Step-by-step injection molding parameter control method and system for large joint angle sealing strip

Abstract

The invention provides a step-by-step injection molding parameter control method and system for a large joint angle sealing strip, and relates to the technical field of injection molding, and the method comprises the steps that step-by-step vulcanization splicing control logic corresponding to a large joint angle vulcanization splicing structure is deeply analyzed, process demand differences of different molding stages are identified, and a molding operation period is configured; the cooperative work proportion of the common mold unit and the independent work quota of the special mold unit are determined; adjusting the vulcanization temperature section of the core forming process and the dynamic pressure section of the auxiliary forming process, and establishing a forming parameter optimization model; and on the basis of the forming parameter optimization model, process execution parameters and splicing precision in a forming operation period are optimized, and a step-by-step injection forming control strategy is obtained. The technical problem that in the prior art, the step-by-step injection molding parameter control quality of the large joint angle sealing strip is poor can be solved, and the technical effect of improving the step-by-step injection molding parameter control quality is achieved.

Description

Technical Field

[0001] This application relates to the field of injection molding technology, and in particular to a method and system for controlling step-by-step injection molding parameters for large corner sealing strips. Background Technology

[0002] With the increasing demands for sealing performance, durability, and aesthetic consistency from the automotive, rail transit equipment, and high-end rubber sealing product industries, EPDM sealing strip molding technology based on injection molding has gradually become an important technical route in the sealing product manufacturing field. Among these processes, the large-corner vulcanization injection molding process involving complex geometries has become a critical factor affecting product quality. In this type of injection molding process, the flow behavior of the rubber compound within the mold, the temperature field distribution, and the pressure loading path all directly affect the vulcanization uniformity and splicing reliability of the corner areas.

[0003] Currently, existing sealing strip vulcanization splicing processes generally rely on fixed temperature settings, static pressure loading, and experience-based molding cycles to maintain molding stability. These processes typically lack a refined differentiation and dynamic control mechanism for process parameters at different stages of injection molding. However, in practical applications, due to significant differences in heat requirements at different molding stages, inconsistent compatibility levels of mold units, fluctuations in rubber vulcanization kinetics, and the particular sensitivity of the joint area to crosslinking rates, traditional processes struggle to achieve precise matching. This leads to problems such as uneven vulcanization, weak splicing, wrinkling and separation, and high energy consumption. Furthermore, existing process adjustment strategies often focus on single parameters or a few process variables, lacking global optimization capabilities for the entire molding cycle. They cannot systematically analyze the coupled effects between multiple variables such as mold opening and closing frequency, injection pressure fluctuations, and temperature zone switching thresholds, resulting in significant lag and uncertainty in process adjustment.

[0004] In summary, the existing technology suffers from a lack of a process configuration mechanism that dynamically identifies changes in heat demand at different molding stages and simultaneously adjusts the temperature and pressure paths. This results in rigid temperature settings and delayed pressure loading, making it difficult to achieve uniform vulcanization and stable splicing during the molding process. Consequently, it further affects the consistency of the molding quality and the reliability of the structural strength of the sealing strip. Summary of the Invention

[0005] The purpose of this application is to provide a step-by-step injection molding parameter control method and system for large corner sealing strips, in order to solve the technical problems in the prior art, which are caused by the lack of a process configuration mechanism that dynamically identifies changes in heat demand for different molding stages and synchronously adjusts the temperature and pressure path, resulting in rigid temperature settings and delayed pressure loading, making it difficult to achieve uniform vulcanization and stable splicing in the molding process, and further affecting the consistency of the molding quality and the reliability of the structural strength of the sealing strip.

[0006] In view of the above problems, this application provides a method and system for controlling the step-by-step injection molding parameters of large corner sealing strips.

[0007] Firstly, this application provides a step-by-step injection molding parameter control method for large corner sealing strips, implemented through a step-by-step injection molding parameter control system for large corner sealing strips. This includes: based on historical molding records of EPDM sealing strips and mold unit operation data, conducting in-depth analysis of the step-by-step vulcanization splicing control logic corresponding to the large corner vulcanization splicing structure, identifying the differences in process requirements at different molding stages, and configuring the molding operation cycle; simultaneously, determining the collaborative work ratio of shared mold units and the independent work quota of dedicated mold units based on the process synergy adaptability and stage-specific demand intensity of each molding stage; adjusting the M vulcanization temperature segments of the core molding process and the N dynamic pressure segments of the auxiliary molding process based on the collaborative work ratio of the shared mold units and the independent work quota of the dedicated mold units, and establishing a molding parameter optimization model; and optimizing the process execution parameters and splicing accuracy within the molding operation cycle based on the molding parameter optimization model to obtain a step-by-step injection molding control strategy.

[0008] Preferably, the step-by-step injection molding parameter control method for the large corner sealing strip further includes: grouping the process execution parameters of different molding stages, identifying the basic execution process, sensitive execution process, and cross-stage shared process of each molding stage, and generating a process requirement difference matrix; based on the process requirement difference matrix, extracting the historical molding records and the mold unit operation data, wherein the mold unit operation data includes mold opening and closing frequency, energy consumption ratio, and vulcanization temperature threshold set.

[0009] Preferably, the step-by-step injection molding parameter control method for the large corner sealing strip further includes: defining process synergy compatibility by scoring mold compatibility and vulcanization adaptability, and establishing a process synergy matching rule library by using the historical molding records and the mold specification requirements of the sealing strip at different molding stages; scoring mold compatibility based on the process synergy matching rule library, and obtaining the independent work quota of the dedicated mold unit by combining the stage-specific demand intensity.

[0010] Preferably, the step-by-step injection molding parameter control method for the large corner sealing strip further includes: identifying key vulcanization influencing factors that affect the splicing strength and vulcanization crosslinking uniformity of the sealing strip based on the process requirement difference matrix; and configuring M vulcanization temperature segments for adjusting the core molding process according to the key vulcanization influencing factors, molding process duration, and mold unit operation data.

[0011] Preferably, the step-by-step injection molding parameter control method for the large corner sealing strip further includes: determining a first vulcanization temperature threshold subset for the core molding process based on the key vulcanization influencing factors, molding process duration, and average operation time in the mold unit operation data; and setting the M vulcanization temperature segments based on the first vulcanization temperature threshold subset for the core molding process.

[0012] Preferably, the step-by-step injection molding parameter control method for the large corner sealing strip further includes: the auxiliary molding process is divided into an upper corner injection process, a lower corner splicing process, and a post-molding shaping process according to the process requirement cycle; by referring to the mold opening and closing frequency in the mold unit operation data, the upper corner injection process, the lower corner splicing process, and the post-molding shaping process, and in combination with the second vulcanization temperature threshold subset of the auxiliary molding process, the N dynamic pressure segments are configured, wherein the vulcanization temperature threshold set includes a first vulcanization temperature threshold subset and a second vulcanization temperature threshold subset.

[0013] Preferably, the step-by-step injection molding parameter control method for the large corner sealing strip further includes: the molding parameter optimization model is configured with optimization objectives to minimize molding energy consumption, minimize process response delay time, and minimize the probability of sealing strip wrinkling and separation; wherein, the minimized molding energy consumption is positively correlated with vulcanization temperature, the minimized process response delay time is positively correlated with mold opening and closing interval, and the minimized probability of sealing strip wrinkling and separation is positively correlated with injection pressure fluctuation amplitude.

[0014] Preferably, the step-by-step injection molding parameter control method for the large corner sealing strip further includes: the input parameters of the molding parameter optimization model include the collaborative work ratio of the shared mold unit, the independent work quota of the dedicated mold unit, the vulcanization temperature threshold set, and the dynamic pressure segmentation rule; the optimal parameter combination is iteratively solved according to the optimization objective and output, and the optimal parameter combination is written into the step-by-step injection molding control strategy.

[0015] Preferably, the step-by-step injection molding parameter control method for the large corner sealing strip further includes: configuring an objective function according to the optimization objective, and performing a fitness evaluation based on the objective function; simultaneously, using selection, crossover, and mutation operations, searching for the optimal parameter combination in the solution space that satisfies the constraints, including mold load requirements and sealing strip molding accuracy requirements.

[0016] Secondly, this application also provides a step-by-step injection molding parameter control system for large corner sealing strips, used to execute the step-by-step injection molding parameter control method for large corner sealing strips as described in the first aspect, including: a molding operation cycle configuration module, used to perform in-depth analysis of the step-by-step vulcanization splicing control logic corresponding to the large corner vulcanization splicing structure based on the historical molding records of EPDM sealing strips and the mold unit operation data, identify the differences in process requirements at different molding stages, and configure the molding operation cycle; an independent operation quota determination module, used to determine the collaborative work ratio of the shared mold unit and the independent operation quota of the dedicated mold unit based on the process synergy adaptability and stage-specific demand intensity of each molding stage; a molding parameter optimization model establishment module, used to adjust the M vulcanization temperature segments of the core molding process and the N dynamic pressure segments of the auxiliary molding process based on the collaborative work ratio of the shared mold unit and the independent operation quota of the dedicated mold unit, and establish a molding parameter optimization model; and a step-by-step injection molding control strategy acquisition module, used to optimize the process execution parameters and splicing accuracy within the molding operation cycle based on the molding parameter optimization model, and obtain a step-by-step injection molding control strategy.

[0017] The technical solution provided in this application has at least the following technical effects or advantages: by achieving the technical goal of dynamic parameter coordinated control based on the differences in process requirements throughout the molding cycle, it achieves the technical effects of improving the uniformity of vulcanization crosslinking, enhancing the strength of splicing interfaces, and improving molding stability.

[0018] The above description is merely an overview of the technical solution of this application. To enable a clearer understanding of the technical means of this application and to facilitate its implementation according to the description, and to make the above and other objects, features, and advantages of this application more apparent, specific embodiments of this application are described below. It should be understood that the content described in this section is not intended to identify key or important features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent through the following description. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the step-by-step injection molding parameter control method for the large corner sealing strip of this application.

[0021] Figure 2This is a schematic diagram of the step-by-step injection molding parameter control system for the large corner sealing strip of this application.

[0022] Figure labeling: Molding operation cycle configuration module 1, independent operation quota determination module 2, molding parameter optimization model establishment module 3, step-by-step injection molding control strategy acquisition module 4. Detailed Implementation

[0023] This application provides a step-by-step injection molding parameter control method and system for large-angle sealing strips. It solves the technical problem in existing technologies where the lack of a process configuration mechanism to dynamically identify changes in heat demand at different molding stages and synchronously adjust the temperature and pressure paths leads to rigid temperature settings and delayed pressure loading. This makes it difficult to achieve uniform vulcanization and stable splicing during the molding process, further affecting the consistency of the sealing strip's molding quality and the reliability of its structural strength. The application achieves the technical goal of dynamic parameter coordinated control based on the differences in process requirements throughout the molding cycle, thereby improving the uniformity of vulcanization crosslinking, enhancing the strength of the splicing interface, and improving molding stability.

[0024] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. It should be understood that this application is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application. It should also be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, not all of them.

[0025] Example 1, please refer to the appendix. Figure 1 This application provides a method for controlling the step-by-step injection molding parameters of a large corner sealing strip, which is applied to the step-by-step injection molding parameter control system of the large corner sealing strip, specifically including: S1: Based on the historical molding records of EPDM sealing strips and the operation data of the mold unit, a deep analysis of the step-by-step vulcanization splicing control logic corresponding to the large joint angle vulcanization splicing structure is conducted to identify the differences in process requirements at different molding stages and configure the molding operation cycle.

[0026] Furthermore, this application also includes: grouping the process execution parameters of different molding stages, identifying the basic execution processes, sensitive execution processes and cross-stage shared processes of each molding stage, and generating a process requirement difference matrix; based on the process requirement difference matrix, extracting the historical molding records and the mold unit operation data, wherein the mold unit operation data includes mold opening and closing frequency, energy consumption ratio, and vulcanization temperature threshold set.

[0027] Specifically, when grouping the process execution parameters for different molding stages, the parameter characteristics of each stage are categorized and analyzed using process parameters recorded during the molding process, such as temperature, pressure, time, material feed rate, and mold operation cycle time. This allows for the differentiation of basic execution processes that maintain stable operation under normal molding conditions, sensitive execution processes that are prone to quality fluctuations when the molding window changes or the material flow state is sensitive, and cross-stage shared processes that are called or continuously affect the process chain in multiple molding stages. Based on this, a process requirement difference matrix is ​​constructed to describe the degree of difference and interaction between various processes. The process requirement difference matrix consists of matrix row dimensions, matrix column dimensions, and corresponding difference measurement elements. The matrix row dimensions are used to characterize the grouped molding stages or process types, including at least two of the following: basic execution processes, sensitive execution processes, and cross-stage shared processes. The matrix column dimensions are used to characterize the key process requirement indicators for the corresponding process at different molding stages. Key process requirement indicators include at least the target temperature range, pressure holding level, time duration requirements, material feed rate stability requirements, and mold operation cycle time constraints. The matrix elements in the process requirement difference matrix are used to represent the degree of difference in requirements between different molding stages of the same process type or between different process types in the same molding stage. The degree of difference is calculated by comparing the numerical deviation, variation range or stability range of the corresponding key process requirement indicators, and can be characterized by normalized difference value, weighted difference value or relative sensitivity coefficient.

[0028] Subsequently, based on the process demand difference matrix, historical molding records and mold unit operation data were correlated and extracted. By using the parameter demand weights in the process demand difference matrix, molding data significantly impacting process stage differences were selected. Mold unit operation data includes mold opening and closing frequency (characterizing mold action frequency), energy consumption ratio (reflecting mold energy usage), and a set of vulcanization temperature thresholds (defining temperature ranges for different vulcanization stages). This allows for the extraction and correlation analysis of key operating states in the molding process. Parameter demand weights characterize the relative importance of different molding parameters in distinguishing process demand differences across molding stages; specifically, they are defined as the quantification coefficients of each molding parameter's contribution to the difference measurement elements in the process demand difference matrix. Molding parameters include at least vulcanization temperature, injection pressure, holding time, mold opening and closing cycle time, and material feeding stability. The parameter requirement weights are determined based on a combination of historical molding data statistical analysis and quality correlation analysis. Specifically, within multiple complete molding operation cycles, the correspondence between corresponding molding parameters and molding quality evaluation indicators is collected, and the parameter fluctuation amplitude and quality response sensitivity of each molding parameter at different molding stages are calculated. The parameter fluctuation amplitude reflects the degree of parameter change during stage switching, and the quality response sensitivity reflects the impact of parameter changes on splicing strength, crosslinking uniformity, or the probability of wrinkling and separation. Subsequently, each molding parameter is normalized based on the parameter fluctuation amplitude and quality response sensitivity, and the corresponding parameter requirement weights are generated using weighted summation or product mapping. Molding data is filtered through the parameter requirement weights in the process requirement difference matrix. Specifically, the molding data collected within the molding operation cycle is segmented and mapped according to molding stages, and the molding parameter value corresponding to each segment of molding data is weighted and calculated with its parameter requirement weight to form a stage-weighted feature vector. Subsequently, the degree of difference between the stage-weighted feature vectors and different molding stages is compared and analyzed. Among them, the quantitative standard of significant impact is determined by a preset difference threshold. The difference threshold is determined based on the statistical distribution range of the weighted feature vectors of each molding stage under historical stable molding conditions. When the weighted difference value of a certain molding data between different molding stages exceeds the difference threshold, it is determined that the molding data has a significant impact on the process stage difference and is selected as the effective input data for the subsequent molding parameter optimization model.

[0029] In the in-depth analysis of the step-by-step vulcanization splicing control logic corresponding to the large-angle vulcanization splicing structure, a systematic modeling of the vulcanization behavior, material flow path, heat transfer efficiency, and mold stress mode of the large-angle sealing strip at the splicing location is performed. The temperature escalation method, pressure loading sequence, rubber material propulsion rate, and mold response cycle involved in the control logic are analyzed. The large-angle vulcanization splicing structure characterizes the three-dimensional splicing geometry formed at the large-angle turning point of the sealing strip. The step-by-step vulcanization splicing control logic describes the control rules that are executed segment by segment according to preset stages in the vulcanization process. In-depth analysis refers to the full-process mechanism decomposition and multi-dimensional correlation calculation of these control rules, thereby clarifying the impact path of the control logic on the product molding quality. The systematic modeling of the vulcanization behavior, material flow path, heat transfer efficiency, and mold stress mode of the large-angle sealing strip at the splicing location includes establishing sub-models of vulcanization reaction kinetics, rubber material flow behavior, heat conduction and convection coupling, and mold mechanical response, respectively. A multi-physics coupling model is constructed through time step synchronization. Among them, the vulcanization reaction kinetics sub-model is established based on the activation temperature threshold of the vulcanizing agent and the reaction rate function, and is used to describe the law of crosslinking rate changing with time in different temperature ranges; the rubber flow behavior sub-model is based on the mold cavity geometry and injection pressure change curve, and describes the propulsion path, shear rate distribution and filling uniformity of the rubber in the large joint area; the heat conduction and convection coupling sub-model is used to characterize the mold cavity temperature gradient, the internal heat diffusion efficiency of the rubber and the interface heat exchange process; the mold mechanical response sub-model is used to describe the deformation response, closure stability and constraint effect on the flow of rubber under different pressure loading sequences. Furthermore, the analysis of the temperature escalation method, pressure loading sequence, rubber material propulsion rate, and mold response cycle involved in the control logic is specifically achieved by solving the state variables of the multiphysics coupling model in each step of vulcanization. Specifically, the temperature escalation method is characterized by the time series of discrete temperature nodes; the pressure loading sequence is described by the time series function of injection pressure and holding pressure; the rubber material propulsion rate is calculated as a function of the flow front displacement over time; and the mold response cycle is quantified by the time interval between mold opening and closing actions and force changes. Further, the in-depth analysis method specifically includes: calculating the vulcanization degree distribution, rubber material flow uniformity index, splicing interface thermal history curve, and mold stress stability index in each molding stage defined by the step vulcanization splicing control logic. These indices are then correlated and mapped with molding quality evaluation results such as splicing strength, crosslinking uniformity, and wrinkling / seam risk, thereby forming a causal relationship path between control parameter changes and molding quality response, used to clarify the impact mechanism of different control logic configurations on product molding quality.

[0030] Subsequently, to identify the differences in process requirements at different molding stages, a comparison of requirements was made for the preheating stage of the rubber compound before molding, the rubber compound injection stage at the splicing area, the vulcanization and curing stage, and the stabilization stage after molding. By analyzing the requirements of each stage on temperature range, pressure change rate, mold fitting accuracy, and material crosslinking rate, the differences in process requirements were determined. These differences in process requirements characterize the varying degrees of dependence of different stages on molding resources, process windows, and mold actions. The molding stage indicates a specific time period with an independent function within the entire molding process. The comparison of requirements for the preheating stage of the rubber compound before molding, the rubber compound injection stage at the splicing area, the vulcanization and curing stage, and the stabilization stage after molding was specifically achieved by constructing a process requirement vector for each molding stage. Each molding stage's process requirement vector consists of a temperature requirement range, a pressure change rate range, a mold fitting accuracy threshold, and a target value for the material crosslinking rate. The temperature requirement range characterizes the upper and lower limits of the temperature at which the rubber compound is in a stable operating state during this stage. The pressure change rate range characterizes the allowable range of pressure rise or fall slopes during injection or holding. The mold fitting accuracy threshold limits the allowable error range of the cavity gap after mold closure. The target value of the material crosslinking rate characterizes the target rate range of the vulcanization reaction progression during this stage. Further, the technical means for requirement comparison include: based on historical stable molding records and experimental calibration data, parameter normalization is performed on the process requirement vectors corresponding to each molding stage, and the requirement difference value between any two molding stages is calculated using vector distance or a weighted difference function. The weights of different process parameters in the difference calculation are pre-set based on their influence on splicing strength and crosslinking uniformity, or obtained through statistical analysis. The determination of process requirement differences is specifically based on the following: when the requirement difference value between a certain molding stage and other molding stages exceeds a preset difference threshold, it is determined that the molding stage has independent difference characteristics in process requirements; when the requirement difference value is within the threshold range, it is determined that the relevant molding stages have process synergy or can adopt a shared process configuration. The difference threshold is determined based on the statistical distribution of demand differences within the quality stability range during historical molding processes. By identifying these differences, the most significant changes in key demand points along the process flow can be determined, providing a basis for configuring molding parameters.

[0031] Next, when configuring the molding cycle, a work plan framework is constructed based on the differences in process requirements to calibrate the duration of each molding stage, the trigger sequence of each control action, and the mold switching rhythm. The molding cycle characterizes the complete process time structure from the entry of the rubber compound into the mold to the completion of vulcanization molding, including multi-stage, segmentable time slice configuration logic. The configuration process requires adjusting the time proportion of each stage according to the thermal management requirements, pressure transmission requirements, and mold response capabilities of different stages. This ensures that temperature stability, pressure continuity, and splicing accuracy are all satisfied during the molding process, thereby achieving a balanced and efficient molding production rhythm. Adjusting the time proportion of each stage according to the thermal management requirements, pressure transmission requirements, and mold response capabilities of different stages specifically includes: constructing stage time requirement models for the preheating stage of the rubber compound before molding, the rubber compound injection stage at the splicing area, the vulcanization heating and curing stage, and the post-molding stabilization stage. The stage time requirement models use the accumulated heat requirement value, the effective pressure transmission time requirement value, and the mold response compensation time as input parameters. The cumulative heat requirement value characterizes the effective heat integral required for the rubber compound to reach the target vulcanization or flow state within the corresponding molding stage. It is calculated based on the target temperature range, heating rate, and material specific heat parameters. The effective pressure transmission time requirement value characterizes the minimum duration for which pressure can stably act on the rubber compound within the molding stage. It is determined based on the injection pressure plateau value, pressure rise slope, and material viscoelastic response characteristics. The mold response compensation time characterizes the system response time required by the mold during opening, closing, locking, and thermal stabilization processes. It is obtained based on the mold opening and closing frequency, temperature control response delay, and historical stable running time statistics from the mold unit operation data. Furthermore, the cumulative heat requirement value, effective pressure transmission time requirement value, and mold response compensation time for each molding stage are normalized and weighted and summed according to preset weights to obtain the comprehensive time requirement index for the corresponding molding stage. The weights are set according to the degree of influence of thermal management requirements, pressure transmission requirements, and mold response capabilities on splicing strength and molding stability. Furthermore, using the total molding cycle time as a constraint, the corresponding stage time proportion is allocated according to the proportion of the comprehensive time requirement index of each molding stage in the total requirement index. By comparing and correcting with historical stable molding cycles, the actual execution time of each molding stage within the molding cycle is finally determined.

[0032] S2: At the same time, based on the process synergy and adaptability of each molding stage and the intensity of stage-specific requirements, determine the collaborative work ratio of shared mold units and the independent work quota of dedicated mold units.

[0033] Furthermore, this application also includes: defining process synergy compatibility based on mold compatibility and vulcanization adaptability scores, and establishing a process synergy matching rule library through the historical molding records and the sealing strip mold specification requirements of different molding stages; performing mold compatibility scoring based on the process synergy matching rule library, and obtaining the independent work quota of the dedicated mold unit by combining the stage-specific demand intensity.

[0034] Specifically, when defining process synergy compatibility using mold compatibility and vulcanization compatibility scores, a comprehensive evaluation is conducted on various molds used for molding large-angle sealing strips in terms of structural matching degree, heat equalization capability, flow channel layout, and rubber molding characteristics. Mold compatibility characterizes the degree of matching between the mold structure and the process conditions at different molding stages; vulcanization compatibility describes the mold's adaptability to rubber properties during vulcanization heating, cross-linking curing, and heat preservation stabilization; and process synergy compatibility reflects the mold's ability to achieve stable molding when working in conjunction with process requirements. Furthermore, by retrieving historical molding records and combining them with the mold specifications required for sealing strips at different molding stages, a process synergy matching rule library is established to describe the correspondence, matching rules, and adaptation boundary conditions between molds and processes, thereby achieving correlation modeling of mold usage characteristics and process execution requirements.

[0035] Subsequently, when scoring mold compatibility based on the process collaborative matching rule base, the mold's structural features, response speed, and temperature control capability are compared with the required parameters of the process stage using the pre-set matching logic in the rule base, resulting in a more detailed compatibility score. The compatibility score quantifies the degree to which the mold meets the process requirements. When comparing the mold's structural features, response speed, and temperature control capability with the required parameters of the process stage, structural features include at least the matching degree of cavity geometry, the curvature continuity of the corner transition area, the distribution and number of flow channels, the density of heating elements, and the fitting accuracy of the mold's closed surface. These characteristics characterize the mold's ability to meet the material flow and splicing requirements of different molding stages at the physical structure level. Response speed includes at least the average response time of mold opening and closing actions, the start-up lag of the actuator, and the time for pressure loading to reach a stable state. This reflects the mold's ability to follow staged process actions after the process command is triggered. Temperature control capability includes at least the deviation range between the target temperature and the measured temperature of the cavity, the stability of the heating and cooling rates, and the temperature gradient distribution in different cavity areas. This characterizes the mold's control accuracy and uniformity of heat input during vulcanization. Furthermore, by combining the stage-specific demand intensity, which characterizes the degree of specific dependence of a molding stage on mold performance or process resources, and using the mold compatibility score as the basic indicator reflecting the ability of a mold unit to stably execute process tasks under the target molding stage, and using the stage-specific demand intensity as an adjustment factor characterizing the degree of dependence of the molding stage on mold performance, the mold compatibility score is normalized to ensure that the score results of different mold units are within a comparable range. The normalized score results are then weighted and corrected according to the stage-specific demand intensity to obtain the corresponding independent work quota for allocating each dedicated mold unit. The independent work quota is used to limit the work duration or work proportion that the mold unit can independently participate in throughout the entire molding operation cycle, so as to ensure the dynamic matching of resource input and process requirements.

[0036] When determining the collaborative work ratio of shared mold units based on the process synergy adaptability and stage-specific demand intensity of each molding stage, a quantitative analysis is conducted on the requirements of each molding stage in terms of temperature transfer capability, pressure response continuity, material flow stability, and mold operation cycle time. Process synergy adaptability characterizes the ability of the mold unit to achieve stable vulcanization, uniform filling, and reliable splicing when working in conjunction with the process conditions of that stage. Subsequently, the two types of indicators are normalized, and the collaborative work ratio undertaken by the shared mold unit in the multi-stage molding sequence is dynamically evaluated through a joint calculation method of the adaptability contribution and demand intensity ratio of different stages. This collaborative work ratio is used to limit the proportion of work, load level, and control rhythm that the shared mold unit needs to participate in throughout the entire molding cycle, ensuring that it meets the process requirements of key stages while maintaining the overall production synergy and resource utilization balance. The method of jointly calculating the adaptability contribution and demand intensity ratio at different stages specifically includes: for each molding stage, obtaining the corresponding process collaboration adaptability contribution parameter and stage-specific demand intensity parameter. The process collaboration adaptability contribution parameter characterizes the degree to which the shared mold unit supports process stability and molding accuracy within that molding stage, while the stage-specific demand intensity parameter characterizes the degree to which that molding stage relies on dedicated process resources. Further, the process collaboration adaptability contribution parameter and the stage-specific demand intensity parameter are first normalized to eliminate the influence of different dimensions on the joint calculation. After normalization, a weighted product operation is used to jointly calculate the two types of parameters to obtain the joint adaptability demand value for the corresponding molding stage. The expression for the weighted product operation is: the joint adaptability demand value equals the product of the normalized process collaboration adaptability contribution parameter and the normalized stage-specific demand intensity parameter, and is corrected according to a preset weighting coefficient. As an optional implementation method, the joint calculation method employs a weighted summation operation, which linearly superimposes the normalized process synergy and adaptability contribution parameter with the stage-specific demand intensity parameter according to their corresponding weights to obtain the joint adaptability demand value; wherein, the weight coefficients are determined based on historical molding stability data or experimental calibration results. Furthermore, based on the proportion of the joint adaptability demand value of each molding stage in the total joint adaptability demand value of all molding stages, the collaborative work ratio of shared mold units or the independent operation quota of dedicated mold units is determined, thereby achieving quantitative decision-making on mold resource allocation.

[0037] S3: Based on the collaborative work ratio of the shared mold unit and the independent work quota of the dedicated mold unit, adjust the M vulcanization temperature segments of the core molding process and the N dynamic pressure segments of the auxiliary molding process to establish a molding parameter optimization model.

[0038] Furthermore, this application also includes: identifying key vulcanization influencing factors that affect the splicing strength and vulcanization crosslinking uniformity of the sealing strip based on the process requirement difference matrix; and configuring M vulcanization temperature segments for adjusting the core molding process according to the key vulcanization influencing factors, molding process duration, and mold unit operation data.

[0039] Furthermore, this application also includes: determining a first vulcanization temperature threshold subset for the core molding process based on the key vulcanization influencing factors, molding process duration, and average operation time in the mold unit operation data; and setting the M vulcanization temperature segments based on the first vulcanization temperature threshold subset for the core molding process.

[0040] Furthermore, this application also includes: the auxiliary molding process is divided into upper corner injection process, lower corner splicing process, and post-molding shaping process according to the process requirement cycle; by referring to the mold opening and closing frequency in the mold unit operation data, the upper corner injection process, lower corner splicing process, and post-molding shaping process, and in combination with the second vulcanization temperature threshold subset of the auxiliary molding process, the N dynamic pressure segments are configured, wherein the vulcanization temperature threshold set includes a first vulcanization temperature threshold subset and a second vulcanization temperature threshold subset.

[0041] Furthermore, this application also includes: the molding parameter optimization model is configured with optimization objectives to minimize molding energy consumption, minimize process response delay time, and minimize the probability of sealing strip wrinkling and separation; wherein, the minimized molding energy consumption is positively correlated with vulcanization temperature, the minimized process response delay time is positively correlated with mold opening and closing interval, and the minimized probability of sealing strip wrinkling and separation is positively correlated with injection pressure fluctuation amplitude.

[0042] Furthermore, this application also includes: the input parameters of the molding parameter optimization model include the collaborative work ratio of the shared mold unit, the independent work quota of the dedicated mold unit, the vulcanization temperature threshold set, and the dynamic pressure segmentation rule; the optimal parameter combination is iteratively solved according to the optimization objective and output, and the optimal parameter combination is written into the step-by-step injection molding control strategy.

[0043] Furthermore, this application also includes: configuring an objective function according to the optimization objective, and performing a fitness evaluation based on the objective function; simultaneously, using selection, crossover, and mutation operations, searching for the optimal parameter combination within the solution space that satisfies the constraints, including mold load requirements and sealing strip forming accuracy requirements.

[0044] Specifically, based on the collaborative work ratio of shared mold units and the independent work quota of dedicated mold units, and using a process demand difference matrix to identify key vulcanization influencing factors affecting the splicing strength and vulcanization crosslinking uniformity of sealing strips, the process systematically screens key variables in the process chain that may cause a decrease in splicing strength or uneven crosslinking structure by correlating mold resource allocation with the demand differences of different molding stages. The collaborative work ratio of shared mold units characterizes the proportion of collaborative effects undertaken by this type of mold in multi-stage molding, while the independent work quota of dedicated mold units limits their ability to undertake independent processing tasks at specific stages. The process demand difference matrix describes the differences in temperature, pressure, material flowability, and mold response behavior at different stages. By identifying core variables directly affecting vulcanization quality—the key vulcanization influencing factors—these sensitive parameters of EPDM rubber compounds during vulcanizing agent activation, crosslinking reaction rate, heat absorption efficiency, and cavity temperature gradient changes are characterized. Furthermore, key control points related to insufficient joint strength and uneven crosslinking are located.

[0045] When determining the first vulcanization temperature threshold subset for the core molding process based on key vulcanization influencing factors, molding process duration, and average operating time from mold unit operation data, the reaction kinetics characteristics of EPDM rubber at different vulcanization stages were analyzed. Key vulcanization influencing factors were used to identify core variables affecting the vulcanization reaction rate, crosslink density formation, and heat transfer efficiency. These key vulcanization influencing factors include parameters such as vulcanizing agent activation threshold, rubber heating rate sensitivity, and mold cavity temperature gradient. Subsequently, the key vulcanization influencing factors were combined with the molding process duration representing the production rhythm requirements of each molding stage. Based on the average operating time of the mold unit operation data reflecting temperature control changes and heating response speed in actual batch molding, constraint analysis was performed on the achievable, maintainable, or stable transition temperature ranges. This yielded a first vulcanization temperature threshold subset that conforms to the vulcanization reaction law and adapts to the equipment operating characteristics. This subset is used to define the temperature start point, upper temperature limit, and temperature transition boundary of the core molding process at different stages. Constraint analysis is performed on the achievable, maintainable, or steady-state transition temperature ranges. Specifically, for each molding stage, the achievability, maintainability, and steady-state transition constraints corresponding to the target temperature setpoint are analyzed. The achievability constraint determines whether the mold temperature control system can reach the target temperature within a specified time window under a predetermined heating rate. The criteria include the maximum heating rate of the temperature control system, the upper limit of the allowable heating power, and the temperature difference between the target temperature and the initial temperature. When the required heating time does not exceed the preset time limit for that molding stage, the target temperature is considered achievable. The maintainability constraint determines whether the target temperature can be stably maintained during the molding stage. The criteria include a temperature fluctuation amplitude threshold and a minimum holding time requirement. The temperature fluctuation amplitude threshold is limited to a positive and negative preset deviation range of the target temperature. The minimum holding time requirement is that the temperature must be maintained continuously within this deviation range for at least a preset time proportion. When these conditions are met, the target temperature is considered maintainable. Steady-state transition constraints are used to determine whether a smooth transition can be achieved when switching the temperature from one molding stage to the next. The criteria for determination include the maximum allowable temperature change slope during the transition stage and the steady-state convergence time threshold. The maximum allowable temperature change slope is used to limit the temperature gradient change during the heating or cooling process, and the steady-state convergence time threshold is used to limit the maximum allowable time for the temperature to enter the target steady-state range. When the temperature change curve meets the slope and convergence time requirements, the temperature range is determined to be a stable transition temperature range.

[0046] Subsequently, when setting M vulcanization temperature segments based on the first vulcanization temperature threshold subset of the core molding process, each temperature threshold is divided into intervals according to the stage characteristics of the vulcanization reaction. The initial heating stage, the rapid growth stage of the crosslinking rate, the steady-state maintenance stage of the crosslinking, and the final curing stage of the vulcanization reaction are each corresponding to different temperature segments. The optimal temperature point in the threshold subset is used as the segment boundary, thus establishing M vulcanization temperature segments. When using the optimal temperature point in the first vulcanization temperature threshold subset as the boundary for vulcanization temperature segments, the optimal temperature point is not arbitrarily selected, but rather a control temperature node determined comprehensively based on the reaction characteristics of the EPDM rubber compound during the vulcanization process and the molding quality requirements. Specifically, the optimal temperature point is determined based on at least one or more of the following criteria: the temperature at which the vulcanization reaction rate of the rubber compound reaches a stage peak or enters a stable plateau range, representing the temperature range where the vulcanizing agent is fully activated and the crosslinking reaction efficiency is highest; the temperature at which the crosslinking density of the rubber compound reaches the target degree of crosslinking and the growth rate tends to flatten in the temperature-dependent curve, to avoid over-vulcanization or under-vulcanization; and the control temperature that can be stably maintained within the predetermined operation time and with temperature fluctuations within the allowable range, combined with the molding process duration and mold unit operation data, to ensure feasibility and stability under actual production conditions. In the specific implementation process, the criteria can be jointly analyzed through historical molding records, vulcanization experimental data, or online temperature and molding quality feedback data. When a certain temperature point simultaneously meets the requirements of vulcanization reaction efficiency, crosslinking uniformity, and equipment operation stability, that temperature point is determined as the optimal temperature point, and is used as the boundary for dividing adjacent vulcanization temperature segments, thereby achieving smooth transition and fine control between different stages of the vulcanization process. Each segment is designed to provide different heating rates, holding times, and thermal stability at specific stages to meet the optimal vulcanization conditions of the rubber compound at each stage, ensuring uniform heating and sufficient cross-linking of the material within the cavity, and effectively avoiding uneven or insufficient vulcanization in the joint areas.

[0047] When dividing the auxiliary molding process into upper corner injection molding, lower corner splicing, and post-molding shaping processes according to process requirements, it is necessary to break down the auxiliary processing sequence into stages based on the molding characteristics and stress requirements of the large corner sealing strip at different processing stages. Specifically, the upper corner injection molding process is used to achieve directional filling of the rubber material in the upper area of ​​the corner and form the initial interface structure; the lower corner splicing process is used to complete material splicing and interface fusion in the lower molding area; and the post-molding shaping process is used to correct the shape of the sealing strip and ensure geometric accuracy and corner consistency after the vulcanization reaction is basically completed. This staged division clarifies the pressure requirements, temperature characteristics, and material deformation modes corresponding to different stages of the auxiliary molding process, providing a basis for the precise configuration of subsequent pressure segments.

[0048] Subsequently, by analyzing the mold opening and closing frequency in the mold unit's operational data, and comparing it with the upper corner injection process, lower corner splicing process, and post-molding shaping process, and combining it with the second vulcanization temperature threshold subset of the auxiliary molding process to configure N dynamic pressure segments, the operating parameters reflecting the mold's action rhythm and operational stability based on the mold opening and closing frequency are used to match the mold's opening and closing rhythm in actual production with the pressure requirements of each auxiliary process stage. This allows identification of the variation patterns of injection pressure, splicing pressure, and shaping pressure required in each stage. The second vulcanization temperature threshold subset is used to characterize the allowable temperature fluctuation range when the material is in the semi-vulcanized, critically vulcanized, and post-vulcanized states during the auxiliary stages, ensuring the synchronization of pressure control with the material's reaction state. By jointly constraining the mold opening and closing frequency and the temperature threshold subset, N dynamic pressure segments can be configured to achieve adaptive adjustment of pressure as the process stage changes. Furthermore, the vulcanization temperature threshold set consists of the first vulcanization temperature threshold subset and the second vulcanization temperature threshold subset, which are used for the temperature control requirements of the core molding process and the auxiliary molding process, respectively, thus forming a complete temperature constraint system.

[0049] The molding parameter optimization model is a multi-objective parameter optimization model that jointly optimizes the segmented parameters of vulcanization temperature and injection pressure while satisfying molding constraints. The input parameters of the molding parameter optimization model include the vulcanization temperature threshold set, injection pressure segmented parameters, mold opening and closing interval parameters, and molding cycle constraint parameters. The output is the optimal combination of vulcanization temperature segmented parameters and dynamic pressure segmented parameters for the corresponding molding stage. The molding parameter optimization model uses minimizing molding energy consumption, minimizing process response delay time, and minimizing the probability of sealing strip wrinkling and separation as configuration optimization objectives. This means that based on the operating characteristics of the molding equipment, the vulcanization characteristic curve, and the dynamic changes of key process variables during the sealing strip molding process, an objective function system is established that can quantify the impact of different parameter combinations on energy consumption, cycle time, and finished product defect probability, so as to achieve optimal comprehensive performance of the molding process under multiple constraints. In the process of training or solving the molding parameter optimization model, a sample dataset is first constructed based on historical molding records and quality inspection data. Each sample includes corresponding temperature segment parameters, pressure segment parameters, mold opening and closing parameters, and corresponding energy consumption values, response delay times, and wrinkling / seam risk labels. Subsequently, the sample data is normalized, and weight coefficients are set according to the multi-objective optimization requirements, transforming the multi-objective objective function into a comprehensive fitness function. Further, a heuristic search algorithm is used to solve the fitness function. This heuristic search algorithm includes genetic algorithms or particle swarm optimization, iteratively searching for the optimal parameter combination within the solution space that satisfies mold load constraints, molding accuracy constraints, and process window constraints through selection, crossover, and mutation operations. In each iteration, candidate parameter combinations are evaluated based on the comprehensive fitness function, and the parameter combination with the best fitness is retained for the next iteration until the convergence condition is met or the preset number of iterations is reached.

[0050] Among these, minimizing molding energy consumption describes the actual thermal and mechanical energy consumed by the molding device within a preset vulcanization cycle. By modeling quantitative indicators such as vulcanization temperature, heating power, and heating rate, it demonstrates a positive correlation between higher vulcanization temperature and greater heat required, thus guiding the optimization of molding temperature control strategies. Furthermore, minimizing process response delay time describes the degree of lag in mold action during mold opening, mold closing, and material flow stabilization stages. By modeling mold opening and closing intervals, control actuator response time, and process synchronization errors, it demonstrates a positive correlation between longer mold opening and closing intervals and slower overall process response, supporting process cycle optimization and time synchronization adjustments. In addition, minimizing the probability of sealing strip wrinkling and separation describes the structural stability of the sealing strip during cavity filling and pressure holding stages. By modeling injection pressure fluctuation amplitude, material flow rate change rate, and local force differences in the cavity, it demonstrates a positive correlation between greater pressure fluctuations and a greater likelihood of sealing strip wrinkling and separation defects, allowing for optimization of pressure control accuracy and filling uniformity.

[0051] The input parameters of the molding parameter optimization model include the collaborative work ratio of shared mold units, the independent work quota of dedicated mold units, the vulcanization temperature threshold set, and dynamic pressure segmentation rules. The collaborative work ratio of shared mold units describes the proportion of multiple interchangeable molds participating in collaborative molding operations within the same production cycle. By quantifying the frequency of synchronous actions among shared molds, the shared cavity resource occupancy rate, and the consistency of interactive cycle times, it reflects the impact of mold collaboration on process stability. Furthermore, the independent work quota of dedicated mold units describes the number of molding tasks independently undertaken by a dedicated mold within the production cycle. The time ratio is used to limit the intensity of investment of dedicated mold units in the molding of specific structural parts, so as to ensure the consistency of molding quality of key components under controlled environment. In addition, the vulcanization temperature threshold set is used to describe the upper and lower limits of acceptable vulcanization temperature corresponding to different material systems and product structures. By presetting multiple switchable target temperature ranges, it is used to limit the iterative adjustment space of thermal conditions. Furthermore, the dynamic pressure segmentation rule is used to describe the segmented control method of injection pressure in stages such as filling, holding and pressure replenishment. By setting pressure change points, allowable fluctuation ranges and step switching logic, it is used to construct the dynamic adjustment boundary of injection pressure curve.

[0052] The optimal parameter combination is iteratively solved and output based on the optimization objective. That is, within the input space, based on a comprehensive objective function that minimizes preset energy consumption, response delay, and defect risk, the set of molding parameters that satisfies the overall optimal process performance is obtained through multiple rounds of iterative calculation, condition constraint linearization, and multivariate coupling solution. The optimal parameter combination is then written into the step-by-step injection molding control strategy, that is, the finally determined collaborative work ratio, independent operation quota, temperature threshold, and pressure segmentation rules are embedded into the step-by-step injection process. This allows the control system to automatically adjust the mold fit, temperature range, and pressure curve according to the optimized parameters when actually executing each stage of the action, thereby ensuring the stability and consistency of the molding process.

[0053] Furthermore, an objective function is configured based on the optimization objective, and a fitness evaluation is performed based on the objective function. The objective function is used to uniformly evaluate multiple objectives in the molding parameter optimization model. It is constructed by comprehensively evaluating the molding energy consumption value, process response delay time, and the probability of wrinkling and separation of the sealing strip. Specifically, the objective function first obtains the molding energy consumption value, process response delay time, and probability of wrinkling and separation of the sealing strip under the current candidate molding parameter combination. The molding energy consumption value is determined by the vulcanization temperature level and the corresponding operation time in each molding stage. The higher the vulcanization temperature and the longer the duration, the greater the corresponding energy consumption evaluation value. The process response delay time is determined by the difference between the time consumed by the mold to complete the opening and closing, locking and temperature control response during actual operation and the theoretical minimum response time of the system. The larger the mold opening and closing interval, the higher the corresponding delay evaluation value. The probability of wrinkling and separation of the sealing strip is obtained by comprehensively evaluating the fluctuation range of injection pressure during the molding cycle, the stability of pressure change, and the frequency of defect occurrence under similar parameter combinations in history. The more severe the pressure fluctuation, the higher the corresponding risk evaluation value. The objective function unifies the optimization of three types of evaluation values, ensuring that each value decreases. Specifically, the overall evaluation result of the objective function tends towards optimization when molding energy consumption, process response delay time, and the probability of wrinkling and separation risk all decrease simultaneously. Furthermore, based on the degree of impact of different optimization objectives on molding quality and production efficiency, corresponding weight coefficients are assigned to molding energy consumption evaluation, response delay evaluation, and risk evaluation, ensuring that evaluation items with a more significant impact on molding stability and product quality occupy a higher proportion in the objective function. Finally, the objective function outputs an evaluation value that measures the overall merits of the current molding parameter combination. This value serves as the basis for fitness evaluation in the molding parameter optimization model, comparing the merits of different candidate parameter combinations during iterative optimization and guiding the optimization algorithm towards parameter combinations with lower molding energy consumption, faster process response, and lower risk of wrinkling and separation. The optimization objective describes the comprehensive performance requirements that the molding process must simultaneously meet, including energy consumption control, cycle time response, and finished product quality constraints. By transforming multidimensional performance indicators into quantifiable evaluation expressions, a mathematical model is constructed to measure the merits of candidate parameter combinations. The objective function is used to uniformly represent the optimization objective through weighted summation, piecewise penalty, or hierarchical evaluation, so that each candidate solution can output a corresponding fitness value through the objective function, thereby determining the degree to which it meets the process performance requirements. In addition, the fitness evaluation is used to rank the candidate parameter combinations based on the objective function results, and to quantitatively evaluate their comprehensive performance in terms of energy consumption, response speed, and molding stability, providing a basis for the subsequent search process.

[0054] Simultaneously employing selection, crossover, and mutation operations, the optimal parameter combination is searched within the solution space that satisfies the constraints. The selection operation prioritizes solutions with higher fitness in the candidate solution set to improve the convergence efficiency of subsequent searches. The crossover operation simulates parameter characteristic combinations of different candidate solutions, exchanging parameter fragments between two parent solutions at a set ratio to form new child solutions, thus increasing the diversity of the search process. The mutation operation randomly perturbs some parameters in the candidate solutions to expand the search range and prevent getting trapped in local optima. Constraints limit the solution space, including mold load requirements and sealing strip forming accuracy requirements. The mold load requirements describe the maximum thermal and mechanical loads the mold can withstand under a specific forming cycle, ensuring that the optimized parameters do not lead to mold overload. The sealing strip forming accuracy requirements describe the quality indicators of the sealing strip in terms of size, deformation control, and interface bonding, ensuring that candidate solutions meet the minimum quality requirements of the finished product.

[0055] S4: Based on the molding parameter optimization model, the process execution parameters and splicing accuracy within the molding operation cycle are optimized to obtain a step-by-step injection molding control strategy.

[0056] Specifically, based on the molding parameter optimization model, the process execution parameters and splicing accuracy within the molding cycle are optimized to obtain a step-by-step injection molding control strategy. The molding parameter optimization model is used to quantitatively model multi-dimensional parameters such as temperature, pressure, cycle time, and mold coordination status during the molding process, and evaluates the merits of candidate parameter combinations through objective functions and constraints. The molding cycle describes the complete operational time window from material injection, splicing, vulcanization to shaping, containing multiple stages with different process characteristics. Furthermore, the process execution parameters represent the core process variables that need to be dynamically adjusted within the molding cycle, including vulcanization temperature, injection pressure, holding time, and mold opening and closing rhythm, to characterize the dynamic changes in heat input and mechanical loading during the molding process. Simultaneously, the splicing accuracy reflects the quality stability of the sealing strip corner joints in terms of geometric matching, interface adhesion, and cross-linking uniformity. Optimization of this indicator improves corner strength and enhances overall structural continuity.

[0057] In summary, the step-by-step injection molding parameter control method for large corner sealing strips provided in this application has the following technical effects: by achieving the technical goal of dynamic parameter coordinated control based on the differences in process requirements throughout the molding cycle, it achieves the technical effects of improving vulcanization crosslinking uniformity, enhancing splicing interface strength, and improving molding stability.

[0058] Example 2: Based on the same inventive concept as the step-by-step injection molding parameter control method for the large corner sealing strip in the foregoing examples, this application also provides a step-by-step injection molding parameter control system for the large corner sealing strip. Please refer to the appendix. Figure 2 The system includes: a molding operation cycle configuration module 1, used to perform in-depth analysis of the step-by-step vulcanization splicing control logic corresponding to the large-angle vulcanization splicing structure based on the historical molding records and mold unit operation data of the EPDM sealing strip, identify the differences in process requirements at different molding stages, and configure the molding operation cycle; an independent operation quota determination module 2, used to determine the collaborative work ratio of the shared mold unit and the independent operation quota of the dedicated mold unit based on the process synergy adaptability and stage-specific demand intensity of each molding stage; a molding parameter optimization model establishment module 3, used to adjust the M vulcanization temperature segments of the core molding process and the N dynamic pressure segments of the auxiliary molding process based on the collaborative work ratio of the shared mold unit and the independent operation quota of the dedicated mold unit, and establish a molding parameter optimization model; and a step-by-step injection molding control strategy acquisition module 4, used to optimize the process execution parameters and splicing accuracy within the molding operation cycle based on the molding parameter optimization model, and obtain the step-by-step injection molding control strategy.

[0059] Furthermore, the step-by-step injection molding parameter control system for the large corner sealing strip is also used to: group the process execution parameters of different molding stages, identify the basic execution processes, sensitive execution processes, and cross-stage shared processes of each molding stage, and generate a process requirement difference matrix; based on the process requirement difference matrix, extract the historical molding records and the mold unit operation data, wherein the mold unit operation data includes mold opening and closing frequency, energy consumption ratio, and vulcanization temperature threshold set.

[0060] Furthermore, the step-by-step injection molding parameter control system for the large corner sealing strip is also used to: define process synergy compatibility by scoring mold compatibility and vulcanization adaptability, and establish a process synergy matching rule library by using the historical molding records and the mold specification requirements of the sealing strip at different molding stages; perform mold compatibility scoring based on the process synergy matching rule library, and obtain the independent work quota of the dedicated mold unit by combining the stage-specific demand intensity.

[0061] Furthermore, the step-by-step injection molding parameter control system for the large corner sealing strip is also used to: identify key vulcanization influencing factors affecting the splicing strength and vulcanization crosslinking uniformity of the sealing strip based on the process requirement difference matrix; and configure M vulcanization temperature segments for adjusting the core molding process according to the key vulcanization influencing factors, molding process duration, and mold unit operation data.

[0062] Furthermore, the step-by-step injection molding parameter control system for the large corner sealing strip is also used to: determine the first vulcanization temperature threshold subset of the core molding process based on the key vulcanization influencing factors, molding process duration, and the average operation time in the mold unit operation data; and set the M vulcanization temperature segments based on the first vulcanization temperature threshold subset of the core molding process.

[0063] Furthermore, the step-by-step injection molding parameter control system for the large corner sealing strip is also used for: dividing the auxiliary molding process into upper corner injection process, lower corner splicing process, and post-molding shaping process according to the process requirement cycle; configuring the N dynamic pressure segments by referring to the upper corner injection process, lower corner splicing process, and post-molding shaping process in the mold unit operation data, in conjunction with the second vulcanization temperature threshold subset of the auxiliary molding process, and by referring to the mold opening and closing frequency in the mold unit operation data; wherein the vulcanization temperature threshold subset includes the first vulcanization temperature threshold subset and the second vulcanization temperature threshold subset.

[0064] Furthermore, the step-by-step injection molding parameter control system for the large corner sealing strip is also used for: the molding parameter optimization model to configure optimization objectives to minimize molding energy consumption, minimize process response delay time, and minimize the probability of sealing strip wrinkling and separation; wherein, the minimized molding energy consumption is positively correlated with vulcanization temperature, the minimized process response delay time is positively correlated with mold opening and closing interval, and the minimized probability of sealing strip wrinkling and separation is positively correlated with injection pressure fluctuation amplitude.

[0065] Furthermore, the step-by-step injection molding parameter control system for the large corner sealing strip is also used for: the input parameters of the molding parameter optimization model include the collaborative work ratio of the shared mold unit, the independent work quota of the dedicated mold unit, the vulcanization temperature threshold set, and the dynamic pressure segmentation rules; iteratively solving for the optimal parameter combination according to the optimization objective and outputting it, and writing the optimal parameter combination into the step-by-step injection molding control strategy.

[0066] Furthermore, the step-by-step injection molding parameter control system for the large corner sealing strip is also used to: configure an objective function according to the optimization objective, and perform fitness evaluation according to the objective function; at the same time, using selection operation, cross operation, and mutation operation, search for the optimal parameter combination in the solution space that satisfies the constraints, including mold load requirements and sealing strip molding accuracy requirements.

[0067] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The step-by-step injection molding parameter control method and specific examples of the large corner sealing strip in the foregoing embodiment one are also applicable to the step-by-step injection molding parameter control system of the large corner sealing strip in this embodiment. Through the foregoing detailed description of the step-by-step injection molding parameter control method of the large corner sealing strip, those skilled in the art can clearly understand the step-by-step injection molding parameter control system of the large corner sealing strip in this embodiment. Therefore, for the sake of brevity, it will not be described in detail here.

[0068] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0069] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for controlling injection molding parameters in a step-by-step manner for large corner sealing strips, characterized in that, The method includes: Based on the historical molding records and mold unit operation data of EPDM sealing strips, an in-depth analysis of the step-by-step vulcanization splicing control logic corresponding to the large joint vulcanization splicing structure is conducted to identify the differences in process requirements at different molding stages and configure the molding operation cycle. At the same time, based on the process synergy and adaptability of each molding stage and the intensity of stage-specific requirements, the proportion of collaborative work of shared mold units and the independent work quota of dedicated mold units are determined. Based on the collaborative work ratio of the shared mold unit and the independent work quota of the dedicated mold unit, adjust the M vulcanization temperature segments of the core molding process and the N dynamic pressure segments of the auxiliary molding process to establish a molding parameter optimization model. Based on the molding parameter optimization model, the process execution parameters and splicing accuracy within the molding operation cycle are optimized to obtain a step-by-step injection molding control strategy.

2. The step-by-step injection molding parameter control method for the large corner sealing strip as described in claim 1, characterized in that, Based on the historical molding records and mold unit operation data of EPDM sealing strips, a deep analysis of the step-by-step vulcanization splicing control logic corresponding to the large-angle vulcanization splicing structure is conducted to identify the differences in process requirements at different molding stages and configure the molding operation cycle. The method also includes: The process execution parameters of different molding stages are grouped, and the basic execution processes, sensitive execution processes and cross-stage shared processes of each molding stage are identified to generate a process requirement difference matrix. Based on the process requirement difference matrix, the historical molding records and the mold unit operation data are extracted, wherein the mold unit operation data includes mold opening and closing frequency, energy consumption ratio, and vulcanization temperature threshold set.

3. The step-by-step injection molding parameter control method for the large corner sealing strip as described in claim 1, characterized in that, Based on the process synergy and adaptability of each molding stage and the intensity of stage-specific requirements, the independent work quota of the dedicated mold unit is determined. The method includes: The process synergy compatibility is defined by scoring mold compatibility and vulcanization adaptability, and a process synergy matching rule library is established by combining the historical molding records with the mold specifications of the sealing strip at different molding stages. Based on the process collaboration matching rule base, mold compatibility is scored, and combined with the stage-specific demand intensity, the independent work quota of the dedicated mold unit is obtained.

4. The step-by-step injection molding parameter control method for the large corner sealing strip as described in claim 2, characterized in that, The method of adjusting the M vulcanization temperature segments of the core molding process includes: Based on the process requirement difference matrix, key vulcanization influencing factors affecting the splicing strength and vulcanization crosslinking uniformity of the sealing strip are identified. Based on the key influencing factors of vulcanization, the molding process duration, and the mold unit operation data, configure M vulcanization temperature segments for adjusting the core molding process.

5. The step-by-step injection molding parameter control method for the large corner sealing strip as described in claim 4, characterized in that, Based on the key influencing factors of vulcanization, the molding process duration, and the mold unit operation data, configure M vulcanization temperature segments for adjusting the core molding process. The method includes: Based on the key influencing factors of vulcanization and the molding process duration, combined with the average operation time in the mold unit operation data, the first vulcanization temperature threshold subset of the core molding process is determined. Based on the first vulcanization temperature threshold subset of the core molding process, the M vulcanization temperature segments are set.

6. The step-by-step injection molding parameter control method for the large corner sealing strip as described in claim 5, characterized in that, The method for adjusting N dynamic pressure segments in the auxiliary molding process includes: The auxiliary molding process is divided into upper corner injection process, lower corner splicing process and post-molding shaping process according to the process requirement cycle. Based on the mold opening and closing frequency in the mold unit operation data, and in conjunction with the upper corner injection process, lower corner splicing process, and post-molding shaping process, and combined with the second vulcanization temperature threshold subset of the auxiliary molding process, the N dynamic pressure segments are configured, wherein the vulcanization temperature threshold set includes the first vulcanization temperature threshold subset and the second vulcanization temperature threshold subset.

7. The step-by-step injection molding parameter control method for the large corner sealing strip as described in claim 6, characterized in that, The method for establishing a molding parameter optimization model includes: The molding parameter optimization model is configured with optimization objectives to minimize molding energy consumption, minimize process response delay time, and minimize the risk probability of sealing strip wrinkling and separation. Among them, the minimum molding energy consumption value is positively correlated with the vulcanization temperature, the minimum process response delay time is positively correlated with the mold opening and closing interval, and the minimum probability of sealing strip wrinkling and separation is positively correlated with the injection pressure fluctuation range.

8. The step-by-step injection molding parameter control method for the large corner sealing strip as described in claim 7, characterized in that, Based on the collaborative work ratio of the shared mold unit and the independent work quota of the dedicated mold unit, the M vulcanization temperature segments of the core molding process and the N dynamic pressure segments of the auxiliary molding process are adjusted to establish a molding parameter optimization model. The method includes: The input parameters of the molding parameter optimization model include the collaborative work ratio of shared mold units, the independent work quota of dedicated mold units, the vulcanization temperature threshold set, and the dynamic pressure segmentation rules. The optimal parameter combination is iteratively solved according to the optimization objective and output, and the optimal parameter combination is written into the step-by-step injection molding control strategy.

9. The step-by-step injection molding parameter control method for the large corner sealing strip as described in claim 8, characterized in that, The method includes iteratively solving for and outputting the optimal parameter combination based on the optimization objective. Based on the optimization objective, configure the objective function, and perform fitness evaluation based on the objective function; Simultaneously, selection, crossover, and mutation operations are used to search for the optimal parameter combination within the solution space that satisfies the constraints, including mold load requirements and sealing strip forming accuracy requirements.

10. A step-by-step injection molding parameter control system for large corner sealing strips, characterized in that, The steps for implementing the step-by-step injection molding parameter control method for the large corner sealing strip according to any one of claims 1 to 9 include: The molding cycle configuration module is used to perform in-depth analysis of the step vulcanization splicing control logic corresponding to the large joint angle vulcanization splicing structure based on the historical molding records of EPDM sealing strips and the mold unit operation data, identify the differences in process requirements at different molding stages, and configure the molding cycle. The independent work quota determination module is used to determine the collaborative work ratio of shared mold units and the independent work quota of dedicated mold units based on the process synergy adaptability and stage-specific demand intensity of each molding stage. The molding parameter optimization model establishment module is used to adjust the M vulcanization temperature segments of the core molding process and the N dynamic pressure segments of the auxiliary molding process based on the collaborative work ratio of the shared mold unit and the independent work quota of the dedicated mold unit, and to establish a molding parameter optimization model. The step-by-step injection molding control strategy acquisition module is used to optimize the process execution parameters and splicing accuracy within the molding operation cycle based on the molding parameter optimization model, thereby obtaining the step-by-step injection molding control strategy.

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