based on the optimized wear rate map and the preset optimal performance point, and perform model surface offset compensation on the initial three-dimensional design model to obtain the pre-compensated three-dimensional model; Step S4: Bind the pre-compensated 3D model to the optimized working condition configuration file, and generate a molding die intelligent design data package based on the pre-compensated 3D model and the optimized working condition configuration file.

2. The intelligent three-dimensional design and generation method for molding dies according to claim 1, characterized in that, Step S2, which involves performing standard operating condition simulation calculations based on the monitoring area and molding die parameters, includes: Static and quasi-static simulation calculations based on standard operating condition parameters are performed in the monitoring area to extract the pressure distribution, shear stress distribution, and stress concentration points at the initial contact instant. Attach pressure-sensitive paper to the mold parting surface, apply the rated clamping force to close the mold, and record the actual contact pressure distribution on the parting surface. Use an R-angle gauge to measure the actual chamfer radius of the mold corner transition area, and mark the sharp areas with a radius less than 0.5mm; The pressure and stress distributions are overlaid on the corresponding contact surfaces of the initial 3D design model in the form of color cloud maps to form a reference contact state diagram.

3. The intelligent three-dimensional design and generation method for molding dies according to claim 2, characterized in that, Step S2, which involves adjusting process and structural parameters through a preset interactive interface, includes: High-stress areas with stress values ​​exceeding a preset stress threshold are identified from the baseline contact condition diagram; Install resistance strain gauges on the mold, connect a strain tester, record the strain values ​​of the parting surface under different clamping forces, and plot the clamping force-strain curve; Three sets of test blocks were fabricated, and the stress concentration factor at each chamfer radius was measured. Based on the clamping force-strain curve and stress concentration factor, the high-stress area is associated with the clamping force and the chamfer radius of the contact surface, and the parameter adjustment slider is configured. Each time a parameter slider is adjusted, a lightweight wear calculation is performed.

4. The intelligent three-dimensional design and generation method for molding dies according to claim 3, characterized in that, Step S2, which involves real-time calculation and display of the wear rate distribution on the mold contact surface, includes: The contact surface pressure distribution is recalculated based on the adjusted parameters to generate updated contact surface pressure data. Substitute the updated contact surface pressure data into the preset wear model to calculate the wear rate value for each contact point; A wear prediction cloud map is generated based on the wear rate value and updated and displayed on the interface in real time. Calculate the regional wear uniformity index of the wear prediction cloud map.

5. The intelligent three-dimensional design and generation method for molding dies according to claim 4, characterized in that, Step S2, which involves color homogenization of the wear prediction cloud map, includes: By repeatedly adjusting multiple parameter sliders, the color distribution of the wear prediction cloud map tends to be uniform. The uniformity evaluation standard is that the ratio of the wear rate of the high wear area to the low wear area does not exceed the preset wear threshold. Each parameter adjustment is recorded to form parameter-uniformity relationship data; When the wear distribution reaches the preset wear uniformity, record the specific values ​​of all current parameter sliders and generate an optimized working condition configuration file; at the same time, save the current wear prediction results as an optimized wear rate map in the form of a three-dimensional data matrix.

6. The intelligent three-dimensional design and generation method for molding dies according to claim 1, characterized in that, Step S3, which calculates the cumulative wear depth based on the optimized wear rate map and the preset optimal performance point, includes: Receive the number of production cycles expected by the user to achieve the best fit of the mold, and set this number as the optimal performance point; By controlling the wear amount of the grinding wheel, the wear state of different cycles is simulated, and the dimensional deviation under each state is measured; Measure the actual clearance change of the parting surface under different clamping forces, and calibrate the predicted wear depth value; Based on the optimized wear rate map, the cumulative total wear depth at each contact surface grid point of the mold is calculated during the number of cycles from the first cycle to the optimal performance point. The cumulative total wear depth is stored in the form of three-dimensional mesh data to generate the target cycle wear depth map. The target periodic wear depth map is smoothed to eliminate outliers and discontinuous areas.

7. The intelligent three-dimensional design generation method for molding dies according to claim 6, characterized in that, Step S3, which involves compensating for surface offset in the initial 3D design model, includes: The contact surface of the initial 3D design model is discretized into a high-density grid lattice; The actual mold parting surface is rapidly scanned to capture the surface micro-morphology and compared with the theoretical model using point cloud analysis. Scan the chamfered section of the mold along the set path and extract the actual chamfer curve data; For each point in the grid, read the depth value corresponding to that point in the target periodic wear depth map, and calculate the offset vector based on that depth value; Offset each grid point spatially along the offset vector to construct an offset point cloud; Adaptive reconstruction of the offset point cloud is performed to generate a continuous surface; Perform local feature preservation processing on continuous surfaces; Perform assembly verification and fit relationship check on the model after offset operation.

8. The intelligent three-dimensional design generation method for molding dies according to claim 7, characterized in that, Performing local feature preservation processing on continuous surfaces includes: Identify the geometric features of the mold surface. Local coordinate mapping is performed on the geometric features of the mold surface to establish a topological correspondence between the original features and the offset features; Based on the topological correspondence, the offset surface is locally adjusted to maintain the shape characteristics of the geometric features; Hybrid interpolation is performed in the feature transition region.

9. The intelligent three-dimensional design generation method for molding dies according to claim 7, characterized in that, Assembly verification and mating relationship checks of the model after offset operation include: Perform interference detection on all mating surfaces, mark the interference regions, and calculate the interference volume; For the region where interference is detected, calculate the expected number of interference elimination loops and determine whether the expected number of interference elimination loops is less than the preset loop ratio of the number of loops at the optimal performance point; If the expected number of interference elimination loops is greater than a preset loop ratio of the number of loops at the optimal performance point, then a curvature-based local offset adjustment is performed on the region. For areas where excessive gaps are detected, predict the gap size at the optimal performance point. If the gap exceeds the tolerance requirement, increase the offset of that area. Update all locally adjusted offsets, rebuild the 3D model, and generate a pre-compensated 3D model.

10. An intelligent three-dimensional design and generation system for molding dies, characterized in that, For performing the intelligent 3D design generation method for molding dies as described in claim 1, the intelligent 3D design generation system for molding dies comprises: The model parameter acquisition module is used to read the initial three-dimensional design model of the molding die, identify dynamic contact pairings in the molding die, define the monitoring area, and obtain the molding die parameters. The wear optimization analysis module is used to perform standard working condition simulation calculations based on the monitoring area and molding die parameters. Through an interactive interface, process parameters and structural parameters are adjusted, and the wear rate distribution of the mold contact surface is calculated and displayed in real time to obtain a wear prediction cloud map. The wear prediction cloud map is then color-uniformed to generate an optimized wear rate map and an optimized working condition configuration file. The reverse compensation design module is used to calculate the cumulative wear depth based on the optimized wear rate map and the preset optimal performance point, perform non-uniform surface offset operation on the initial three-dimensional design model, perform assembly verification and fit relationship check on the model after offset operation, and generate a pre-compensated three-dimensional model. The intelligent data integration module is used to bind the pre-compensated 3D model with the optimized working condition configuration file, and generate a molding die intelligent design data package based on the pre-compensated 3D model and the optimized working condition configuration file.

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