Injection molding part regeneration evaluation method and system based on performance recovery

Abstract

The invention discloses an injection molding part regeneration evaluation method and system based on performance recovery, and relates to the technical field of plastic regeneration, and the method comprises the following steps: obtaining the production yield in the injection molding part forming process; obtaining performance requirements of the injection molded part, and recording the performance requirements as reference performance indexes; obtaining performance data of all available injection molding raw materials at present; to-be-selected injection molding raw materials are screened out; based on the regeneration performance of each to-be-selected injection molding raw material and the production yield in the injection molding part forming process, the regeneration injection molding scene of each to-be-selected injection molding raw material during injection molding part forming is evaluated; and based on a regeneration injection molding scene when each to-be-selected injection molding raw material is subjected to injection molding part forming, and in combination with the cost of each to-be-selected injection molding raw material, an injection molding part raw material selection scheme is intelligently evaluated and decided. By constructing a set of dynamic evaluation model fusing historical production data, a raw material regeneration performance degradation rule and multi-cycle cost accounting, the performance of different injection molding raw materials in the whole life cycle can be scientifically predicted.

Description

Technical Field

[0001] This invention relates to the field of plastic recycling technology, specifically to a method and system for evaluating the recycling of injection molded parts based on performance recovery. Background Technology

[0002] In the current plastic injection molding industry, raw material selection is a critical factor affecting product quality and cost, but existing technologies have significant limitations. Traditional methods mainly rely on engineers' experience or simply match the initial performance parameters of virgin materials with product design requirements. This static assessment cannot address the complex scenarios following the introduction of recycled materials. It fails to quantify the performance degradation patterns of different raw materials in multiple recycling cycles, and it also fails to incorporate dynamic factors such as historical yield fluctuations of the production line, recycling costs, and regeneration efficiency into a comprehensive consideration. As a result, companies cannot accurately predict the long-term economic benefits and quality risks of using specific recycled materials.

[0003] This limitation makes the current selection process uncertain: being too conservative leads to the overuse of high-cost virgin materials, wasting resources; being too aggressive may cause batch quality problems due to insufficient performance prediction of recycled materials. Therefore, the industry urgently needs an intelligent evaluation method that can deeply integrate performance degradation models, production big data analysis, and dynamic cost accounting to break through the bottleneck of existing technologies that can only make one-sided and static judgments, and achieve scientific, precise, and efficient selection of injection molding raw materials. Summary of the Invention

[0004] To address the aforementioned technical problems, a method and system for evaluating the regeneration of injection molded parts based on performance recovery are provided. This technical solution solves at least one of the problems mentioned in the background section.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for evaluating the regeneration of injection molded parts based on performance recovery, comprising: Analyze historical injection molding data of injection molded parts to obtain the production yield during the injection molding process; Obtain the performance requirements of the injection molded part and record them as the baseline performance index; Obtain the performance data of all available injection molding materials, including the initial properties and regeneration properties of the injection molding materials; Injection molding raw materials whose initial performance exceeds the benchmark performance index are selected as candidate injection molding raw materials; Based on the recyclability of each candidate injection molding material and the production yield during the injection molding process, the recyclable injection molding scenario of each candidate injection molding material is evaluated. Based on the recycled injection molding scenario when molding injection parts using each candidate injection molding material, and combined with the cost of each candidate injection molding material, the system intelligently evaluates and decides on the material selection scheme for injection molded parts.

[0006] Preferably, the step of analyzing historical injection molding data of the injection molded part to obtain the production yield during the injection molding process specifically includes: Extract the number of good and defective injection molded parts produced in the production cycles closest to the current time, and calculate the production yield in each production cycle. Using the production yield of several production cycles closest to the current moment as sample data, the production yield of injection molded parts in future production cycles is calculated and predicted.

[0007] Preferably, the specific method for calculating and predicting the production yield of injection molded parts in future production cycles using the production yield of several production cycles closest to the current time as sample data is as follows: predicting the production yield of injection molded parts in future production cycles based on the sample data by regression prediction or averaging. Specifically, the regression prediction method used to predict the production yield of injection molded parts in the future production cycle includes: Based on the time interval between each production cycle and the current moment, time numbers are added to each production cycle in ascending order of time. A regression equation for the production yield of injection molded parts is constructed with the production yield of injection molded parts in each production cycle as the dependent variable and the time sequence number of each production cycle as the independent variable. Predict the production yield of injection molded parts in future production cycles based on the regression equation of injection molded part production yield; Predicting injection molded part production yield in future production cycles using the averaging method specifically includes: Data filtering of sample data is based on Grubbs' criterion; The average of the injection molded part production yield over all sample periods after data filtering is used as the injection molded part production yield for future production periods.

[0008] Preferably, the evaluation of the recyclable injection molding scenario for each candidate injection molding material based on the recyclability of each candidate injection molding material and the production yield during the injection molding process specifically includes: Based on the recycling performance data of each candidate injection molding material, determine the performance data of the candidate injection molding material after each recycling and regeneration injection molding. The maximum number of recycling cycles for the selected injection molding raw material is determined by determining that the performance data of the recycled injection molding raw material is greater than the benchmark performance index. Based on the maximum number of recyclable raw materials to be selected and the production yield of injection molded parts in the future production cycle, the set of recyclable injection molding probabilities of the raw materials to be selected is determined. The elements of the recyclable injection molding probability set are the probability of successful recycling injection each time the raw materials to be selected are used to inject molded parts.

[0009] Preferably, the intelligent evaluation and decision-making process for selecting injection molding materials based on the recycled injection molding scenario for each candidate injection molding material, combined with the cost of each candidate injection molding material, specifically includes: Based on the set of recycling injection probability of the candidate injection molding raw materials, the probability of successful recycling injection is accumulated to obtain the recycling injection yield of the candidate injection molding raw materials; Determine the processing cost of injection molding, the cost of recycling and regenerating injection molded parts, and the total cost of each recycling and regeneration injection molding process; Based on the probability of successful recycling and recycling in each recycling and recycling probability set, the total cost of recycling and recycling in each recycling and recycling, the recycling yield of the selected injection molding raw material and the cost of the selected injection molding raw material, the standard injection molding cost of the selected injection molding raw material is calculated. Select the injection molding raw material with the lowest standard injection molding cost as the candidate injection molding raw material in the next production cycle.

[0010] Preferably, the performance recovery-based injection molded part regeneration assessment method further includes a graded assessment mechanism, which specifically includes: Set a threshold for injection molding yield. If the production yield during the injection molding process is higher than the threshold, intelligently evaluate and decide on the raw material selection scheme for the injection molded part. If the production yield during the injection molding process is lower than the injection molding yield threshold, the production line will be stopped for maintenance.

[0011] Furthermore, this solution also proposes a performance recovery-based injection molded part regeneration evaluation system to implement the performance recovery-based injection molded part regeneration evaluation method described above, including: The historical data analysis module is used to analyze historical injection data of injection molded parts to obtain the production yield during the injection molding process. The performance requirement acquisition module is used to acquire the performance requirements of the injection molded parts, which are denoted as the baseline performance indicators. The raw material performance acquisition module is used to acquire the performance data of all currently available injection molding raw materials, including the initial performance and regeneration performance of the injection molding raw materials; The raw material screening module is used to screen out injection molding raw materials whose initial performance exceeds the benchmark performance index, and use them as candidate injection molding raw materials. The recycling scenario assessment module is used to assess the recycling injection scenario of each candidate injection molding material when injection molding parts, based on the recycling performance of each candidate injection molding material and the production yield during the injection molding process. The intelligent decision-making module is used to intelligently evaluate and decide on the raw material selection scheme for injection molded parts based on the recycled injection molding scenario when each candidate injection molding raw material is used for injection molding.

[0012] Optionally, the historical data analysis module includes: The data extraction unit is used to extract the number of good and defective injection molded parts produced in the production cycles closest to the current time, and to calculate the production yield in each production cycle. The prediction unit is used to calculate and predict the production yield of injection molded parts in future production cycles, using the production yield of the production cycles closest to the current time as sample data.

[0013] Optionally, the regeneration scenario assessment module includes: The performance determination unit is used to determine the performance data of each selected injection molding raw material after each recycling and regeneration injection molding based on the recycling performance data of each selected injection molding raw material. The maximum number of recycling units is used to determine the maximum number of recycling cycles that the performance data of the selected injection molding raw material after recycling and re-injection molding is greater than the benchmark performance index, and this number is used as the maximum number of recycling cycles for the selected injection molding raw material. The probability set determination unit is used to determine the recycling probability set of the candidate injection molding raw material based on the maximum number of recyclings of the candidate injection molding raw material and the production yield of injection molded parts in the future production cycle. The elements of the recycling probability set are the probability of successful recycling injection when injection molding parts are made using the candidate injection molding raw material.

[0014] Optionally, the intelligent decision-making module includes: The yield calculation unit is used to accumulate the probability of successful recycling and recycling of each raw material based on the set of recycling and injection molding probabilities of the raw materials to be selected, and to obtain the recycling and injection molding yield of the raw materials to be selected. The cost determination unit is used to determine the processing cost of injection molding, the cost of recycling and regenerating injection molded parts, and the total cost of each recycling and regeneration injection molding process. The standard cost calculation unit is used to calculate the standard injection cost of the selected injection molding material based on the probability of successful recycling injection molding in the recycling injection probability set, the total cost of each recycling injection molding, the recycling injection yield of the selected injection molding material, and the cost of the selected injection molding material. The raw material selection unit is used to screen out the candidate injection molding raw materials with the lowest standard injection molding cost, which will be used as the candidate injection molding raw materials in the next production cycle.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention constructs a dynamic evaluation model that integrates historical production data, raw material recycling performance degradation patterns, and multi-cycle cost accounting. This model can scientifically predict the performance of different injection molding raw materials throughout their entire life cycle. It achieves precise quantitative evaluation of the long-term performance and economic benefits of injection molding raw materials, especially recycled materials, overcoming the shortcomings of traditional methods that rely on static experience and limited data. This guides companies in selecting the optimal raw material solution, ultimately achieving multiple goals: significantly reducing overall manufacturing costs, greatly improving resource recycling rates, and effectively ensuring product quality stability. Attached Figure Description

[0016] Figure 1 This is a flowchart of the performance recovery-based evaluation method for recycled injection molded parts proposed in this scheme; Figure 2 This is a flowchart illustrating the method for obtaining production yield during the injection molding process proposed in this solution. Figure 3 This is a flowchart illustrating the method proposed in this scheme for evaluating the regenerated injection molding scenario when each candidate injection molding material is used to mold injection parts. Figure 4 This is a flowchart illustrating the intelligent evaluation and decision-making method for selecting raw materials for injection molded parts proposed in this scheme. Detailed Implementation

[0017] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0018] Reference Figure 1 As shown, a method for evaluating the regeneration of injection molded parts based on performance recovery includes: By analyzing historical injection molding data of injection molded parts, the production yield during the molding process is obtained. Through a data-driven approach, past production experience is transformed into quantifiable predictive indicators. It is not just a simple statistical analysis of past yields, but also actively predicts the expected yield of future production cycles through algorithms such as regression analysis or data filtering. This establishes a dynamic and forward-looking foundation for subsequent evaluations, rather than relying on static historical averages, thus significantly improving the accuracy and practicality of the evaluation. The performance requirements of the injection molded parts are obtained and recorded as benchmark performance indicators. Establishing benchmark performance indicators sets a clear standard for the entire evaluation process. The product design requirements are transformed into specific and measurable performance parameters such as impact strength and heat resistance temperature, ensuring that all subsequent raw material selection and scenario assessments revolve around meeting the core quality requirements of the final product, thus guaranteeing the practicality and relevance of the evaluation results. Acquire performance data for all available injection molding materials, including initial and recyclable properties, to provide the foundation for accurate evaluation. In particular, "recyclable performance" data, such as key performance data after 1, 2, or n recycling cycles, breaks through the limitation of traditional material selection that only focuses on the performance of virgin materials. It provides key data support for simulating the performance degradation of materials throughout their entire life cycle and is a prerequisite for achieving full life cycle cost and performance analysis. Injection molding materials with initial performance exceeding benchmark performance indicators are selected as candidate materials for preliminary screening. This aims to eliminate materials that cannot even meet quality requirements in the first injection molding, thereby efficiently narrowing the evaluation scope and concentrating computational resources on promising candidate solutions. This ensures that subsequent complex recycling scenario simulations and cost assessments are conducted within the feasible material range, improving the efficiency of the decision-making process. Based on the recyclability of each candidate injection molding material and the production yield during injection molding, the recycling injection scenarios for each candidate material are evaluated. The simulation dynamically calculates the maximum number of times a material can be safely recycled and reused (maximum recycling count) and the probability of success for each recycling attempt, taking into account actual production losses (yield). This transforms the abstract concept of "recyclability" into a concrete and quantifiable "scenario prediction," providing crucial input for the final cost decision. Based on the recycling injection scenario during injection molding of each candidate injection molding material, and combined with the cost of each candidate injection molding material, the system intelligently evaluates and decides on the material selection scheme for injection molded parts. By establishing a comprehensive economic model, the system combines the unit price of raw materials, processing costs, recycling costs, and predicted recycling times and success probabilities to calculate a "standard injection molding cost" that reflects long-term manufacturing costs. Finally, based on the optimal total cost, the system intelligently recommends the best material scheme, achieving a balance between technical feasibility and economic benefits.

[0019] Reference Figure 2 As shown, based on the analysis of historical injection molding data of injection molded parts, the production yield of injection molded parts during the molding process is obtained, specifically including: Extract the number of good and defective injection molded parts produced in the production cycles closest to the current time, and calculate the production yield in each production cycle. Using the production yield of several production cycles closest to the current moment as sample data, the production yield of injection molded parts in future production cycles is calculated and predicted.

[0020] Specifically, under stable operating conditions of some injection molding production lines, the yield rate of injection molded parts in future production cycles is predicted by averaging. The specific steps are as follows: Data filtering of sample data is based on Grubbs' criterion; Grubbs' criterion is as follows: Determine the total quantity of historical production cycles, denoted as N; Determine a detection level, denoted as α; Determined at the significance level The value of the t-distribution under the given conditions is denoted as T; The mathematical expression for screening data using the Grubbs criterion is: ; In the formula, This represents the average yield of injection molded parts across all historical production cycles. The standard deviation of injection molded part production yield over all historical production cycles. The production yield of injection molded parts in the j-th historical production cycle; If the standard data filtering model is met, then retain. .

[0021] The average of the injection molded part production yield over all sample periods after data filtering is used as the injection molded part production yield for future production periods.

[0022] By introducing the Grubbs criterion for data filtering, outliers in historical production data were effectively eliminated, significantly improving the accuracy and representativeness of the sample data used for prediction, thereby avoiding interference from abnormal production cycles on yield prediction.

[0023] In environments where injection molding production lines exhibit significant operational trends, regression prediction is used to forecast the yield of injection molded parts within future production cycles. This includes: Based on the time interval between each production cycle and the current moment, time numbers are added to each production cycle in ascending order of time. A regression equation for the production yield of injection molded parts is constructed with the production yield of injection molded parts in each production cycle as the dependent variable and the time sequence number of each production cycle as the independent variable. The regression equation based on the production yield of injection molded parts is used to predict the production yield of injection molded parts in future production cycles.

[0024] In some preferred embodiments, linear regression is used to predict the production yield of injection molded parts in future production cycles.

[0025] Depending on the differences in the operating status of the production line, a regression method based on trend prediction can also be selected, so that the prediction results of production yield can accurately capture the dynamic patterns of production lines with obvious changing trends.

[0026] The yield acquisition method based on data cleaning and dual-mode prediction provides a highly reliable input benchmark that closely reflects actual production changes for subsequent regeneration scenario simulation and cost decision-making, fundamentally improving the scientificity and reliability of the entire evaluation and decision-making system.

[0027] Reference Figure 3 As shown, based on the recyclability of each candidate injection molding material and the production yield during the injection molding process, the evaluation of recyclable injection molding scenarios for each candidate injection molding material specifically includes: Based on the recycling performance data of each candidate injection molding material, determine the performance data of the candidate injection molding material after each recycling and regeneration injection molding. The maximum number of recycling cycles for the selected injection molding raw material is determined by determining that the performance data of the recycled injection molding raw material is greater than the benchmark performance index. Based on the maximum number of recyclable raw materials to be selected and the production yield of injection molded parts in the future production cycle, the set of recyclable injection molding probabilities of the raw materials to be selected is determined. The elements of the recyclable injection molding probability set are the probability of successful recycling injection each time the raw materials to be selected are used to inject molded parts.

[0028] Specifically, the formula for calculating the probability of successful injection molding from recycled materials is as follows: ; In the formula, The probability of success during the i-th recycling injection molding process. This is to determine the yield rate of injection molded parts during future production cycles.

[0029] Specifically, refer to Figure 4 As shown, based on the recycled injection molding scenario during injection molding of each candidate injection molding material, and combined with the cost of each candidate injection molding material, the intelligent evaluation and decision-making process for selecting injection molding material specifically includes: Based on the set of recycling injection probability of the candidate injection molding raw materials, the probability of successful recycling injection is accumulated to obtain the recycling injection yield of the candidate injection molding raw materials; Determine the processing cost of injection molding, the cost of recycling and regenerating injection molded parts, and the total cost of each recycling and regeneration injection molding process; Based on the probability of successful recycling and recycling in each recycling and recycling probability set, the total cost of recycling and recycling in each recycling and recycling, the recycling yield of the selected injection molding raw material and the cost of the selected injection molding raw material, the standard injection molding cost of the selected injection molding raw material is calculated. Specifically, the calculation process for the standard injection molding cost of the selected injection molding raw materials is as follows: ; In the formula, The standard injection molding cost of the candidate injection molding raw materials, The cost of the candidate injection molding raw materials, Cost per injection molding Cost per recycling The maximum number of recycles of the candidate injection molding raw materials. The yield of recycled injection molding of the candidate injection molding raw materials.

[0030] Specifically, a standard injection cost calculation formula for the candidate injection molding raw materials is constructed. This formula fully considers the injection success rate of the raw materials during recycled injection molding. That is, within the maximum number of recycling cycles of the candidate injection molding raw materials, any successful injection molding can be considered as no waste of the injection molding raw materials. Based on this, the recycling yield of the candidate injection molding raw materials is designed. Meanwhile, when calculating injection molding costs, the probability of successful injection molding of the raw material requiring recycling and regeneration for the i-th time is calculated based on the production yield of the injection molded parts. The production cost of the injection molded parts is analyzed by combining the processing cost and recycling cost required for each injection molding. Then, the standard injection molding cost can be obtained by dividing the recycling and regeneration yield of the raw material to be selected.

[0031] Select the injection molding raw material with the lowest standard injection molding cost as the candidate injection molding raw material in the next production cycle.

[0032] A dynamic cost model based on the probability of successful recycling was constructed, enabling precise quantitative assessment of the entire lifecycle cost of injection molding raw materials. Its core benefits lie in its pioneering integration of the degradation law of raw material recycling performance, actual production line yield, and recycling processing costs into a unified mathematical model. By calculating standard injection molding costs, it can accurately reflect the long-term comprehensive economic benefits of different raw materials, including repeatedly recycled materials. This not only breaks through the limitations of traditional material selection methods that only consider the unit price of virgin materials or the cost of a single injection, but also scientifically predicts the loss risks during the recycling process through a probabilistic model, thereby intelligently recommending the raw material solution with the optimal total cost. Ultimately, while ensuring product quality, it significantly improves resource utilization and maximizes economic benefits.

[0033] In some preferred embodiments, the performance recovery-based injection molded part regeneration assessment method further includes a graded assessment mechanism, which specifically includes: Set a threshold for injection molding yield. If the production yield during the injection molding process is higher than the threshold, intelligently evaluate and decide on the raw material selection scheme for the injection molded part. If the production yield during the injection molding process is lower than the injection molding yield threshold, the production line will be stopped for maintenance.

[0034] By introducing a tiered evaluation mechanism, a scientific quality control checkpoint was established, yielding significant beneficial results. This mechanism constructs an automated decision-making switch by setting injection molding yield thresholds: when the predicted yield is higher than the threshold, the system initiates a complex intelligent evaluation process, ensuring that raw material optimization decisions are based on a stable production process and guaranteeing the reliability of the evaluation results; conversely, when the predicted yield is lower than the threshold, a shutdown and maintenance command is automatically triggered. This effectively avoids the risks of further increasing defect rates, wasting resources, and exacerbating equipment wear and tear that might result from blindly using recycled materials when the production line is in poor condition. Thus, while pursuing economic benefits, the bottom line of production quality is firmly maintained, achieving a balance between efficiency and risk control.

[0035] Specifically, based on the same inventive concept as the above-mentioned performance recovery-based injection molded part regeneration evaluation method, this solution also proposes a performance recovery-based injection molded part regeneration evaluation system, including: The historical data analysis module is used to analyze historical injection data of injection molded parts to obtain the production yield during the injection molding process. The performance requirement acquisition module is used to acquire the performance requirements of the injection molded parts, which are denoted as the baseline performance indicators. The raw material performance acquisition module is used to acquire the performance data of all currently available injection molding raw materials, including the initial performance and recycling performance of the injection molding raw materials. The raw material screening module is used to screen out injection molding raw materials whose initial performance exceeds the benchmark performance index, and use them as candidate injection molding raw materials. The recycling scenario assessment module is used to assess the recycling injection scenario of each candidate injection molding material when injection molding parts, based on the recycling performance of each candidate injection molding material and the production yield during the injection molding process. The intelligent decision-making module is used to intelligently evaluate and decide on the raw material selection scheme for injection molded parts based on the recycled injection molding scenario when each candidate injection molding raw material is used for injection molding.

[0036] The historical data analysis module includes: The data extraction unit is used to extract the number of good and defective injection molded parts produced in the production cycles closest to the current time, and to calculate the production yield in each production cycle. The prediction unit is used to calculate and predict the production yield of injection molded parts in future production cycles, using the production yield of the production cycles closest to the current time as sample data.

[0037] The regeneration scenario assessment module includes: The performance determination unit is used to determine the performance data of each selected injection molding raw material after each recycling and regeneration injection molding based on the recycling performance data of each selected injection molding raw material. The maximum number of recycling units is used to determine the maximum number of recycling cycles that the performance data of the selected injection molding raw material after recycling and re-injection molding is greater than the benchmark performance index, and this number is used as the maximum number of recycling cycles for the selected injection molding raw material. The probability set determination unit is used to determine the recycling probability set of the candidate injection molding raw material based on the maximum number of recyclings of the candidate injection molding raw material and the production yield of injection molded parts in the future production cycle. The elements of the recycling probability set are the probability of successful recycling injection when injection molding parts are made using the candidate injection molding raw material.

[0038] The intelligent decision-making module includes: The yield calculation unit is used to accumulate the probability of successful recycling and recycling of each raw material based on the set of recycling and injection molding probabilities of the raw materials to be selected, and to obtain the recycling and injection molding yield of the raw materials to be selected. The cost determination unit is used to determine the processing cost of injection molding, the cost of recycling and regenerating injection molded parts, and the total cost of each recycling and regeneration injection molding process. The standard cost calculation unit is used to calculate the standard injection cost of the selected injection molding material based on the probability of successful recycling injection molding in the recycling injection probability set, the total cost of each recycling injection molding, the recycling injection yield of the selected injection molding material, and the cost of the selected injection molding material. The raw material selection unit is used to screen out the candidate injection molding raw materials with the lowest standard injection molding cost, which will be used as the candidate injection molding raw materials in the next production cycle.

[0039] In summary, the advantages of this invention are as follows: By constructing a dynamic evaluation model that integrates historical production data, raw material recycling performance degradation patterns, and multi-cycle cost accounting, it can scientifically predict the performance of different injection molding raw materials throughout their entire life cycle. This achieves precise quantitative evaluation of the long-term performance and economic benefits of injection molding raw materials, especially recycled materials, overcoming the shortcomings of traditional methods that rely on static experience and limited data. This guides enterprises in selecting the optimal raw material solution, ultimately achieving multiple goals such as significantly reducing overall manufacturing costs, greatly improving resource recycling rates, and effectively ensuring product quality stability.

[0040] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A method for evaluating the regeneration of injection molded parts based on performance recovery, characterized in that, include: Analyze historical injection molding data of injection molded parts to obtain the production yield during the injection molding process; Obtain the performance requirements of the injection molded part and denote them as the baseline performance index; Obtain the performance data of all available injection molding materials, including the initial properties and regeneration properties of the injection molding materials; Injection molding raw materials whose initial performance exceeds the benchmark performance index are selected as candidate injection molding raw materials; Based on the recyclability of each candidate injection molding material and the production yield during the injection molding process, the recyclable injection molding scenario of each candidate injection molding material is evaluated. Based on the recycled injection molding scenario when molding injection parts using each candidate injection molding material, and combined with the cost of each candidate injection molding material, the system intelligently evaluates and decides on the material selection scheme for injection molded parts.

2. The method for evaluating the regeneration of injection molded parts based on performance recovery according to claim 1, characterized in that, The analysis of historical injection molding data of injection molded parts to obtain the production yield during the injection molding process specifically includes: Extract the number of good and defective injection molded parts produced in the production cycles closest to the current time, and calculate the production yield in each production cycle. Using the production yield of several production cycles closest to the current moment as sample data, the production yield of injection molded parts in future production cycles is calculated and predicted.

3. The method for evaluating the regeneration of injection molded parts based on performance recovery according to claim 2, characterized in that, The specific method for calculating and predicting the production yield of injection molded parts in future production cycles by using the production yield of several production cycles closest to the current time as sample data is as follows: predict the production yield of injection molded parts in future production cycles by using regression prediction or averaging based on the sample data. Specifically, the regression prediction method used to predict the production yield of injection molded parts in the future production cycle includes: Based on the time interval between each production cycle and the current moment, time numbers are added to each production cycle in ascending order of time. A regression equation for the production yield of injection molded parts is constructed with the production yield of injection molded parts in each production cycle as the dependent variable and the time sequence number of each production cycle as the independent variable. Predict the production yield of injection molded parts in future production cycles based on the regression equation of injection molded part production yield; Predicting injection molded part production yield in future production cycles using the averaging method specifically includes: Data filtering of sample data is based on Grubbs' criterion; The average of the injection molded part production yield over all sample periods after data filtering is used as the injection molded part production yield for future production periods.

4. The method for evaluating the regeneration of injection molded parts based on performance recovery according to claim 3, characterized in that, The evaluation of the recyclable injection molding scenario for each candidate injection molding material, based on its recyclability and production yield during the injection molding process, specifically includes: Based on the recycling performance data of each candidate injection molding material, determine the performance data of the candidate injection molding material after each recycling and regeneration injection molding. The maximum number of recycling cycles for the selected injection molding raw material is determined by determining that the performance data of the recycled injection molding raw material is greater than the benchmark performance index. Based on the maximum number of recyclable raw materials to be selected and the production yield of injection molded parts in the future production cycle, the set of recyclable injection molding probabilities of the raw materials to be selected is determined. The elements of the recyclable injection molding probability set are the probability of successful recycling injection each time the raw materials to be selected are used to inject molded parts.

5. The method for evaluating the regeneration of injection molded parts based on performance recovery according to claim 4, characterized in that, The intelligent evaluation and decision-making process for selecting injection molding materials based on the recycled injection molding scenario for each candidate injection molding material, combined with the cost of each candidate injection molding material, specifically includes: Based on the set of recycling injection probability of the candidate injection molding raw materials, the probability of successful recycling injection is accumulated to obtain the recycling injection yield of the candidate injection molding raw materials; Determine the processing cost of injection molding, the cost of recycling and regenerating injection molded parts, and the total cost of each recycling and regeneration injection molding process; Based on the probability of successful recycling and recycling in each recycling and recycling probability set, the total cost of recycling and recycling in each recycling and recycling, the recycling yield of the selected injection molding raw material and the cost of the selected injection molding raw material, the standard injection molding cost of the selected injection molding raw material is calculated. Select the injection molding raw material with the lowest standard injection molding cost as the candidate injection molding raw material in the next production cycle.

6. A method for evaluating the regeneration of injection molded parts based on performance recovery according to any one of claims 1-5, characterized in that, The method also includes a hierarchical evaluation mechanism, which specifically includes: Set a threshold for injection molding yield. If the production yield during the injection molding process is higher than the threshold, intelligently evaluate and decide on the raw material selection scheme for the injection molded part. If the production yield during the injection molding process is lower than the injection molding yield threshold, the production line will be stopped for maintenance.

7. A performance recovery-based evaluation system for the regeneration of injection molded parts, characterized in that, The method for evaluating the regeneration of injection molded parts based on performance recovery as described in any one of claims 1-6 includes: The historical data analysis module is used to analyze historical injection data of injection molded parts to obtain the production yield during the injection molding process. The performance requirement acquisition module is used to acquire the performance requirements of the injection molded parts, which are denoted as the baseline performance indicators. The raw material performance acquisition module is used to acquire the performance data of all currently available injection molding raw materials, including the initial performance and regeneration performance of the injection molding raw materials; The raw material screening module is used to screen out injection molding raw materials whose initial performance exceeds the benchmark performance index, and use them as candidate injection molding raw materials. The recycling scenario assessment module is used to assess the recycling injection scenario of each candidate injection molding material when injection molding parts, based on the recycling performance of each candidate injection molding material and the production yield during the injection molding process. The intelligent decision-making module is used to intelligently evaluate and decide on the raw material selection scheme for injection molded parts based on the recycled injection molding scenario when each candidate injection molding raw material is used for injection molding.

8. The performance recovery-based evaluation system for regenerated injection molded parts according to claim 7, characterized in that, The historical data analysis module includes: The data extraction unit is used to extract the number of good and defective injection molded parts produced in the production cycles closest to the current time, and to calculate the production yield in each production cycle. The prediction unit is used to calculate and predict the production yield of injection molded parts in future production cycles, using the production yield of the production cycles closest to the current time as sample data.

9. The performance recovery-based evaluation system for regenerated injection molded parts according to claim 7, characterized in that, The regeneration scenario assessment module includes: The performance determination unit is used to determine the performance data of each selected injection molding raw material after each recycling and regeneration injection molding based on the recycling performance data of each selected injection molding raw material. The maximum number of recycling units is used to determine the maximum number of recycling cycles that the performance data of the selected injection molding raw material after recycling and re-injection molding is greater than the benchmark performance index, and this number is used as the maximum number of recycling cycles for the selected injection molding raw material. The probability set determination unit is used to determine the recycling probability set of the candidate injection molding raw material based on the maximum number of recyclings of the candidate injection molding raw material and the production yield of injection molded parts in the future production cycle. The elements of the recycling probability set are the probability of successful recycling injection when injection molding parts are made using the candidate injection molding raw material.

10. The performance recovery-based evaluation system for regenerated injection molded parts according to claim 7, characterized in that, The intelligent decision-making module includes: The yield calculation unit is used to accumulate the probability of successful recycling and recycling of each raw material based on the set of recycling and injection molding probabilities of the raw materials to be selected, and to obtain the recycling and injection molding yield of the raw materials to be selected. The cost determination unit is used to determine the processing cost of injection molding, the cost of recycling and regenerating injection molded parts, and the total cost of each recycling and regeneration injection molding process. The standard cost calculation unit is used to calculate the standard injection cost of the selected injection molding material based on the probability of successful recycling injection molding in the recycling injection probability set, the total cost of each recycling injection molding, the recycling injection yield of the selected injection molding material, and the cost of the selected injection molding material. The raw material selection unit is used to screen out the candidate injection molding raw materials with the lowest standard injection molding cost, which will be used as the candidate injection molding raw materials in the next production cycle.

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