An automobile covering mold process parameter optimization method and system

Abstract

The application discloses a kind of automobile covering piece mould process parameter optimization method and system, it is related to mould optimization technical field, including: based on the mould three-dimensional digital model of target automobile covering piece, the working part of mould is divided into multiple key areas with different structural characteristics;For each key area divided, quantitatively define the region to meet one or more processing performance requirements required to achieve stable processing;At least one preliminary surface strengthening or modification process scheme and its initial parameter range are generated for each region, forming a differentiated process scheme set for the mould;Analysis of the interrelated effects that different regions of the process can produce during implementation;Generate globally executable collaborative manufacturing process chain.The application has the advantages that: establish the quantitative mapping and collaborative optimization mechanism from the structural characteristics of mould to processing requirements, to specific process scheme and parameter, realize the precision, differentiation design of covering piece mould surface treatment.

Description

Technical Field

[0001] This invention relates to the field of mold optimization technology, specifically to a method and system for optimizing process parameters of automotive body panel molds. Background Technology

[0002] In the automotive manufacturing industry, automotive body panel molds are core equipment in the stamping process. The wear resistance, anti-adhesion, and fatigue performance of their working surfaces directly determine the forming quality, production efficiency, and mold life of the body panels. With the increasingly widespread application of lightweight and high-strength materials in automobiles, the service conditions of molds are becoming increasingly demanding. Traditional mold process parameter optimization relies heavily on engineers' experience, failing to adequately consider the differentiated performance requirements of different areas of the mold. It often employs a uniform, "one-size-fits-all" surface treatment process, leading to premature failure in critical areas and making it difficult for the overall mold life and stability to meet the requirements of modern, efficient, and high-precision manufacturing.

[0003] Existing technologies have included process optimization for specific mold regions, but they generally lack systematic collaborative consideration. Most methods focus on matching independent process parameters for a single region, failing to comprehensively consider the physical interrelationships between different regions during implementation, such as thermal effects and stress concentration, which can easily lead to process chain conflicts or performance bottlenecks. Furthermore, process scheme verification often relies on trial and error or simple simulations, resulting in insufficient evaluation of the overall mold performance, which includes differentiated surface characteristics, leading to uncertainties in the process chain during actual production. Therefore, there is an urgent need for a systematic optimization method that can achieve collaborative design of differentiated processes across all mold regions and be fully verified through virtual simulation before manufacturing, in order to improve the overall performance of the mold and ensure manufacturing feasibility and economy. Summary of the Invention

[0004] To solve the above-mentioned technical problems, a method and system for optimizing the process parameters of automotive body panel molds are provided. This technical solution solves at least one of the technical problems mentioned in the background section.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for optimizing process parameters of automotive body panel molds includes: Based on the three-dimensional digital model of the mold for the target automotive body panel, and combined with the simulation results of the molding process, the working part of the mold is divided into several key areas with different structural features. For each key region identified, based on its structural characteristics and its function in the stamping process, the region is quantitatively defined as one or more processing performance requirements that need to be met to achieve stable processing. The quantified processing performance requirements, shape, and location of each region are matched with a pre-set process knowledge base to generate at least one preliminary surface strengthening or modification process scheme and its initial parameter range for each region, forming a set of differentiated process schemes for the mold. The analysis examines the potential interrelationships between the processes matched to different regions within the aforementioned set of differentiated process solutions during physical implementation. Based on the results of the correlation impact analysis, the execution order of processes in all regions is optimized and sorted, and for process combinations with negative correlation impacts, corresponding elimination processes or compensation measures are designed and inserted to generate a globally executable collaborative manufacturing process chain. A mold simulation model is established, which includes the surface layer characteristics of each region determined by the matrix material and the aforementioned collaborative manufacturing process chain. Multiphysics coupling simulation is performed under simulated stamping cyclic load to evaluate the overall performance of the mold and the feasibility of the process chain. Output the final set of process parameters verified by simulation and the collaborative manufacturing process chain to generate a digital process specification that can directly guide production.

[0006] Preferably, the three-dimensional digital model of the mold based on the target automotive body panel, combined with the molding process simulation results, divides the working part of the mold into multiple key areas with different structural features, specifically including: Import the 3D model of the mold and load the stamping process simulation data corresponding to the mold; Based on the stress distribution, strain distribution and material flow information in the simulation data, combined with the preset mold area division rules, the working surfaces of the punch, die and blank holder are automatically identified and divided into the main surface area, the severely deformed fillet area, the blank holder contact area and the drawbead area. Key geometric and mechanical characteristic parameters of each divided region are extracted, including radius of curvature, draft angle, relative sliding distance with the sheet metal, average contact pressure, and angle of material flow direction.

[0007] Preferably, for each of the defined key regions, based on its structural characteristics and its function in the stamping process, the quantitative definition of one or more processing performance requirements that the region must meet to achieve stable processing specifically includes: Establish a quantitative index system for processing performance requirements, including at least the wear resistance grade, anti-adhesion grade, fatigue resistance grade, surface hardness requirement range, and lubrication retention requirement; For each key area, based on the extracted structural feature parameters and the experience of mold design experts, the quantitative values ​​or levels corresponding to various performance requirements are calculated. A structured set of processing performance requirements is generated for each key region, which will serve as the input condition for subsequent matching of specific process solutions.

[0008] Preferably, the step of matching the quantified processing performance requirements of each region with a pre-set process knowledge base to generate at least one preliminary surface strengthening or modification process scheme and its initial parameter range for each region, forming a set of differentiated process schemes for the mold, specifically includes: Based on historical mold processing data, a process knowledge base is constructed that includes the mapping relationship between regional attributes and process parameters. The regional attributes include at least three dimensions: performance requirements, regional shape, and regional location. The process parameters include at least the process type and parameter range. Based on the quantified processing performance requirements, shape, and location of a region, the data is matched with the process knowledge base. At least one historical processing data of a mold that meets the processing performance requirements of the region and whose shape and location are more than a threshold similar to the region is selected as the region's matching data. Extract the process parameters from the matching data of the region to serve as the preliminary surface strengthening or modification process scheme and its initial parameter range for the region; Summarize the preliminary surface strengthening or modification process schemes and their initial parameter ranges for all regions to form a set of differentiated process schemes for the mold.

[0009] Preferably, the analysis of the differential process scheme set, specifically including the potential interrelationships between the processes matched to different regions during physical implementation, includes: Construct a knowledge base of interference relationships between processes, which defines the mutual constraints of different surface treatment or strengthening processes in terms of implementation temperature, environmental requirements, and surface condition influence; For the set of differentiated process solutions initially matched for each region, reasoning is performed based on the knowledge base of interference relationships between processes to identify the potential negative correlations that may occur when processes in different regions are implemented sequentially.

[0010] Preferably, the step of optimizing and sorting the execution order of processes in all regions based on the correlation impact analysis results, and designing and inserting corresponding elimination processes or compensation measures for process combinations with negative correlation impacts to generate a globally executable collaborative manufacturing process chain specifically includes: Based on the identification results, with the goal of reducing the impact of correlation and optimizing manufacturing efficiency, a process parameter is selected from all the preliminary surface strengthening or modification process schemes and their initial parameter ranges for each region as the strengthening process for that region, and the main process chain for mold processing is constructed based on the strengthening process for each region. Based on the main process chain of mold processing, for situations where the performance of subsequent process areas may be damaged due to the high temperature thermal effects of previous processes, a process for applying a temporary protective coating to sensitive areas or a process for local repair reprocessing of affected areas is inserted into the process chain. For process combinations with cross-contamination risks, a process for local shielding, special cleaning, or adjusting the processing sequence to concentrate the execution of contaminating processes is inserted into the process chain. For situations where stress accumulation in the mold substrate is caused by multiple high-energy beam local treatments, a global or local stress relief heat treatment process is inserted at the end of the process chain to obtain a globally executable collaborative manufacturing process chain.

[0011] Preferably, the step of establishing a mold simulation model that includes the surface layer characteristics of each region determined by the matrix material and the collaborative manufacturing process chain, and performing multiphysics coupling simulation under simulated stamping cyclic loads to evaluate the overall mold performance and the feasibility of the process chain specifically includes: Simulate the stress state at the interface between the reinforcement layer and the matrix in each region under cyclic thermo-mechanical loading; Analyze the performance transition gradient at the interface of different process zones and whether stress concentration exists; Evaluate the impact of differentiated processes on the overall thermal deformation and dimensional stability of the mold.

[0012] A system for optimizing process parameters of automotive body panel molds, used to implement the above-described method for optimizing process parameters of automotive body panel molds, includes: The region division and demand quantification module is used to divide the working part of the mold into multiple key regions with different structural features based on the three-dimensional digital model of the mold of the target automotive body panel and the simulation results of the forming process. For each key region, the processing performance requirements are quantitatively defined according to its structural features and its function in the stamping process. The process matching and collaborative chain generation module is used to match the quantified processing performance requirements, regional shape, and regional location of each region with a pre-set process knowledge base, generating at least one preliminary surface strengthening or modification process scheme and its initial parameter range for each region, forming a set of differentiated process schemes; analyzing the interrelationships between the processes matched in different regions within the set of differentiated process schemes; based on the results of the correlation analysis, optimizing and sorting the execution order of processes in all regions, and designing and inserting corresponding elimination processes or compensation measures for process combinations with negative correlation effects, generating a globally executable collaborative manufacturing process chain; The simulation verification and procedure output module is used to establish a mold simulation model that includes the surface layer characteristics of each region determined by the matrix material and the collaborative manufacturing process chain. It performs multi-physics coupling simulation under simulated stamping cyclic load, evaluates the overall performance of the mold and the feasibility of the process chain, and outputs the final process parameter set verified by simulation and the collaborative manufacturing process chain to generate a digital process procedure.

[0013] Optionally, the region division and demand quantification module specifically includes: The model and data import unit is used to import the 3D model of the mold and load the corresponding stamping process simulation data; The critical area division unit is used to automatically identify and divide the working surfaces of the punch, die, and blank holder into critical areas, including the main profile area, the severely deformed fillet area, the blank holder contact area, and the drawbead area, based on the stress distribution, strain distribution, and material flow information in the simulation data and in combination with the preset mold area division rules. The feature extraction and demand quantification unit is used to extract the key geometric and mechanical feature parameters of each divided region, and calculate and generate a structured set of processing performance demand descriptions for each key region based on the preset processing performance demand quantification index system and the feature parameters.

[0014] Optionally, the process matching and collaborative chain generation module specifically includes: The process knowledge base stores the regional attribute-process parameter mapping relationship built based on the historical processing data of the mold, as well as the process interference relationship knowledge base that defines the mutual constraints between different processes; The differentiated scheme matching unit is used to match historical data from the process knowledge base based on the processing performance requirements, shape, and location of the region, and generate at least one preliminary surface strengthening or modification process scheme and its initial parameter range for each region. The process chain collaborative optimization unit is used to analyze the negative correlation between processes in different regions of the differentiated process scheme set based on the knowledge base of interference relationships between processes. With the goal of reducing correlation effects and optimizing manufacturing efficiency, it optimizes the process execution sequence and designs and inserts corresponding elimination processes or compensation measures for process combinations with negative correlation effects, thereby generating a collaborative manufacturing process chain.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention achieves precise and differentiated design of the surface treatment of cover part molds by establishing a quantitative mapping and collaborative optimization mechanism from mold structural features to processing requirements, and then to specific process schemes and parameters. By quantifying requirements by region and matching them with historical process knowledge, the traditional "one-size-fits-all" approach is abandoned, and targeted enhancement of the performance of key areas is achieved, thereby significantly improving the overall lifespan and stability of the mold. By systematically analyzing the correlation between processes and optimizing the process chain, necessary compensation procedures are introduced to effectively avoid mutual interference between the implementation of processes in different regions, ensuring the feasibility of complex collaborative manufacturing schemes. By establishing a simulation model containing differentiated surface characteristics for multi-physics coupling verification, the effects of the process chain can be predicted and evaluated before actual manufacturing, greatly reducing trial and error costs and production risks. The final digital process specification can directly guide production, improving the reliability, efficiency, and economy of process design. Attached Figure Description

[0016] Figure 1 This is a flowchart of the method for optimizing the process parameters of automotive body panel molds proposed in this invention; Figure 2 This is a flowchart of the method for dividing a mold into multiple key areas proposed in this invention; Figure 3 This is a flowchart of the method for quantitatively defining the processing performance requirements of each region proposed in this invention; Figure 4 This is a flowchart of the method for generating a set of differentiated process solutions for molds proposed in this invention; Figure 5 This is a flowchart of the method for analyzing interrelated influences proposed in this invention; Figure 6 This is a flowchart of the method for generating a globally executable collaborative manufacturing process chain proposed in this invention. Detailed Implementation

[0017] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0018] Reference Figure 1 As shown, a method for optimizing process parameters of automotive body panel molds includes: Based on a 3D digital model of the mold for the target automotive body panel, and combined with molding process simulation results, the working part of the mold is divided into multiple key areas with different structural features. This breaks away from the traditional approach of treating the mold as a homogeneous whole and intelligently partitions it according to the actual service conditions. By importing the 3D mold model and stamping simulation data, different functional areas such as main surfaces, fillets, and draw beads are automatically identified. This "function-load" based partitioning method ensures that subsequent process design can accurately correspond to the actual wear and stress state of each part of the mold, providing input conditions for precise "targeted" reinforcement. For each key region that is divided, based on its structural characteristics and its function in the stamping process, one or more processing performance requirements that the region needs to meet to achieve stable processing are quantitatively defined. For each divided region, based on its geometric and mechanical characteristics, its functional requirements are transformed into specific and quantifiable performance indicators through built-in expert rules or models, providing clear and calculable targets for subsequent precise matching of specific process parameters. The quantified processing performance requirements, shape, and location of each region are matched with a pre-built process knowledge base to generate at least one preliminary surface strengthening or modification process scheme and its initial parameter range for each region, forming a set of differentiated process schemes for the mold. A pre-built process knowledge base containing a large number of historical cases is then used for matching and retrieval. When the quantified requirements, shape, and location of a region are input, similar cases are searched in the knowledge base, and proven effective process schemes such as plasma nitriding and laser cladding, along with their key parameter ranges, are recommended. This process generates customized preliminary process options for each key region of the mold, ultimately summarizing them into a set of differentiated process schemes for the entire mold, containing multiple possible process paths. This analysis examines the potential interrelationships between different regions within a set of differentiated process solutions during physical implementation. It identifies how the optimal processes for individual regions may conflict when combined. For instance, high-temperature heat treatment in region A might thermally affect the performance of the completed region B; or the coating in region C and the diffusion layer in region D may have compatibility issues at their interface. By performing global reasoning on the initial solution set, potential negative interrelationships such as thermal effects, chemical contamination, and stress interference are identified, providing a problem list for the next stage of overall process chain optimization. Based on the correlation impact analysis results, the execution sequence of all regional processes is optimized and sorted. For process combinations with negative correlation impacts, corresponding elimination processes or compensation measures are designed and inserted to generate a globally executable collaborative manufacturing process chain. This integrates a series of independent regional process schemes into a logically rigorous and efficiently executable sequence of manufacturing instructions. The execution sequence of each process is optimized with the goal of minimizing correlation impacts and improving manufacturing efficiency. Simultaneously, compensation measures are automatically designed for identified process conflicts, such as inserting protective processes before areas susceptible to heat effects or adding a stress-relieving annealing step after all high-energy beam processing. The final output is a feasible collaborative manufacturing process chain that considers inter-process interactions, includes necessary buffering and compensation processes, and is ready for implementation. A mold simulation model was established, incorporating the characteristics of the surface layers in each region as determined by the substrate material and the collaborative manufacturing process chain. Multiphysics coupling simulation was performed under simulated stamping cyclic loads to evaluate the overall mold performance and the feasibility of the process chain. Based on the final scheme determined by the collaborative manufacturing process chain, a refined simulation model was established that reflects the mold substrate and the differentiated surface layers in each region, such as coating thickness, hardness, residual stress, and bonding strength. By applying simulated cyclic stamping loads from actual production to this model, the overall deformation, stress distribution, fatigue life, and bonding reliability between different process layers of the mold can be proactively evaluated. This serves as a digital trial run before actual manufacturing, verifying the effectiveness of the process chain and identifying potential design flaws in advance. The system outputs a final set of process parameters and a collaborative manufacturing process chain, validated through simulation. This generates a digital process specification that can directly guide production. After intelligent decision-making and simulation validation through all the aforementioned steps, the final output consists of two main parts: first, an optimized and validated final set of process parameters containing specific process types and precise parameters for each region; and second, a collaborative manufacturing process chain that details the execution sequence, compensation measures, and process requirements for each process. Together, these two components constitute a digital process specification that can be directly deployed to the production workshop to guide the actual surface strengthening manufacturing of molds, seamlessly connecting the intelligent design results from the front end to the production execution at the back end.

[0019] Reference Figure 2 As shown, in this scheme, based on the three-dimensional digital model of the mold for the target automotive body panel and combined with the simulation results of the molding process, the working part of the mold is divided into several key areas with different structural features, specifically including: Import the 3D model of the mold and load the stamping process simulation data corresponding to the mold; Based on the stress distribution, strain distribution and material flow information in the simulation data, combined with the preset mold area division rules, the working surfaces of the punch, die and blank holder are automatically identified and divided into the main surface area, the severely deformed fillet area, the blank holder contact area and the drawbead area. Extract the key geometric and mechanical characteristic parameters of each divided region, including radius of curvature, draft angle, relative sliding distance with the sheet metal, average contact pressure, and angle of material flow direction.

[0020] Specifically, the above steps aim to perform refined and automated functional zoning of the mold's working surface based on its actual service condition. By importing the mold's 3D model and corresponding stamping simulation data, objective mechanical and physical field basis is provided for zoning, rather than relying solely on geometry. Based on pre-defined, expert-knowledge-based region division rules, for example, areas with high average contact pressure and severe material sliding are identified as "severely deformable fillet areas," automatically classifying and identifying the working surfaces of the punch, die, and blank holder. The preset main profile area, severely deformable fillet area, blank holder contact area, and drawbead area in this embodiment basically cover all typical service locations of the cover die with different failure modes. Multi-dimensional parameters, including geometric and dynamic mechanical characteristics, are extracted for each zone, laying the data foundation for the next step of accurately quantifying performance requirements. This process achieves objectification of zoning standards and automation of the operation process, ensuring the targeted and consistent nature of process optimization.

[0021] Reference Figure 3 As shown, in this scheme, for each key region, based on its structural characteristics and function in the stamping process, one or more processing performance requirements are quantitatively defined for that region to achieve stable processing. These requirements specifically include: Establish a quantitative index system for processing performance requirements, including at least the wear resistance grade, anti-adhesion grade, fatigue resistance grade, surface hardness requirement range, and lubrication retention requirement; For each key area, based on the extracted structural feature parameters and the experience of mold design experts, the quantitative values ​​or levels corresponding to various performance requirements are calculated. A structured set of processing performance requirements is generated for each key region, which will serve as the input condition for subsequent matching of specific process solutions.

[0022] Specifically, the above steps achieve a quantitative mapping from the physical characteristics of the mold area to its required service performance, which is a key step in realizing customized process design. The quantitative index system provides a unified, multi-dimensional benchmark for measuring mold performance. The calculation process based on expert experience essentially combines industry knowledge with specific data. For example, the required "wear resistance level" can be automatically calculated based on the "average contact pressure" and "relative sliding distance" of a region. Finally, the "structured processing performance requirement description set" generated for each region is a digital list containing multiple specific performance indicators and target values. This list replaces qualitative judgments relying on the technician's personal experience and becomes the sole and clear input condition for the subsequent precise and intelligent matching of the process knowledge base, fundamentally ensuring the objectivity and scientific nature of process solution selection.

[0023] Reference Figure 4 As shown, this solution matches the quantified processing performance requirements of each region with a pre-set process knowledge base, generating at least one preliminary surface strengthening or modification process scheme and its initial parameter range for each region, forming a set of differentiated process schemes for the mold, specifically including: Based on historical mold processing data, a process knowledge base is constructed that includes the mapping relationship between regional attributes and process parameters. Regional attributes include at least three dimensions: performance requirements, regional shape, and regional location. Process parameters include at least the process type and parameter range. Based on the quantified processing performance requirements, shape, and location of a region, the data is matched with the process knowledge base. At least one historical processing data of a mold that meets the processing performance requirements of the region and whose shape and location are more than a threshold similar to the region is selected as the region's matching data. Extract the process parameters from the matching data of the region to serve as the preliminary surface strengthening or modification process scheme and its initial parameter range for the region; Summarize the preliminary surface strengthening or modification process schemes and their initial parameter ranges for all regions to form a set of differentiated process schemes for the mold.

[0024] The constructed process knowledge base is essentially a database formed by digitizing and structuring historical successful mold processing cases. Each case serves as a record, with its regional attributes fully describing the characteristics of a specific area on a historical mold, including quantified performance requirements, specific geometric parameters, and its exact location on the mold. Its process parameters record the final processes that have been validated and proven effective for that area, such as laser hardening and its key parameters, such as the range of power and scanning speed. When matching a solution for a specific area of ​​a new mold, a simple keyword search is not performed; instead, a multi-dimensional similarity calculation is executed. Here, "similarity" is a comprehensive evaluation value, typically calculated by combining geometric similarity and topological (positional) similarity. Geometric similarity is calculated by comparing the curvature distribution, area, and contour shape of two areas; positional similarity assesses their relative positions within the mold, such as whether they are both located at the corner of the die cavity or adjacent draw beads. Historical cases whose performance requirements are completely covered or exceeded by historical cases, and whose combined shape and positional similarity exceeds a set threshold, are selected. Subsequently, the process solutions and parameter ranges adopted by these most similar cases are recommended as preliminary solutions for the current area. Finally, the recommended solutions from all regions were compiled to form a "set of differentiated process solutions" for the entire mold, which integrates historical experience from multiple parties, providing a rich foundation of options for subsequent collaborative optimization.

[0025] Reference Figure 5 As shown in the diagram, the specific interrelationships that may arise during the physical implementation of the differentiated process solutions in this analysis set include: Construct a knowledge base of interference relationships between processes, which defines the mutual constraints of different surface treatment or strengthening processes in terms of implementation temperature, environmental requirements, and surface condition influence; For the set of differentiated process solutions initially matched for each region, reasoning is performed based on the knowledge base of interference relationships between processes to identify the potential negative associations that may occur when processes in different regions are implemented sequentially.

[0026] The "Inter-Process Interference Relationship Knowledge Base" is a rule base summarized from materials science, heat treatment principles, and extensive engineering practice. It formally defines the inherent constraints between different processes, such as nitriding, carburizing, chromium plating, and laser cladding. For example, the rules clearly state that "high-temperature tempering above 550℃ will significantly reduce the hardness of the completed nitriding layer," or "physical vapor deposition requires an absolutely clean substrate surface; if oil or oxidation occurs in the preceding process, it will lead to coating adhesion failure." When reasoning about the preliminary set of solutions based on this knowledge base, it is not a simple listing of processes, but rather a simulation of their logical sequence and spatial relationships. For example, if a high-temperature thermal spraying is planned for region A, and a low-temperature PVD coating is planned for the adjacent region B, then when process A is executed first, its high-temperature heat-affected zone will cover region B, thereby destroying the substrate condition required for subsequent PVD in region B. This type of analysis can systematically identify potential negative correlations caused by heat effects, contamination, secondary heating, stress superposition, etc., providing an accurate "problem list" for the next stage of global process chain sequencing and compensation design, thereby avoiding irreparable process defects in actual manufacturing.

[0027] Reference Figure 6 As shown, this solution optimizes the execution sequence of processes in all regions based on the results of the correlation impact analysis. For process combinations with negative correlation impacts, corresponding elimination processes or compensation measures are designed and inserted to generate a globally executable collaborative manufacturing process chain, specifically including: Based on the identification results, with the goal of reducing the impact of correlation and optimizing manufacturing efficiency, a process parameter is selected from all the preliminary surface strengthening or modification process schemes and their initial parameter ranges for each region as the strengthening process for that region, and the main process chain for mold processing is constructed based on the strengthening process for each region. Specifically, when designing the main processing chain, an iterative optimization approach is adopted. A multi-region refined finite element model of the mold, including information on the matrix material and gradient reinforcement layer, is established as the basic model. The negative correlation effects of the preceding process are used as constraints. The preliminary surface strengthening or modification process schemes and their initial parameter ranges of all regions are arranged and combined in an orderly manner. The ordered processing chain is then assigned to the basic model. Coupled simulation is performed under simulated periodic stamping loads and thermal loads to obtain the overall service life prediction data of the mold under different processing chain. With the goals of minimizing correlation effects, optimizing manufacturing efficiency, and maximizing the overall service life of the mold, the optimal ordered processing chain is selected as the main processing chain for the mold. Based on the main process chain of mold processing, for processes that are negatively related to previous processes, repair or auxiliary processes are inserted. For example, if the high temperature thermal effect of previous processes will damage the performance of areas in subsequent processes, a process to apply a temporary protective coating to sensitive areas or a process to perform local repair reprocessing on affected areas is inserted into the process chain. For process combinations with cross-contamination risks, processes such as local shielding, special cleaning, or adjusting the processing sequence to concentrate the execution of contaminating processes are inserted into the process chain. For cases where stress accumulation in the mold substrate is caused by multiple local treatments of high-energy beams, a global or local stress relief heat treatment process is inserted at the end of the process chain to obtain a globally executable collaborative manufacturing process chain.

[0028] This embodiment introduces a decision-making mechanism of "virtual manufacturing-service performance joint simulation optimization" to achieve global optimization of the process chain. Instead of simply ranking the preferred processes for each region, it constructs a refined finite element model of the mold, including information on the matrix and gradient reinforcement layer, as a "digital twin," and uses the identified negative inter-process correlations as hard constraints. Through iterative simulation, it evaluates the overall service life of the mold under simulated cyclic stamping loads for different process combinations, thereby finding the optimal balance between multiple objectives such as reducing correlation effects, improving manufacturing efficiency, and extending mold life, ultimately selecting the comprehensively optimal "main processing chain." This is equivalent to rehearsing the final effects of different production processes in a virtual space, thus enabling scientific decision-making. Based on this, intelligent compensation processes are inserted for specific risk points still existing in the main process chain. For example, a peelable protective coating is applied to sensitive areas before high-temperature processes, or stress-relief annealing is arranged after high-energy beam processing. These measures are not simply a stacking of processes, but a precise "hedging" strategy based on a process interference knowledge base. The resulting "collaborative manufacturing process chain" is a detailed production guide that fully considers manufacturing feasibility and service reliability.

[0029] This scheme establishes a mold simulation model that includes the surface layer characteristics of each region determined by the matrix material and the collaborative manufacturing process chain. Multiphysics coupling simulation is performed under simulated stamping cyclic loads to evaluate the overall mold performance and the feasibility of the process chain. Specifically, this includes: Simulate the stress state at the interface between the reinforcement layer and the matrix in each region under cyclic thermo-mechanical loading; Analyze the performance transition gradient at the interface of different process zones and whether stress concentration exists; Evaluate the impact of differentiated processes on the overall thermal deformation and dimensional stability of the mold.

[0030] In multiphysics coupled simulations, the stress state at the interface between the reinforced layer and the substrate in each region is monitored to predict whether interface delamination or early cracking will occur under alternating loads. Simultaneously, a detailed analysis of the material property gradient and stress distribution at the boundaries of different process regions, such as the laser-hardened zone and the adjacent PVD coating zone, is conducted to identify micro-stress concentrations caused by abrupt performance changes or residual stress mismatches, which could become fatigue crack initiations. From a macroscopic perspective, the thermal deformation compatibility and dimensional stability of the mold as a whole after differentiated treatment under cyclic temperature rise and mechanical impact are evaluated to determine whether localized reinforcement will lead to unexpected overall deformation. This simulation process is essentially a final virtual test of all the aforementioned design decisions, and its evaluation results provide quantitative criteria for the feasibility of the process chain.

[0031] Based on the same inventive concept as the above-mentioned method for optimizing process parameters of automotive body panel molds, this invention also proposes an embodiment of an automotive body panel mold process parameter optimization system, comprising: The region division and demand quantification module is used to divide the working part of the mold into multiple key regions with different structural features based on the three-dimensional digital model of the mold of the target automotive body panel and the simulation results of the forming process. For each key region, the processing performance requirements are quantitatively defined according to its structural features and its function in the stamping process. The process matching and collaborative chain generation module is used to match the quantified processing performance requirements, regional shape, and regional location of each region with a pre-set process knowledge base, generating at least one preliminary surface strengthening or modification process scheme and its initial parameter range for each region, forming a set of differentiated process schemes; analyzing the interrelationships between the processes matched in different regions within the set of differentiated process schemes; based on the results of the correlation analysis, optimizing and sorting the execution order of processes in all regions, and designing and inserting corresponding elimination processes or compensation measures for process combinations with negative correlation effects, generating a globally executable collaborative manufacturing process chain; The simulation verification and procedure output module is used to establish a mold simulation model that includes the surface layer characteristics of each region determined by the matrix material and the collaborative manufacturing process chain. It performs multi-physics coupling simulation under simulated stamping cyclic load, evaluates the overall performance of the mold and the feasibility of the process chain, and outputs the final process parameter set and collaborative manufacturing process chain verified by simulation, generating a digital process procedure.

[0032] The regional division and demand quantification module specifically includes: The model and data import unit is used to import the 3D model of the mold and load the corresponding stamping process simulation data; The critical area division unit is used to automatically identify and divide the working surfaces of the punch, die, and blank holder into critical areas, including the main profile area, the severely deformed fillet area, the blank holder contact area, and the drawbead area, based on the stress distribution, strain distribution, and material flow information in the simulation data and in combination with the preset mold area division rules. The feature extraction and demand quantification unit is used to extract the key geometric and mechanical feature parameters of each divided region, and based on the preset processing performance demand quantification index system and feature parameters, calculate and generate a structured processing performance demand description set for each key region.

[0033] The process matching and collaborative chain generation module specifically includes: The process knowledge base stores the regional attribute-process parameter mapping relationship built based on the historical processing data of the mold, as well as the process interference relationship knowledge base that defines the mutual constraints between different processes; The differentiated scheme matching unit is used to match historical data from the process knowledge base based on the processing performance requirements, shape, and location of the region, and generate at least one preliminary surface strengthening or modification process scheme and its initial parameter range for each region. The process chain collaborative optimization unit is used to analyze the negative correlation between processes in different regions of a differentiated process scheme set based on a knowledge base of interference relationships between processes. With the goal of reducing correlation effects and optimizing manufacturing efficiency, it optimizes the process execution sequence and designs and inserts corresponding elimination processes or compensation measures for process combinations with negative correlation effects, thereby generating a collaborative manufacturing process chain.

[0034] In summary, the advantages of this invention are: establishing a quantitative mapping and collaborative optimization mechanism from mold structural features to processing requirements, and then to specific process schemes and parameters, thereby achieving precise and differentiated design of the surface treatment of the cover mold.

[0035] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A method for optimizing process parameters of automotive body panel molds, characterized in that, include: Based on the three-dimensional digital model of the mold for the target automotive body panel, and combined with the simulation results of the molding process, the working part of the mold is divided into several key areas with different structural features. For each key region identified, based on its structural characteristics and its function in the stamping process, the region is quantitatively defined as one or more processing performance requirements that need to be met to achieve stable processing. The quantified processing performance requirements, shape, and location of each region are matched with a pre-set process knowledge base to generate at least one preliminary surface strengthening or modification process scheme and its initial parameter range for each region, forming a set of differentiated process schemes for the mold. The analysis examines the potential interrelationships between the processes matched to different regions within the aforementioned set of differentiated process solutions during physical implementation. Based on the results of the correlation impact analysis, the execution order of processes in all regions is optimized and sorted, and for process combinations with negative correlation impacts, corresponding elimination processes or compensation measures are designed and inserted to generate a globally executable collaborative manufacturing process chain. A mold simulation model is established, which includes the surface layer characteristics of each region determined by the matrix material and the aforementioned collaborative manufacturing process chain. Multiphysics coupling simulation is performed under simulated stamping cyclic load to evaluate the overall performance of the mold and the feasibility of the process chain. Output the final set of process parameters verified by simulation and the collaborative manufacturing process chain to generate a digital process specification that can directly guide production.

2. The method for optimizing process parameters of automotive body panel molds according to claim 1, characterized in that, The three-dimensional digital model of the mold based on the target automotive body panel, combined with the molding process simulation results, divides the working part of the mold into several key areas with different structural features, specifically including: Import the 3D model of the mold and load the stamping process simulation data corresponding to the mold; Based on the stress distribution, strain distribution and material flow information in the simulation data, combined with the preset mold area division rules, the working surfaces of the punch, die and blank holder are automatically identified and divided into the main surface area, the severely deformed fillet area, the blank holder contact area and the drawbead area. Key geometric and mechanical characteristic parameters of each divided region are extracted, including radius of curvature, draft angle, relative sliding distance with the sheet metal, average contact pressure, and angle of material flow direction.

3. The method for optimizing process parameters of automotive body panel molds according to claim 2, characterized in that, For each of the defined key regions, based on its structural characteristics and function in the stamping process, the quantitative definition of one or more processing performance requirements that the region must meet to achieve stable processing specifically includes: Establish a quantitative index system for processing performance requirements, including at least the wear resistance grade, anti-adhesion grade, fatigue resistance grade, surface hardness requirement range, and lubrication retention requirement; For each key area, based on the extracted structural feature parameters and the experience of mold design experts, the quantitative values ​​or levels corresponding to various performance requirements are calculated. A structured set of processing performance requirements is generated for each key region, which will serve as the input condition for subsequent matching of specific process solutions.

4. The method for optimizing process parameters of an automotive body panel mold according to claim 3, characterized in that, The process of matching the quantified processing performance requirements of each region with a pre-set process knowledge base to generate at least one preliminary surface strengthening or modification process scheme and its initial parameter range for each region, forming a set of differentiated process schemes for the mold, specifically includes: Based on historical mold processing data, a process knowledge base is constructed that includes the mapping relationship between regional attributes and process parameters. The regional attributes include at least three dimensions: performance requirements, regional shape, and regional location. The process parameters include at least the process type and parameter range. Based on the quantified processing performance requirements, shape, and location of a region, the data is matched with the process knowledge base. At least one historical processing data of a mold that meets the processing performance requirements of the region and whose shape and location are more than a threshold similar to the region is selected as the region's matching data. Extract the process parameters from the matching data of the region to serve as the preliminary surface strengthening or modification process scheme and its initial parameter range for the region; Summarize the preliminary surface strengthening or modification process schemes and their initial parameter ranges for all regions to form a set of differentiated process schemes for the mold.

5. The method for optimizing process parameters of an automotive body panel mold according to claim 4, characterized in that, The analysis of the differentiated process scheme set, specifically the potential interrelationships between the processes matched to different regions during physical implementation, includes: Construct a knowledge base of interference relationships between processes, which defines the mutual constraints of different surface treatment or strengthening processes in terms of implementation temperature, environmental requirements, and surface condition influence; For the set of differentiated process solutions initially matched for each region, reasoning is performed based on the knowledge base of interference relationships between processes to identify the potential negative correlations that may occur when processes in different regions are implemented sequentially.

6. The method for optimizing process parameters of an automotive body panel mold according to claim 5, characterized in that, Based on the correlation impact analysis results, the execution order of processes in all regions is optimized and sorted. For process combinations with negative correlation impacts, corresponding elimination processes or compensation measures are designed and inserted to generate a globally executable collaborative manufacturing process chain. Specifically, this includes: Based on the identification results, with the goal of reducing the impact of correlation and optimizing manufacturing efficiency, a process parameter is selected from all the preliminary surface strengthening or modification process schemes and their initial parameter ranges for each region as the strengthening process for that region, and the main process chain for mold processing is constructed based on the strengthening process for each region. Based on the main process chain of mold processing, for situations where the performance of subsequent process areas may be damaged due to the high temperature thermal effects of previous processes, a process for applying a temporary protective coating to sensitive areas or a process for local repair reprocessing of affected areas is inserted into the process chain. For process combinations with cross-contamination risks, a process for local shielding, special cleaning, or adjusting the processing sequence to concentrate the execution of contaminating processes is inserted into the process chain. For situations where stress accumulation in the mold substrate is caused by multiple high-energy beam local treatments, a global or local stress relief heat treatment process is inserted at the end of the process chain to obtain a globally executable collaborative manufacturing process chain.

7. The method for optimizing process parameters of an automotive body panel mold according to claim 6, characterized in that, The establishment of a mold simulation model that includes the surface layer characteristics of each region determined by the matrix material and the collaborative manufacturing process chain, and the evaluation of the overall mold performance and the feasibility of the process chain under simulated stamping cyclic loads through multiphysics coupling simulation, specifically includes: Simulate the stress state at the interface between the reinforcement layer and the matrix in each region under cyclic thermo-mechanical loading; Analyze the performance transition gradient at the interface of different process zones and whether stress concentration exists; Evaluate the impact of differentiated processes on the overall thermal deformation and dimensional stability of the mold.

8. A system for optimizing process parameters of automotive body panel molds, used to implement the method for optimizing process parameters of automotive body panel molds as described in any one of claims 1-7, characterized in that, include: The region division and demand quantification module is used to divide the working part of the mold into multiple key regions with different structural features based on the three-dimensional digital model of the mold of the target automotive body panel and the simulation results of the forming process. For each key region, the processing performance requirements are quantitatively defined according to its structural features and its function in the stamping process. The process matching and collaborative chain generation module is used to match the quantified processing performance requirements, regional shape and location of each region with the pre-set process knowledge base to generate at least one preliminary surface strengthening or modification process scheme and its initial parameter range for each region, forming a set of differentiated process schemes. Analyze the interrelationships and influences between the processes matched in different regions of the differentiated process scheme set; Based on the results of the correlation impact analysis, the execution order of processes in all regions is optimized and sorted, and corresponding elimination processes or compensation measures are designed and inserted for process combinations with negative correlation impacts, generating a globally executable collaborative manufacturing process chain. The simulation verification and procedure output module is used to establish a mold simulation model that includes the surface layer characteristics of each region determined by the matrix material and the collaborative manufacturing process chain. It performs multi-physics coupling simulation under simulated stamping cyclic load, evaluates the overall performance of the mold and the feasibility of the process chain, and outputs the final process parameter set verified by simulation and the collaborative manufacturing process chain to generate a digital process procedure.

9. The automotive body panel mold process parameter optimization system according to claim 8, characterized in that, The regional division and demand quantification module specifically includes: The model and data import unit is used to import the 3D model of the mold and load the corresponding stamping process simulation data; The critical area division unit is used to automatically identify and divide the working surfaces of the punch, die, and blank holder into critical areas, including the main profile area, the severely deformed fillet area, the blank holder contact area, and the drawbead area, based on the stress distribution, strain distribution, and material flow information in the simulation data and in combination with the preset mold area division rules. The feature extraction and demand quantification unit is used to extract the key geometric and mechanical feature parameters of each divided region, and calculate and generate a structured set of processing performance demand descriptions for each key region based on the preset processing performance demand quantification index system and the feature parameters.

10. The automotive body panel mold process parameter optimization system according to claim 9, characterized in that, The process matching and collaborative chain generation module specifically includes: The process knowledge base stores the regional attribute-process parameter mapping relationship built based on the historical processing data of the mold, as well as the process interference relationship knowledge base that defines the mutual constraints between different processes; The differentiated scheme matching unit is used to match historical data from the process knowledge base based on the processing performance requirements, shape, and location of the region, and generate at least one preliminary surface strengthening or modification process scheme and its initial parameter range for each region. The process chain collaborative optimization unit is used to analyze the negative correlation between processes in different regions of the differentiated process scheme set based on the knowledge base of interference relationships between processes. With the goal of reducing correlation effects and optimizing manufacturing efficiency, it optimizes the process execution sequence and designs and inserts corresponding elimination processes or compensation measures for process combinations with negative correlation effects, thereby generating a collaborative manufacturing process chain.

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