A method and system for optimizing a precision molding process of a mobile phone card holder

Abstract

The application discloses a mobile phone card holder precision carving forming process optimization method and system, and belongs to the field of metal material processing process optimization, wherein the method comprises the following steps: activating sensing data for real-time collection, and setting a chatter state index; traversing initial processing parameters for cutting analysis, determining a cutting force data set for simulation layering cutting on a to-be-processed mobile phone card holder, generating a precision carving three-dimensional model for multi-layer comparison, and multiple cutting force deviation values and the multi-layers of the precision carving three-dimensional model have a corresponding relationship; based on the multiple cutting force deviation values, the cutting force data set is reversely corrected, the chatter state index is updated according to the correction result, and a vibration optimization processing parameter set is generated to perform precision carving processing on the to-be-processed mobile phone card holder. The application solves the technical problems of lacking systematic chatter monitoring and parameter optimization mechanism in the prior art, thereby leading to poor processing process stability, blind parameter adjustment, insufficient card holder size precision and low production efficiency.

Description

Technical Field

[0001] This invention relates to the field of metal material processing technology optimization, specifically to a method and system for optimizing the precision engraving process of a mobile phone SIM card tray. Background Technology

[0002] As smartphones rapidly evolve towards thinner and lighter designs and higher integration, the requirements for dimensional accuracy and surface finish of the SIM card tray, a key component that carries the core card, continue to increase.

[0003] Current mainstream engraving processes rely heavily on manual experience to set initial parameters, lacking dynamic optimization mechanisms. This makes it difficult to adapt to the processing characteristics of different material trays, resulting in low processing efficiency, unstable finished product quality, and an inability to meet the production needs of high-end models. Summary of the Invention

[0004] This application provides a method and system for optimizing the precision carving process of mobile phone SIM card trays, aiming to solve the technical problems in the existing technology of mobile phone SIM card tray precision carving process, which lacks a systematic vibration monitoring and parameter optimization mechanism, resulting in poor process stability, blind parameter adjustment, insufficient dimensional accuracy of the SIM card tray, and low production efficiency.

[0005] In view of the above problems, this application provides an optimized method and system for the precision engraving process of mobile phone SIM card trays.

[0006] The first aspect disclosed in this application provides a method for optimizing the precision carving process of a mobile phone SIM card tray. This method includes: retrieving initial processing parameters from a precision carving equipment, activating sensor data for real-time acquisition, and setting a chatter state index; performing cutting analysis by traversing the initial processing parameters according to the chatter state index, determining a cutting force dataset, performing simulated layered cutting on the mobile phone SIM card tray to be processed, generating a precision carving 3D model, performing multi-layer comparison, generating multiple cutting force deviation values, wherein the multiple cutting force deviation values ​​correspond to multiple layers of the precision carving 3D model; performing forming correction on the cutting force dataset based on the multiple cutting force deviation values, updating the chatter state index according to the correction result, and generating a vibration-optimized processing parameter set for the precision carving equipment to perform precision carving on the mobile phone SIM card tray to be processed.

[0007] Another aspect of this application discloses a mobile phone SIM card tray precision carving process optimization system. This system includes: a real-time acquisition module for retrieving initial processing parameters of the precision carving equipment, activating sensor data for real-time acquisition, and setting a chatter state index; a deviation value generation module for performing cutting analysis by traversing the initial processing parameters according to the chatter state index, determining a cutting force dataset, performing simulated layered cutting on the mobile phone SIM card tray to be processed, generating a precision carving 3D model, performing multi-layer comparison, and generating multiple cutting force deviation values, wherein the multiple cutting force deviation values ​​correspond to the multiple layers of the precision carving 3D model; and a processing parameter set generation module for performing forming correction on the cutting force dataset based on the multiple cutting force deviation values, updating the chatter state index according to the correction result, and generating a vibration-optimized processing parameter set for the precision carving equipment to perform precision carving on the mobile phone SIM card tray to be processed.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] By employing a systematic technical solution that involves activating sensors to collect vibration data to set chatter indices, traversing parameters to simulate cutting and construct a precision carving model, comparing multiple layers to generate cutting force deviation values, and then correcting parameters and updating indices, this solution solves the technical problems in existing technologies where the precision carving of mobile phone SIM card trays lacks a systematic chatter monitoring and parameter optimization mechanism, resulting in poor processing stability, blind parameter adjustments, insufficient dimensional accuracy, and low production efficiency. This achieves the technical effects of improving processing stability and accuracy, reducing ineffective trial cuts, and ensuring the quality of mass production.

[0010] The above description is merely an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below. Attached Figure Description

[0011] Figure 1 This application provides a flowchart illustrating an optimized method for precision carving and molding of a mobile phone SIM card tray.

[0012] Figure 2 This application provides a schematic diagram of the process for simulating layered cutting of a mobile phone SIM card tray by determining the cutting force dataset in an optimization method for precision engraving of the mobile phone SIM card tray.

[0013] Figure 3 This application provides a schematic diagram of the structure of a mobile phone SIM card tray precision engraving and molding process optimization system.

[0014] Figure labeling: Real-time acquisition module 11, deviation value generation module 12, processing parameter set generation module 13. Detailed Implementation

[0015] The overall concept of the technical solution provided in this application is as follows:

[0016] This application provides a method and system for optimizing the precision carving process of a mobile phone SIM card tray. First, vibration data is collected via sensors to set a chatter index. Then, a precision carving model is constructed by simulating layered cutting using initial parameters. The cutting force deviation value is obtained by comparing it with the actual model. The parameters are then corrected in reverse, and the chatter index is updated, forming a closed-loop optimization to achieve precise optimization of the mobile phone SIM card tray precision carving process.

[0017] After introducing the basic principles of this application, various non-limiting embodiments of this application will be described in detail below with reference to the accompanying drawings. Example 1

[0018] like Figure 1 As shown in the figure, this application provides an optimized method for the precision carving and molding process of a mobile phone SIM card tray, the method comprising:

[0019] Step S100: Retrieve the initial processing parameters of the engraving equipment, activate the sensor data for real-time acquisition, and set the chatter status index.

[0020] Specifically, the initial processing parameters of a CNC engraving machine refer to the basic process parameters preset according to the material of the SIM card tray before the machine processes it. These parameters include spindle speed, feed rate, and depth of cut. The chatter status index is a standard used to quantitatively determine whether the equipment is experiencing chatter and the degree of chatter.

[0021] First, the CNC control system of the precision carving equipment retrieves the preset initial processing parameters. Based on the processing characteristics corresponding to these parameters, the sensing devices installed at key positions on the equipment are activated. The analog signals captured by the sensors are converted into processable digital signals through the data acquisition card, realizing the real-time acquisition of sensor data such as vibration acceleration and cutting temperature. In addition, the sampling focus of the sensors is adjusted according to the processing requirements of different material trays. Then, the data processing software is used to perform spectrum analysis on the collected high-frequency vibration data, and the chatter state index adapted to the current tray material is set in combination with the processing requirements.

[0022] This step provides a precise basis for determining the state of the cutting parameters for subsequent optimization, thereby ensuring the stability of the mobile phone SIM card tray machining process and reducing defective products caused by chatter.

[0023] Step S200: According to the flutter state index, traverse the initial processing parameters to perform cutting analysis, determine the cutting force dataset, perform simulated layer cutting on the mobile phone card tray to be processed, generate a fine-carved 3D model, perform multi-layer comparison, and generate multiple cutting force deviation values. The multiple cutting force deviation values ​​have a corresponding relationship with the multi-layer of the fine-carved 3D model.

[0024] Specifically, layered cutting refers to dividing the 3D model of the card holder to be processed into multiple layers in the actual machining direction, such as the thickness direction or edge contour direction, and simulating the precision carving cutting process layer by layer. For example, a thin card holder can be divided into a surface layer, a middle layer, and a bottom layer according to the thickness direction, and the cutting tool can be simulated to cut from the surface layer to the bottom layer. The geometric information of the precision carving 3D model card holder incorporates key process data of precision carving, such as cutting path, layered cutting marks, and simulated stress state, and is mainly used for simulation, process verification, or prediction of processing effect of precision carving. The cutting force deviation value is the difference value of the cutting force of each layer after comparing the precision carving 3D model with the actual precision carving 3D model in multiple layers, and each deviation value corresponds to a specific layer of the model, such as the difference between the cutting force of the surface layer of the simulated model and the cutting force of the surface layer of the actual model, and the corresponding difference in the cutting force of the middle layer.

[0025] Specifically, based on preset chatter state indicators, parameter analysis tools, such as MATLAB, are used to iterate through different combinations of initial machining parameters one by one to verify and eliminate parameter combinations that may trigger chatter. Then, cutting dynamics calculations are performed on each of the selected parameter combinations to analyze the force situation when the tool cuts the chuck under different parameters, generating a cutting force dataset containing radial and axial forces. Then, an initial 3D model of the chuck to be machined is constructed using 3D modeling software. The model is then divided into multiple layers to be cut, such as surface, middle, and bottom layers, according to the actual machining direction. The cutting force dataset is then imported into finite element simulation software to simulate the precision carving process for each layer one by one, obtaining stress and strain data for each layer. These data are then combined to construct a simulated precision carving 3D model. At the same time, machining log data of historical qualified chucks are retrieved, and the actual precision carving 3D model is constructed using the same modeling software and layered in the same way. Afterward, a model comparison tool is used to compare the geometric features of each layer of the simulation model with the corresponding layer of the actual model. Then, a mechanical calculation software is used to convert the geometric deviations into corresponding cutting force differences, generating a cutting force deviation value for each layer, ensuring that each deviation value can accurately correspond to a specific layer of the model.

[0026] This step provides a clear direction for subsequent reverse correction of cutting parameters, eliminating the need for repeated trial cuts that waste material. It also improves the accuracy of cutting force data, laying the foundation for subsequent optimization of machining parameters and ensuring the machining accuracy of the card slot. This significantly reduces production costs and increases the yield rate of finished products.

[0027] Step S300: Based on the multiple cutting force deviation values, the cutting force dataset is reverse-engineered and corrected. The chatter state index is updated according to the correction results, and a vibration optimization processing parameter set of the precision carving equipment is generated for precision carving of the mobile phone card tray to be processed.

[0028] Specifically, the vibration-optimized machining parameter set refers to a combination of machining parameters generated based on the correction results and updated chatter indices, which can reduce chatter and ensure accuracy, including spindle speed, feed rate, etc.

[0029] Specifically, based on multiple cutting force deviation values ​​as input parameters, a backpropagation algorithm is used to correct the cutting force dataset. The required cutting force parameters are calculated in reverse using the deviation values, making the corrected dataset more in line with the mechanical requirements of actual machining. The correction results are compared and analyzed with the original chatter state index, the chatter state index is updated, and the corrected cutting force data is converted into specific machining parameters by combining the updated chatter index, generating a vibration-optimized machining parameter set. This parameter set is then imported into the CNC system of the precision carving equipment for actual precision carving of the mobile phone SIM card tray to be processed.

[0030] This step, based on the reverse correction of the cutting force deviation value, makes the cutting force data closer to reality, avoiding accuracy errors caused by the disconnect between the simulation ideal value and the actual machining.

[0031] Furthermore, the initial processing parameters of the engraving equipment are retrieved to activate sensor data for real-time acquisition, and a chatter state index is set. The method includes: activating a vibration sensor based on the initial processing parameters to acquire three-dimensional vibration acceleration signals; sampling vibration frequencies according to the three-dimensional vibration acceleration signals to capture high-frequency vibration data; converting the high-frequency vibration data to the frequency domain for spectral analysis to obtain a vibration spectrum; dividing the vibration spectrum according to the vibration frequency to obtain multiple characteristic frequency bands for distribution calculation to generate energy distribution characteristics; comparing the energy distribution characteristics with a preset energy fluctuation amplitude, identifying the chatter parameter set for stability classification, and setting the chatter state index.

[0032] Specifically, triaxial vibration acceleration signals refer to signals collected by vibration sensors along the X, Y, and Z spatial directions, reflecting the vibration intensity of the engraving equipment. These signals comprehensively capture the multidimensional vibration state of the equipment during processing. High-frequency vibration data refers to higher-frequency vibration data filtered from the triaxial vibration acceleration signals. This type of data is usually directly related to equipment chatter, such as the high-frequency vibration data generated by the spindle due to increased cutting resistance when processing stainless steel mobile phone card trays, which differs from the low-frequency vibration data during normal equipment operation. Characteristic frequency bands are specific frequency intervals divided according to processing requirements based on the frequency distribution of the vibration spectrum. For example, the spectrum can be divided into low-frequency bands (normal equipment operation vibration), mid-frequency bands (cutting load vibration), and high-frequency bands (chatter-related vibration). Different frequency bands correspond to different equipment operating states. Energy distribution characteristics refer to the distribution pattern obtained after calculating the vibration energy within each characteristic frequency band, reflecting the energy proportion of vibration in different frequency bands. For example, a high proportion of high-frequency vibration energy indicates a risk of equipment chatter.

[0033] Specifically, based on the initial processing parameters of the engraving equipment, three-dimensional vibration sensors installed at key locations on the equipment are activated. The sensors collect vibration signals from the equipment in real time along the X, Y, and Z directions, filtering out high-frequency vibration data related to chatter, thus eliminating low-frequency vibration interference that would interfere with normal equipment operation. Next, data processing software, such as MATLAB, is used to perform a Fast Fourier Transform on the high-frequency vibration data, converting the time-domain vibration acceleration signal into a frequency-domain signal, and generating a vibration spectrum through spectral analysis. Subsequently, based on the technological characteristics of engraving, the vibration spectrum is divided into multiple characteristic frequency bands, such as low-frequency, mid-frequency, and high-frequency bands, and the vibration energy of each band is calculated to generate energy distribution characteristics. Finally, this energy distribution characteristic is compared with a preset energy fluctuation amplitude. If the energy of a certain characteristic frequency band exceeds the preset range, the vibration parameters corresponding to that frequency band are included in the chatter parameter set, and the equipment stability is classified according to the degree of deviation, such as mild chatter, moderate chatter, and severe chatter. Finally, a chatter state index adapted to the current processing scenario is set.

[0034] This step, based on actual machining data, sets chatter status indicators that can adapt to the machining characteristics of different material trays. It provides accurate status basis for subsequent cutting parameter optimization, reduces invalid machining attempts, and improves overall machining efficiency and finished product qualification rate.

[0035] Furthermore, such as Figure 2 As shown, the method involves performing cutting analysis by traversing the initial machining parameters according to the chatter state index, determining the cutting force dataset, and performing simulated layered cutting on the mobile phone SIM card tray to be machined. The method includes: numerically dividing the initial machining parameters based on the chatter state index to determine multiple parameter combinations; performing cutting dynamics calculations according to the multiple parameter combinations to obtain cutting force fluctuation data for machining screening, generating a cutting force dataset; constructing a three-dimensional model of the mobile phone SIM card tray to be machined; layering the three-dimensional model of the mobile phone SIM card tray to be machined along the machining direction based on the cutting force dataset to determine multiple layers to be cut; performing finite element simulation cutting calculations according to the multiple layers to be cut to obtain multi-layered simulation cutting data, which includes stress distribution simulation data and strain distribution simulation data; and performing three-dimensional registration and alignment based on the stress distribution simulation data and the strain distribution simulation data to construct the precision-carved three-dimensional model.

[0036] Specifically, cutting dynamics calculation refers to the analysis of the mechanical process of the interaction between the tool and the cutting tool holder based on the cutting principle. Cutting force fluctuation data refers to the data on the change of cutting force with time or machining position during the cutting process, reflecting the cutting stability.

[0037] Specifically, based on chatter state indicators, parameter analysis tools such as MATLAB are used to numerically divide the initial machining parameters. For example, the spindle speed is divided into three segments: low, medium, and high, and the feed rate is divided into two segments: low and medium. Combinations that may trigger chatter are eliminated to determine multiple effective parameter combinations. These parameter combinations are then imported into cutting dynamics software such as ANSYS Workbench to calculate the cutting force fluctuation data under each combination. Data sets with stable fluctuations are selected to generate a cutting force dataset. Subsequently, 3D modeling software such as UG is used to construct the initial 3D model of the card to be machined. Based on the cutting force dataset, the model is divided into multiple layers to be cut along the machining direction, such as the surface layer, middle layer, and bottom layer. Then, each layer model and the corresponding cutting force data are imported into finite element simulation software to perform simulated cutting calculations and obtain the stress distribution simulation data and strain distribution simulation data of each layer. Finally, 3D registration tools, such as Geomagic Control X which uses the nearest point iteration algorithm, are used to accurately align the multi-layer simulation data in space based on stress concentration points and strain characteristic points.

[0038] This step, through layered simulation and 3D registration, can accurately restore the mechanical state of each cutting stage, significantly improving the consistency between the precision-carved 3D model and the actual machining process, and providing a high-precision digital basis for subsequent model comparison and cutting force deviation calculation.

[0039] Furthermore, the method for constructing the precision-carved 3D model involves three-dimensional registration and alignment based on the stress distribution simulation data and the strain distribution simulation data. This includes: mapping the multi-layer simulated cutting data to the multiple layers to be cut for positioning, delineating stress concentration regions and plastic deformation regions; identifying the maximum values ​​in the stress concentration regions based on the stress distribution simulation data, and extracting the target stress point location information; performing strain gradient analysis on the plastic deformation regions based on the strain distribution simulation data, and extracting strain gradient features; traversing the multiple layers to be cut and performing equivalent calculations based on the target stress point location information and the strain gradient features to obtain multi-layer equivalent stress features and multi-layer equivalent strain distribution features; performing intersection analysis on adjacent layers of the multiple layers to be cut based on the multi-layer equivalent stress features and the multi-layer equivalent strain distribution features to obtain common feature points, which include stress concentration points and strain feature points; and performing nearest-point iterative registration on the multiple layers to be cut according to the stress concentration points and the strain feature points to construct the precision-carved 3D model.

[0040] Specifically, stress concentration regions refer to areas in simulated cutting where the stress is significantly higher than the surrounding area due to abrupt shape changes in the cassette, such as corners or edges of the cassette. Plastic deformation regions refer to areas in simulated cutting where the cassette material undergoes permanent deformation due to stress exceeding its elastic limit. Maximum value identification refers to the process of finding the point with the highest stress value from the stress distribution data, used to locate the position most susceptible to damage due to excessive stress; for example, identifying the point with the highest stress value in the stress concentration region at the corner of the cassette. Strain gradient characteristics are feature parameters used to describe the deformation variation law.

[0041] Specifically, multi-layer simulated cutting data is mapped to each layer to be cut. Finite element post-processing software, such as ANSYS Post, is used to delineate stress concentration regions and plastic deformation regions in each layer. Then, based on the stress distribution simulation data, maximum value identification is performed on each stress concentration region to extract the location information of target stress points. Simultaneously, based on the strain distribution simulation data, strain gradient analysis is performed on the plastic deformation region to extract strain gradient characteristics, such as the increasing strain along the thickness direction at the middle layer edge. Subsequently, all layers to be cut are traversed, and equivalent calculations are performed by combining the target stress point location information and strain gradient characteristics to convert the stress / strain data of each layer into a unified standard, obtaining multi-layer equivalent stress characteristics and multi-layer equivalent strain distribution characteristics. Next, for adjacent layers, 3D analysis software is used to perform intersection analysis of their equivalent stress / strain characteristics to find common feature points. Finally, the nearest point iterative registration algorithm is used, with these common feature points as a benchmark, to iteratively optimize the spatial position of adjacent layers, completing the registration of all layers to be cut layer by layer.

[0042] This step accurately captures key mechanical features in the SIM card tray machining by identifying stress concentration points and strain gradient characteristics, providing a reliable benchmark for registration. The nearest point iterative registration algorithm can effectively eliminate spatial deviations between layers, enabling seamless connection of mechanical data of each layer in three-dimensional space, significantly improving the integrity and accuracy of the precision-carved 3D model, reducing process adjustment errors caused by model distortion, and ultimately improving the machining accuracy and consistency of the SIM card tray.

[0043] Furthermore, the method involves performing nearest-point iterative registration on the multiple layers to be cut according to the stress concentration points and strain feature points to construct the sculpted 3D model. The method includes: identifying adjacent layers based on the stress concentration points and strain feature points to obtain a set of adjacent layer feature points; performing nearest-point transformation analysis based on the adjacent layer feature point set to construct an initial transformation matrix; traversing the initial transformation matrix to calculate feature point distances and obtain multiple feature point distance error values; using the multiple feature point distance error values ​​as iteration conditions to minimize the multiple feature point distance error values; iteratively optimizing the initial transformation matrix based on the minimum feature point distance error value to set a registration accuracy value; and registering the multiple layers to be cut according to the registration accuracy value to construct the sculpted 3D model.

[0044] Specifically, adjacent layer identification refers to adding associated markers to consecutive layers to be cut, clarifying the sequence and correspondence between layers. Registration accuracy value refers to the maximum allowable distance error between feature points, serving as the criterion for successful registration.

[0045] Specifically, based on stress concentration points and strain characteristic points, adjacent layers to be cut, such as L1 and L2, are identified, and corresponding characteristic points of the two layers are extracted to form a set of adjacent layer characteristic points, such as point A of L1, point a of L2, point B of L1, and point b of L2. A nearest-point transformation analysis is performed on this set of characteristic points to calculate the spatial transformation relationship that allows the L1 characteristic points to initially match the L2 characteristic points, constructing an initial transformation matrix. Then, the initial transformation matrix is ​​traversed to transform the coordinates of the L1 characteristic points to the L2 coordinate system. The spatial distance between the transformed characteristic points and their corresponding L2 characteristic points is calculated to obtain multiple... The distance error values ​​of each feature point are then used as iterative conditions. An optimization algorithm, such as the Levenberg-Marquardt algorithm, is employed to minimize the error values. By repeatedly adjusting the translation and rotation parameters of the transformation matrix, the error values ​​are gradually reduced until the preset registration accuracy value is reached, thus completing the iterative optimization of the initial transformation matrix. Finally, according to the optimized transformation matrix and registration accuracy value, L1 and L2 are precisely aligned. Other adjacent layers, such as L2 and L3, are then processed in the same way. Ultimately, all layers to be cut are seamlessly spliced ​​together to construct a complete finely sculpted 3D model.

[0046] This step uses stress concentration points and strain feature points as registration benchmarks, ensuring the physical meaning of registration and avoiding the blindness of random point registration. On the other hand, the iteratively optimized transformation matrix can control the distance error between feature points of adjacent layers within the registration accuracy value, enabling seamless connection of each layer in three-dimensional space and significantly improving the overall consistency of the fine-carved 3D model.

[0047] Furthermore, a finely sculpted 3D model is generated for multi-layer comparison to generate multiple cutting force deviation values. The method includes: constructing an actual finely sculpted 3D model based on historical mobile phone SIM card tray fine-sculpting data logs; dividing the actual finely sculpted 3D model into equal-thickness layers according to the multiple layers to be cut, obtaining multiple layered cross sections; comparing the geometric features of the multi-layered simulated cutting data with the multiple layered cross sections to calculate the multi-layered geometric deviation; and performing cutting calculations based on the multi-layered geometric deviation to obtain the multiple cutting force deviation values.

[0048] Specifically, the actual precision-carved 3D model is a 3D model built based on historical data logs, reflecting the true and qualified shape of the caliber, and serves as the reference benchmark for the simulation model. Equal-thickness layering refers to splitting the actual precision-carved 3D model along the processing direction with the same thickness, ensuring that each layer is of uniform thickness.

[0049] Specifically, key data is extracted from historical mobile phone SIM card tray engraving data logs. A 3D modeling software is used to construct an actual engraved 3D model. The actual engraved 3D model is then divided into layers of equal thickness according to the determined thickness of multiple layers to be cut, resulting in multiple layered cross-sections consistent with the number and thickness of the simulated layers. Then, 3D comparison software, such as GOMInspect, is used to compare the geometric features of the multi-layered simulated cutting data with the corresponding actual layered cross-sections. For example, the edge straightness and the center position of the card slot are compared to calculate the geometric deviation of each layer. Based on these multi-layered geometric deviations and the material mechanics parameters of the mobile phone SIM card tray, the cutting force is converted to obtain the cutting force deviation value corresponding to each layer, ensuring that each deviation value accurately corresponds to a specific layer in the engraved 3D model.

[0050] This step, based on historical qualified data, constructs an actual precision-carved 3D model, providing a real and reliable reference benchmark for the simulation model and avoiding meaningless comparisons between virtual simulation and virtual standards. This process makes subsequent parameter corrections more targeted, reduces material waste caused by blind trial cutting, and improves the practicality of cutting force data. It provides a precise basis for optimizing machining parameters and ensuring the machining accuracy of the card slot, significantly improving the finished product qualification rate and production efficiency.

[0051] Furthermore, cutting calculations are performed based on the multi-layer geometric deviations to obtain the multiple cutting force deviation values. The method includes: numbering the multiple layers to be cut in the fine-carved 3D model to obtain multiple layer numbers; performing correlation analysis based on the multi-layer geometric deviations and the multiple layer numbers to obtain a multi-layer mapping relationship; retrieving the material mechanical parameters of the machine tool holder and analyzing them in conjunction with the multi-layer geometric deviations according to the multi-layer mapping relationship to construct a geometry-cutting force conversion relationship; and calculating the multi-layer geometric deviations according to the multiple layer numbers based on the geometry-cutting force conversion relationship to obtain the multiple cutting force deviation values.

[0052] Specifically, layer numbering is a unique identifier assigned to multiple layers to be cut in a finely sculpted 3D model according to their processing sequence or spatial position. This clearly distinguishes different layers and avoids confusion. For example, the five layers to be cut in an aluminum alloy SIM card tray (from the surface to the bottom) are sequentially numbered L1, L2, L3, L4, and L5, each corresponding to a fixed spatial position. Material mechanical parameters refer to the inherent mechanical properties of the material used in the SIM card tray, such as aluminum alloy or stainless steel. These parameters determine the stress and deformation patterns of the material during cutting. Common parameters include elastic modulus, Poisson's ratio, yield strength, and hardness. The geometry-cutting force conversion relationship is a quantitative correspondence between geometric deviations and cutting force deviations, constructed based on material mechanics principles or experimental models. It transforms abstract geometric differences into calculable mechanical differences.

[0053] Specifically, the process involves opening the 3D model and sequentially numbering the multiple layers to be cut according to the machining direction. Then, data processing software is used to correlate each layer number with its corresponding multi-layer geometric deviation, generating a multi-layer mapping table of "layer number - geometric deviation," ensuring that each deviation precisely corresponds to a unique layer. Next, the mechanical parameters of the current Cato material are retrieved from the material parameter database. Combined with the geometric deviation in the multi-layer mapping, a material mechanics calculation tool is used to construct a geometry-cutting force conversion relationship. For example, a quantitative formula is derived from the material mechanics formula: "Cutting force deviation value = (yield strength / elastic modulus) × geometric deviation × cutting area coefficient," where the cutting area coefficient is calculated from the cross-sectional area of ​​the Cato layer. Finally, according to this conversion relationship, the geometric deviation corresponding to each layer number is calculated one by one, ultimately obtaining multiple cutting force deviation values ​​that correspond one-to-one with all layer numbers.

[0054] This step ensures that each cutting force deviation value can be accurately traced to a specific layer through layer numbering and mapping relationships, avoiding the blindness of adjusting parameters in general; the quantitative conversion relationship based on material mechanical parameters makes the calculation of cutting force deviation values ​​more scientific.

[0055] Furthermore, the cutting force dataset is backpropagated and corrected based on the multiple cutting force deviation values. The method includes: performing backpropagation optimization on the cutting force dataset based on the multiple cutting force deviation values ​​to obtain an optimized cutting force dataset; performing spatial interpolation on the optimized cutting force dataset to generate a cutting force field, wherein the cutting force field is continuously distributed; performing shaping correction on the machining position based on the continuously distributed cutting force field to construct a three-dimensional cutting force distribution map; and adding the three-dimensional cutting force distribution map to the correction result.

[0056] Specifically, spatial interpolation refers to using mathematical methods to fill in the gaps between discrete cutting force data points, transforming scattered, layered data into continuously distributed spatial data. Common methods include Kriging interpolation and linear interpolation. The cutting force field refers to the overall representation of the continuously distributed cutting forces in three-dimensional space after spatial interpolation, reflecting the magnitude and direction of the cutting forces at different locations in Cato's work.

[0057] Specifically, multiple cutting force deviation values ​​are input into a parameter optimization tool, such as a backpropagation model built on TensorFlow. Using the deviation value as the objective function, the original cutting force dataset is optimized through backpropagation. The algorithm iteratively calculates the adjustment amount of the cutting force at each layer, resulting in an optimized cutting force dataset. Specifically, the backpropagation model takes the original cutting force data and cutting force deviation values ​​as input, and the optimized cutting force data as output. A three-layer fully connected neural network is constructed: the input layer contains the original force value and deviation value features, two hidden layers, and the output layer outputs the optimized force value. Mean squared error is used as the loss function, and the model is trained using historical processing cutting force data. Forward propagation calculates the predicted value, and backpropagation uses the chain rule to calculate the gradient of the loss with respect to the weights of each layer. The Adam optimizer iteratively updates the weights until the loss converges, completing the model construction.

[0058] Next, spatial interpolation tools were used to process the optimized dataset. Using the cutting force data of each layer as discrete points, a continuously distributed cutting force field was generated in three-dimensional space through interpolation. The interpolation filled in the cutting force values ​​in the positions not covered by the original layer data. Based on the continuous cutting force field, the machining position of the caddie was corrected using three-dimensional modeling software. The machining path corresponding to the abnormal force value area was fine-tuned, and the corrected cutting force distribution was presented graphically to construct a three-dimensional cutting force distribution map. This three-dimensional distribution map was integrated with the cutting force optimization dataset and stored as a complete correction result, providing a visual and quantitative basis for subsequent chatter index updates and parameter optimization.

[0059] This step optimizes and eliminates the deviation between the cutting force data and the actual data through backpropagation, reducing the error of the optimized dataset. The continuous cutting force field generated by spatial interpolation fills the information gaps between the layered data, avoiding the omission of transition zone correction caused by relying solely on layered data. This step significantly improves the spatial continuity and accuracy of the cutting force data, providing a more comprehensive basis for subsequent vibration index updates and parameter optimization, further reducing the dimensional errors and chatter risks in the Cato machining process, and improving the consistency of finished products.

[0060] Furthermore, based on the correction results, the flutter state index is updated, and a vibration-optimized processing parameter set for the precision carving equipment is generated for precision carving of the mobile phone SIM card tray to be processed. The method includes: performing processing response analysis based on the three-dimensional cutting force distribution map to obtain process frequency response parameters; traversing the process frequency response parameters to evaluate the contribution of the flutter state index, determining key flutter parameters to update the flutter state index, and generating a vibration-optimized processing parameter set for the precision carving equipment; executing the vibration-optimized processing parameter set for precision carving of the mobile phone SIM card tray to be processed, iteratively correcting the vibration-optimized processing parameter set based on the precision carving processing data, and constructing a precision carving quality report; and precision carving the mobile phone SIM card tray to be processed according to the precision carving quality report.

[0061] Specifically, process frequency response parameters refer to the vibration frequency response characteristics of equipment to changes in cutting force during the machining process, reflecting the correlation between cutting force and equipment vibration.

[0062] Specifically, the three-dimensional cutting force distribution map is imported into spectrum analysis software, such as LMS Test.Lab. By analyzing the correlation between cutting force and equipment vibration at different locations, process frequency response parameters are obtained. These parameters are iterated through, and contribution rate algorithms, such as random forest feature importance assessment, are used to evaluate the contribution of the original chatter state index to identify key chatter parameters. Based on this, the chatter state index is updated, generating a vibration-optimized machining parameter set. This set is then imported into the CNC system of the engraving equipment for trial machining of the first batch of trays to be processed. Real-time engraving forming data is collected and analyzed. The actual results are compared with the expectations, and the parameter set is iteratively corrected to generate an engraving forming quality report, including the pass rate and reasons for deviations. The trays to be processed are then batch-processed according to the optimized parameters in the report to ensure stable forming quality.

[0063] This step, based on the process response analysis of cutting force distribution, makes the chatter index update more in line with the actual machining mechanical characteristics, avoiding efficiency loss caused by excessive parameter restrictions; in addition, the machining data-driven iterative correction makes the parameter set continuously approach the optimal state, achieving a technical effect of balancing machining efficiency with high precision and high stability.

[0064] In summary, the optimized method for precision carving of a mobile phone SIM card tray provided in this application has the following technical effects:

[0065] 1. By integrating chatter monitoring, simulated cutting, model comparison, and parameter optimization, a closed-loop process system is formed, solving the problems of blind parameter adjustment and insufficient chatter control in traditional mobile phone SIM card tray engraving. This comprehensively improves the stability and forming accuracy of the processing, reduces material waste caused by ineffective trial cuts, and provides a systematic quality assurance solution for SIM card tray mass production.

[0066] 2. By selecting parameters based on chatter indices and performing layered simulation cutting, the risks associated with using chatter-prone parameters are mitigated in advance. Layered processing makes the simulation more closely resemble the characteristics of actual machining stages, and the generated precision-carved 3D model accurately reflects the mechanical state at each stage, laying a high-precision foundation for subsequent comparison with the actual model and reducing the deviation between simulation and reality.

[0067] 3. By optimizing backpropagation and spatial interpolation, the cutting force data is made closer to reality and continuously distributed, filling the information gaps between layers. The three-dimensional cutting force distribution map intuitively presents the force distribution, solving the problem of incomplete correction caused by the discreteness of traditional data, providing a more complete mechanical basis for chatter index updates, and improving the pertinence of parameter optimization. Example 2

[0068] Based on the same inventive concept as the optimized method for precision carving and molding of a mobile phone SIM card tray in the foregoing embodiments, such as Figure 3 As shown in the figure, this application provides a mobile phone SIM card tray precision carving process optimization system. The system includes: a real-time acquisition module 11, used to retrieve the initial processing parameters of the precision carving equipment, activate sensor data for real-time acquisition, and set a chatter state index; a deviation value generation module 12, used to traverse the initial processing parameters according to the chatter state index to perform cutting analysis, determine the cutting force dataset, perform simulated layer-by-layer cutting on the mobile phone SIM card tray to be processed, generate a precision carving 3D model, perform multi-layer comparison, and generate multiple cutting force deviation values, wherein the multiple cutting force deviation values ​​correspond to the multiple layers of the precision carving 3D model; and a processing parameter set generation module 13, used to perform forming correction on the cutting force dataset based on the multiple cutting force deviation values, update the chatter state index according to the correction result, and generate a vibration optimization processing parameter set for the precision carving equipment to perform precision carving processing on the mobile phone SIM card tray to be processed.

[0069] Furthermore, the real-time acquisition module 11 is also used to perform the following steps: activating the vibration sensor based on the initial processing parameters to acquire triaxial vibration acceleration signals, sampling vibration frequencies according to the triaxial vibration acceleration signals to capture high-frequency vibration data; converting the high-frequency vibration data to the frequency domain for spectral analysis to obtain the vibration spectrum; dividing the vibration spectrum according to the vibration frequency to obtain multiple characteristic frequency bands for distribution calculation to generate energy distribution characteristics; comparing the energy distribution characteristics with a preset energy fluctuation amplitude, identifying the flutter parameter set for stability division, and setting the flutter state index.

[0070] Furthermore, the deviation value generation module 12 is also used to perform the following steps: based on the chatter state index, traverse the initial processing parameters to perform numerical division and determine multiple parameter combinations; perform cutting dynamics calculations according to the multiple parameter combinations to obtain cutting force fluctuation data for processing screening and generate a cutting force dataset; construct a three-dimensional model of the mobile phone SIM card tray to be processed, and based on the cutting force dataset, layer the three-dimensional model of the mobile phone SIM card tray to be processed along the processing direction to determine multiple layers to be cut; perform finite element simulation cutting calculations according to the multiple layers to be cut to obtain multi-layer simulation cutting data, the multi-layer simulation cutting data including stress distribution simulation data and strain distribution simulation data; perform three-dimensional registration and alignment according to the stress distribution simulation data and the strain distribution simulation data to construct the precision-carved three-dimensional model.

[0071] Furthermore, the deviation value generation module 12 is also used to perform the following steps: mapping the multi-layer simulation cutting data to the multiple layers to be cut for positioning, and delineating stress concentration areas and plastic deformation areas; identifying the maximum value of the stress concentration area based on the stress distribution simulation data, and extracting the target stress point location information; performing strain gradient analysis on the plastic deformation area based on the strain distribution simulation data, and extracting strain gradient features; traversing the multiple layers to be cut and combining the target stress point location information and the strain gradient features to perform equivalent calculations, obtaining multi-layer equivalent stress features and multi-layer equivalent strain distribution features; performing intersection analysis on adjacent layers of the multiple layers to be cut based on the multi-layer equivalent stress features and the multi-layer equivalent strain distribution features, obtaining common feature points, the common feature points including stress concentration points and strain feature points; performing nearest-point iterative registration on the multiple layers to be cut according to the stress concentration points and the strain feature points, and constructing the fine-carved 3D model.

[0072] Furthermore, the deviation value generation module 12 is also used to perform the following steps: identifying adjacent layers based on the stress concentration points and the strain feature points to obtain a set of adjacent layer feature points; performing nearest-point transformation analysis based on the set of adjacent layer feature points to construct an initial transformation matrix; traversing the initial transformation matrix to calculate the distance between feature points and obtain multiple feature point distance error values; using the multiple feature point distance error values ​​as iteration conditions to minimize the multiple feature point distance error values; iteratively optimizing the initial transformation matrix based on the minimum feature point distance error value to set a registration accuracy value; and registering the multiple layers to be cut according to the registration accuracy value to construct the fine-carved 3D model.

[0073] Furthermore, the deviation value generation module 12 is also used to perform the following steps: constructing an actual precision-carved 3D model based on historical mobile phone SIM card tray precision carving data logs; dividing the actual precision-carved 3D model into equal-thickness layers according to the multiple layers to be cut, obtaining multiple layered cross sections; comparing the geometric features of the multi-layer simulation cutting data with the multiple layered cross sections, and calculating the multi-layer geometric deviation; performing cutting calculations based on the multi-layer geometric deviation, and obtaining the multiple cutting force deviation values.

[0074] Furthermore, the deviation value generation module 12 is also used to perform the following steps: numbering the multiple layers to be cut in the fine-carved 3D model to obtain multiple layer numbers; performing correlation analysis based on the multi-layer geometric deviation amount and the multiple layer numbers to obtain a multi-layer mapping relationship; retrieving the material mechanical parameters of the machine card holder and analyzing them in conjunction with the multi-layer geometric deviation amount according to the multi-layer mapping relationship to construct a geometry-cutting force conversion relationship; calculating the multi-layer geometric deviation amount according to the geometry-cutting force conversion relationship according to the multiple layer numbers to obtain the multiple cutting force deviation values.

[0075] Furthermore, the machining parameter set generation module 13 is also used to perform the following steps: performing backpropagation optimization on the cutting force dataset based on the multiple cutting force deviation values ​​to obtain a cutting force optimization dataset; performing spatial interpolation processing on the cutting force optimization dataset to generate a cutting force field, wherein the cutting force field is continuously distributed; performing shaping correction on the machining position based on the continuously distributed cutting force field to construct a three-dimensional cutting force distribution map; and adding the three-dimensional cutting force distribution map to the correction result.

[0076] Furthermore, the processing parameter set generation module 13 is also used to perform the following steps: perform processing process response analysis based on the three-dimensional cutting force distribution map to obtain process frequency response parameters; traverse the process frequency response parameters to evaluate the contribution of the chatter state index, determine key chatter parameters to update the chatter state index, and generate a vibration optimization processing parameter set for the precision carving equipment; execute the vibration optimization processing parameter set to perform precision carving on the mobile phone SIM card tray to be processed, iteratively correct the vibration optimization processing parameter set based on the precision carving forming processing data, and construct a precision carving forming quality report; and perform precision carving forming on the mobile phone SIM card tray to be processed according to the precision carving forming quality report.

[0077] In summary, any step of the method described above can be stored as a computer instruction or program in an unrestricted computer memory, and can be called and identified by an unrestricted computer processor to implement any method in the embodiments of this application, without any additional restrictions.

[0078] Furthermore, the "first" or "second" mentioned above may not only represent a sequential relationship, but may also represent a specific concept, and / or refer to the individual or collective selection of multiple elements. Clearly, those skilled in the art can make various modifications and variations to this application without departing from its scope. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application intends to include such modifications and variations.

Claims

1. An optimized method for precision carving and molding of a mobile phone SIM card tray, characterized in that, The method includes: The initial processing parameters of the engraving equipment are retrieved, sensor data is activated for real-time acquisition, and chatter status indicators are set. According to the flutter state index, the initial processing parameters are traversed for cutting analysis to determine the cutting force dataset. The mobile phone card tray to be processed is then subjected to simulated layer cutting to generate a fine-carved 3D model. Multiple layers are compared to generate multiple cutting force deviation values. The multiple cutting force deviation values ​​correspond to the multiple layers of the fine-carved 3D model. Based on the multiple cutting force deviation values, the cutting force dataset is corrected in reverse. The chatter state index is updated according to the correction results, and a set of vibration optimization processing parameters for the precision carving equipment is generated for precision carving of the mobile phone card tray to be processed. The method for constructing the finely sculpted 3D model involves performing 3D registration and alignment based on stress distribution simulation data and strain distribution simulation data. Multi-layer simulation cutting data is mapped to multiple layers to be cut for positioning, and stress concentration areas and plastic deformation areas are delineated; Based on the stress distribution simulation data, the maximum value of the stress concentration region is identified, and the location information of the target stress point is extracted. Based on the strain distribution simulation data, strain gradient analysis is performed on the plastic deformation region to extract strain gradient features; By traversing the multiple layers to be cut and combining the target stress point location information and the strain gradient characteristics, equivalent calculations are performed to obtain the multi-layer equivalent stress characteristics and multi-layer equivalent strain distribution characteristics. Based on the multi-layer equivalent stress characteristics and the multi-layer equivalent strain distribution characteristics, an intersection analysis is performed on the adjacent layers of the multiple layers to be cut to obtain common feature points, which include stress concentration points and strain feature points. Based on the stress concentration points and strain characteristic points, the multiple layers to be cut are iteratively registered to the nearest point to construct the fine-carved 3D model. The method for constructing the precision-carved 3D model involves performing nearest-point iterative registration on the multiple layers to be cut according to the stress concentration points and strain characteristic points, thereby building the precision-carved 3D model. Based on the stress concentration points and strain characteristic points, adjacent layer identification is performed to obtain a set of adjacent layer characteristic points; Based on the adjacent hierarchical feature point set, perform nearest point transformation analysis to construct an initial transformation matrix; The initial transformation matrix is ​​traversed to calculate the distance between feature points, and multiple feature point distance error values ​​are obtained. The distance error values ​​of the multiple feature points are used as iteration conditions to minimize the distance error values ​​of the multiple feature points. The initial transformation matrix is ​​iteratively optimized based on the minimum feature point distance error value, and a registration accuracy value is set. The multiple layers to be cut are registered according to the registration accuracy value to construct the fine-carved 3D model.

2. The method for optimizing the precision carving process of a mobile phone SIM card tray as described in claim 1, characterized in that, The initial processing parameters of the engraving equipment are retrieved to activate sensor data for real-time acquisition, and chatter status indicators are set. The methods include: Based on the initial processing parameters, the vibration sensor is activated to acquire triaxial vibration acceleration signals in three directions. Vibration frequency is sampled according to the triaxial vibration acceleration signals to capture high-frequency vibration data. The high-frequency vibration data is converted to the frequency domain for spectral analysis to obtain the vibration spectrum. The vibration spectrum is divided according to the vibration frequency to obtain multiple characteristic frequency bands, and the distribution is calculated to generate energy distribution characteristics; The energy distribution characteristics are compared with the preset energy fluctuation amplitude to identify the flutter parameter set for stability classification and to set the flutter state index.

3. The method for optimizing the precision carving process of a mobile phone SIM card tray as described in claim 1, characterized in that, According to the chatter state index, the initial machining parameters are traversed to perform cutting analysis, and the cutting force dataset is determined. Simulation layer-by-layer cutting is then performed on the mobile phone SIM card tray to be machined. The method includes: Based on the flutter state index, the initial processing parameters are traversed to perform numerical division and determine multiple parameter combinations; Cutting dynamics calculations are performed based on the combination of the aforementioned parameters to obtain cutting force fluctuation data, which is then processed and filtered to generate a cutting force dataset. A three-dimensional model of the mobile phone card tray to be processed is constructed. Based on the cutting force dataset, the three-dimensional model of the mobile phone card tray to be processed is divided into layers along the processing direction to determine multiple layers to be cut. Finite element simulation cutting calculations are performed on the multiple layers to be cut to obtain multi-layer simulation cutting data, which includes stress distribution simulation data and strain distribution simulation data. The finely sculpted 3D model is constructed by performing 3D registration and alignment based on the stress distribution simulation data and the strain distribution simulation data.

4. The method for optimizing the precision carving process of a mobile phone SIM card tray as described in claim 3, characterized in that, The method involves generating a finely crafted 3D model, performing multi-layer comparison, and generating multiple cutting force deviation values. A three-dimensional model of the actual fine carving was constructed based on historical mobile phone SIM card tray fine carving data logs; The actual fine-carved 3D model is divided into layers of equal thickness according to the multiple layers to be cut, to obtain multiple layered cross sections; The multi-layer simulated cutting data is compared with the geometric features of the multiple layered sections to calculate the multi-layer geometric deviation. Cutting calculations are performed based on the aforementioned multi-layer geometric deviations to obtain the multiple cutting force deviation values.

5. The method for optimizing the precision carving process of a mobile phone SIM card tray as described in claim 4, characterized in that, The method for obtaining the multiple cutting force deviation values ​​by performing cutting calculations based on the aforementioned multi-layer geometric deviations includes: The multiple layers to be cut in the finely sculpted 3D model are numbered to obtain multiple layer numbers; Based on the multi-layer geometric deviation and the multiple layer numbers, a correlation analysis is performed to obtain the multi-layer mapping relationship; The material mechanical parameters of the SIM card tray are retrieved and analyzed in conjunction with the multi-layer geometric deviations according to the multi-layer mapping relationship to construct a geometry-cutting force conversion relationship; The geometric deviation of the multi-layer structure is calculated according to the multiple layer numbers based on the geometric-cutting force conversion relationship to obtain the multiple cutting force deviation values.

6. The method for optimizing the precision carving process of a mobile phone SIM card tray as described in claim 1, characterized in that, The method involves reversing the shape correction of the cutting force dataset based on the multiple cutting force deviation values, including: Based on the multiple cutting force deviation values, backpropagation optimization is performed on the cutting force dataset to obtain the cutting force optimized dataset; Spatial interpolation is performed on the cutting force optimization dataset to generate a cutting force field, which is continuously distributed. Based on the continuously distributed cutting force field, the machining position is shaped and corrected to construct a three-dimensional cutting force distribution map; Add the three-dimensional cutting force distribution map to the correction result.

7. The method for optimizing the precision carving process of a mobile phone SIM card tray as described in claim 6, characterized in that, The flutter state index is updated based on the correction results, and a vibration optimization processing parameter set for the precision engraving equipment is generated for precision engraving of the mobile phone SIM card tray to be processed. The method includes: Based on the three-dimensional cutting force distribution map, a machining process response analysis is performed to obtain process frequency response parameters. The contribution of the process frequency response parameters to the chatter state index is evaluated by iterating through them. Key chatter parameters are determined and the chatter state index is updated to generate a set of vibration optimization processing parameters for the precision carving equipment. The vibration-optimized processing parameter set is executed to perform precision carving on the mobile phone card tray to be processed. Based on the precision carving data, the vibration-optimized processing parameter set is iteratively corrected to construct a precision carving quality report. The mobile phone SIM card tray to be processed was precision shaped according to the precision sculpting quality report.

8. A mobile phone SIM card tray precision engraving and molding process optimization system, characterized in that, A method for optimizing the precision carving process of a mobile phone SIM card tray as described in any one of claims 1 to 7, the system comprising: The real-time acquisition module is used to retrieve the initial processing parameters of the engraving equipment, activate sensor data for real-time acquisition, and set the chatter status index. The deviation value generation module is used to perform cutting analysis by traversing the initial processing parameters according to the chatter state index, determine the cutting force dataset, perform simulated layered cutting on the mobile phone card tray to be processed, generate a fine-carved 3D model, perform multi-layer comparison, and generate multiple cutting force deviation values. The multiple cutting force deviation values ​​have a corresponding relationship with the multi-layer of the fine-carved 3D model. The processing parameter set generation module is used to reverse the cutting force dataset based on the multiple cutting force deviation values, update the chatter state index according to the correction result, and generate a vibration optimization processing parameter set for the precision carving equipment to perform precision carving of the mobile phone card tray to be processed.

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