Mobile phone cover automatic processing method and related equipment

Abstract

The invention discloses a mobile phone cover automatic processing method and related equipment, and the method comprises the steps: depositing an oxide thin layer on the surface of a mold cavity, forming a lattice point window, depositing a conductive thin layer on a lattice point window area and a non-lattice point window area, carrying out passivation treatment to obtain a passivated conductive thin layer, and dividing the passivated conductive thin layer into a plurality of electrode areas; bimodal detection is carried out on the electrode area, first wavelength rectangular light pulses and second wavelength femtosecond light pulses are emitted, reflected signal intensity data and sound wave phase amplitude data are obtained, and film thickness data and interface bonding intensity data are obtained; and writing the data into the phase change storage unit, recording change values of two adjacent times of sampling, and judging the pollution degree according to the accumulation trend of the change values. According to the technical scheme, real-time nondestructive monitoring of the submicron organic pollutants on the surface of the mobile phone cover injection mold can be achieved, the problem that in the prior art, online quantitative evaluation of the surface state of the mold is difficult is effectively solved, and the production efficiency and the product quality are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of manufacturing and testing mobile phone accessories, and in particular to an automated processing method for mobile phone cases and related equipment. Background Art

[0002] Automated mobile phone case processing refers to the mass production of mobile phone cases using automated production equipment and processes. This process typically includes automated feeding, injection molding, surface treatment, demolding, and testing, with injection molding being the most critical step. With the rapid growth of the smartphone market, mobile phone cases, as a key accessory, are facing increasing demands for surface quality, dimensional accuracy, and production efficiency in their manufacturing. This is driving the industry's rapid development towards intelligent and sophisticated manufacturing.

[0003] Existing automated processing of mobile phone cases primarily relies on the coordinated collaboration of high-precision injection molding machines, temperature control systems, and robotic arms to complete production. However, during continuous, high-rate production, materials commonly used in mobile phone cases, such as TPU and liquid silicone, release low-molecular-weight softeners and decomposition products during high-temperature injection molding. These volatile organic compounds gradually condense and adhere to the mirrored mold cavity surface each time the mold is opened and closed, forming a transparent organic film with a thickness of 100-300 nanometers. This organic film, with a refractive index very close to that of the steel substrate, is virtually invisible to the naked eye under conventional visible light. However, its presence significantly alters the interfacial tension between the molten resin and the mold wall. This change can lead to quality issues such as ripple flow marks on the product surface, melt front splitting, and even decreased optical transmittance. Currently, the industry's detection method for this problem still relies on periodic shutdowns and mold removal inspections. This method is not only inefficient, but also severely impacts production efficiency and product yield, as a large number of substandard products may have already been produced during the inspection intervals. Therefore, how to achieve real-time non-destructive detection of submicron-level organic adhesions on the surface of the mold cavity has become a technical problem that needs to be solved urgently. Summary of the Invention

[0004] The main purpose of the present invention is to solve the technical problem that the existing mobile phone case injection mold surface contamination detection technology is unable to quantitatively evaluate submicron organic pollutants on the mold surface in real time.

[0005] A first aspect of the present invention provides an automated processing method for a mobile phone case, the automated processing method for a mobile phone case comprising: Depositing a first oxide thin layer on the surface of the mold cavity, forming regularly distributed lattice windows on the first oxide thin layer, depositing a conductive thin layer on the lattice window region and the non-lattice window region of the first oxide thin layer, passivating the surface of the conductive thin layer to obtain a passivated conductive thin layer, and dividing the passivated conductive thin layer into a plurality of electrode regions; Performing dual-modal detection on the electrode region, including emitting a rectangular light pulse of a first wavelength and obtaining reflected signal intensity data, emitting a femtosecond light pulse of a second wavelength and obtaining acoustic wave phase amplitude data, and obtaining film thickness data and interface bonding strength data of the electrode region based on the reflected signal intensity data and the acoustic wave phase amplitude data; The film thickness data and interface bonding strength data of the electrode area are written into the phase change memory unit respectively, and the change values of the film thickness data and the interface bonding strength data of two adjacent samplings of the electrode area are recorded. The degree of contamination of the electrode area is judged according to the cumulative trend of the change values of the film thickness data and the change values of the interface bonding strength data.

[0006] Preferably, a first oxide thin layer is deposited on the surface of the mold cavity, regularly distributed lattice windows are formed on the first oxide thin layer, a conductive thin layer is deposited on the lattice window region and the non-lattice window region of the first oxide thin layer, the surface of the conductive thin layer is passivated to obtain a passivated conductive thin layer, and the passivated conductive thin layer is divided into a plurality of electrode regions, including: Treating the mold cavity surface with a decontamination gas, and depositing a silicon oxide layer having a thickness within the peak-to-valley range of the original roughness of the mold on the decontaminated mold surface as a first oxide thin layer; The silicon oxide layer is regionally etched according to the geometric structure of the mold cavity surface, forming lattice window structures with different distribution forms in the plane, fillet, camera ring and function key slot areas, respectively. The depth of the lattice window structure extends to the decontaminated mold surface, and the unetched area of the silicon oxide layer constitutes a non-lattice window area; Depositing a transparent conductive oxide layer with uniform thickness as a conductive thin layer on the non-lattice window area and the bottom of the lattice window, wherein the thickness of the transparent conductive oxide layer is less than the thickness of the silicon oxide layer; Passivating the surface of the transparent conductive oxide layer to obtain a passivated conductive thin layer with a surface contact angle of 90 degrees; The passivated conductive thin layer is divided into electrode regions adapted to the geometric structure of the mold surface, and the areas of adjacent electrode regions are distributed in a gradient as the curvature changes.

[0007] Preferably, depositing a transparent conductive oxide layer of uniform thickness as a conductive thin layer on the non-lattice window region and the bottom of the lattice window, wherein the thickness of the transparent conductive oxide layer is less than the thickness of the silicon oxide layer, comprises: Depositing a first transparent indium tin oxide layer in the non-lattice window region and at the bottom of the lattice window, wherein the thickness of the first transparent indium tin oxide layer in the non-lattice window region and at the bottom of the lattice window is consistent, and the thickness of the first transparent indium tin oxide layer on the peripheral wall of the lattice window gradually decreases from the bottom to the opening; Doping the first transparent indium tin oxide layer with indium to form a first doping concentration in the planar area, a second doping concentration in the rounded corner area, a third doping concentration in the camera ring area, a fourth doping concentration in the function key slot area, and a fifth doping concentration in the lattice window peripheral wall area, wherein the second doping concentration is greater than the first doping concentration, the third doping concentration is greater than the second doping concentration, the fourth doping concentration is greater than the third doping concentration, and the fifth doping concentration gradually increases from the bottom toward the opening on the peripheral wall; A second transparent indium tin oxide layer is deposited on the surface of the first transparent indium tin oxide layer. The second transparent indium tin oxide layer has the same thickness in the non-lattice window area and the bottom of the lattice window, and gradually increases in thickness from the bottom to the opening on the peripheral wall of the lattice window. The total thickness of the second transparent indium tin oxide layer and the first transparent indium tin oxide layer is less than the thickness of the silicon oxide layer, and the resistivity of the second transparent indium tin oxide layer is less than the resistivity of the first transparent indium tin oxide layer.

[0008] Preferably, the dual-modal detection of the electrode region includes emitting a rectangular light pulse of a first wavelength and obtaining reflected signal intensity data, emitting a femtosecond light pulse of a second wavelength and obtaining acoustic wave phase amplitude data, and obtaining film thickness data and interface bonding strength data of the electrode region based on the reflected signal intensity data and the acoustic wave phase amplitude data, including: emitting a first rectangular light pulse with a wavelength of 235 nanometers to the lattice window region and the non-lattice window region of the electrode region, respectively, to obtain a first reflection signal from the lattice window region and a second reflection signal from the non-lattice window region; Performing a time domain analysis on the first reflection signal to obtain a reference reflection intensity of the mold surface after decontamination, and performing a time domain analysis on the second reflection signal to obtain a combined reflection intensity of the silicon oxide layer and the passivation conductive thin layer; Superimposing and analyzing the reference reflection intensity and the combined reflection intensity to obtain reflection signal intensity data of the electrode area; emitting a second wavelength femtosecond light pulse of 257 nanometers to the lattice window region and the non-lattice window region of the electrode region, respectively, to obtain a first acoustic wave signal from the lattice window region and a second acoustic wave signal from the non-lattice window region; Performing weighted processing on the first acoustic wave signal and the second acoustic wave signal according to the first doping concentration, the second doping concentration, the third doping concentration, and the fourth doping concentration of each region to obtain an acoustic wave phase signal and an acoustic wave amplitude signal of the electrode region; Reconstructing the acoustic wave phase signal and the acoustic wave amplitude signal according to the doping concentration to obtain acoustic wave phase and amplitude data of the electrode region; Calculating film thickness data of the electrode region according to a difference between the reflection signal intensity data and the reference reflection intensity; The interface bonding strength data of the electrode region is calculated according to the corresponding relationship between the acoustic wave phase amplitude data and the doping concentration gradient.

[0009] Preferably, the step of writing the film thickness data and the interface bonding strength data of the electrode region into a phase change memory unit, recording the change values of the film thickness data and the interface bonding strength data of two adjacent samplings of the electrode region, and judging the contamination degree of the electrode region according to the cumulative trend of the change values of the film thickness data and the change values of the interface bonding strength data, comprises: Writing the film thickness data of the electrode region into the first phase-change memory unit, and writing the interface bonding strength data of the electrode region into the second phase-change memory unit; Calculating the difference between the film thickness data of two adjacent samples in the electrode area to obtain a film thickness data change value, and calculating the difference between the interface bonding strength data of two adjacent samples in the electrode area to obtain an interface bonding strength data change value; Accumulating the film thickness data change values to obtain a film thickness cumulative value, and accumulating the interface bonding strength data change values to obtain a strength cumulative value; Determine the contamination rate of the electrode region according to the growth rate of the film thickness cumulative value, and determine the contamination stability of the electrode region according to the growth rate of the intensity cumulative value; The pollution speed is compared with a preset speed threshold, and the pollution stability is compared with a preset stability threshold to obtain the pollution degree of the electrode area.

[0010] Preferably, the mobile phone case automated processing method further includes performing pollution suppression processing on the electrode area where the pollution speed is greater than the preset speed threshold and the pollution stability is greater than the preset stability threshold, specifically comprising: Obtaining a growth direction of a film thickness cumulative value in the first phase-change memory unit and a growth direction of an intensity cumulative value in the second phase-change memory unit to determine a contaminant migration trend in the electrode region; applying a reverse bias voltage to the electrode region according to the migration trend of the pollutants to form a potential difference between the lattice window region and the non-lattice window region; The bias voltage is regionally adjusted based on the geometric structure of the electrode area, applying a first type of bias voltage to the plane area, a second type of bias voltage to the rounded corner area, a third type of bias voltage to the camera ring area, and a fourth type of bias voltage to the function key slot area; Performing time-domain modulation on the potential difference to form a first electric field gradient in the lattice window region and a second electric field gradient in the non-lattice window region, wherein the first electric field gradient is greater than the second electric field gradient; The injection pressure parameters of the injection molding process are adjusted according to the distribution of the electric field gradient, and a directional shear flow field is formed at the boundary of the electrode area to guide the pollutants from the grid window area to the non-grid window area.

[0011] Preferably, the automated processing method for mobile phone cases further comprises performing Rayleigh wave cleaning on the electrode area after the directional shear flow field continues to act for more than a preset time, specifically comprising: Acquiring a film thickness accumulation value and an intensity accumulation value in the first phase-change memory unit and the second phase-change memory unit, and setting cleaning parameters for the electrode region according to the film thickness accumulation value and the intensity accumulation value; emitting a Rayleigh wave of a first frequency toward a lattice window region of the electrode region, and emitting a Rayleigh wave of a second frequency toward a non-lattice window region of the electrode region, wherein the first frequency is greater than the second frequency; The propagation direction of the Rayleigh wave is adjusted according to the geometric structure of the electrode area, forming traveling wave propagation in the plane area, forming standing wave resonance in the rounded corner area, forming a ring wave in the camera ring area, and forming a focusing wave in the function key slot area; Spraying a low surface tension liquid into the electrode region in an atomized state, wherein the low surface tension liquid forms different spreading coefficients in the grid window region and the non-grid window region; Writing the frequency parameter, propagation direction parameter of the Rayleigh wave and the spreading coefficient of the low surface tension liquid into the first phase change storage unit and the second phase change storage unit for setting the next round of cleaning parameters; The film thickness accumulation value and the intensity accumulation value in the first phase-change memory unit and the second phase-change memory unit are reset.

[0012] A second aspect of the present invention provides an automated processing device for mobile phone cases, the automated processing device for mobile phone cases comprising: a functionalized interface preparation module, configured to deposit a first oxide thin layer on the surface of the mold cavity, form regularly distributed lattice windows on the first oxide thin layer, deposit a conductive thin layer on the lattice window regions and non-lattice window regions of the first oxide thin layer, passivate the surface of the conductive thin layer to obtain a passivated conductive thin layer, and divide the passivated conductive thin layer into a plurality of electrode regions; a dual-modal detection module for performing dual-modal detection on the electrode region, comprising emitting a rectangular light pulse of a first wavelength and obtaining reflected signal intensity data, emitting a femtosecond light pulse of a second wavelength and obtaining acoustic wave phase amplitude data, and obtaining film thickness data and interface bonding strength data of the electrode region based on the reflected signal intensity data and the acoustic wave phase amplitude data; A data processing module is used to write the film thickness data and interface bonding strength data of the electrode area into the phase change storage unit respectively, record the change value of the film thickness data and the change value of the interface bonding strength data of two adjacent samples of the electrode area, and judge the degree of contamination of the electrode area according to the cumulative trend of the change value of the film thickness data and the change value of the interface bonding strength data.

[0013] A third aspect of the present invention provides an automated processing device for mobile phone cases, comprising: a memory and at least one processor, wherein the memory stores instructions, and the memory and the at least one processor are interconnected via a circuit; the at least one processor calls the instructions in the memory to enable the automated processing device for mobile phone cases to execute the steps of the above-mentioned automated processing method for mobile phone cases.

[0014] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions that, when executed on a computer, enable the computer to execute the steps of the above-mentioned method for automated processing of mobile phone cases.

[0015] In the technical solution provided by the embodiment of the present application, a thin layer of silicon oxide is deposited on the mold surface as the first oxide layer. Its thickness is strictly controlled at about 25 nanometers, which is on the same order of magnitude as the micro-roughness of the original polished surface of the mold (Ra≤0.02µm, i.e. 20-25nm). Atomic layer deposition (ALD) technology grows thin films layer by layer through chemical adsorption to ensure uniform coverage on complex curved surfaces. This deposition method actually fills the microscopic peaks and valleys on the mold surface rather than simply piling them up, so it does not change the macroscopic dimensions of the mold.

[0016] A lattice window structure is laser-etched into the silicon oxide layer, exposing the steel substrate in specific areas and establishing a clear optical reference for comparison. The depth is precisely controlled down to the mold's original surface, ensuring a consistently measurable difference in optical performance between the lattice and non-lattice areas. The spacing and distribution of the lattice structure are optimized to ensure sufficient sampling accuracy without compromising mold functionality.

[0017] The conductive thin layer (transparent ITO) is designed to be 20 nanometers thick, less than the silicon oxide layer, ensuring a total coverage thickness of less than 45 nanometers. ITO has excellent conductivity and optical transparency, and its high hardness (6-7 GPa) allows it to remain in the purely elastic deformation range under mold operating pressure. Surface passivation treatment adjusts the contact angle to approximately 90°, which ensures that the resin melt flow behavior is almost identical to that of a conventional mold surface.

[0018] Dual-modal detection uses deep ultraviolet light (235nm and 257nm) as a detection source. Its wavelength characteristics make the system extremely sensitive to transparent organic films with thicknesses between 100 and 300 nanometers. The optical reflection signal primarily reflects changes in film thickness, while the acoustic signal more sensitively captures changes in interfacial bonding. These two physical quantities complement each other, providing more comprehensive information on contamination characteristics than a single detection method alone.

[0019] The phase-change memory cell uses Ge2Sb2Te5 phase-change material to physically record detection data as resistance changes, eliminating the need for complex mathematical model calculations. This design, directly processed by the FPGA, achieves a response time of less than 20 microseconds, meeting the real-time requirements of high-speed production environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0021] Figure 1 A schematic diagram of an embodiment of the automated processing method for mobile phone cases according to an embodiment of the present invention; Figure 2 This is a schematic diagram of an embodiment of an automatic processing device for mobile phone cases according to an embodiment of the present invention; Figure 3 Schematic diagram of an embodiment of the automatic processing equipment for mobile phone cases in an embodiment of the present invention.

[0022] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0024] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture. If the specific posture changes, the directional indications will also change accordingly.

[0025] In addition, the descriptions of "first", "second", etc. in the present invention are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, "and / or" in the full text includes three solutions. Taking A and / or B as an example, it includes technical solution A, technical solution B, and technical solution that satisfies both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, and must be based on the ability of ordinary technicians in this field to implement. When the combination of technical solutions is mutually contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0026] An embodiment of the present application provides an automated processing method for a mobile phone case. Figure 1 A flowchart of a method for automatically processing a mobile phone case according to an embodiment of the present application. In this embodiment, the method includes: See also Figure 1 , depositing a first oxide thin layer on the surface of the mold cavity, forming regularly distributed lattice windows on the first oxide thin layer, depositing a conductive thin layer on the lattice window region and the non-lattice window region of the first oxide thin layer, passivating the surface of the conductive thin layer to obtain a passivated conductive thin layer, and dividing the passivated conductive thin layer into a plurality of electrode regions; In one embodiment of the present invention, a first oxide thin layer is deposited on the surface of the mold cavity, regularly distributed lattice windows are formed on the first oxide thin layer, a conductive thin layer is deposited on the lattice window region and the non-lattice window region of the first oxide thin layer, the surface of the conductive thin layer is passivated to obtain a passivated conductive thin layer, and the passivated conductive thin layer is divided into a plurality of electrode regions, including: Treating the mold cavity surface with a decontamination gas, and depositing a silicon oxide layer having a thickness within the peak-to-valley range of the original roughness of the mold on the decontaminated mold surface as a first oxide thin layer; The silicon oxide layer is regionally etched according to the geometric structure of the mold cavity surface, forming lattice window structures with different distribution forms in the plane, fillet, camera ring and function key slot areas, respectively. The depth of the lattice window structure extends to the decontaminated mold surface, and the unetched area of the silicon oxide layer constitutes a non-lattice window area; Depositing a transparent conductive oxide layer with uniform thickness as a conductive thin layer on the non-lattice window area and the bottom of the lattice window, wherein the thickness of the transparent conductive oxide layer is less than the thickness of the silicon oxide layer; Passivating the surface of the transparent conductive oxide layer to obtain a passivated conductive thin layer with a surface contact angle of 90 degrees; The passivated conductive thin layer is divided into electrode regions adapted to the geometric structure of the mold surface, and the areas of adjacent electrode regions are distributed in a gradient as the curvature changes.

[0027] The following is a detailed description of the steps involved in the above embodiment: First, the surface of the mold cavity is treated with a decontamination gas. After decontamination, a silicon oxide layer with a thickness within the peak and valley range of the original roughness of the mold is deposited on the mold surface as the first oxide thin layer. In specific implementation, a low-temperature plasma cleaning machine is used to decontaminate the surface of the mold cavity. The plasma gas is a mixture of oxygen and argon with a gas ratio of 1:3. The treatment time is 3 minutes, the power is set to 300W, and the pressure is 50Pa. This treatment can effectively remove polishing residues and air-adsorbed water films on the mold surface, providing a clean surface for subsequent deposition. After decontamination, an atomic layer deposition (ALD) device is used to deposit the silicon oxide layer. The specific operating parameters are: reaction temperature 120°C, precursors are tetramethylsilane (TMOS) and ozone (O3), pulse times are 0.5 seconds and 1.0 seconds respectively, nitrogen purge time is 2.0 seconds, and the deposition rate is controlled at 0.6Å / s. The deposition thickness is controlled at 25nm, which is just within the peak-to-valley range of the surface roughness Ra value of the mobile phone case injection mold (usually 0.02μm or 20nm). For example, for a mold surface with a large flat area roughness Ra of 0.018μm on the back panel, after 25nm of silicon oxide deposition, the surface roughness Ra is reduced to 0.006μm, but the actual size of the mold does not change by more than 5μm, which is much smaller than the production tolerance of the mobile phone case wall thickness of 30μm. The design of the thickness of the silicon oxide layer is sophisticated in that if the thickness is less than 20nm, it will not be able to effectively submerge the microscopic peaks and valleys on the mold surface, affecting the benchmark stability of subsequent optical inspections; if the thickness is greater than 30nm, it will change the macroscopic size of the mold, affecting the product precision, and increasing the risk of thermal stress accumulation.

[0028] The silicon oxide layer is regionally etched according to the geometry of the mold cavity surface, forming a specifically distributed grid window structure in different areas. Precision processing is performed using a femtosecond laser etching system with an 800nm laser wavelength, 300fs pulse width, 1kHz repetition rate, and a focused spot diameter of 10μm. Differentiated parameters are used for different areas: the grid windows in the planar area are arranged in a square grid pattern with a spacing of 500μm and a single window size of 50×50μm. The grid windows in the rounded corner area are radially distributed with a central angular spacing of 15° and a radial spacing of 300μm. The grid windows in the camera ring area are arranged in concentric rings with a spacing of 250μm and arc segments with an arc length of 100μm. The grid windows in the key slot area are arranged in strips along the slot, with a strip width of 30μm and a spacing of 200μm. The etching depth of all grid windows is precisely controlled to 25±2nm, ensuring complete exposure of the decontaminated mold steel substrate without over-etching. The lattice window structure refers to the regularly distributed opening areas formed on the silicon oxide thin layer, through which the mold surface can be exposed. The non-lattice window area refers to the part of the silicon oxide layer that has not been etched and maintains the original thickness. For example, for a camera ring area with a diameter of 12mm, three circles of concentric ring grid windows are used, with 40 windows distributed in each circle, which can provide sufficient sampling points while ensuring structural stability. The design of the grid window distribution allows the plane area to use a larger spacing to reduce the impact on the mold strength; the rounded corner area uses a radial distribution to adapt to the curvature change; the camera ring and function key slot use a special distribution pattern to adapt to complex geometric shapes, ensuring that the detection signal remains consistent and reliable in anisotropic structures.

[0029] A transparent conductive oxide layer with uniform thickness is deposited on the non-lattice window area and the bottom of the lattice window as a conductive thin layer. A magnetron sputtering device is used to deposit an indium tin oxide (ITO) thin layer. The specific process parameters are: background vacuum degree 5×10 -6 Pa, the working gas is a mixture of argon and oxygen in a ratio of 20:1, the working pressure is 0.5Pa, the sputtering power is 80W, the substrate temperature is 150°C, the rotation speed is 10rpm, and the deposition rate is controlled at 0.2nm / s. The deposition thickness is strictly controlled at 20nm, which is less than the 25nm thickness of the silicon oxide layer. The transparent conductive oxide layer refers to a metal oxide film with good electrical conductivity and visible light transparency. ITO is selected in this embodiment. The conductive thin layer forms a continuous coverage at the bottom of the lattice window (i.e., the mold surface) and the non-lattice window area (i.e., the surface of the silicon oxide layer). For example, for a functional key slot area, the resistivity of the ITO layer is 3.5×10 -4Ω·cm, with visible light transmittance exceeding 85%, ensuring the dual functions of subsequent electrical control and optical detection. The ITO layer thickness is designed to be 20nm because when the thickness is less than 15nm, the film continuity is poor and the conductivity is insufficient. When the thickness is greater than 25nm, the total thickness combined with the silicon oxide layer will exceed the mold roughness peak-valley range, increasing the risk of thermal stress. A 20nm thickness ensures sufficient conductivity (sheet resistance <100 ohms per square) while maintaining the required optical properties and structural stability.

[0030] The surface of the transparent conductive oxide layer is passivated to obtain a passivated conductive thin layer with a surface contact angle of 90 degrees. A hydrogen plasma treatment system is used for surface passivation, and the treatment parameters are: hydrogen flow rate 50sccm, working pressure 20Pa, RF power 150W, treatment time 45 seconds, and substrate temperature controlled at 80°C. After passivation treatment, a contact angle meter is used to detect the surface contact angle to ensure that it reaches 90±2 degrees. Passivation treatment refers to the process of changing the surface chemical groups and adjusting the surface energy of the material through the action of plasma. The passivated conductive thin layer refers to the ITO layer after passivation treatment, which is a functional layer with specific surface characteristics. For example, for the large flat area of the backplane, the contact angle of the ITO surface is 65 degrees before passivation and is adjusted to 90 degrees after passivation, which is close to the 93 degrees of the original mold surface, ensuring the consistency of the flow behavior of the injection molding material. The significance of setting the contact angle to 90 degrees is that when the contact angle is less than 85 degrees, the affinity of the injection molding material is too strong, which can easily lead to uneven flow rate at the melt front; when the contact angle is greater than 95 degrees, the demoulding friction coefficient increases, affecting the ejection force; a contact angle of 90 degrees can take into account both fluidity and demoulding properties while maintaining interfacial tension characteristics similar to the original mold surface.

[0031] The passivated conductive thin layer is divided into electrode areas that match the geometry of the mold surface. The area of adjacent electrode areas is distributed in a gradient as the curvature changes. A UV lithography system is used for electrode division, and photoresist AZ5214 is used for pattern transfer. The exposure energy is set to 15mJ / cm 2 , the development time is 35 seconds. Then the pattern is developed using ion beam etching equipment, and the etching depth is controlled at 5nm, only cutting the continuity of ITO without damaging the underlying silicon oxide. The specific division scheme is: the entire mold surface is divided into an 8×8 electrode matrix, where the flat area electrode area is 10×10mm 2 The electrode area of the part with a radius of curvature greater than 5 mm is 5×5 mm. 2 The electrode area of the curvature radius 3-5mm is 3×3mm 2 The electrode area of the part with a curvature radius less than 3 mm is 2×2 mm 2, there is a sector-shaped electrode every 45° in the camera annular area, and each groove in the function key slot area serves as an independent electrode. The electrode area refers to an independent conductive unit formed by etching separation. Different electrode areas are electrically isolated but maintain physical continuity. For example, for a standard mobile phone case mold, the back panel area is divided into 16 large-area electrodes, and the surrounding rounded corner areas are divided into 24 small and medium-area electrodes, forming an area gradient distribution. The significance of the gradient distribution of electrode area with curvature is that: the high curvature area has a complex structure and high pollution sensitivity, requiring finer monitoring resolution; the planar area has a simple structure, and the electrode area can be appropriately increased to reduce system complexity; the area gradient design can balance detection accuracy and system complexity, and adapt to the physical field distribution characteristics of different geometric areas.

[0032] In one embodiment of the present invention, depositing a transparent conductive oxide layer of uniform thickness as a conductive thin layer on the non-lattice window region and the bottom of the lattice window, wherein the thickness of the transparent conductive oxide layer is less than the thickness of the silicon oxide layer, comprises: Depositing a first transparent indium tin oxide layer in the non-lattice window region and at the bottom of the lattice window, wherein the thickness of the first transparent indium tin oxide layer in the non-lattice window region and at the bottom of the lattice window is consistent, and the thickness of the first transparent indium tin oxide layer on the peripheral wall of the lattice window gradually decreases from the bottom to the opening; Doping the first transparent indium tin oxide layer with indium to form a first doping concentration in the planar area, a second doping concentration in the rounded corner area, a third doping concentration in the camera ring area, a fourth doping concentration in the function key slot area, and a fifth doping concentration in the lattice window peripheral wall area, wherein the second doping concentration is greater than the first doping concentration, the third doping concentration is greater than the second doping concentration, the fourth doping concentration is greater than the third doping concentration, and the fifth doping concentration gradually increases from the bottom toward the opening on the peripheral wall; A second transparent indium tin oxide layer is deposited on the surface of the first transparent indium tin oxide layer. The second transparent indium tin oxide layer has the same thickness in the non-lattice window area and the bottom of the lattice window, and gradually increases in thickness from the bottom to the opening on the peripheral wall of the lattice window. The total thickness of the second transparent indium tin oxide layer and the first transparent indium tin oxide layer is less than the thickness of the silicon oxide layer, and the resistivity of the second transparent indium tin oxide layer is less than the resistivity of the first transparent indium tin oxide layer.

[0033] The following is a detailed description of the steps involved in the above embodiment: When depositing the first transparent indium tin oxide layer in the non-lattice window area and the bottom of the lattice window, a multi-target magnetron sputtering device is used for precise deposition. The operating parameters of the device are set as follows: the background vacuum is 6×10 -6Pa, the working atmosphere is a mixture of argon and oxygen (ratio of 20:1), the working gas pressure is 0.5Pa, and the substrate temperature is controlled at 160°C. During the sputtering process, the substrate rotates at a speed of 10rpm to ensure deposition uniformity. The sputtering power is 100W, the deposition rate is controlled at 0.15nm / s, the total deposition time is 80 seconds, and a first transparent indium tin oxide layer with a thickness of 12nm is obtained. The first transparent indium tin oxide layer refers to the indium tin oxide conductive layer deposited on the mold surface for the first time, which is the base layer of the entire conductive thin layer system. The lattice window wall refers to the side wall area from the bottom of the window to the opening. Because magnetron sputtering has a certain directionality, a thickness gradient is formed on the lattice window wall. The thickness near the bottom area is close to 12nm, while the thickness near the opening is only about 6nm. This thickness distribution can be verified by cross-sectional scanning electron microscopy observation. In practical applications, taking a 50μm×50μm square lattice window as an example, the ITO thickness at the window bottom (i.e., the original mold surface) and non-lattice area (i.e., the silicon oxide surface) is 12±0.5nm, while the thickness above the window wall is reduced to 6±1nm. This thickness distribution ensures sufficient conductivity at the bottom of the window while maintaining the structural integrity of the window outline. This deposition process avoids window closure or film breakage, ensuring continuous transmission of electrical signals between different surfaces.

[0034] When doping the first transparent indium tin oxide layer with indium, a regional selective ion implantation technique was used. Different regions were treated differently using an ion implanter, and the indium ion acceleration energy was set to 30keV. The doping area was precisely controlled by a metal mask, and a dose of 1×10 15 ions / cm 2 (first doping concentration, about 3.5at%), the dose applied to the fillet area is 2×10 15 ions / cm 2 (Second doping concentration, about 5.1at%), the dose applied to the camera ring area is 3×10 15 ions / cm 2 (third doping concentration, about 6.8at%), the dose applied to the functional key groove area is 4×10 15 ions / cm 2 (The fourth doping concentration is about 8.5at%). The doping concentration refers to the percentage of the number of atoms of indium doped per unit volume. The electrical and optical properties of the ITO layer are changed by doping. For the lattice window wall area (the fifth doping concentration), the tilted ion beam implantation technology is used. The incident angle gradually increases from the bottom to the opening, forming a concentration gradient from 4.0at% to 10.0at%. Taking the functional key slot area as an example, the resistivity after doping is increased from the original 3.5×10 -4 Ω·cm is reduced to 1.8×10 -4Ω·cm, while maintaining over 80% visible light transmittance. The doping gradient design in different regions enhances signal transmission efficiency and improves the uniformity of current density distribution. In particular, the higher doping concentration in areas of high curvature compensates for the increased resistance caused by geometric factors, ensuring consistent response across the entire electrode system. After doping, annealing is performed at 300°C in a nitrogen atmosphere for 10 minutes to activate the doped atoms and repair lattice defects.

[0035] When depositing the second transparent indium tin oxide layer on the surface of the first transparent indium tin oxide layer, atomic layer deposition (ALD) technology is used for precise control. The ALD equipment parameters are set as follows: reaction temperature 180°C, precursors are trimethyl indium (TMIn) and ozone (O3), pulse times are 0.8 seconds and 1.2 seconds respectively, and nitrogen purge time is 3.0 seconds. The ALD process has excellent step coverage ability and can form uniform thin films on complex three-dimensional structures. A second transparent indium tin oxide layer with a thickness of 8nm is deposited in the non-lattice window area and the bottom of the grid window, and a thickness gradient is formed in the lattice window wall area, which is 8nm at the bottom and gradually thickens to 14nm toward the opening. The second transparent indium tin oxide layer refers to the ITO functional layer deposited again on the first transparent indium tin oxide layer, and the two-layer structure forms a composite conductive system. By adjusting the oxygen partial pressure ratio during the ALD process, the oxygen vacancy concentration of the second ITO layer is made higher than that of the first ITO layer, thereby reducing its resistivity to 8.5×10 -5 Ω·cm, which is about 1 / 4 of the resistivity of the first ITO layer. The maximum total thickness of the two layers of ITO is 26nm (12nm+14nm), which is still less than the 30nm thickness of the silicon oxide layer, ensuring that the overall coating system will not change the macroscopic size and precision of the mold. Taking the camera ring area as an example, the double-layer ITO structure reduces the surface resistance of the electrode from 110 ohms per square to 42 ohms per square. At the same time, a complementary structure of a "thin bottom and thick top" first layer and a "thick bottom and thin top" second layer is formed on the wall of the grid window, which jointly ensure the conductive continuity at the window contour. This double-layer design enables regions with different geometric curvatures to obtain more consistent electric field distribution, reduces local current congestion caused by complex shapes, and improves the ability to precisely control the subsequent electrophoretic bias. At the same time, the double-layer structure enhances the coating system's resistance to thermal cycling and mechanical stress, and improves the coating stability during long-term use of the mold.

[0036] Please continue reading Figure 1 , performing dual-modal detection on the electrode region, including emitting a rectangular light pulse of a first wavelength and obtaining reflected signal intensity data, emitting a femtosecond light pulse of a second wavelength and obtaining acoustic wave phase amplitude data, and obtaining film thickness data and interface bonding strength data of the electrode region based on the reflected signal intensity data and the acoustic wave phase amplitude data; In one embodiment of the present invention, the dual-modal detection of the electrode region includes emitting a rectangular light pulse of a first wavelength and obtaining reflected signal intensity data, emitting a femtosecond light pulse of a second wavelength and obtaining acoustic wave phase amplitude data, and obtaining film thickness data and interface bonding strength data of the electrode region based on the reflected signal intensity data and the acoustic wave phase amplitude data, including: emitting a first rectangular light pulse with a wavelength of 235 nanometers to the lattice window region and the non-lattice window region of the electrode region, respectively, to obtain a first reflection signal from the lattice window region and a second reflection signal from the non-lattice window region; Performing a time domain analysis on the first reflection signal to obtain a reference reflection intensity of the mold surface after decontamination, and performing a time domain analysis on the second reflection signal to obtain a combined reflection intensity of the silicon oxide layer and the passivation conductive thin layer; Superimposing and analyzing the reference reflection intensity and the combined reflection intensity to obtain reflection signal intensity data of the electrode area; emitting a second wavelength femtosecond light pulse of 257 nanometers to the lattice window region and the non-lattice window region of the electrode region, respectively, to obtain a first acoustic wave signal from the lattice window region and a second acoustic wave signal from the non-lattice window region; Performing weighted processing on the first acoustic wave signal and the second acoustic wave signal according to the first doping concentration, the second doping concentration, the third doping concentration, and the fourth doping concentration of each region to obtain an acoustic wave phase signal and an acoustic wave amplitude signal of the electrode region; Reconstructing the acoustic wave phase signal and the acoustic wave amplitude signal according to the doping concentration to obtain acoustic wave phase and amplitude data of the electrode region; Calculating film thickness data of the electrode region according to a difference between the reflection signal intensity data and the reference reflection intensity; The interface bonding strength data of the electrode region is calculated according to the corresponding relationship between the acoustic wave phase amplitude data and the doping concentration gradient.

[0037] The following is a detailed description of the steps involved in the above embodiment: A deep ultraviolet (DUV) spectroscopy detection system was used to detect the presence of rectangular light pulses with a first wavelength of 235 nm emitted from the grid window region and non-grid window region of the electrode region. The system comprises a pulsed laser, a beam splitter, an optical fiber array, and a high-speed photodetector. Laser parameters were set as follows: wavelength 235 ± 0.5 nm, pulse width 50 nanoseconds, repetition rate 5 kHz, and single pulse energy 5 μJ. The optical fiber array was embedded in the mold parting surface, with eight fiber probes corresponding to each electrode region, each with a diameter of 100 μm. Detection was initiated 0.15 seconds after the locking pressure stabilized, and the optical fiber array simultaneously emitted light pulses at a 20° angle of incidence toward the grid window region and non-grid window region. The first rectangular light pulses were laser pulses with a wavelength of 235 nm and a rectangular temporal distribution. The first reflection signal from the grid window region and the second reflection signal from the non-grid window region represent the temporal variation of the light reflection intensity from the two different surface structures, respectively. Taking the camera's annular area as an example, the reflectivity of the grid window region is approximately 0.62 (corresponding to a steel-based material), while the reflectivity of the non-grid window region is approximately 0.38 (corresponding to a silicon oxide-ITO composite structure). The reflected signal is received by a photodetector, converted into an electrical signal, and sampled and stored at 10GS / s. A wavelength of 235 nanometers was chosen for its high sensitivity to organic thin films while avoiding the plasma resonance frequency of the mold material, reducing thermal interference and improving the signal-to-noise ratio. At this wavelength, a 100-nanometer-thick organic contamination film can cause a reflectivity change of approximately 8%, far exceeding the system's 0.5% detection accuracy. The entire detection process is integrated into the injection molding machine's normal pressure holding phase, taking only 0.05 seconds. This process does not extend the standard injection molding cycle (typically 15-25 seconds) and has no impact on production efficiency.

[0038] When performing time-domain analysis on the first reflection signal, a high-speed digital signal processor performs time-domain integration and Fourier transform on the sampled data. Time-domain analysis refers to the analysis of the signal's temporal characteristics. The baseline reflection intensity refers to the standard light intensity value reflected from a clean mold surface, serving as a reference standard. The combined reflection intensity refers to the composite light intensity value reflected from the multilayer structure surface. The processing flow is as follows: First, the sampled signal is subjected to a 100MHz high-pass filter to remove ambient light interference. It is then integrated over a 50 nanosecond time window to obtain the total energy value. The time-domain integral of the first reflection signal in the grid window area is divided by a calibration factor (the inverse of the integral of the reflection signal from the clean mold surface) to obtain the baseline reflection intensity of the decontaminated mold surface. Similarly, the second reflection signal from the non-grid window area is processed to obtain the combined reflection intensity of the silicon oxide layer and the passivating conductive thin layer. For example, for a flat surface, the baseline reflection intensity is 1.00, and the combined reflection intensity in an uncontaminated state is approximately 0.61. When the surface is contaminated with 100 nanometers of organic contamination, the baseline reflection intensity drops to 0.92, and the combined reflection intensity drops to 0.56. Time-domain analysis isolates the reflection characteristics of different structures, eliminating the effects of time delay and multiple scattering, and improving measurement accuracy. Data processing is performed in a field-programmable gate array (FPGA) embedded in the mold, with a processing time of just 0.01 seconds. This is performed in parallel with the injection molding process, eliminating the need to occupy the main controller's resources.

[0039] When overlaying and analyzing the baseline reflection intensity and combined reflection intensity, a weighted average algorithm is used to process the data from each sampling point. Overlay analysis refers to the process of combining multiple data sources into a single dataset according to specific rules. Reflection signal intensity data represents a comprehensive numerical value representing the optical properties of the surface. The specific implementation method is to calculate weighting coefficients α and β (α + β = 1) based on the area ratio of the grid window to the non-grid window. For example, for α = 0.2 and β = 0.8 (corresponding to a 20% grid window), the reflection signal intensity data for the electrode area is equal to α × baseline reflection intensity + β × combined reflection intensity. In actual operation, the system calculates the final reflection signal intensity data for multiple sampling points within the electrode area and then takes the average value. For rounded corners, since curvature affects the light reflection angle, the system introduces an angle compensation factor to correct for this. This overlay analysis method comprehensively considers the optical properties of both microstructures, reduces the impact of local inhomogeneities, and improves the representativeness and reliability of the overall detection. The data overlay process is completed within the same FPGA, seamlessly integrating with the previous processing without adding additional time overhead.

[0040] When emitting a second wavelength femtosecond light pulse with a wavelength of 257 nanometers in the lattice window area and the non-lattice window area of the electrode area, respectively, an ultrafast laser system is used for operation. The system parameters are set as follows: wavelength 257±0.5 nanometers, pulse width 300 femtoseconds, repetition rate 1kHz, and single pulse energy 20μJ. The second wavelength femtosecond light pulse refers to an ultrashort laser pulse with a wavelength of 257 nanometers and a pulse width in the femtosecond range. The first acoustic wave signal and the second acoustic wave signal refer to the acoustic response signals generated by the excitation of the light pulse. While emitting the light pulse, the system receives the acoustic wave signal through the piezoelectric sensor array (bandwidth 10MHz) installed around the mold. The femtosecond pulse produces a transient thermoelastic effect on the surface of the material, inducing stress waves to propagate in the material. For a typical mobile phone case mold, the speed of sound waves propagating in steel is about 5900m / s. The sound source position can be calculated by detecting the arrival time of the sound wave (typical value is 10-15 microseconds). The 257-nanometer wavelength was chosen because the femtosecond pulse has a moderate penetration depth (approximately 30 nanometers) at this wavelength, effectively exciting interfacial stress waves without damaging the material surface. This wavelength also complements the 235-nanometer primary detection wavelength, providing material information at varying depths. Photoacoustic and optical reflection testing are performed continuously, taking a total of no more than 0.15 seconds, during the pressure-holding phase of the conventional injection molding process. This eliminates the need for additional downtime or extended production cycles, and has no impact on production tact.

[0041] A dedicated algorithm is executed using a digital signal processor to weight the first and second acoustic wave signals based on the doping concentration of each region. The acoustic phase signal refers to the time delay characteristic of the acoustic wave, and the acoustic amplitude signal refers to the intensity characteristic of the acoustic wave. The specific steps of the weighted processing are as follows: first, the original acoustic wave signal is bandpass filtered from 1 to 8 MHz to extract the effective frequency band. Then, weighting coefficients are set based on the doping concentration of each region: the coefficient for the flat region (first doping concentration) is 1.0, the coefficient for the rounded corner region (second doping concentration) is 0.85, the coefficient for the camera ring region (third doping concentration) is 0.72, and the coefficient for the key slot region (fourth doping concentration) is 0.65. Different doping concentrations affect the acoustic impedance of the material, thereby changing the sound wave propagation characteristics. For example, in the key slot region (doping concentration of 8.5 at%), the sound wave propagation speed is approximately 7% faster than in the flat region (doping concentration of 3.5 at%). This weighted processing compensates for the impact of different material properties on sound wave propagation, making the test results comparable. The weighted signal is subjected to Hilbert transform to separate the phase and amplitude information of the sound wave, and obtain the sound wave phase signal and the sound wave amplitude signal.

[0042] When reconstructing the acoustic phase and amplitude signals based on doping concentration, a multidimensional mapping algorithm is used to process the data. Acoustic phase and amplitude data refers to comprehensive acoustic characteristic data that combines phase and amplitude information. The reconstruction process includes: establishing a correspondence table between doping concentration and acoustic parameters, performing interpolation calculations based on the known doping concentration gradients in each region to obtain a continuous acoustic parameter mapping; inputting the weighted phase and amplitude signals into a mapping function to convert them into standardized acoustic phase and amplitude data. Taking a sampling point in the key slot area as an example, the original phase delay is 2.3μs and the amplitude is 0.78V. After doping concentration mapping, the standardized phase and amplitude data is reconstructed to (1.0, 0.85). The reconstruction process eliminates the influence of material inhomogeneity on measurement, creates a unified evaluation standard, and enables direct comparability of data from different regions and geometries. The reconstruction algorithm is stored as a fixed program in the FPGA, eliminating the need for recompilation each time, ensuring real-time processing capabilities.

[0043] The Beer-Lambert law and Fresnel reflection theory are applied to calculate film thickness data based on the difference between the reflected signal intensity data and the baseline reflected intensity data. Film thickness data refers to the thickness of the surface organic contamination layer. The calculation process is as follows: First, the baseline reflection intensity R0 in the clean state and the currently measured reflected signal intensity data R are obtained; then, the difference between the two, ΔR = R0 - R, is calculated; finally, the corresponding film thickness data is obtained by querying a pre-calibrated ΔR-film thickness comparison table. This comparison table is established through standard sample testing and covers a film thickness range of 0-300 nanometers. In actual application, for a 25-nanometer-thick organic contamination layer, the change in reflection intensity at a wavelength of 235 nanometers is approximately 3.2%. The film thickness data has a resolution of up to 5 nanometers, meeting the requirements for accurate monitoring of submicron-level contaminants. The entire calculation process is completed in parallel during the pressure holding phase, without taking up additional time in the injection molding cycle.

[0044] The acoustic elastic parameter method is used to calculate the interface bonding strength data based on the correspondence between the acoustic wave phase amplitude data and the doping concentration gradient. Interface bonding strength data refers to data that characterizes the adhesion between the contaminant and the substrate. The calculation process is as follows: the acoustic wave propagation time is calculated based on the acoustic wave phase information, and the interface reflection coefficient is analyzed in combination with the acoustic wave amplitude information; the interface acoustic impedance difference is inversely calculated using the acoustic impedance equation combined with the known doping concentration gradient; and finally, the acoustic impedance difference is converted into interface bonding strength data. Taking a flat surface as an example, the standardized bonding strength value of a clean interface is 1.0. When a 100-nanometer organic contamination layer forms on the interface, the bonding strength drops to 0.72. Interface bonding strength data can effectively reflect the adhesion state of contaminants to the mold surface, predict the difficulty of contaminant removal, and provide a decision-making basis for subsequent cleaning plans. All detection and calculation processes are integrated into the injection molding machine control system and take a total time of approximately 0.25 seconds. They are completed during the pressure holding phase of the injection molding cycle, without extending the production cycle or reducing production capacity. Compared with traditional methods that require shutdown and mold removal for inspection, this technology shortens the inspection time from several hours to milliseconds, and can obtain the mold status in real time during each injection cycle, significantly improving production efficiency and product yield.

[0045] Please continue reading Figure 1 , write the film thickness data and interface bonding strength data of the electrode area into the phase change memory unit respectively, record the change value of the film thickness data and the change value of the interface bonding strength data of two adjacent samplings of the electrode area, and judge the degree of contamination of the electrode area according to the cumulative trend of the change value of the film thickness data and the change value of the interface bonding strength data.

[0046] In one embodiment of the present invention, the step of writing the film thickness data and the interface bonding strength data of the electrode region into a phase change memory unit, recording the change values of the film thickness data and the interface bonding strength data of two adjacent samplings of the electrode region, and judging the contamination degree of the electrode region based on the cumulative trend of the change values of the film thickness data and the change values of the interface bonding strength data, comprises: Writing the film thickness data of the electrode region into the first phase-change memory unit, and writing the interface bonding strength data of the electrode region into the second phase-change memory unit; Calculating the difference between the film thickness data of two adjacent samples in the electrode area to obtain a film thickness data change value, and calculating the difference between the interface bonding strength data of two adjacent samples in the electrode area to obtain an interface bonding strength data change value; Accumulating the film thickness data change values to obtain a film thickness cumulative value, and accumulating the interface bonding strength data change values to obtain a strength cumulative value; Determine the contamination rate of the electrode region according to the growth rate of the film thickness cumulative value, and determine the contamination stability of the electrode region according to the growth rate of the intensity cumulative value; The pollution speed is compared with a preset speed threshold, and the pollution stability is compared with a preset stability threshold to obtain the pollution degree of the electrode area.

[0047] The following is a detailed description of the steps involved in the above embodiment: An embedded phase-change memory array control system is used to write the film thickness data of the electrode region into the first phase-change memory cell and the interface bonding strength data of the electrode region into the second phase-change memory cell. A phase-change memory cell is a non-volatile memory device made of phase-change materials such as Ge2Sb2Te5. It records data through phase changes in the material and features fast write speeds, low power consumption, and strong radiation resistance. The first and second phase-change memory cells are two independent phase-change memory arrays, each corresponding one-to-one to the electrode matrix. The system writes data at the end of the pressure-holding phase of the injection molding cycle. The specific steps are: converting the film thickness data into a current signal in an 8-bit precision format. Using an FPGA-controlled drive circuit, a 200mA / 50ns current pulse is applied to the first phase-change memory cell, causing the phase-change material to transition from a high-resistance state to a low-resistance state. Similarly, the interface bonding strength data is written to the second phase-change memory cell. Taking a mold with 64 electrode areas as an example, the phase-change memory array consists of 64 x 2 memory cells, each measuring 10μm x 10μm, integrated on a chip around the outer edge of the mold frame. The writing process is completed during the injection molding machine's operation intervals, without affecting the production cycle. Compared to traditional volatile memory, phase-change memory can retain data even during power outages and adapt to the high-temperature environment of the mold. The inherent memory properties of the material simplify the data accumulation process, reducing the computational burden.

[0048] A real-time differential comparison circuit is used to calculate the difference between the film thickness data of two adjacent samples taken in the electrode region to obtain the film thickness data change value, and to calculate the difference between the interface bonding strength data of two adjacent samples taken in the electrode region to obtain the interface bonding strength data change value. The film thickness data change value refers to the difference between the film thickness data of the current cycle and the previous cycle, and the interface bonding strength data change value refers to the difference between the interface bonding strength data of the current cycle and the previous cycle. The specific implementation method is as follows: at the beginning of a new injection molding cycle, the controller reads the previous cycle film thickness data T(n-1) and the current cycle film thickness data T(n) stored in the first phase-change memory unit, calculates the difference ΔT=T(n)-T(n-1), and obtains the film thickness data change value; similarly, the interface bonding strength data S(n-1) and S(n) in the second phase-change memory unit are read, and the difference ΔS=S(n)-S(n-1) is calculated to obtain the interface bonding strength data change value. For example, if the film thickness data for a planar electrode area in two adjacent injection molding cycles is 15nm and 17nm, respectively, the film thickness change in that area is +2nm; if the interface bonding strength data drops from 0.95 to 0.92, the interface bonding strength change is -0.03. The differential comparison circuit uses a 10-bit comparator with a resolution of 0.1nm and 0.001 unit intensity value, capable of capturing subtle changes. This adjacent cycle differential calculation method eliminates the effects of absolute value drift, improves detection sensitivity, and is particularly suitable for early detection of contaminant growth trends.

[0049] When accumulating the film thickness data change values to obtain the film thickness cumulative value, and accumulating the interface bonding strength data change values to obtain the strength cumulative value, a dedicated accumulator circuit is used for processing. The film thickness cumulative value refers to the sum of the film thickness data change values over multiple consecutive cycles, and the strength cumulative value refers to the sum of the interface bonding strength data change values over multiple consecutive cycles. The processing flow is as follows: First, an independent 64-bit accumulation register is set for each electrode area; after each injection molding cycle, the film thickness data change value ΔT for that cycle is added to the corresponding accumulation register, that is, A(n) = A(n-1) + ΔT, where A represents the film thickness cumulative value; similarly, the interface bonding strength data change value ΔS is added to the corresponding accumulation register, that is, B(n) = B(n-1) + ΔS, where B represents the strength cumulative value. In actual production, the film thickness data for the camera ring area shows changes over 10 consecutive cycles of +1.5nm, +1.8nm, +2.0nm, +2.2nm, +2.5nm, +2.6nm, +2.8nm, +3.0nm, +3.2nm, and +3.5nm, respectively. The accumulated film thickness is +25.1nm, indicating a trend of continued contamination growth in this area. This accumulation process directly reflects the actual accumulation of pollutants at the physical level, avoiding errors caused by complex mathematical models.

[0050] A digital slope analyzer is used to determine the contamination rate of an electrode region based on the growth rate of the accumulated film thickness and the contamination stability of an electrode region based on the growth rate of the accumulated intensity. The contamination rate refers to the increase in film thickness per unit time or cycle, while contamination stability refers to the consistency and persistence of changes in interfacial bonding strength. The determination method is to calculate the linear regression slope K1 of the accumulated film thickness over the most recent N cycles (contamination rate = K1 / N, expressed in nm / cycle); and to calculate the linear regression slope K2 of the accumulated intensity over the most recent N cycles (contamination stability = |K2| / N, expressed in intensity units / cycle). N is typically set to 10 to cover a sufficient sample while maintaining timely response. In actual application, for the functional key slot area, the accumulated film thickness increased from 5.8 nm to 18.3 nm over 10 cycles, resulting in a calculated contamination rate of 1.25 nm / cycle. Over the same period, the accumulated intensity decreased from -0.05 to -0.28, resulting in a calculated contamination stability of 0.023 nm / cycle. Slope analysis uses the least squares method, which offers superior accuracy to traditional moving average methods. It can filter out random fluctuations and reflect true trends. This method distinguishes between the speed and stability of pollution, providing a more comprehensive assessment of pollution status and facilitating targeted interventions.

[0051] A multi-level threshold judgment circuit is used to determine the degree of contamination in the electrode area by comparing the contamination rate with a preset speed threshold and the contamination stability with a preset stability threshold. The contamination level is a comprehensive indicator that characterizes the severity of the surface contamination in the electrode area. The comparison process involves setting differentiated thresholds based on the geometric characteristics and material properties of different areas. For planar areas, the preset speed threshold is 0.8nm / cycle, and the preset stability threshold is 0.015 / cycle. For high-curvature areas such as functional key slots, the preset speed threshold is reduced to 0.6nm / cycle, and the preset stability threshold is increased to 0.020 / cycle. The system uses a digital comparator to compare the actual contamination rate with the preset speed threshold, and the actual contamination stability with the preset stability threshold, generating a binary result matrix. The comparison results are then mapped to contamination level levels based on predefined logical rules: normal (level 1), mild (level 2), moderate (level 3), severe (level 4), and critical (level 5). For example, the measured pollution velocity in a rounded corner area is 0.95nm / cycle, exceeding the preset threshold of 0.7nm / cycle; the measured pollution stability is 0.021 / cycle, exceeding the preset threshold of 0.018 / cycle. The system determines the pollution level in this area as "moderate (Level 3)." The multi-level threshold design accommodates the differences in pollution sensitivity in different areas, improving the accuracy of judgments. Combining the dual indicators of speed and stability, the system can distinguish short-term fluctuations from true trends, reducing the rate of false positives.

[0052] In one embodiment of the present invention, the mobile phone case automated processing method further includes performing pollution suppression processing on the electrode area where the pollution speed is greater than the preset speed threshold and the pollution stability is greater than the preset stability threshold, specifically comprising: Obtaining a growth direction of a film thickness cumulative value in the first phase-change memory unit and a growth direction of an intensity cumulative value in the second phase-change memory unit to determine a contaminant migration trend in the electrode region; applying a reverse bias voltage to the electrode region according to the migration trend of the pollutants to form a potential difference between the lattice window region and the non-lattice window region; The bias voltage is regionally adjusted based on the geometric structure of the electrode area, applying a first type of bias voltage to the plane area, a second type of bias voltage to the rounded corner area, a third type of bias voltage to the camera ring area, and a fourth type of bias voltage to the function key slot area; Performing time-domain modulation on the potential difference to form a first electric field gradient in the lattice window region and a second electric field gradient in the non-lattice window region, wherein the first electric field gradient is greater than the second electric field gradient; The injection pressure parameters of the injection molding process are adjusted according to the distribution of the electric field gradient, and a directional shear flow field is formed at the boundary of the electrode area to guide the pollutants from the grid window area to the non-grid window area.

[0053] The following is a detailed description of the steps involved in the above embodiment: A gradient vector analysis system is used to determine the contaminant migration trend across the electrode region by obtaining the direction of the cumulative film thickness value in the first phase-change memory cell and the direction of the cumulative intensity value in the second phase-change memory cell. The direction of the cumulative film thickness value refers to the spatial distribution trend of the cumulative film thickness value, the direction of the cumulative intensity value refers to the spatial distribution trend of the cumulative interface bonding strength value, and the contaminant migration trend refers to the directional characteristics of the movement and accumulation of organic contaminants on the mold surface. The specific implementation process is as follows: the FPGA controller first reads the cumulative film thickness values of adjacent electrode regions, calculates the film thickness difference between adjacent electrodes, and generates a film thickness gradient vector. Similarly, the difference in the cumulative intensity values between adjacent electrodes is calculated to generate an intensity gradient vector. Then, through vector superposition analysis, the dominant direction and rate of contaminant migration are determined. For example, the average cumulative film thickness value for the eight inner electrode regions is +18.5 nm, while the average for the eight outer electrode regions is +12.3 nm, indicating an inward-to-outward migration trend. Furthermore, the average cumulative intensity value for the inner region is -0.25, while that for the outer region is -0.17, further confirming the inward-to-outward migration trend. This analytical method can detect the macroscopic flow patterns of microscopic pollutants, providing directional guidance for subsequent precise intervention. In the early stages of pollution, migration trend information can better reflect the essence of the problem than a single cumulative value, helping to identify the pollution source and prevent its spread.

[0054] A multi-channel, high-precision voltage source system is used to apply a reverse bias voltage to the electrode region based on the contaminant migration trend, forming a potential difference between the grid window region and the non-grid window region. A reverse bias voltage refers to the application of voltage in the opposite direction of contaminant migration, and a potential difference refers to the potential difference between the two regions. The operating process is as follows: Based on the direction vector of the contaminant migration trend, the voltage source controller calculates the direction of the electric field to be applied; then, a DC bias voltage in the range of 3-5V is applied to the electrode region through a precision low-noise D / A converter, with the voltage polarity opposite to the direction of contaminant migration; at the same time, a potential difference of 0.5-1.0V is ensured between the grid window region and the non-grid window region. Taking the function key slot area as an example, when the contaminant migration trend from the slot bottom to the slot wall is detected, the system applies a +3.5V voltage to the slot bottom electrode and a +4.2V voltage to the slot wall electrode, forming a reverse electric field with a potential difference of 0.7V. The voltage range is set at 3-5V because it generates a sufficiently strong electrophoretic force without causing an electrolytic reaction. The potential difference is controlled at 0.5-1.0V to form a moderate electric field gradient to guide the directional migration of low-molecular substances. This reverse electric field effect causes the slightly charged low-molecular softeners and degradation products to be affected by the electrophoretic force, moving them against their original migration direction, reducing their accumulation in key areas and effectively slowing the formation of fouling films.

[0055] A geometrically adaptive voltage control system is used to adjust the bias voltage regionally based on the electrode geometry. The first, second, third, and fourth bias voltages are specific voltage parameter combinations adapted to specific geometrically defined regions. The specific adjustment method is as follows: a standard first bias voltage of 4.0V and a 40% duty cycle is applied to planar regions; a gradient second bias voltage of 3.5V and a 35% duty cycle is applied to rounded corners; a circumferentially distributed third bias voltage of 4.5V and a 45% duty cycle is applied to the camera ring region; and a pulse-modulated fourth bias voltage of 5.0V and a 30% duty cycle is applied to the key slot region. The parameter settings for different regions take into account the impact of geometry on the electric field distribution. For example, in rounded corners, where greater curvature leads to more pronounced field attenuation, a lower voltage and duty cycle are used to prevent excessive current concentration. In complex geometries, such as key slots, a higher voltage and lower duty cycle pulse method is used to avoid local overheating caused by sustained high voltage. Taking the actual production of mobile phone case mold as an example, the back plate plane area is about 120cm 2 After applying the first type of bias voltage, the migration speed of pollutants slowed down by about 65%; while the keyway area (area of about 2cm 2 After applying the fourth type of bias voltage, the contaminant migration rate slowed by approximately 85%. This regionalized voltage regulation strategy makes the electric field distribution more uniform, avoids electric field distortion in areas with varying curvature, improves electrophoresis efficiency, and minimizes the impact on mold and injection molding material properties.

[0056] When performing time-domain modulation of the potential difference, a digital pulse width modulator (PWM) is used. The first electric field gradient refers to the rate of change of the electric field intensity within the grid window region, while the second electric field gradient refers to the rate of change of the electric field intensity within the non-grid window region. Specifically, a high-precision timer generates a carrier signal with a fundamental frequency of 1kHz, and a digital pulse width modulator controls the voltage waveform and phase in different regions. A steep pulse with a rise time of 5μs is applied to the grid window region, creating a first electric field gradient with an average gradient of 0.8V / μm. A gentle pulse with a rise time of 15μs is applied to the non-grid window region, creating a second electric field gradient with an average gradient of 0.3V / μm. Time-domain modulation is a technique for controlling the electric field distribution through voltage variations in the time dimension. For example, within the camera's circular area, the pulse peak value is 4.8V in the inner grid window region, while the pulse peak value is 3.9V in the outer non-grid window region. The phase difference between the two is controlled at 60°, creating an inward-outward electric field fluctuation that effectively guides the directional migration of pollutants. The purpose of setting the first electric field gradient greater than the second electric field gradient is to create a stronger electrophoretic driving force in the grid window area and a relatively weaker resistance in the non-grid window area. This gradient difference creates a "channel" for the directional migration of contaminants, improving electrophoresis efficiency. Time-domain modulation also avoids material polarization and electrochemical reactions that can be caused by continuous DC voltage, reducing interference with the properties of the injection molding resin.

[0057] The adaptive injection molding control system is used to adjust the injection pressure parameters of the injection molding process according to the distribution of the electric field gradient. The directional shear flow field refers to the material flow shear area with a specific direction formed at the boundary of the electrode area. The operation process is as follows: the injection pressure control system receives the electric field gradient distribution data and calculates the optimal injection pressure curve through an algorithm; when a high contamination risk area is detected, the system superimposes a 1.5% peak pressure increase at the end of the injection pressure curve, so that the local shear rate increases from 2.0×10 3 s -1 Increased to 2.3×10 3 s -1The system also adjusts the pressure differential based on regional geometric characteristics: the boost duration is 0.3 seconds for flat surfaces, 0.2 seconds for rounded corners, 0.25 seconds for the camera ring, and 0.15 seconds for the keyway. For example, when contamination risk arises on the flat surface of the backplate, the injection molding machine's original shot pressure curve peaks at 80 MPa. At the end of the holding phase, the system automatically increases the pressure to 81.2 MPa and maintains it for 0.3 seconds, creating a localized high shear zone. For the high-curvature keyway, the boost amplitude is reduced to 0.8% and the duration is shortened to 0.15 seconds to prevent melt tearing. Precise control of the shot pressure parameters creates a flow field effect that synergizes with the electric field gradient, generating directional shear forces at the electrode boundary. This high-speed wall-attached flow further reduces the concentration of organic molecules in the mirror boundary layer. The combined effects of electric field drive and flow shear force drive contaminants from the grid window region (critical for optical inspection) to the non-grid window region, significantly shortening the contaminant accumulation period. Furthermore, since the operation is performed only within a short time window, it does not adversely affect the overall part quality.

[0058] In one embodiment of the present invention, the automated processing method for mobile phone cases further includes performing Rayleigh wave cleaning on the electrode area after the directional shear flow field continues to act for more than a preset time, specifically comprising: Acquiring a film thickness accumulation value and an intensity accumulation value in the first phase-change memory unit and the second phase-change memory unit, and setting cleaning parameters for the electrode region according to the film thickness accumulation value and the intensity accumulation value; emitting a Rayleigh wave of a first frequency toward a lattice window region of the electrode region, and emitting a Rayleigh wave of a second frequency toward a non-lattice window region of the electrode region, wherein the first frequency is greater than the second frequency; The propagation direction of the Rayleigh wave is adjusted according to the geometric structure of the electrode area, forming traveling wave propagation in the plane area, forming standing wave resonance in the rounded corner area, forming a ring wave in the camera ring area, and forming a focusing wave in the function key slot area; Spraying a low surface tension liquid into the electrode region in an atomized state, wherein the low surface tension liquid forms different spreading coefficients in the grid window region and the non-grid window region; Writing the frequency parameter, propagation direction parameter of the Rayleigh wave and the spreading coefficient of the low surface tension liquid into the first phase change storage unit and the second phase change storage unit for setting the next round of cleaning parameters; The film thickness accumulation value and the intensity accumulation value in the first phase-change memory unit and the second phase-change memory unit are reset.

[0059] The following is a detailed description of the steps involved in the above embodiment: The film thickness cumulative value and intensity cumulative value in the first phase change storage unit and the second phase change storage unit are obtained, and when the cleaning parameters of the electrode area are set according to the film thickness cumulative value and the intensity cumulative value, an adaptive parameter optimization system is used. Cleaning parameter setting refers to the process of determining the values of various parameters of the cleaning process according to the characteristics of the pollutants. The specific implementation is: the controller first reads the film thickness cumulative value data matrix of each electrode area in the first phase change storage unit and the intensity cumulative value data matrix in the second phase change storage unit through a dedicated data bus; then, by querying the preset parameter mapping table, the corresponding cleaning parameters are allocated for different numerical intervals. Taking the camera annular area as an example, when the film thickness cumulative value reaches 45nm and the intensity cumulative value reaches -0.35, the system automatically sets the Rayleigh wave frequency to 4.2MHz, the pulse width to 0.3ms, and the power density to 2.5W / cm 2 . The parameter setting follows the zoning strategy. For areas with cumulative film thickness greater than 30nm, the enhanced cleaning parameter group is used. For areas with 15-30nm, the standard cleaning parameter group is used. For areas less than 15nm, the maintenance parameter group is used. At the same time, the intensity accumulation value is used to adjust the cleaning time. The lower the value, the stronger the interface bonding, and the action time needs to be increased. This parameter adaptive adjustment method based on measured pollution data accurately matches the cleaning intensity with the degree of pollution, avoids damage to the mold surface due to excessive cleaning, and prevents efficiency reduction caused by insufficient cleaning. The entire parameter setting process is completed in the ejector pin reset window and does not occupy the effective time of the injection molding cycle.

[0060] When emitting Rayleigh waves of the first frequency to the lattice window area of the electrode area and emitting Rayleigh waves of the second frequency to the non-lattice window area of the electrode area, a distributed piezoelectric transducer array system is used. Rayleigh waves are a special type of surface acoustic wave that propagates along the surface of a solid. The energy is mainly concentrated within a wavelength depth range near the surface and has an elliptical particle displacement trajectory characteristic perpendicular to the propagation direction. The first frequency and the second frequency refer to the Rayleigh wave vibration frequencies used in different areas. The implementation method is as follows: a strip PZT (lead zirconate titanate) piezoelectric transducer with a thickness of 12μm is embedded in the mold parting surface, and each electrode area corresponds to 4-8 independently controlled transducer units; a high-frequency driving signal with a center frequency of 4.2MHz is applied to the transducer in the lattice window area to generate a first-frequency Rayleigh wave; a driving signal with a center frequency of 3.5MHz is applied to the transducer in the non-lattice window area to generate a second-frequency Rayleigh wave. Taking a functional key slot area as an example, the frequency of the Rayleigh wave at the lattice window is 4.5MHz, and the amplitude is 0.6μm; the frequency at the non-lattice window is 3.8MHz, and the amplitude is 0.4μm. The design of the first frequency being greater than the second frequency enables the lattice window area to obtain a stronger acoustic energy density. The first frequency is selected in the range of 4.0-4.5MHz because the penetration depth of the Rayleigh wave on the steel surface at this frequency is about 100-150nm, which matches the thickness of the organic contamination film and can effectively produce a cavitation effect at the membrane-substrate interface; the second frequency is selected in the range of 3.5-3.8MHz to form an auxiliary cleaning force in the non-lattice window area, while avoiding damage to the conductive thin layer by excessively strong sound fields. This partitioned frequency design greatly improves cleaning efficiency and selectivity, enabling the lattice window area to obtain a more thorough cleaning effect while protecting the sensitive functional membrane layer structure. It is worth noting that the selected Rayleigh wave frequency range and amplitude parameters have been precisely calculated to ensure that the silicon oxide layer and conductive thin layer on the mold surface are not damaged. The bonding strength of these functional layers (>200MPa) is much higher than the shear stress (<25MPa) generated by the Rayleigh wave under these parameters. Therefore, the cleaning process will not cause delamination or performance changes of the detection structure.

[0061] A phase-controlled ultrasonic focusing system is used to adjust the propagation direction of Rayleigh waves based on the geometric structure of the electrode area. Traveling wave propagation refers to the wave form in which Rayleigh wave energy propagates in a single direction; standing wave resonance refers to the fixed waveform pattern formed by the superposition of incident Rayleigh waves and reflected waves; ring waves refer to Rayleigh waves that propagate along a circular path; and focused waves refer to Rayleigh waves whose energy converges toward a specific point. The specific adjustment method involves precisely controlling the excitation phase of each piezoelectric transducer unit through a multi-channel digital signal processor. In planar areas, the excitation phase difference between adjacent transducers is set to 90°, forming a unidirectional traveling wave whose propagation direction aligns with the direction of contaminant migration. In rounded corners, the relative transducer phase is set to 180°, forming a standing wave resonance, generating a sound pressure node at the center of the corner's curvature. In the camera ring area, the transducers are evenly distributed along the circumference, with the phase varying linearly with the ring's position, forming a ring wave that propagates radially along the ring. In the function key slot area, the phases of multiple transducers are set to a focused distribution, converging the wave energy toward the slot center, forming a focused wave. Taking the camera ring area as an example, 12 transducer units are evenly distributed along the ring, with a phase difference of 30° between adjacent units, forming a stable ring wave field. The cleaning efficiency is about 40% higher than that of single-direction propagation. The design of different propagation directions adapts to the geometric characteristics of each area. The traveling waves in the plane area can efficiently remove large-area pollution; the standing wave resonance in the rounded corner area enhances the cleaning effect of the curvature area that is difficult to directly contact; the ring wave and the focused wave are respectively targeted at the special needs of the ring structure and the narrow slot structure, ensuring that the sound energy is evenly distributed or directionally concentrated. This geometrically adaptive sound field design significantly improves the comprehensiveness and uniformity of cleaning. It is particularly important to note that the design of the wave propagation mode fully considers the integrity protection of the mold surface detection structure. For example, at the junction of the grid window area and the conductive thin layer, the wave field intensity is designed to be gradually distributed to avoid the risk of interface delamination caused by stress concentration.

[0062] When spraying low surface tension liquid into the electrode area in an atomized state, a precision pulse spray system is used. Low surface tension liquid refers to a special solvent with a surface tension value lower than that of water, usually a fluoroether environmentally friendly solvent; the spreading coefficient refers to an index of the diffusion ability of the liquid on the solid surface. The implementation method is: through the micro-atomizing nozzle installed at the exhaust hole, while under the action of Rayleigh waves, the fluoroether solvent with a boiling point of 20°C and a surface tension of 12mN / m is sprayed into the mold cavity in a micro-mist state with a particle size of 30μm; the liquid injection pressure is controlled at 0.3MPa, and the injection duration is 0.2 seconds. In different areas, the droplet distribution density is controlled by adjusting the nozzle angle and flow rate; the droplet density in the grid window area is 600±50 drops / cm 2 , the non-grid window area is 400±50 drops / cm 2Taking a planar electrode area as an example, the liquid spreading coefficient at the grid window is 2.8, and at the non-grid window is 1.9. The difference in spreading coefficient comes from the difference in surface structure and material. The reason for choosing a low surface tension liquid with a surface tension of 12mN / m is that this value is lower than the adhesion threshold of most organic pollutants and the mold interface (about 15-20mN / m), which can penetrate between the contamination layer and the substrate and weaken the adhesion; at the same time, the boiling point of 20°C is selected to ensure that the liquid vaporizes rapidly at the mold operating temperature (usually 80-120°C) without leaving any residue. This super-wetting liquid works synergistically with Rayleigh waves. While the sound waves cause interfacial cavitation, the liquid quickly spreads and rolls away from the loosened contamination layer, forming an efficient cleaning mechanism of "acoustic-liquid dual activation". Importantly, the selected fluoroether solvent is chemically inert to the silicon oxide layer and the ITO conductive thin layer, and will not cause corrosion or dissolution of the material. At the same time, its volatility ensures that no residue is left on the surface of the functional layer, ensuring the performance stability of the detection structure.

[0063] A parameter feedback storage system is used to write the Rayleigh wave frequency parameters, propagation direction parameters, and spreading coefficient of the low-surface-tension liquid into the first and second phase-change memory cells. The propagation direction parameter refers to a set of numerical values that control the propagation direction of the Rayleigh wave, while the spreading coefficient is a quantitative indicator of the liquid's ability to diffuse on a solid surface. Specifically, during the cleaning process, embedded sensors collect the actual Rayleigh wave frequency, propagation direction, and liquid spreading in real time. After data acquisition, the analog signals are converted to digital data using a high-speed data converter and integrated into a parameter data packet according to a predetermined format. These parameters are then written into specific areas of the phase-change memory cells via an FPGA controller. The frequency and propagation direction parameters are stored in the high-order segment of the first phase-change memory cell, while the spreading coefficient is stored in the high-order segment of the second phase-change memory cell. For the keyway area, the system recorded the optimal cleaning frequency during the actual cleaning process to be 4.3 MHz, the best cleaning effect when the focus offset was 2°, and the strongest synergy with the acoustic wave when the liquid spreading coefficient was 2.5. These data are used to optimize the parameters for the next cleaning cycle. The parameter recording and storage mechanism enables the cleaning system to self-learn. Each cleaning session provides a reference for the next, continuously optimizing system performance with increasing use. The non-volatile nature of phase-change storage media ensures that these optimized parameters are retained even after a power outage or system reset, ensuring long-term stable operation.

[0064] Selective data clearing is used to reset the accumulated film thickness and intensity values in the first and second phase-change memory cells. Resetting refers to restoring the values in a specific memory cell to their initial state. The process is as follows: After cleaning is complete, the control system first verifies the cleaning effect by performing a rapid scan of the cleaned electrode area. If the test results indicate that the contaminants have been effectively removed (the reflection intensity in the grid window area has returned to above 95% of the baseline value), a specific reset command is sent to the phase-change memory cell. This reset command resets the accumulated film thickness and intensity values within the memory cell by writing a predetermined current pattern (typically a pulse sequence of 150mA / 100ns), which returns the phase-change material from a low-resistance state to a high-resistance state. For example, in the backplane area, the accumulated film thickness value before cleaning was +38.5nm, and the accumulated intensity value was -0.42. After effective cleaning, the system automatically resets these values to 0 and 0, while retaining the data in the parameter-optimized area. This reset mechanism ensures that the monitoring system maintains high sensitivity to new contamination, avoiding biased judgments caused by the accumulation of historical data. Furthermore, the selective reset only clears contamination records, retaining parameter optimization data. This differentiated approach ensures the system's responsiveness to new contamination while preserving historical cleaning experience, continuously improving overall system performance. The entire reset process is completed within 0.1 seconds, without affecting the mold's normal operating cycle. It's worth noting that cleaning effectiveness verification utilizes the same optical and acoustic methods as the original inspection system. By comparing signal characteristics before and after cleaning, the structural performance of the functional layer remains stable.

[0065] The above describes the automatic processing method of the mobile phone case in the embodiment of the present invention. The following describes the automatic processing device of the mobile phone case in the embodiment of the present invention. Figure 2 In one embodiment of the present invention, an automatic processing device for mobile phone cases includes: Functionalized interface preparation module 101 is used to deposit a first oxide thin layer on the surface of the mold cavity, form regularly distributed lattice windows on the first oxide thin layer, deposit a conductive thin layer on the lattice window region and non-lattice window region of the first oxide thin layer, passivate the surface of the conductive thin layer to obtain a passivated conductive thin layer, and divide the passivated conductive thin layer into multiple electrode regions; a dual-modal detection module 102 for performing dual-modal detection on the electrode region, including emitting a rectangular light pulse of a first wavelength and obtaining reflected signal intensity data, emitting a femtosecond light pulse of a second wavelength and obtaining acoustic wave phase amplitude data, and obtaining film thickness data and interface bonding strength data of the electrode region based on the reflected signal intensity data and the acoustic wave phase amplitude data; The data processing module 103 is used to write the film thickness data and the interface bonding strength data of the electrode area into the phase change storage unit respectively, record the change value of the film thickness data and the change value of the interface bonding strength data of two adjacent samples of the electrode area, and judge the degree of contamination of the electrode area according to the cumulative trend of the change value of the film thickness data and the change value of the interface bonding strength data.

[0066] above Figure 2 The mobile phone case automated processing device in the embodiment of the present invention is described in detail from the perspective of modular functional entities. The mobile phone case automated processing equipment in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0067] Figure 3 The figure is a schematic diagram of the structure of an automated mobile phone case processing device provided by an embodiment of the present invention. The automated mobile phone case processing device 200 may vary significantly depending on its configuration or performance. It may include one or more processors 210 (e.g., one or more processors), memory 220, and one or more storage media 230 (e.g., one or more mass storage devices) storing application programs 233 or data 232. The memory 220 and storage medium 230 may be either transient or persistent storage. The program stored in the storage medium 230 may include one or more modules (not shown), each of which may include a series of instructions for the automated mobile phone case processing device 200. Furthermore, the processor 210 may be configured to communicate with the storage medium 230, executing the series of instructions stored in the storage medium 230 on the automated mobile phone case processing device 200 to implement the steps of the automated mobile phone case processing method described above.

[0068] The mobile phone case automated processing equipment 200 may further include one or more power supplies 240, one or more wired or wireless network interfaces 250, one or more input and output interfaces 260, and / or one or more operating systems 231, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc. It will be understood by those skilled in the art that Figure 3 The structure of the mobile phone case automated processing equipment shown does not constitute a limitation on the mobile phone case automated processing equipment provided by the present invention, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0069] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. The computer-readable storage medium stores instructions. When the instructions are run on a computer, the computer executes the steps of the mobile phone case automated processing method.

[0070] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0071] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0072] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. All equivalent structural transformations made by using the contents of the present invention description and drawings under the inventive concept of the present invention, or direct / indirect application in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. A method for automatically processing a mobile phone case, characterized in that: include: Depositing a first oxide thin layer on the surface of the mold cavity, forming regularly distributed lattice windows on the first oxide thin layer, depositing a conductive thin layer on the lattice window region and the non-lattice window region of the first oxide thin layer, passivating the surface of the conductive thin layer to obtain a passivated conductive thin layer, and dividing the passivated conductive thin layer into a plurality of electrode regions; Performing dual-modal detection on the electrode region, including emitting a rectangular light pulse of a first wavelength and obtaining reflected signal intensity data, emitting a femtosecond light pulse of a second wavelength and obtaining acoustic wave phase amplitude data, and obtaining film thickness data and interface bonding strength data of the electrode region based on the reflected signal intensity data and the acoustic wave phase amplitude data; The film thickness data and interface bonding strength data of the electrode area are written into the phase change memory unit respectively, and the change values of the film thickness data and the interface bonding strength data of two adjacent samplings of the electrode area are recorded. The degree of contamination of the electrode area is judged according to the cumulative trend of the change values of the film thickness data and the change values of the interface bonding strength data.

2. The mobile phone case automated processing method according to claim 1, characterized in that: The method comprises depositing a first oxide thin layer on the surface of the mold cavity, forming regularly distributed lattice windows on the first oxide thin layer, depositing a conductive thin layer on the lattice window region and the non-lattice window region of the first oxide thin layer, passivating the surface of the conductive thin layer to obtain a passivated conductive thin layer, and dividing the passivated conductive thin layer into a plurality of electrode regions, including: Treating the mold cavity surface with a decontamination gas, and depositing a silicon oxide layer having a thickness within the peak-to-valley range of the original roughness of the mold on the decontaminated mold surface as a first oxide thin layer; The silicon oxide layer is regionally etched according to the geometric structure of the mold cavity surface, forming lattice window structures with different distribution forms in the plane, fillet, camera ring and function key slot areas, respectively. The depth of the lattice window structure extends to the decontaminated mold surface, and the unetched area of the silicon oxide layer constitutes a non-lattice window area; Depositing a transparent conductive oxide layer with uniform thickness as a conductive thin layer on the non-lattice window area and the bottom of the lattice window, wherein the thickness of the transparent conductive oxide layer is less than the thickness of the silicon oxide layer; Passivating the surface of the transparent conductive oxide layer to obtain a passivated conductive thin layer with a surface contact angle of 90 degrees; The passivated conductive thin layer is divided into electrode regions adapted to the geometric structure of the mold surface, and the areas of adjacent electrode regions are distributed in a gradient as the curvature changes.

3. The automated processing method for mobile phone cases according to claim 2, characterized in that: The method comprises depositing a transparent conductive oxide layer with uniform thickness as a conductive thin layer on the non-lattice window area and the bottom of the lattice window, wherein the thickness of the transparent conductive oxide layer is less than the thickness of the silicon oxide layer, comprising: Depositing a first transparent indium tin oxide layer in the non-lattice window region and at the bottom of the lattice window, wherein the thickness of the first transparent indium tin oxide layer in the non-lattice window region and at the bottom of the lattice window is consistent, and the thickness of the first transparent indium tin oxide layer on the peripheral wall of the lattice window gradually decreases from the bottom to the opening; Doping the first transparent indium tin oxide layer with indium to form a first doping concentration in the planar area, a second doping concentration in the rounded corner area, a third doping concentration in the camera ring area, a fourth doping concentration in the function key slot area, and a fifth doping concentration in the lattice window peripheral wall area, wherein the second doping concentration is greater than the first doping concentration, the third doping concentration is greater than the second doping concentration, the fourth doping concentration is greater than the third doping concentration, and the fifth doping concentration gradually increases from the bottom toward the opening on the peripheral wall; A second transparent indium tin oxide layer is deposited on the surface of the first transparent indium tin oxide layer. The second transparent indium tin oxide layer has the same thickness in the non-lattice window area and the bottom of the lattice window, and gradually increases in thickness from the bottom to the opening on the peripheral wall of the lattice window. The total thickness of the second transparent indium tin oxide layer and the first transparent indium tin oxide layer is less than the thickness of the silicon oxide layer, and the resistivity of the second transparent indium tin oxide layer is less than the resistivity of the first transparent indium tin oxide layer.

4. The automated processing method for mobile phone cases according to claim 3, characterized in that: The dual-modal detection of the electrode region includes emitting a rectangular light pulse of a first wavelength and obtaining reflected signal intensity data, emitting a femtosecond light pulse of a second wavelength and obtaining acoustic wave phase amplitude data, and obtaining film thickness data and interface bonding strength data of the electrode region based on the reflected signal intensity data and the acoustic wave phase amplitude data, including: emitting a first rectangular light pulse with a wavelength of 235 nanometers to the lattice window region and the non-lattice window region of the electrode region, respectively, to obtain a first reflection signal from the lattice window region and a second reflection signal from the non-lattice window region; Performing a time domain analysis on the first reflection signal to obtain a reference reflection intensity of the mold surface after decontamination, and performing a time domain analysis on the second reflection signal to obtain a combined reflection intensity of the silicon oxide layer and the passivation conductive thin layer; Superimposing and analyzing the reference reflection intensity and the combined reflection intensity to obtain reflection signal intensity data of the electrode area; emitting a second wavelength femtosecond light pulse of 257 nanometers to the lattice window region and the non-lattice window region of the electrode region, respectively, to obtain a first acoustic wave signal from the lattice window region and a second acoustic wave signal from the non-lattice window region; Performing weighted processing on the first acoustic wave signal and the second acoustic wave signal according to the first doping concentration, the second doping concentration, the third doping concentration, and the fourth doping concentration of each region to obtain an acoustic wave phase signal and an acoustic wave amplitude signal of the electrode region; Reconstructing the acoustic wave phase signal and the acoustic wave amplitude signal according to the doping concentration to obtain acoustic wave phase and amplitude data of the electrode region; Calculating film thickness data of the electrode region according to a difference between the reflection signal intensity data and the reference reflection intensity; The interface bonding strength data of the electrode region is calculated according to the corresponding relationship between the acoustic wave phase amplitude data and the doping concentration gradient.

5. The automated processing method for mobile phone cases according to claim 1, characterized in that: Writing the film thickness data and the interface bonding strength data of the electrode region into a phase change memory unit respectively, recording the change values of the film thickness data and the interface bonding strength data of two adjacent samplings of the electrode region, and judging the contamination degree of the electrode region according to the cumulative trend of the change values of the film thickness data and the change values of the interface bonding strength data, includes: Writing the film thickness data of the electrode region into the first phase-change memory unit, and writing the interface bonding strength data of the electrode region into the second phase-change memory unit; Calculating the difference between the film thickness data of two adjacent samples in the electrode area to obtain a film thickness data change value, and calculating the difference between the interface bonding strength data of two adjacent samples in the electrode area to obtain an interface bonding strength data change value; Accumulating the film thickness data change values to obtain a film thickness cumulative value, and accumulating the interface bonding strength data change values to obtain a strength cumulative value; Determine the contamination rate of the electrode region according to the growth rate of the film thickness cumulative value, and determine the contamination stability of the electrode region according to the growth rate of the intensity cumulative value; The pollution speed is compared with a preset speed threshold, and the pollution stability is compared with a preset stability threshold to obtain the pollution degree of the electrode area.

6. The automated processing method for mobile phone cases according to claim 5, characterized in that: The mobile phone case automated processing method further includes performing pollution suppression processing on the electrode area where the pollution speed is greater than the preset speed threshold and the pollution stability is greater than the preset stability threshold, specifically including: Obtaining a growth direction of a film thickness cumulative value in the first phase-change memory unit and a growth direction of an intensity cumulative value in the second phase-change memory unit to determine a contaminant migration trend in the electrode region; applying a reverse bias voltage to the electrode region according to the migration trend of the pollutants to form a potential difference between the lattice window region and the non-lattice window region; The bias voltage is regionally adjusted based on the geometric structure of the electrode area, applying a first type of bias voltage to the plane area, a second type of bias voltage to the rounded corner area, a third type of bias voltage to the camera ring area, and a fourth type of bias voltage to the function key slot area; Performing time-domain modulation on the potential difference to form a first electric field gradient in the lattice window region and a second electric field gradient in the non-lattice window region, wherein the first electric field gradient is greater than the second electric field gradient; The injection pressure parameters of the injection molding process are adjusted according to the distribution of the electric field gradient, and a directional shear flow field is formed at the boundary of the electrode area to guide the pollutants from the grid window area to the non-grid window area.

7. The automated processing method for mobile phone cases according to claim 6, characterized in that: The automated processing method for mobile phone cases further includes performing Rayleigh wave cleaning on the electrode area after the directional shear flow field continues to act for more than a preset time, specifically comprising: Acquiring a film thickness accumulation value and an intensity accumulation value in the first phase-change memory unit and the second phase-change memory unit, and setting cleaning parameters for the electrode region according to the film thickness accumulation value and the intensity accumulation value; emitting a Rayleigh wave of a first frequency toward a lattice window region of the electrode region, and emitting a Rayleigh wave of a second frequency toward a non-lattice window region of the electrode region, wherein the first frequency is greater than the second frequency; The propagation direction of the Rayleigh wave is adjusted according to the geometric structure of the electrode area, forming traveling wave propagation in the plane area, forming standing wave resonance in the rounded corner area, forming a ring wave in the camera ring area, and forming a focusing wave in the function key slot area; Spraying a low surface tension liquid into the electrode region in an atomized state, wherein the low surface tension liquid forms different spreading coefficients in the grid window region and the non-grid window region; Writing the frequency parameter, propagation direction parameter of the Rayleigh wave and the spreading coefficient of the low surface tension liquid into the first phase change storage unit and the second phase change storage unit for setting the next round of cleaning parameters; The film thickness accumulation value and the intensity accumulation value in the first phase-change memory unit and the second phase-change memory unit are reset.

8. A mobile phone case automatic processing device, characterized in that: The mobile phone case automated processing device adopts the mobile phone case automated processing method according to any one of claims 1 to 7, and the mobile phone case automated processing device comprises: a functionalized interface preparation module, configured to deposit a first oxide thin layer on the surface of the mold cavity, form regularly distributed lattice windows on the first oxide thin layer, deposit a conductive thin layer on the lattice window regions and non-lattice window regions of the first oxide thin layer, passivate the surface of the conductive thin layer to obtain a passivated conductive thin layer, and divide the passivated conductive thin layer into a plurality of electrode regions; a dual-modal detection module for performing dual-modal detection on the electrode region, comprising emitting a rectangular light pulse of a first wavelength and obtaining reflected signal intensity data, emitting a femtosecond light pulse of a second wavelength and obtaining acoustic wave phase amplitude data, and obtaining film thickness data and interface bonding strength data of the electrode region based on the reflected signal intensity data and the acoustic wave phase amplitude data; A data processing module is used to write the film thickness data and interface bonding strength data of the electrode area into the phase change storage unit respectively, record the change value of the film thickness data and the change value of the interface bonding strength data of two adjacent samples of the electrode area, and judge the degree of contamination of the electrode area according to the cumulative trend of the change value of the film thickness data and the change value of the interface bonding strength data.

9. An automated processing equipment for mobile phone cases, characterized in that: The mobile phone case automated processing equipment includes: a memory and at least one processor, wherein the memory stores instructions; The at least one processor calls the instructions in the memory to enable the mobile phone case automated processing equipment to perform the steps of the mobile phone case automated processing method according to any one of claims 1 to 7.

10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the steps of the automatic processing method for mobile phone cases according to any one of claims 1 to 7 are implemented.

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