Two-color high-gloss injection molding method for automotive engine bay parts

Abstract

The application is suitable for the technical field of automobile part injection molding, and particularly relates to a double-color high-gloss injection molding method for automobile engine compartment parts. The double-color high-gloss injection molding method for automobile engine compartment parts comprises the following steps: determining a reference high-gloss parameter based on a first high-gloss parameter when a first material is used to injection mold a basic layer of an automobile engine compartment part; in response to the completion of injection molding of the first material and the switching of a mold cavity to a second material injection molding station, performing an operation of injection molding a functional layer of the engine compartment part by using the second material, and simultaneously obtaining a second high-gloss parameter when the second material is injection molded; generating a high-gloss parameter difference value based on the second high-gloss parameter and the reference high-gloss parameter; and when the high-gloss parameter difference value is greater than a preset high-gloss threshold value, dynamically adjusting injection molding process parameters of the second material based on the high-gloss parameter difference value. The method improves the appearance uniformity and quality stability of double-color molded products of automobile engine compartment parts.

Description

Technical Field

[0001] This application belongs to the field of automotive component injection molding technology, and particularly relates to a two-color high-gloss injection molding method for automotive engine compartment parts. Background Technology

[0002] As the automotive industry upgrades its demands for "refined appearance and composite performance" in engine compartment components, traditional single-material injection molding technology can no longer meet market requirements. On the one hand, consumers are paying more attention to the visual experience of the car's interior, requiring engine compartment components to have diverse appearance effects such as high-gloss texture and color zoning. On the other hand, different parts of the engine compartment components have significantly different requirements for material performance; for example, the surface layer needs high gloss and wear resistance, while the structural layer needs high strength and impact resistance. Against this backdrop, two-color high-gloss injection molding technology has emerged. This technology injects two materials with different properties sequentially into the same mold, allowing the product to possess the advantages of both materials, achieving both a high-gloss appearance and ensuring structural performance. Two-color injection molding refers to the injection molding process in which two different colored or different-property plastic materials are injected into the mold cavity in two separate injection processes within the same mold, ultimately forming a product with a composite structure of two materials.

[0003] In existing technologies, due to the fluctuations in the performance of different batches of materials, the surface gloss of the two materials may differ significantly after injection molding, thus affecting the stability and consistency of the product. Summary of the Invention

[0004] This application provides a two-color high-gloss injection molding method for automotive engine compartment parts, which can solve the problem of large differences in surface gloss of automotive engine compartment parts.

[0005] In a first aspect, embodiments of this application provide a two-color high-gloss injection molding method for automotive engine compartment components, including:

[0006] Based on the first gloss parameter when the first material is injected into the base layer of the automotive engine compartment component, a reference gloss parameter is determined; wherein, the first gloss parameter is used to indicate the gloss and smoothness parameters of the molded surface of the first material during the molding process in the mold cavity;

[0007] In response to the completion of injection molding of the first material and the switching of the mold cavity to the injection molding station of the second material, the operation of the functional layer of the second material injection molding machine is performed, and the second gloss parameter during the injection molding of the second material is determined; wherein, the second gloss parameter is used to indicate the gloss and smoothness parameters of the surface of the second material during the molding process in the molding cavity.

[0008] Generate a specular parameter difference based on the second specular parameter and the reference specular parameter;

[0009] When the difference in the highlight parameters is greater than a preset highlight threshold, the injection molding process parameters of the second material are dynamically adjusted based on the difference in the highlight parameters.

[0010] The technical solutions described in this application embodiment have at least the following technical effects:

[0011] The dual-color high-gloss injection molding method for automotive engine compartment parts provided in this application, after completing the injection molding of the first material, determines a reference high-gloss parameter based on the gloss and smoothness parameters of the surface of the first material during the molding process in the mold cavity when the first material is used to injection mold the base layer of the automotive engine compartment part; in response to the completion of the injection molding of the first material and the switching of the mold cavity to the injection molding station of the second material, the operation of the second material injection molding of the functional layer of the engine compartment part is performed, and at the same time, a second high-gloss parameter is determined based on the gloss and smoothness parameters of the surface of the second material during the molding process in the mold cavity when the second material is used to injection mold; then, a high-gloss parameter difference is generated based on the second high-gloss parameter and the reference high-gloss parameter; when the high-gloss parameter difference is greater than a preset high-gloss threshold, the injection molding process parameters of the second material are dynamically adjusted based on the high-gloss parameter difference. This method uses the first gloss parameter during the injection molding of the first material as a reference benchmark to accurately anchor the target standard for the surface quality of automotive engine compartment parts. When switching to the second material injection molding functional layer, the second gloss parameter is simultaneously collected and the difference between it and the reference gloss parameter is calculated, allowing real-time monitoring of the gloss and smoothness consistency of the two materials' molded surfaces. When the gloss parameter difference exceeds a preset threshold, the injection molding process parameters of the second material are dynamically adjusted based on this difference, achieving closed-loop feedback optimization of process parameters. This effectively solves the problem of inconsistent surface quality caused by differences in material properties and mold temperature variations in existing two-color high-gloss injection molding, significantly improving the appearance uniformity and quality stability of two-color molded automotive engine compartment parts. Simultaneously, it reduces the scrap rate caused by fixed parameters, ensuring product quality uniformity during mass production.

[0012] Secondly, embodiments of this application provide a two-color high-gloss injection molding system for automotive engine compartment components, comprising:

[0013] The first determining module is used to determine reference highlight parameters based on the first highlight parameters when the first material is injected into the base layer of the automotive engine compartment component; wherein, the first highlight parameters are used to indicate the gloss and smoothness parameters of the molded surface of the first material during the molding process in the mold cavity;

[0014] The second determining module is used to respond to the completion of injection molding of the first material and the switching of the mold cavity to the injection molding station of the second material, to perform the operation of the functional layer of the second material injection molding machine, and at the same time determine the second gloss parameter during the injection molding of the second material; wherein, the second gloss parameter is used to indicate the gloss and smoothness parameters of the surface of the second material during the molding process in the molding cavity of the mold;

[0015] The generation module is used to generate a specular parameter difference based on the second specular parameter and the reference specular parameter;

[0016] The adjustment module is used to dynamically adjust the injection molding process parameters of the second material based on the difference in the high-gloss parameters when the difference in the high-gloss parameters is greater than a preset high-gloss threshold.

[0017] Thirdly, embodiments of this application provide a two-color high-gloss injection molding equipment for automotive cabin parts, including an injection molding device and a control device. The control device is electrically connected to the injection molding device. The control device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method described in any one of the first aspects above.

[0018] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in any one of the first aspects above.

[0019] Fifthly, embodiments of this application provide a computer program product that, when run on a two-color high-gloss injection molding machine for automotive engine compartment parts, causes the two-color high-gloss injection molding machine for automotive engine compartment parts to perform the two-color high-gloss injection molding method for automotive engine compartment parts described in any of the first aspects above.

[0020] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a schematic flowchart of the two-color high-gloss injection molding method for automotive engine compartment parts provided in the embodiments of this application;

[0023] Figure 2 This is a schematic diagram illustrating the implementation process of the two-color high-gloss injection molding method for automotive engine compartment parts provided in this application embodiment;

[0024] Figure 3 This is a schematic diagram of the structure of the two-color high-gloss injection molding system for automotive engine compartment parts provided in the embodiments of this application;

[0025] Figure 4 This is a schematic diagram of the control device of the two-color high-gloss injection molding equipment for automotive cabin parts provided in the embodiments of this application. Detailed Implementation

[0026] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0027] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0028] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0029] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determination" or "if the described condition or event is detected" may be interpreted, depending on the context, as "once determination," "in response to determination," "once the described condition or event is detected," or "in response to the detection of the described condition or event."

[0030] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0031] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0032] Because the molding temperatures and shrinkage rates of the first and second materials differ, and the base layer is already cooled during the second injection, the melting flow and solidification process of the second material are affected, leading to differences in gloss and smoothness between the second and first materials. Simultaneously, changes in the temperature field distribution within the mold cavity during the two injection processes exacerbate surface quality inconsistencies, especially at the joint edges of the two materials, where sudden changes in gloss and smoothness deviations are likely to occur, affecting the uniformity of the product's appearance. Existing two-color high-gloss injection molding process parameters mostly use preset fixed values, making dynamic adjustment difficult based on actual molding conditions. Due to fluctuations in the properties of different batches of materials and changes in the surface condition of the mold cavity during long-term use, preset fixed parameters cannot adapt to these dynamic factors. For example, when the high-gloss parameters of the first material change due to batch differences, if the injection parameters of the second material remain unchanged, the difference in high-gloss parameters between the two will increase, resulting in a decrease in product surface quality.

[0033] To address the aforementioned issues, this application provides a two-color high-gloss injection molding method for automotive engine compartment components. In this method, after injection molding of the first material is completed, a reference high-gloss parameter is determined based on the gloss and smoothness parameters of the first material's surface during the molding process within the mold cavity when the first material is used to injection mold the base layer of the automotive engine compartment component. In response to the completion of injection molding of the first material and the switching of the mold cavity to the second material injection station, the operation of injection molding the functional layer of the engine compartment component using the second material is executed. Simultaneously, a second high-gloss parameter is determined based on the gloss and smoothness parameters of the second material's surface during the molding process within the mold cavity when the second material is used for injection molding. Then, a high-gloss parameter difference is generated based on the second high-gloss parameter and the reference high-gloss parameter. When the high-gloss parameter difference exceeds a preset high-gloss threshold, the injection molding process parameters of the second material are dynamically adjusted based on the high-gloss parameter difference. This method uses the first gloss parameter during the injection molding of the first material as a reference benchmark to accurately anchor the target standard for the surface quality of automotive engine compartment parts. When switching to the second material injection molding functional layer, the second gloss parameter is simultaneously collected and the difference between it and the reference gloss parameter is calculated, allowing real-time monitoring of the gloss and smoothness consistency of the two materials' molded surfaces. When the gloss parameter difference exceeds a preset threshold, the injection molding process parameters of the second material are dynamically adjusted based on this difference, achieving closed-loop feedback optimization of process parameters. This effectively solves the problem of inconsistent surface quality caused by differences in material properties and mold temperature variations in existing two-color high-gloss injection molding, significantly improving the appearance uniformity and quality stability of two-color molded automotive engine compartment parts. Simultaneously, it reduces the scrap rate caused by fixed parameters, ensuring product quality uniformity during mass production.

[0034] The two-color high-gloss injection molding method for automotive engine compartment parts provided in this application embodiment can be applied to a two-color high-gloss injection molding equipment for automotive engine compartment parts. In this case, the two-color high-gloss injection molding equipment for automotive engine compartment parts is the executing entity of the two-color high-gloss injection molding method for automotive engine compartment parts provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of two-color high-gloss injection molding equipment for automotive engine compartment parts.

[0035] For example, a two-color high-gloss injection molding equipment for automotive engine compartment parts may include an injection molding unit and a control unit, with the control unit electrically connected to the injection molding unit. The injection molding unit is used to injection mold two different materials into the base layer and functional layer of the automotive engine compartment parts, respectively. For instance, the injection molding unit includes a dual-barrel injection unit, a mold cavity switching mechanism, and a high-gloss parameter detection component. The dual-barrel injection unit corresponds to the melting and injection of the first and second materials, respectively. The mold cavity switching mechanism enables precise switching of the core with the base layer between different injection stations. The high-gloss parameter detection component can integrate a gloss meter, a flatness measurement sensor, etc., for real-time acquisition of high-gloss parameters during the molding process of the first and second materials. The control unit monitors and controls the entire melting, extrusion, and cooling processes.

[0036] For example, the control device can be a PLC, microcontroller, mobile phone, tablet computer, laptop computer, ultra-mobile personal computer (UMPC), netbook, personal digital assistant (PDA), desktop computer, smart screen, smart TV and other terminal devices, IoT terminal, computer, laptop computer, customer premises equipment (CPE) and / or other devices used for communication over wireless systems, as well as next-generation communication systems, such as mobile terminals in 5G networks or mobile terminals in future evolved Public Land Mobile Networks (PLMNs).

[0037] To better understand the two-color high-gloss injection molding method for automotive engine compartment parts provided in this application, the specific implementation process of the two-color high-gloss injection molding method for automotive engine compartment parts provided in this application will be described exemplarily below.

[0038] Figure 1 and Figure 2 This illustration shows a schematic flowchart of a two-color high-gloss injection molding method for automotive engine compartment parts provided in an embodiment of this application. The two-color high-gloss injection molding method for automotive engine compartment parts includes:

[0039] S100, based on the first gloss parameter when the first material is injected into the base layer of the automotive engine compartment component, a reference gloss parameter is determined; wherein, the first gloss parameter is used to indicate the gloss and smoothness parameters of the molded surface of the first material during the molding process in the mold cavity.

[0040] It is understandable that the first gloss parameter is not data from a single point in time, but rather a complete set of gloss and smoothness parameters of the molded surface at all key time points throughout the entire injection molding cycle of the first material (the core structural material of the automotive engine compartment base layer, such as high-strength ABS, heat-resistant PP, etc.). This covers the three stages of melt filling, pressure holding and solidification, and cooling and setting, reflecting the dynamic changes in the surface quality of the base layer. The first gloss parameter can be measured using a gloss meter at a preset incident angle to detect the gloss of the base layer surface, and smoothness can be detected using a smoothness sensor (such as a laser profilometer or coordinate measuring machine). The gloss parameter serves as a reference for the surface quality of the subsequent injection molding of the second material (functional layer material, such as high-gloss PMMA, scratch-resistant PC, etc.).

[0041] For example, a time series diagram of highlight parameters can be generated based on the first highlight parameters when the first material is used to inject the base layer of the automotive engine compartment component, and then a reference highlight parameter can be determined based on the time series diagram of highlight parameters; alternatively, the first highlight parameters can be divided into a filling layer, a pressure holding layer, and a cooling layer according to the injection molding stage, and the parameter data of each layer can be clustered using the K-means clustering algorithm (the K value can be set to 3, corresponding to violent fluctuation, gentle fluctuation, and stable). For example, after clustering 30 sets of data from the pressure-holding layer, the stable class contains 22 sets of data (gloss 84-86 GU, smoothness 0.58-0.62 μm), the class with gentle fluctuations contains 5 sets of data (gloss 82-88 GU, smoothness 0.55-0.65 μm), and the class with severe fluctuations contains 3 sets of data (gloss 78-90 GU, smoothness 0.5-0.7 μm). Then, the stability index of each class of data is calculated [stability index = 1 - (standard deviation of parameters within the class / mean of parameters within the class)]. The classes with a stability index ≥ 0.95 are selected as the core stable set. The arithmetic mean of the core stable set data is calculated as the reference specular parameter, and so on, but not limited to this.

[0042] In one possible implementation, in step S100, a reference highlight parameter is determined based on the first highlight parameter when the first material is used to injection mold the base layer of the automotive engine compartment component, including:

[0043] S110, Based on the first specular parameters when the base layer of the automotive engine compartment component is injection molded from the first material, a specular parameter timing diagram is generated; wherein, the specular parameter timing diagram is used to reflect the change of surface specular parameters of the base layer formed by the first material as the injection molding progress progresses.

[0044] It is understandable that the timing diagram structure of the gloss parameter can adopt a dual-vertical-axis + multi-curve superposition method: the horizontal axis is in seconds and marks key injection nodes (such as "0 seconds: start injection", "18 seconds: enter holding pressure", "45 seconds: start cooling"); the vertical axis is divided into upper and lower layers, the upper layer is gloss (unit: GU), the range is set to 40-100GU (covering the common range of low to high gloss of the base layer material of automotive engine compartment parts, such as the gloss value of ABS material is usually 80-90GU), and the lower layer is flatness (unit: μm), the range is set to 0-1.5μm (meeting the requirements of high precision surface, such as Ra≤0.8μm is qualified), and both vertical axes are marked with scale and unit. Meanwhile, key process parameter curves of the first material (such as mold cavity temperature, injection pressure, and holding time) can be superimposed on the high-gloss parameter time sequence diagram. For example, the process of the cavity temperature rising from room temperature (25℃) to 65℃ (the optimal molding temperature for ABS) is marked with a green dashed line, and the change of injection pressure from 60MPa to 90MPa and then to 70MPa is marked with a blue dotted line. By superimposing multiple curves, the correlation between process parameter adjustment and high-gloss parameter change can be observed intuitively.

[0045] S120, based on the specular parameter timing diagram, determines the reference specular parameters.

[0046] For example, a stable forming stage can be identified based on the specular parameter time series diagram. The average value of the parameters within the stable forming stage can be calculated and determined as the reference specular parameter. Alternatively, the 3σ principle (data exceeding the mean ± 3 times the standard deviation is considered anomaly) can be used to filter the data in the stable stage. For example, in the stable stage (30-50 seconds), the gloss mean is 85.4 GU, the standard deviation is 0.8 GU, and the 3σ range is 83-87.8 GU. If a set of data is 79.5 GU, it is considered an outlier because it exceeds the range. After removing the outliers, the remaining data are sorted from smallest to largest, and the value in the middle position is taken as the reference value (when the data volume is even, the average of the two middle numbers is taken). For example, after removing one set of outliers, nine sets of gloss data remain: 84.8, 85.0, 85.2, 85.3, 85.4, 85.5, 85.6, 85.7, and 85.9, with a median of 85.4 GU; after removing outliers from the smoothness data, nine sets remain, with a median of 0.60 μm. Reference highlight parameters are obtained in this way, and so on, but not limited to these.

[0047] This setup allows for the generation of a high-gloss parameter time sequence diagram based on the first high-gloss parameter during the injection molding of the first material's base layer. This visualizes the dynamic changes in the surface high-gloss parameters (gloss and smoothness) of the first material throughout the entire molding cycle, clearly presenting the parameter fluctuation characteristics at different stages such as melt filling, pressure holding and solidification, and cooling and shaping. Furthermore, by determining reference high-gloss parameters based on this time sequence diagram, the molding stage with the smallest parameter fluctuation amplitude and the most stable process state can be accurately identified. This ensures that the reference high-gloss parameters better match the actual optimal surface quality of the base layer, providing a precise benchmark for subsequent comparison of high-gloss parameters and process adjustments during the injection molding of the second material. This effectively reduces inconsistencies in surface gloss and smoothness between the two materials caused by inaccurate reference benchmarks.

[0048] In one possible implementation, in step S120, determining reference specular parameters based on the specular parameter timing map includes:

[0049] S121, based on the timing diagram of the high-gloss parameters, identifies the stable forming stage.

[0050] It is understandable that in the specular parameter time series diagram, parameter fluctuations can be detected segment by segment in 10-second sliding windows: if the gloss fluctuation of all data within a certain window is ≤2GU and the smoothness fluctuation is ≤0.05μm, it is initially marked as a potential stable window; then the continuity of the window is verified, such as if the continuous duration is ≥15 seconds (covering the core period of the pressure holding and curing stage, ensuring parameter stability rather than instantaneous fluctuations), for example, within the 18-second window of 30-48 seconds in the time series diagram, the gloss is stable at 84.6-86.2GU (fluctuation of 1.6GU) and the smoothness is stable at 0.59-0.63μm (fluctuation of 0.04μm), and the fluctuation threshold is continuously met, it can be determined as a stable molding stage.

[0051] S122, based on the average value of parameters within the calculation stage of the stable forming stage, the average value of parameters is determined as the reference specular parameters.

[0052] It is understandable that, taking gloss calculation as an example: the 17 sets of valid data are 84.6, 84.8, 84.9, 85.0, 85.1, 85.2, 85.3, 85.4, 85.5, 85.6, 85.7, 85.8, 85.9, 86.0, 86.1, 86.2, and 86.3. The data are evenly distributed, and the arithmetic mean is (84.6 + 84.8 + ... + 86.3) / 17 ≈ 85.4 GU; the mean of the 17 sets of valid data for smoothness is calculated to be 0.61 μm, so the reference specular parameter is (85.4 GU, 0.61 μm).

[0053] This setup, by accurately identifying the stable molding stage from the highlight parameter timeline, effectively eliminates interference data from unstable stages such as insufficient mold preheating in the early stages of injection molding and material residue in the later stages. It focuses on the core period when the surface quality of the base layer is most stable and the process state is most controllable, reducing the reference deviation caused by the inclusion of abnormal fluctuations in the traditional full-cycle data average. Then, based on the average value of the parameters calculated in this stable stage, the reference highlight parameters are determined, fully utilizing the consistent characteristics of surface gloss and smoothness within the stable period, making the reference value more closely match the actual optimal surface quality of the base layer. Compared to relying on manual experience to select reference values ​​or directly using the full-cycle average, this not only significantly improves the accuracy and representativeness of the reference highlight parameters, providing a precise benchmark for comparing highlight parameters in subsequent second material injection molding, effectively reducing inconsistencies in surface gloss and smoothness between the two materials, but also reduces the trial-and-error costs of process adjustments caused by inaccurate reference benchmarks. Furthermore, through standardized stable stage identification and average calculation logic, the batch stability of reference values ​​in mass production is improved, further ensuring the quality uniformity of two-color molded automotive engine compartment parts.

[0054] S200, in response to the completion of injection molding of the first material and the switching of the mold cavity to the injection molding station of the second material, performs the operation of the functional layer of the second material injection molding machine chamber, and at the same time acquires the second gloss parameter during the injection molding of the second material; wherein, the second gloss parameter is used to indicate the gloss and smoothness parameters of the surface of the second material during the molding process in the molding cavity.

[0055] It is understandable that the acquisition method for the second gloss parameter can be similar to that for the first gloss parameter. Specifically, gloss detection uses a portable gloss meter with an incident angle of 60° (accuracy ±1GU). Six detection points are selected on the surface of the functional layer (one point at the center and five points at the edges, covering the key appearance areas of the functional layer) to capture the gloss changes during melt filling. Flatness detection uses a laser profilometer to scan along the diagonal direction of the functional layer and record the arithmetic mean deviation (Ra) and maximum height difference (Rz) of the surface profile. The scanning frequency is synchronized with the gloss acquisition.

[0056] S300 generates a specular parameter difference based on the second specular parameter and the reference specular parameter.

[0057] It is understandable that the gloss parameter difference is used to quantify the surface quality difference between the second material functional layer and the first material base layer, and is the core basis for determining whether the injection molding process of the second material needs to be adjusted. For example, the gloss difference and flatness difference between the second gloss parameter and the reference gloss parameter can be calculated, and the parameter pair composed of the gloss difference and flatness difference can be determined as the gloss parameter difference. Alternatively, the comprehensive difference value can be calculated according to production needs. For engine compartment parts with higher appearance priority (such as exposed trim panels in the engine compartment), the gloss difference can be assigned a weight of 0.6 and the flatness difference can be assigned a weight of 0.4. The comprehensive difference value can be calculated (e.g., gloss difference -5GU, flatness difference +0.1μm, comprehensive difference value = -5×0.6+0.1×0.4=-2.96), which can intuitively reflect the overall quality deviation.

[0058] In one possible implementation, step S300 involves generating a specular parameter difference based on the second specular parameter and the reference specular parameter, including:

[0059] S310, calculate the gloss difference and smoothness difference between the second highlight parameter and the reference highlight parameter respectively.

[0060] It can be understood that the gloss difference = gloss value of the second highlight parameter - gloss value of the reference highlight parameter. A positive difference indicates that the functional layer has a higher gloss (e.g., 88GU-85GU=+3GU), and a negative difference indicates that it has a lower gloss (e.g., 82GU-85GU=-3GU); the smoothness difference = smoothness value of the second highlight parameter - smoothness value of the reference highlight parameter. A positive difference indicates that the surface of the functional layer is rougher (e.g., 0.7μm-0.6μm=+0.1μm), and a negative difference indicates that it is smoother (e.g., 0.5μm-0.6μm=-0.1μm).

[0061] S320 defines the parameter pair consisting of gloss difference and smoothness difference as the highlight parameter difference.

[0062] This setup allows for precise quantification of the surface quality differences between the two materials by separately calculating the gloss difference and the flatness difference between the second and reference gloss parameters. The difference identification covers the core requirements of automotive engine compartment parts' appearance (gloss) and assembly performance (flatness). Furthermore, the parameter pair formed by these two factors is defined as the gloss parameter difference, which intuitively presents the synergistic relationship between the two-dimensional differences. At the same time, the structured parameter pair format facilitates the tracing of the root cause of related process parameters (such as an excessively low cavity temperature corresponding to a certain parameter pair), thereby improving the first-time compliance rate of the second material's process adjustments. This effectively reduces problems such as inconsistent appearance and poor assembly of automotive engine compartment parts caused by inaccurate difference positioning, ensuring the stability and consistency of product quality during mass production.

[0063] S400: When the difference in highlight parameters is greater than the preset highlight threshold, the injection molding process parameters of the second material are dynamically adjusted based on the difference in highlight parameters.

[0064] It is understandable that the preset gloss threshold refers to the upper limit of tolerance for differences in gloss parameters (gloss difference, smoothness difference) based on the appearance acceptance standards of automotive engine compartment parts, dual-material assembly requirements, and the process stability of the first material. It can be manually input, retrieved from an injection molding database, etc., but is not limited to these methods. The injection molding database refers to a database containing gloss thresholds corresponding to various specifications of automotive engine compartment parts. This data can be obtained through laboratory experiments, on-site measurements and monitoring, and past experience. After acquisition, the collected data is organized, classified, and archived, useful information and patterns are extracted, and the relevant data is then saved into the database to form the injection molding database.

[0065] For example, process adjustment parameter curves for the first and second materials can be constructed, and then the injection molding process parameters of the second material can be dynamically adjusted according to the process adjustment parameter curves. Alternatively, the sensitivity of different process parameters to gloss parameters can be quantified, and adjustment amounts can be allocated according to the magnitude of the difference. For example, for the second material PMMA, the effects of cavity temperature, injection pressure, and holding time on gloss and smoothness can be tested in a laboratory environment. For example, for every 1°C change in cavity temperature, the gloss difference changes by 0.3 GU (sensitivity coefficient 0.3 GU / °C), and the smoothness difference changes by 0.01 μm (sensitivity coefficient 0.01 μm / °C); for every 1 MPa change in injection pressure, the gloss difference changes by 0.15 GU (sensitivity coefficient 0.15 GU / MPa), and the smoothness difference changes by 0.008 μm (sensitivity coefficient 0.008 μm / MPa). The sensitivity coefficients can be stored in a process database. When high-gloss parameter differences occur in actual production (such as gloss difference -3GU, smoothness difference +0.1μm), the parameter with the highest sensitivity should be adjusted first: the gloss difference needs to be compensated by 3GU, the cavity temperature has the highest sensitivity, the adjustment amount = 3GU ÷ 0.3GU / ℃ = 10℃ (increase by 10℃); the smoothness difference needs to be compensated by 0.1μm, the adjustment amount = 0.1μm ÷ 0.01μm / ℃ = 10℃ (consistent with the gloss adjustment direction, can be executed simultaneously). If the difference still exceeds the standard after adjustment, the injection pressure should be adjusted again (if an additional 0.5GU needs to be compensated, the pressure adjustment amount = 0.5GU ÷ 0.15GU / MPa ≈ 3.3MPa), etc., but not limited to this.

[0066] In one possible implementation, in step S400, the injection molding process parameters of the second material are dynamically adjusted based on the difference in gloss parameters, including:

[0067] S410, based on the difference in specular parameters, constructs process adjustment parameter curves for the first and second materials.

[0068] For example, a mapping relationship between a first specular parameter and a second specular parameter can be constructed. Then, based on the difference in specular parameters and the mapping relationship, the process adjustment range corresponding to the difference in specular parameters can be determined. Finally, based on the mapping relationship and the corresponding process adjustment range, process adjustment parameter curves for the first material and the second material can be fitted and generated. Alternatively, the first material, the second material, and the difference in specular parameters can be input into the learning model, and the learning model can output the corresponding process adjustment parameter curves, and so on, but not limited to these methods. The learning model is trained using multiple sets of training data. Each set of training data includes the first material, the second material, the difference in specular parameters, and the corresponding process adjustment parameter curves.

[0069] In one possible implementation, in step S410, based on the difference in specular parameters, a process adjustment parameter curve for the first material and the second material is constructed, including:

[0070] S411, construct the mapping relationship between the first highlight parameter and the second highlight parameter.

[0071] It is understandable that a quantitative correlation equation between the two material parameters can be established using statistical methods to make the mapping relationship calculable. Using the first highlight parameter as the independent variable (x) and the second highlight parameter as the dependent variable (y), gloss and smoothness are fitted separately: For gloss, linear regression yields y = 1.02x + 5.2 (R² = 0.96), indicating that for every 1 GU change in ABS gloss, PMMA gloss changes by 1.02 GU, with the baseline value being 5.2 GU higher; for smoothness, the fitted equation is y = 0.85x - 0.01 (R² = 0.95), indicating that for every 0.1 μm change in ABS smoothness, PMMA smoothness changes by 0.085 μm, with the baseline value being 0.01 μm lower.

[0072] S412, based on the difference in highlight parameters and the mapping relationship, determine the process adjustment range corresponding to the difference in highlight parameters.

[0073] It is understandable that the process adjustment range is used to reflect the specific quantitative value of the adjustment required to the injection molding process parameters of the second material in order to eliminate the deviation between the actual surface quality of the second material and the ideal quality determined by the reference of the first material plus the intrinsic difference of the material. For example, based on the mapping relationship, the correlation weights of the first and second highlight parameters in different numerical ranges can be determined. Then, according to the numerical range of the highlight parameter difference, the corresponding correlation weight is called, and the highlight parameter difference is multiplied by the correlation weight to obtain the process adjustment range corresponding to the highlight parameter difference. Alternatively, a sensitivity database of process parameters and highlight parameters can be constructed. When an abnormal process difference occurs in actual production, the parameter with the highest sensitivity (cavity temperature) is selected first to calculate the adjustment amount, and so on, but not limited to these methods. The construction of the sensitivity database of process parameters and highlight parameters can be carried out in a laboratory environment by fixing other parameters and adjusting only the target parameter (such as the cavity temperature being gradually increased from 55℃ to 75℃ in 5℃ increments), collecting the second highlight parameter corresponding to each set of parameters, and calculating the sensitivity coefficient (the change in highlight parameter for every 1 unit change in the parameter). For example, for PMMA material: Cavity temperature sensitivity: for every 1°C increase, gloss increases by 0.35 GU (coefficient K1=0.35 GU / °C) and smoothness improves by 0.009 μm (K2=0.009 μm / °C); Injection pressure sensitivity: for every 1 MPa increase, gloss increases by 0.18 GU (K3=0.18 GU / MPa) and smoothness improves by 0.007 μm (K4=0.007 μm / MPa).

[0074] In one possible implementation, step S412 involves determining the process adjustment range corresponding to the highlight parameter difference based on the highlight parameter difference and the mapping relationship, including:

[0075] S4121, Based on the mapping relationship, determine the association weights of the first highlight parameter and the second highlight parameter in different numerical ranges.

[0076] It is understandable that the correlation weight quantifies the degree of influence of the first highlight parameter on the second highlight parameter within different numerical ranges. Based on the fitted equation of the mapping relationship and the process standard range of the first material, the first highlight parameter is divided into "low range, medium range, and high range," with each range reflecting the difference in the parameter's influence on the second material. For example, the process standard for the gloss of the first material (ABS) is 80-90 GU. Combining the mapping equation y=1.02x+5.2 (PMMA gloss), the ranges are divided as follows: Low range 80≤x<83GU (corresponding to the ideal PMMA gloss of 86-89.6GU; in this range, ABS gloss is relatively low, and PMMA is more sensitive to its changes); Medium range 83≤x<87GU (corresponding to the ideal PMMA gloss of 89.6-93.7GU; ABS gloss is stable, and PMMA sensitivity is moderate); High range 87≤x≤90GU (corresponding to the ideal PMMA gloss of 93.7-97GU; ABS gloss is relatively high, and PMMA sensitivity is decreased). The logic for dividing the smoothness intervals is consistent. For example, the smoothness standard for the first material (ABS) is 0.5-0.7μm. Combining this with the mapping equation y=0.85x-0.01 (PMMA smoothness), it is divided into a low interval (0.5≤x<0.55μm), a medium interval (0.55≤x<0.65μm), and a high interval (0.65≤x≤0.7μm). Then, within each interval, the actual change in the second highlight parameter (i.e., interval sensitivity) is calculated when the first highlight parameter changes by 1 unit. This value is the core basis for the correlation weight. For example, for the low gloss range (80-83 GU), three typical values ​​(e.g., 80, 81.5, 83 GU) are selected. ABS and PMMA are injection molded under the same process, and the PMMA gloss is measured: when ABS=80 GU, PMMA=86 GU; when ABS=81.5 GU, PMMA=88.5 GU; when ABS=83 GU, PMMA=89.6 GU. The range sensitivity is calculated as (89.6-86) ÷ (83-80) ≈ 1.2 GU / GU (for every 1 GU increase in ABS, PMMA increases by 1.2 GU). Similarly, the sensitivity in the middle range (83-87 GU) is ≈ 1.02 GU / GU (consistent with the slope of the mapping equation), and the sensitivity in the high range (87-90 GU) is ≈ 0.85 GU / GU. The logic for calculating the flatness interval sensitivity is the same. For example, the sensitivity of the middle interval (0.55-0.65μm) is ≈0.85μm / μm (consistent with the slope of the mapping equation), the sensitivity of the low interval is ≈0.95μm / μm, and the sensitivity of the high interval is ≈0.75μm / μm. Finally, the sensitivity of each interval is converted into a correlation weight in the range of 0-1.

[0077] S4122, based on the numerical range of the highlight parameter difference, calls the corresponding associated weight.

[0078] It can be understood that the difference in specular parameters = actual parameters of the second material - reference parameters of the first material. First, the range to which the specular parameter belongs is determined based on the reference parameters of the first material. Then, the difference is used to determine the baseline range corresponding to the actual parameters of the second material. For example, if the reference gloss of the first material is 82 GU (belonging to the low range of 80-83 GU), and the actual gloss of the second material is 85 GU, the difference is 85 - 82 = -3 GU. In this case, the difference corresponds to the difference under the baseline of the low range of the first material, and it needs to be located in the low range of the first material, not the parameter range of the second material. Based on the located range, the corresponding association weight is retrieved from the database.

[0079] S4123, multiply the difference in highlight parameters with the associated weight to obtain the process adjustment range corresponding to the difference in highlight parameters.

[0080] It is understandable that, since the correlation weight is a positive number (which only reflects the intensity of the influence, not the direction), we can first take the absolute value of the difference in the highlight parameters (to ensure that the adjustment range is positive, and the direction is determined by the positive or negative value of the difference), and then combine the positive or negative value of the difference to determine the adjustment direction (for example, if the gloss difference is negative, the temperature needs to be increased to improve the gloss; if it is positive, the temperature needs to be decreased). For example, a gloss difference of -3GU (absolute value 3GU) corresponds to an adjustment direction of "increasing cavity temperature"; a smoothness difference of +0.05μm (absolute value 0.05μm) corresponds to an adjustment direction of "increasing holding pressure (improving smoothness)". Multiplying the absolute value of the difference by the corresponding associated weight yields the basic adjustment range. For example, with an absolute value of 3GU for the gloss difference and an associated weight of 1.0, the basic adjustment range is 3 × 1.0 = 3GU (the gloss difference to be compensated). Given that the sensitivity coefficient of cavity temperature to PMMA gloss is 0.35GU / ℃ (for every 1℃ increase, gloss increases by 0.35GU), the actual temperature adjustment is 3 ÷ 0.35 ≈ 8.6℃ (an increase of 8.6℃). Similarly, for flatness: the absolute value of the difference is 0.05μm, the correlation weight is 0.85, and the basic adjustment range is 0.05×0.85=0.0425μm; the pressure sensitivity coefficient is 0.007μm / MPa (for every 1MPa increase, the flatness improves by 0.007μm), so the pressure adjustment is 0.0425÷0.007≈6.1MPa (an increase of 6.1MPa).

[0081] This setup, by dividing the numerical ranges of the first and second specular parameters based on mapping relationships and determining corresponding correlation weights, can accurately capture the nonlinear correlation characteristics of the surface parameters of the two materials under different quality benchmarks (e.g., when the specular parameter of the first material is in a low range, the second material is more sensitive to its changes and needs to be assigned a higher weight). Then, based on the range of the specular parameter difference, an appropriate weight is applied, and the difference is converted into a process adjustment range through multiplication, allowing the adjustment intensity to dynamically match the difference compensation requirements. For example, for the same gloss difference, a larger adjustment range can be calculated using a high weight in the low range (high sensitivity) of the first material, while a moderate adjustment range can be obtained using a low weight in the high range (low sensitivity). This reduces the risk of insufficient adjustment in the low range leading to an excessive difference, while also preventing excessive adjustment in the high range from causing new defects such as material degradation and surface bubbles.

[0082] S413, Based on the mapping relationship and the corresponding process adjustment range, fit and generate the process adjustment parameter curves of the first material and the second material.

[0083] It is understandable that, since the influence of process parameters on gloss parameters is often nonlinear (e.g., gloss is significantly improved in the early stage of cavity temperature rise; when the temperature approaches the material melting limit, the improvement effect gradually weakens), a quadratic polynomial model or B-spline curve model is usually preferred. Taking the cavity temperature adjustment amount (ΔT) as an example, with the gloss process abnormality difference (x1) and the flatness process abnormality difference (x2) as independent variables and ΔT as the dependent variable, a quadratic polynomial equation is obtained by fitting the sample data: ΔT=0.12x1²+0.85x1+0.3x2²+1.2x2+0.5. In the equation, the absolute value of the coefficient of x1 is greater than that of x2, reflecting the process logic of prioritizing the adjustment of gloss difference (appearance is more critical for cabin parts). The introduction of quadratic terms (x1², x2²) accurately captures nonlinear relationships. For example, when x1 = -5GU (severely low), ΔT = 0.12 × 25 + 0.85 × (-5) + ... = 3 - 4.25 + ..., reducing the excessive amplification of adjustment caused by the linear model (e.g., the linear model may calculate ΔT = 15℃, exceeding the equipment's safe range). The fitting process uses the least squares method to minimize the error between the predicted value and the actual sample adjustment range, and must satisfy the model's coefficient of determination R² ≥ 0.95 (gloss-related) and R² ≥ 0.93 (smoothness-related), so as to improve the curve's explanatory power and prediction accuracy for discrete samples.

[0084] This setup, by first establishing a mapping relationship between the first and second specular parameters, allows for precise quantification of the intrinsic differences between the two materials due to their inherent properties. This eliminates the interference of these differences on subsequent process adjustments and avoids misjudging the material's natural properties as process issues. Then, based on the specular parameter difference and the mapping relationship, the process adjustment range is determined, transforming actual quality deviations into executable process operations. This ensures that the adjustment direction aligns with the coupling characteristics of the two materials, preventing over- or under-adjustment. Finally, by combining the mapping relationship with the adjustment range to generate a process adjustment parameter curve, the discrete adjustment logic is transformed into a continuous and reusable mathematical model, enabling automated control of the input difference as the output adjustment scheme.

[0085] S420 dynamically adjusts the injection molding process parameters of the second material based on the process adjustment parameter curve.

[0086] For example, a target curve segment can be determined based on the process adjustment parameter curve, and then the injection molding process parameters of the second material can be dynamically adjusted based on the target curve segment. Alternatively, for the current difference in gloss parameters (such as gloss -3.0GU, smoothness +0.05μm), the corresponding adjustment amounts can be matched in the "temperature adjustment curve", "pressure adjustment curve", and "holding time adjustment curve" respectively: the temperature curve outputs +9.5℃, the pressure curve outputs +2.2MPa, and the holding time curve outputs +1.5 seconds. Then, the weights are assigned according to the priority of the injection molding process parameters' influence on the gloss parameters (such as temperature weight 0.6, pressure weight 0.3, and holding time weight 0.1). If the total adjustment amount exceeds the equipment load (such as temperature +9.5℃ + pressure +2.2MPa may cause melt overheating), the adjustment amount is compressed according to the weight ratio: the temperature is compressed to +9℃ (0.6 × total compression amount 0.5℃), the pressure is compressed to +2.0MPa (0.3 × total compression amount 0.2MPa), and the holding time is maintained at +1.5 seconds, etc., but not limited to these.

[0087] With this setup, by first constructing the process adjustment parameter curves of the first and second materials based on the difference in specular parameters, the discrete correlation between the surface quality difference of the two materials and the amount of process adjustment can be transformed into a continuous and reusable mathematical model, accurately quantifying the optimal process adjustment rules corresponding to different differences.

[0088] In one possible implementation, in step S420, the injection molding process parameters of the second material are dynamically adjusted based on the process adjustment parameter curve, including:

[0089] S421, determine the target curve segment based on the process adjustment parameter curve.

[0090] It is understandable that determining the target curve segment based on the process adjustment parameter curve involves accurately locating the effective adjustment range that matches the current production scenario (gloss parameter difference, material condition, equipment limitations) from the complete curve. For example, the corresponding position of the gloss parameter difference on the process adjustment parameter curve can be determined, then the continuous curve interval at that position can be extracted, and finally, the continuous curve interval can be extended over a preset range on the process adjustment parameter curve to obtain the target curve segment. Alternatively, weights can be assigned according to the importance of the target, such as a weight of 0.5 for appearance accuracy (gloss and smoothness meet standards), 0.3 for production efficiency (no need for secondary adjustments after adjustment), and 0.2 for cost control (small adjustment amount, low energy consumption). Then, each interval of the process adjustment parameter curve can be scored, and the interval with the highest weighted total score can be selected as the target curve segment, and so on, but not limited to these methods.

[0091] In one possible implementation, step S421, determining the target curve segment based on the process adjustment parameter curve, includes:

[0092] S4211, Determine the corresponding position of the highlight parameter difference in the process adjustment parameter curve based on the process adjustment parameter curve.

[0093] It can be understood that the process adjustment parameter curve uses the difference in gloss parameters as the horizontal axis (independent variable x) and the process adjustment range as the vertical axis (dependent variable y), and establishes independent curves for gloss and smoothness respectively (such as "gloss difference - temperature adjustment curve" and "smoothness difference - pressure adjustment curve"). For example, the mathematical model of the gloss adjustment curve is y = 0.12x² + 0.85x + 0.5 (x is the gloss process abnormality difference, and y is the cavity temperature adjustment amount). It is necessary to first identify the curve type corresponding to the current difference (such as the temperature curve corresponding to the gloss difference), substitute the difference into the curve mathematical model, calculate the corresponding vertical axis coordinate (adjustment range), and obtain a unique coordinate point on the curve. For example, substituting x=-3.2GU into the temperature adjustment curve, we can calculate y=0.12×(-3.2)²+0.85×(-3.2)+0.5≈0.12×10.24-2.72+0.5≈1.23-2.72+0.5≈-0.99℃ (this is just an example; the actual adjustment should be positive and needs to be corrected based on the curve model). That is, the coordinates of the point on the curve are (-3.2GU, -0.99℃).

[0094] S4212, extract the continuous curve interval at the corresponding position.

[0095] It can be understood that a basic range is formed by expanding a fixed step size (set according to the common fluctuation range of the difference in production, such as ±0.3GU or ±0.02μm) in both positive and negative directions, centered on the difference in positioning points. For example, if the difference in positioning points is -3.2GU and the step size is set to ±0.3GU, then the basic range is -3.5GU to -2.9GU; if the flatness difference is +0.06μm and the step size is ±0.02μm, then the basic range is +0.04μm to +0.08μm.

[0096] S4213 extends the continuous curve interval over a preset range on the process adjustment parameter curve to obtain the target curve segment.

[0097] It is understandable that the core of extending the continuous curve range is to add a buffer range to the basic range to cope with unforeseen small fluctuations in differences during production (such as ±0.2GU changes caused by batch differences in raw materials), avoiding the need to frequently re-extract the target segment due to differences exceeding the basic range, and improving the flexibility and stability of adjustments. The preset range can be manually entered, matched through the injection molding database, etc., but is not limited to these methods.

[0098] This setup, by first precisely locating the corresponding position of the highlight parameter difference on the process adjustment parameter curve, reduces the adjustment deviation caused by traditional fuzzy interval positioning, ensuring that the adjustment anchor point perfectly matches the actual quality difference. Then, by extracting the continuous curve interval at the corresponding position, invalid areas such as abrupt changes and missing data segments in the curve can be eliminated, ensuring that subsequent adjustments follow a smooth process change pattern and reducing defects such as surface bubbles and shrinkage marks caused by sudden parameter changes. Finally, the continuous interval is extended to a preset range, which can cover small changes in the difference caused by raw material batches and environmental temperature fluctuations during production (such as ±0.2GU / ±0.02μm), eliminating the need for frequent re-extraction of the interval and improving the continuity of adjustment.

[0099] S422, dynamically adjust the injection molding process parameters of the second material based on the target curve segment.

[0100] For example, the process adjustment parameter value corresponding to the difference between the target curve segment and the current highlight parameter can be extracted, and the injection molding process parameters of the second material can be adjusted in real time; or when the target curve segment contains the adjustment rules of multiple process parameters (such as temperature, pressure, and holding time), the adjustment amount of each parameter needs to be extracted from the curve segment, and the adjustment priority is allocated according to the influence weight of the parameter on the highlight parameter, etc., but not limited to this.

[0101] This setup, by first determining the target curve segment based on the process adjustment parameter curve, allows for the precise selection of effective intervals from the complete curve that are suitable for the current production scenario (difference range, equipment limitations, material characteristics), eliminating invalid or risky intervals (such as extreme segments exceeding equipment capabilities), and reducing the risk of inaccurate adjustments or safety hazards caused by blindly using the entire curve. Then, the injection molding process parameters of the second material are dynamically adjusted based on the target curve segment. This not only ensures that the adjustment amount accurately matches the real-time difference by relying on the continuous pattern of the curve segment, but also addresses small fluctuations in the difference during production (such as ±0.2GU changes caused by batch differences in raw materials) through the preset range of the curve segment, eliminating the need for frequent recalculation of the adjustment plan.

[0102] In one possible implementation, step S422 involves dynamically adjusting the injection molding process parameters of the second material based on the target curve segment, including:

[0103] Extract the process adjustment parameter value corresponding to the difference between the target curve segment and the current highlight parameter, and adjust the injection molding process parameters of the second material in real time.

[0104] With this setting, the process adjustment parameter value corresponding to the difference between the target curve segment and the current highlight parameter is directly extracted and adjusted. The target curve segment has a preset effective range adapted to the current scene. The difference and the adjustment amount have a unique correspondence, which can respond quickly and further improve the stability and consistency of injection molding.

[0105] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0106] Corresponding to the two-color high-gloss injection molding method for automotive engine compartment parts described in the above embodiments, this application also provides a two-color high-gloss injection molding system for automotive engine compartment parts. Each module of this system can realize each step of the two-color high-gloss injection molding method for automotive engine compartment parts. Figure 3 A structural block diagram of a two-color high-gloss injection molding system for automotive cabin parts provided in this application embodiment is shown. For ease of explanation, only the parts related to this application embodiment are shown.

[0107] Reference Figure 3 The dual-color high-gloss injection molding system for automotive cabin components includes:

[0108] The first determining module is used to determine reference highlight parameters based on the first highlight parameters when the first material is injected into the base layer of the automotive engine compartment component; wherein, the first highlight parameters are used to indicate the gloss and smoothness parameters of the molded surface of the first material during the molding process in the mold cavity.

[0109] The second determining module is used to respond to the completion of injection molding of the first material and the switching of the mold cavity to the injection molding station of the second material, to perform the operation of the functional layer of the second material injection molding machine chamber, and at the same time determine the second gloss parameter during the injection molding of the second material; wherein, the second gloss parameter is used to indicate the gloss and flatness parameters of the surface of the second material during the molding process in the molding cavity.

[0110] The generation module is used to generate the difference in specular parameters based on the second specular parameter and the reference specular parameter.

[0111] The adjustment module is used to dynamically adjust the injection molding process parameters of the second material based on the difference in the highlight parameters when the difference in the highlight parameters is greater than the preset highlight threshold.

[0112] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0113] Those skilled in the art will understand that, for the sake of convenience and brevity, the above-described module division is merely an example. In practical applications, the above functions can be assigned to different modules as needed, that is, the internal structure of the system can be divided into different modules to complete all or part of the functions described above. The modules in the embodiments can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0114] This application also provides a two-color high-gloss injection molding equipment for automotive cabin parts, including an injection molding device and a control device, wherein the control device is electrically connected to the injection molding device. Figure 4 This is a schematic diagram of the structure of a control device 6 provided in an embodiment of this application. Figure 4 As shown, the control device 6 in this embodiment includes: at least one processor 60 ( Figure 4 Only one is shown in the image), at least one memory 61 ( Figure 4(Only one is shown in the image) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60, wherein when the processor 60 executes the computer program 62, it causes the control device 6 to perform the steps in any of the above embodiments of the two-color high-gloss injection molding method for automotive cabin parts, or causes the control device 6 to perform the functions of each module in the above system embodiments.

[0115] For example, the computer program 62 may be divided into one or more modules / units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 62 in the control device 6.

[0116] The control device 6 can be a desktop computer, laptop, handheld computer, or cloud server, etc. The dual-color high-gloss injection molding equipment for the automotive engine compartment parts may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that... Figure 4 This is merely an example of control device 6 and does not constitute a limitation on control device 6. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0117] The processor 60 can be a Central Processing Unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0118] In some embodiments, the memory 61 may be an internal storage unit of the control device 6, such as a hard disk or memory of the control device 6. In other embodiments, the memory 61 may be an external storage device of the control device 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the control device 6. Furthermore, the memory 61 may include both internal storage units and external storage devices of the control device 6. The memory 61 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of computer programs. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0119] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0120] This application provides a computer program product that, when run on a two-color high-gloss injection molding machine for automotive engine compartment parts, enables the two-color high-gloss injection molding machine for automotive engine compartment parts to perform the steps in any of the above-described method embodiments.

[0121] 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, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to a two-color high-gloss injection molding equipment for automotive engine compartment parts, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0122] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0123] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0124] In the embodiments provided in this application, it should be understood that the disclosed two-color high-gloss injection molding equipment and system for automotive engine compartment parts can be implemented in other ways. For example, the embodiments of the two-color high-gloss injection molding system for automotive engine compartment parts described above are merely illustrative. For instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0125] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0126] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for two-color high-gloss injection molding of automotive engine compartment parts, characterized in that, include: Based on the first gloss parameter when the first material is injected into the base layer of the automotive engine compartment component, a reference gloss parameter is determined; wherein, the first gloss parameter is used to indicate the gloss and smoothness parameters of the molded surface of the first material during the molding process in the mold cavity; In response to the completion of injection molding of the first material and the switching of the mold cavity to the injection molding station of the second material, the operation of the functional layer of the second material injection molding machine is executed, and the second gloss parameter during the injection molding of the second material is acquired; wherein, the second gloss parameter is used to indicate the gloss and smoothness parameters of the surface of the second material during the molding process in the molding cavity. Generate a specular parameter difference based on the second specular parameter and the reference specular parameter; When the difference in the highlight parameters is greater than a preset highlight threshold, the injection molding process parameters of the second material are dynamically adjusted based on the difference in the highlight parameters. The determination of reference highlight parameters, based on the first highlight parameter when injection molding the base layer of the automotive engine compartment component using the first material, includes: A timing map of highlight parameters is generated based on the first highlight parameters of the base layer of the automotive engine compartment component when the first material is injection molded. The timing map of highlight parameters is used to reflect the changes in the surface highlight parameters of the base layer formed by the first material as the injection molding progress progresses. The stable forming stage was identified based on the time sequence diagram of the high-light parameters; Based on the average value of the parameters calculated during the stable forming stage, the average value of the parameters is determined as the reference specular parameters; The step of dynamically adjusting the injection molding process parameters of the second material based on the difference in high-gloss parameters includes: Based on the difference in the high-gloss parameters, process adjustment parameter curves for the first material and the second material are constructed. Based on the process adjustment parameter curve, the injection molding process parameters of the second material are dynamically adjusted. The dynamic adjustment of the injection molding process parameters of the second material based on the process adjustment parameter curve includes: The target curve segment is determined based on the process adjustment parameter curve; Extract the process adjustment parameter value corresponding to the difference between the target curve segment and the current highlight parameter, and adjust the injection molding process parameters of the second material in real time.

2. The two-color high-gloss injection molding method for automotive engine compartment parts as described in claim 1, characterized in that, The step of constructing process adjustment parameter curves for the first material and the second material based on the difference in specular parameters includes: Construct a mapping relationship between the first specular parameter and the second specular parameter; Based on the difference in the highlight parameters and the mapping relationship, the process adjustment range corresponding to the difference in the highlight parameters is determined; Based on the mapping relationship and the corresponding process adjustment range, process adjustment parameter curves for the first material and the second material are fitted and generated.

3. The two-color high-gloss injection molding method for automotive engine compartment parts as described in claim 2, characterized in that, The step of determining the process adjustment range corresponding to the highlight parameter difference based on the highlight parameter difference and the mapping relationship includes: Based on the mapping relationship, the association weights of the first highlight parameter and the second highlight parameter in different numerical ranges are determined; Based on the numerical range of the difference in the highlight parameters, the corresponding associated weights are invoked; The process adjustment range corresponding to the difference in highlight parameters is obtained by multiplying the difference in highlight parameters with the associated weight.

4. The two-color high-gloss injection molding method for automotive engine compartment parts as described in claim 1, characterized in that, The step of determining the target curve segment based on the process adjustment parameter curve includes: The position of the highlight parameter difference in the process adjustment parameter curve is determined based on the process adjustment parameter curve. Extract the continuous curve interval at the corresponding position; The continuous curve interval is extended over a preset range on the process adjustment parameter curve to obtain the target curve segment.

5. The two-color high-gloss injection molding method for automotive engine compartment parts as described in claim 1, characterized in that, The step of generating a specular parameter difference based on the second specular parameter and the reference specular parameter includes: Calculate the gloss difference and smoothness difference between the second highlight parameter and the reference highlight parameter, respectively; The parameter pair consisting of the gloss difference and the smoothness difference is determined as the specular parameter difference.

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