High-precision household appliance shell injection molding process

Abstract

The invention relates to the technical field of injection molding processes, in particular to a high-precision household appliance shell injection molding process. Comprising the following steps: carrying out in-situ modification pretreatment on a nano composite material; designing a self-adaptive mold based on the shrinkage cloud picture; controlling high-frequency pulse temperature change; multi-stage feedback pressure maintaining is controlled; carrying out stress guide ejection; carrying out online holographic scanning quality inspection; and performing plasma activated self-coloring. According to the technology, through collaborative innovation of materials, molds, processes and detection, traditional limitation is broken through, the materials are endowed with the homogeneous shrinkage characteristic through the nanometer in-situ modification technology, deformation is counteracted in real time in combination with a dynamic compensation mold, and dimensional deviation is restrained from the source; millisecond-level variable temperature control and multi-level feedback pressure maintaining form accurate cooperation of a thermal field, and weld mark and sink mark defects are thoroughly eliminated; micron-sized three-dimensional deformation real-time diagnosis is achieved through online holographic scanning, and mold parameter self-optimization is driven; the plasma activation self-coloring technology replaces high-pollution spraying, and zero-VOC lasting coloring is achieved through the nano capillary effect.

Description

Technical Field

[0001] The present invention relates to the technical field of injection molding technology, in particular to a high-precision injection molding process for household appliance housings. Background Art

[0002] Home appliance housings refer to the external casing components of household appliances such as refrigerators, washing machines, air conditioners, and televisions. They primarily serve three core functions: protecting internal components, supporting the overall structure, and providing decorative appearance. Their design must balance structural strength, dimensional accuracy, surface quality, and assembly compatibility. Traditional manufacturing processes struggle to simultaneously meet the demands of high-precision and low-cost mass production, particularly in the area of large, thin-walled components, where significant technical bottlenecks exist.

[0003] Generally, traditional home appliance housing injection molding uses static molds and fixed process parameters. The process includes raw material drying, injection molding, cooling and shaping, manual trimming and subsequent spraying. This process relies on petrochemical-based plastics. The low mold cooling efficiency leads to a long production cycle. The pressure holding stage cannot dynamically compensate for shrinkage differences, causing warping and internal residual stress. The subsequent spraying process generates a large amount of VOC pollution, and the efficiency of manual quality inspection is low, with a high rate of missed defects. More importantly, there is a lack of closed-loop control mechanisms for problems such as material shrinkage fluctuations and uneven temperature fields, resulting in product size tolerance rates generally exceeding 0.3%, and deformation of large flat areas often exceeding 0.5mm, seriously restricting the appearance quality and assembly accuracy of high-end home appliances.

[0004] Based on this, the present invention provides a high-precision household appliance housing injection molding process to solve the above-mentioned technical problems. Summary of the Invention

[0005] The purpose of the present invention is to provide a high-precision household appliance housing injection molding process to solve the problems raised by the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The present invention proposes a high-precision household appliance housing injection molding process, comprising the following steps:

[0008] S1. In-situ modification pretreatment of nanocomposites;

[0009] S2. Design an adaptive mold based on shrinkage contours;

[0010] S3. Control high-frequency pulse temperature;

[0011] S4. Control multi-level feedback pressure maintenance;

[0012] S5. Stress-guided ejection;

[0013] S6. Perform online holographic scanning quality inspection;

[0014] S7. Perform plasma-activated self-coloring.

[0015] Preferably, the implementation steps of step S1 are:

[0016] S11. The matrix resin and surface-modified nanosilica were fed into a twin-screw extruder with a particle size of 20-30 nm and an addition amount of 1.5 wt %;

[0017] S12. In situ dispersion and interfacial coupling of nanoparticles were performed under temperature segmented control at a screw speed of 200 rpm, a barrel feed section of 160°C, a mixing section of 190°C, and a homogenization section of 180°C;

[0018] S13. Real-time monitoring of melt torque fluctuations and automatic adjustment of screw speed through torque feedback ensures nano-dispersion uniformity with a target range of ±5 N·m and dispersed phase size ≤100 nm.

[0019] Preferably, the implementation steps of step S2 are:

[0020] S21. Import the material dynamic shrinkage measured in step S1 and perform multi-physics coupling simulation based on the product 3D model;

[0021] S22. Preset dynamic compensation cavity during mold design:

[0022] When the measured dynamic shrinkage rate is 0.8-1.2% in the transverse direction and 1.0-1.5% in the longitudinal direction, a piezoelectric ceramic microactuator array with a spacing of 15mm×15mm is embedded in the easily deformed area at the intersection of the reinforcing ribs, and the mold cavity size is expanded by 0.3%-0.7% according to the shrinkage cloud map;

[0023] S23. The cooling water channel adopts a bionic fractal structure, with the main water channel diameter of φ10mm and the branch as low as φ1.5mm, ensuring a distance tolerance of ±0.2mm from the cavity surface.

[0024] Preferably, the implementation steps of step S3 are:

[0025] S31. After the mold is closed, the high-frequency induction heating system is activated to heat the cavity surface to 180°C within 0.8 seconds, with a heating rate of ≥150°C / s.

[0026] S32. When the melt filling is 95% complete, switch to the microchannel nitrogen quenching system and cool to 40°C within 1.5 seconds, with a cooling rate of ≥90°C / s;

[0027] S33. The temperature change process is monitored by an infrared thermal imager, and the surface temperature gradient is controlled within ±3℃ / cm 2 .

[0028] Preferably, the implementation steps of step S4 are:

[0029] S41. Based on the transient temperature field of step S3, perform three-stage dynamic pressure holding:

[0030] S411. Initial pressure holding: 120 MPa for 1.2 seconds, covering the cold start delay period;

[0031] S412. Shrinkage compensation pressure holding: The pressure decreases linearly with temperature to 80 MPa, with a slope of -20 MPa / °C.

[0032] S413. Stress release and pressure maintenance: the pressure is reduced to 20 MPa in steps, with a decrease of 10 MPa every 0.3 seconds;

[0033] S42. The 32-point pressure sensors in the mold provide real-time feedback on melt pressure fluctuations with a sampling frequency of 1 kHz. When the deviation is greater than 5%, the piezoelectric ceramic fine-tuning preset in step S2 is triggered with a displacement accuracy of 0.1 μm.

[0034] Preferably, the implementation steps of step S5 are:

[0035] S51. Analyze the residual stress distribution at the end of the pressure holding step S4. The maximum stress point is marked in red. Plan the ejection sequence:

[0036] The ejector in the low stress area moves first, with a travel speed of 50 mm / s;

[0037] The high stress area starts with a delay of 0.5 seconds and the speed is reduced to 20 mm / s;

[0038] S52. The ejector pin is made of carbon fiber reinforced composite material with an elastic modulus of 150 GPa and an ejection stroke error of ≤0.02 mm.

[0039] Preferably, the implementation steps of step S6 are:

[0040] S61. After ejection, the shell immediately enters the laser holographic scanning station, where coherent light with a wavelength of 532nm is projected at 12 angles.

[0041] S62. Compare the standard point cloud model designed in step S2. The inspection items include:

[0042] S621. 3D deformation: Alarm if deviation from theoretical contour > 0.1mm;

[0043] S622. Sink mark depth: threshold 10 μm;

[0044] S623. Weld line integrity: Grayscale value difference >15% is considered a defect, and holographic data generation time <3 seconds;

[0045] S63. The detected deformation vector graph is automatically transmitted back to step S2 for mold compensation algorithm iteration.

[0046] Preferably, the implementation steps of step S7 are:

[0047] S71. The housing that has passed the quality inspection in step S6 enters the atmospheric pressure plasma treatment chamber;

[0048] S72. Under an argon / oxygen ratio of 9:1 mixed atmosphere, a 1000 Hz pulsed electric field treatment was applied for 40 seconds at a power density of 3 W / cm 2 , so that 50-100nm active micropores are generated on the surface;

[0049] S73. Then spray the coloring liquid with a particle size of <30 nm, using the capillary effect to achieve pore self-filling, and the film thickness is controlled to 15±2μm;

[0050] S74. The plasma processing power parameters are dynamically optimized based on the nanomaterial surface energy data from step S1, and finally the entire process data flow is integrated to construct a process digital twin.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] The process of the present invention breaks through traditional limitations through collaborative innovation in materials, molds, processes, and testing. Nano in-situ modification technology gives the material homogeneous shrinkage characteristics, and combined with dynamic compensation molds, it offsets deformation in real time, suppressing dimensional deviations at the source; millisecond-level temperature control and multi-level feedback pressure holding form precise coordination of the thermal field, completely eliminating weld marks and shrinkage defects; online holographic scanning realizes real-time diagnosis of micron-level three-dimensional deformation and drives self-optimization of mold parameters; plasma-activated self-coloring technology replaces high-pollution spraying, and the nano-capillary effect achieves long-lasting coloring with zero VOC. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 This is a process flow chart of high-precision household appliance housing injection molding in the present invention. DETAILED DESCRIPTION

[0054] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0055] Example 1, please refer to Figure 1 The present invention proposes a high-precision home appliance housing injection molding process, comprising the following steps:

[0056] S1. In-situ modification pretreatment of nanocomposites; S2. Design of adaptive molds based on shrinkage cloud maps; S3. Control of high-frequency pulse temperature change; S4. Control of multi-level feedback pressure holding; S5. Stress-guided ejection; S6. Online holographic scanning quality inspection; S7. Implement plasma-activated self-coloring.

[0057] In this embodiment, it should be noted that the implementation steps of step S1 are:

[0058] S11. The matrix resin and surface-modified nanosilica were fed into a twin-screw extruder with a particle size of 20-30 nm and an addition amount of 1.5 wt %;

[0059] S12. In situ dispersion and interfacial coupling of nanoparticles were performed under temperature segmented control at a screw speed of 200 rpm, a barrel feed section of 160°C, a mixing section of 190°C, and a homogenization section of 180°C;

[0060] S13. Real-time monitoring of melt torque fluctuations and automatic adjustment of screw speed through torque feedback ensures nano-dispersion uniformity with a target range of ±5 N·m and dispersed phase size ≤100 nm.

[0061] In this embodiment, it should be noted that the implementation steps of step S2 are:

[0062] S21. Import the material dynamic shrinkage measured in step S1 and perform multi-physics coupling simulation based on the product 3D model;

[0063] S22. Preset dynamic compensation cavity during mold design:

[0064] When the measured dynamic shrinkage rate is 0.8-1.2% in the transverse direction and 1.0-1.5% in the longitudinal direction, a piezoelectric ceramic microactuator array with a spacing of 15mm×15mm is embedded in the easily deformed area at the intersection of the reinforcing ribs, and the mold cavity size is expanded by 0.3%-0.7% according to the shrinkage cloud map;

[0065] S23. The cooling water channel adopts a bionic fractal structure, with the main water channel diameter of φ10mm and the branch as low as φ1.5mm, ensuring a distance tolerance of ±0.2mm from the cavity surface.

[0066] In this embodiment, it should be noted that the implementation steps of step S3 are:

[0067] S31. After the mold is closed, the high-frequency induction heating system is activated to heat the cavity surface to 180°C within 0.8 seconds, with a heating rate of ≥150°C / s.

[0068] S32. When the melt filling is 95% complete, switch to the microchannel nitrogen quenching system and cool to 40°C within 1.5 seconds, with a cooling rate of ≥90°C / s;

[0069] S33. The temperature change process is monitored by an infrared thermal imager, and the surface temperature gradient is controlled within ±3℃ / cm 2 .

[0070] In this embodiment, it should be noted that the implementation steps of step S4 are:

[0071] S41. Based on the transient temperature field of step S3, perform three-stage dynamic pressure holding:

[0072] S411. Initial pressure holding: 120 MPa for 1.2 seconds, covering the cold start delay period;

[0073] S412. Shrinkage compensation pressure holding: The pressure decreases linearly with temperature to 80 MPa, with a slope of -20 MPa / °C.

[0074] S413. Stress release and pressure maintenance: the pressure is reduced to 20 MPa in steps, with a decrease of 10 MPa every 0.3 seconds;

[0075] S42. The 32-point pressure sensors in the mold provide real-time feedback on melt pressure fluctuations with a sampling frequency of 1 kHz. When the deviation is greater than 5%, the piezoelectric ceramic fine-tuning preset in step S2 is triggered with a displacement accuracy of 0.1 μm.

[0076] In this embodiment, it should be noted that the implementation steps of step S5 are:

[0077] S51. Analyze the residual stress distribution at the end of the pressure holding step S4. The maximum stress point is marked in red. Plan the ejection sequence:

[0078] The ejector in the low stress area moves first, with a travel speed of 50 mm / s;

[0079] The high stress area starts with a delay of 0.5 seconds and the speed is reduced to 20 mm / s;

[0080] S52. The ejector pin is made of carbon fiber reinforced composite material with an elastic modulus of 150 GPa and an ejection stroke error of ≤0.02 mm.

[0081] In this embodiment, it should be noted that the implementation steps of step S6 are:

[0082] S61. After ejection, the shell immediately enters the laser holographic scanning station, where coherent light with a wavelength of 532nm is projected at 12 angles.

[0083] S62. Compare the standard point cloud model designed in step S2. The inspection items include:

[0084] S621. 3D deformation: Alarm if deviation from theoretical contour > 0.1mm;

[0085] S622. Sink mark depth: threshold 10 μm;

[0086] S623. Weld line integrity: Grayscale value difference >15% is considered a defect, and holographic data generation time <3 seconds;

[0087] S63. The detected deformation vector graph is automatically transmitted back to step S2 for mold compensation algorithm iteration.

[0088] In this embodiment, it should be noted that the implementation steps of step S7 are:

[0089] S71. The housing that has passed the quality inspection in step S6 enters the atmospheric pressure plasma treatment chamber;

[0090] S72. Under an argon / oxygen ratio of 9:1 mixed atmosphere, a 1000 Hz pulsed electric field treatment was applied for 40 seconds at a power density of 3 W / cm 2 , so that 50-100nm active micropores are generated on the surface;

[0091] S73. Then spray the coloring liquid with a particle size of <30 nm, using the capillary effect to achieve pore self-filling, and the film thickness is controlled to 15±2μm;

[0092] S74. The plasma processing power parameters are dynamically optimized based on the nanomaterial surface energy data from step S1, and finally the entire process data flow is integrated to construct a process digital twin.

[0093] Example 2, in actual application, a high-precision home appliance housing injection molding process, specifically, includes the following steps:

[0094] S1. In-situ modification pretreatment of nanocomposites;

[0095] S11. The matrix resin and surface-modified nanosilica were fed into a twin-screw extruder with a particle size of 20-30 nm and an addition amount of 1.5 wt %;

[0096] S12. In situ dispersion and interfacial coupling of nanoparticles were performed under temperature segmented control at a screw speed of 200 rpm, a barrel feed section of 160°C, a mixing section of 190°C, and a homogenization section of 180°C;

[0097] S13. Real-time monitoring of melt torque fluctuations and automatic adjustment of screw speed through torque feedback ensures nano-dispersion uniformity with a target range of ±5 N·m and dispersed phase size ≤100 nm.

[0098] Through in-situ modification pretreatment of the S1 nanocomposite material, the in-situ dynamic dispersion control of nanoparticles is achieved through a twin-screw online modification system. A real-time torque feedback system (±5N·m fluctuation threshold) ensures uniform dispersion of nanosilica in the melt at a scale of ≤100nm. Segmented temperature control (160°C → 190°C → 180°C) matches the screw shear field and strengthens the nanoparticle-resin interface coupling effect. Dynamic shrinkage data (0.8-1.2% in the transverse direction, 1.0-1.5% in the longitudinal direction) is directly output to provide a quantitative basis for mold compensation.

[0099] S2. Design an adaptive mold based on shrinkage contours;

[0100] S21. Import the material dynamic shrinkage measured in step S1 and perform multi-physics coupling simulation based on the product 3D model;

[0101] S22. Preset dynamic compensation cavity during mold design:

[0102] When the measured dynamic shrinkage rate is 0.8-1.2% in the transverse direction and 1.0-1.5% in the longitudinal direction, a piezoelectric ceramic microactuator array with a spacing of 15mm×15mm is embedded in the easily deformed area at the intersection of the reinforcing ribs, and the mold cavity size is expanded by 0.3%-0.7% according to the shrinkage cloud map;

[0103] S23. The cooling water channel adopts a bionic fractal structure, with a main channel diameter of φ10mm and branches as low as φ1.5mm, ensuring a distance tolerance of ±0.2mm from the cavity surface;

[0104] Through S2's adaptive mold design based on shrinkage cloud maps, a dynamic mold compensation mechanism driven by multi-physics field coupling simulation is employed: a piezoelectric ceramic microactuator array (15mm×15mm grid) achieves real-time deformation compensation of 0.3%-0.7% of the mold cavity size; a bionic fractal cooling water channel (φ10mm→φ1.5mm gradient branch) ensures a cooling distance tolerance of ±0.2mm on the cavity surface; and the mold cavity expansion rate is strictly mapped to the shrinkage rate data from step S1, forming the basis for closed-loop dimensional control.

[0105] S3. Control high-frequency pulse temperature;

[0106] S31. After the mold is closed, the high-frequency induction heating system is activated to heat the cavity surface to 180°C within 0.8 seconds, with a heating rate of ≥150°C / s.

[0107] S32. When the melt filling is 95% complete, switch to the microchannel nitrogen quenching system and cool to 40°C within 1.5 seconds, with a cooling rate of ≥90°C / s;

[0108] S33. The temperature change process is monitored by an infrared thermal imager, and the surface temperature gradient is controlled within ±3℃ / cm 2 ;

[0109] Through S3 high-frequency pulse temperature control, a millisecond-level rapid thermal cycle system is established: high-frequency induction heating (≥150℃ / s) allows the cavity surface to reach 180℃ in 0.8 seconds, eliminating the cold material at the melt front; micro-channel liquid nitrogen rapid cooling (≥90℃ / s) reduces the temperature to 40℃ within 1.5 seconds, inhibiting the orientation crystallization of macromolecules; infrared thermal imager monitors the temperature gradient (±3℃ / cm 2 ), providing transient temperature field data for pressure maintenance in step S4;

[0110] S4. Control multi-level feedback pressure maintenance;

[0111] S41. Based on the transient temperature field of step S3, perform three-stage dynamic pressure holding:

[0112] S411. Initial pressure holding: 120 MPa for 1.2 seconds, covering the cold start delay period;

[0113] S412. Shrinkage compensation pressure holding: The pressure decreases linearly with temperature to 80 MPa, with a slope of -20 MPa / °C.

[0114] S413. Stress release and pressure maintenance: the pressure is reduced to 20 MPa in steps, with a decrease of 10 MPa every 0.3 seconds;

[0115] S42. 32 pressure sensors within the mold provide real-time feedback on melt pressure fluctuations, with a sampling frequency of 1 kHz. When the deviation exceeds 5%, the piezoelectric ceramic fine-tuning preset in step S2 is triggered, with a displacement accuracy of 0.1 μm.

[0116] Through S4 multi-level feedback holding pressure control, three-stage pressure adaptive regulation is implemented based on the temperature field: initial holding pressure (120MPa / 1.2s) covers melt compensation during the rapid cooling delay period; shrinkage compensation holding pressure (-20MPa / °C slope) matches the real-time cooling curve of step S3; piezoelectric ceramic fine-tuning (0.1μm accuracy) responds to pressure fluctuations at 32 points within the mold with deviations greater than 5%; and a residual stress distribution map is output to guide the ejection action in step S5.

[0117] S5. Stress-guided ejection;

[0118] S51. Analyze the residual stress distribution at the end of the pressure holding step S4. The maximum stress point is marked in red. Plan the ejection sequence:

[0119] The ejector in the low stress area moves first, with a travel speed of 50 mm / s;

[0120] The high stress area starts with a delay of 0.5 seconds and the speed is reduced to 20 mm / s;

[0121] S52. The ejector pin is made of carbon fiber reinforced composite material with an elastic modulus of 150 GPa and an ejection stroke error of ≤0.02 mm.

[0122] Through S5 stress-guided ejection, ejection timing planning is achieved to decouple residual stress: Based on the stress distribution diagram in step S4 (high-stress areas are marked in red), the ejector action timing is differentiated (50 mm / s in low-stress areas → 20 mm / s in high-stress areas + 0.5s delay). The carbon fiber ejector pin (150 GPa modulus) ensures that the deformation during the ejection process is ≤ 0.05%, avoiding secondary stress damage.

[0123] S6. Perform online holographic scanning quality inspection;

[0124] S61. After ejection, the shell immediately enters the laser holographic scanning station, where coherent light with a wavelength of 532nm is projected at 12 angles.

[0125] S62. Compare the standard point cloud model designed in step S2. The inspection items include:

[0126] S621. 3D deformation: Alarm if deviation from theoretical contour > 0.1mm;

[0127] S622. Sink mark depth: threshold 10 μm;

[0128] S623. Weld line integrity: Grayscale value difference >15% is considered a defect, and holographic data generation time <3 seconds;

[0129] S63. The detected deformation vector graph is automatically transmitted back to step S2 for mold compensation algorithm iteration;

[0130] The S6 online holographic scanning quality inspection system completes non-destructive testing of sub-micron 3D defects: 12-angle coherent light (532nm) scans generate a 3D point cloud model (5μm accuracy). Deformation alarm thresholds (>0.1mm deviation), sink mark depth thresholds (10μm), and weld line grayscale thresholds (>15% difference) form quantitative defect judgment criteria. The deformation vector diagram is fed back in real time to the mold compensation algorithm iteration in step S2.

[0131] S7. Implementing plasma activated self-coloring;

[0132] S71. The housing that has passed the quality inspection in step S6 enters the atmospheric pressure plasma treatment chamber;

[0133] S72. Under an argon / oxygen ratio of 9:1 mixed atmosphere, a 1000 Hz pulsed electric field treatment was applied for 40 seconds at a power density of 3 W / cm 2 , so that 50-100nm active micropores are generated on the surface;

[0134] S73. Then spray the coloring liquid with a particle size of <30 nm, using the capillary effect to achieve pore self-filling, and the film thickness is controlled to 15±2μm;

[0135] S74. The plasma processing power parameters are dynamically optimized based on the nanomaterial surface energy data from step S1, and the entire process data flow is finally integrated to build a process digital twin.

[0136] Develop nanoporous capillary self-assembly coloring technology through S7 plasma activation self-coloring: Argon oxygen mixed plasma (1000Hz pulse / 3W / cm 2 ) generates 50-100nm surface micropores; the nano-coloring liquid (particle size <30nm) achieves self-filling of a film thickness of 15±2μm through capillary effect; the processing power is dynamically optimized by the nanomaterial surface energy data of step S1 to ensure pore-colorant size matching.

[0137] Finally, the entire process data flow (material dispersion → cavity compensation → temperature / pressure curve → deformation detection value → coloring adhesion) is integrated to build a process digital twin;

[0138] Deep learning optimization is performed every 100 pieces produced: a convolutional neural network is used to analyze the correlation between deformation and holding parameters, and a new holding slope parameter is output to step S4. At the same time, the shrinkage prediction model of step S2 is updated.

[0139] Through the above steps, the process of the present invention systematically breaks through traditional limitations through four-dimensional collaborative innovation in materials, molds, processes, and testing. Nano-in-situ modification technology gives the material homogeneous shrinkage characteristics, and combined with dynamic compensation molds, it offsets deformation in real time, suppressing dimensional deviation at the source. Millisecond-level temperature control and multi-level feedback pressure holding form a precise synergy of thermal fields, completely eliminating weld marks and shrinkage defects. Online holographic scanning realizes real-time diagnosis of three-dimensional deformation at the micron level and drives self-optimization of mold parameters. Plasma-activated self-coloring technology replaces high-pollution spraying, and the nano-capillary effect achieves zero-VOC long-lasting coloring.

[0140] The full-process data closed loop reduces the overall product defect rate to below 0.1%, improves the flatness accuracy to ±0.1mm, and shortens the production cycle by 40%, building a high-precision, low-energy, zero-pollution intelligent manufacturing process.

[0141] Throughout this specification, references to terms such as "one embodiment," "example," or "specific example" indicate that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0142] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to the specific embodiments described. Obviously, many modifications and variations are possible based on the content of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A high-precision household appliance housing injection molding process, characterized in that: The following steps are involved: S1. In-situ modification pretreatment of nanocomposites; S2. Design an adaptive mold based on shrinkage contours; S3. Control high-frequency pulse temperature; S4. Control multi-level feedback pressure maintenance; S5. Stress-guided ejection; S6. Perform online holographic scanning quality inspection; S7. Perform plasma-activated self-coloring.

2. A high-precision household appliance housing injection molding process according to claim 1, characterized in that: The implementation steps of step S1 are: S11. The matrix resin and surface-modified nanosilica were fed into a twin-screw extruder with a particle size of 20-30 nm and an addition amount of 1.5 wt %; S12. In situ dispersion and interfacial coupling of nanoparticles were performed under temperature segmented control at a screw speed of 200 rpm, a barrel feed section of 160°C, a mixing section of 190°C, and a homogenization section of 180°C; S13. Real-time monitoring of melt torque fluctuations and automatic adjustment of screw speed through torque feedback ensures nano-dispersion uniformity with a target range of ±5 N·m and dispersed phase size ≤100 nm.

3. A high-precision household appliance housing injection molding process according to claim 2, characterized in that: The implementation steps of step S2 are: S21. Import the material dynamic shrinkage measured in step S1 and perform multi-physics coupling simulation based on the product 3D model; S22. Preset dynamic compensation cavity during mold design: When the measured dynamic shrinkage rate is 0.8-1.2% in the transverse direction and 1.0-1.5% in the longitudinal direction, a piezoelectric ceramic microactuator array with a spacing of 15mm×15mm is embedded in the easily deformed area at the intersection of the reinforcing ribs, and the mold cavity size is expanded by 0.3%-0.7% according to the shrinkage cloud map; S23. The cooling water channel adopts a bionic fractal structure, with the main water channel diameter of φ10mm and the branch as low as φ1.5mm, ensuring a distance tolerance of ±0.2mm from the cavity surface.

4. A high-precision household appliance housing injection molding process according to claim 3, characterized in that: The implementation steps of step S3 are: S31. After the mold is closed, the high-frequency induction heating system is activated to heat the cavity surface to 180°C within 0.8 seconds, with a heating rate of ≥150°C / s. S32. When the melt filling is 95% complete, switch to the microchannel nitrogen quenching system and cool to 40°C within 1.5 seconds, with a cooling rate of ≥90°C / s; S33. The temperature change process is monitored by an infrared thermal imager, and the surface temperature gradient is controlled within ±3℃ / cm 2 .

5. A high-precision household appliance housing injection molding process according to claim 4, characterized in that: The implementation steps of step S4 are: S41. Based on the transient temperature field of step S3, perform three-stage dynamic pressure holding: S411. Initial pressure holding: 120 MPa for 1.2 seconds, covering the cold start delay period; S412. Shrinkage compensation pressure holding: The pressure decreases linearly with temperature to 80 MPa, with a slope of -20 MPa / °C. S413. Stress release and pressure maintenance: the pressure is reduced to 20 MPa in steps, with a decrease of 10 MPa every 0.3 seconds; S42. The 32-point pressure sensors in the mold provide real-time feedback on melt pressure fluctuations with a sampling frequency of 1 kHz. When the deviation is greater than 5%, the piezoelectric ceramic fine-tuning preset in step S2 is triggered with a displacement accuracy of 0.1 μm.

6. A high-precision household appliance housing injection molding process according to claim 5, characterized in that: The implementation steps of step S5 are: S51. Analyze the residual stress distribution at the end of the pressure holding step S4. The maximum stress point is marked in red. Plan the ejection sequence: The ejector in the low stress area moves first, with a travel speed of 50 mm / s; The high stress area starts with a delay of 0.5 seconds and the speed is reduced to 20 mm / s; S52. The ejector pin is made of carbon fiber reinforced composite material with an elastic modulus of 150 GPa and an ejection stroke error of ≤0.02 mm.

7. A high-precision household appliance housing injection molding process according to claim 6, characterized in that: The implementation steps of step S6 are: S61. After ejection, the shell immediately enters the laser holographic scanning station, where coherent light with a wavelength of 532nm is projected at 12 angles. S62. Compare the standard point cloud model designed in step S2. The inspection items include: S621. 3D deformation: Alarm if deviation from theoretical contour > 0.1mm; S622. Sink mark depth: threshold 10 μm; S623. Weld line integrity: Grayscale value difference >15% is considered a defect, and holographic data generation time <3 seconds; S63. The detected deformation vector graph is automatically transmitted back to step S2 for mold compensation algorithm iteration.

8. A high-precision household appliance housing injection molding process according to claim 7, characterized in that: The implementation steps of step S7 are: S71. The housing that has passed the quality inspection in step S6 enters the atmospheric pressure plasma treatment chamber; S72. Under an argon / oxygen ratio of 9:1 mixed atmosphere, a 1000 Hz pulsed electric field treatment was applied for 40 seconds at a power density of 3 W / cm 2 , so that 50-100nm active micropores are generated on the surface; S73. Then spray the coloring liquid with a particle size of <30 nm, using the capillary effect to achieve pore self-filling, and the film thickness is controlled to 15±2μm; S74. The plasma processing power parameters are dynamically optimized based on the nanomaterial surface energy data from step S1, and finally the entire process data flow is integrated to construct a process digital twin.

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