Cable production management method and system, device, and storage medium

Abstract

This application provides a cable production management method, system, equipment, and storage medium, belonging to the field of production management technology. The method includes: obtaining the cable model of the target cable; matching the cable model with a cable type classification table to obtain the cable type of the target cable; if the target cable type belongs to Class I cable, determining initial cable production parameters based on the cable model and a production parameter lookup table; adjusting the initial cable production parameters based on the cable production raw material data and production environment data of the target cable to obtain the target cable production parameters; the production parameter lookup table includes a one-to-one correspondence between cable models and cable production parameters; if the target cable type belongs to Class II cable, determining the cable production parameters based on the cable model and the production parameter lookup table. This application can improve the efficiency of production parameter management in the cable production process and enhance the stability of the finished cable quality.

Description

Technical Field

[0001] This application belongs to the field of production management technology, and more specifically, relates to cable production management methods and systems, equipment, and storage media. Background Technology

[0002] Cable production is a complex process involving multiple stages, including extrusion, cooling, traction, and cabling. The quality of the finished product highly depends on the precise control of production parameters at each stage. Different cable models have significantly different requirements for the adaptability of production parameters due to differences in structure and performance requirements.

[0003] In existing technologies, cable production parameter management often adopts a uniform model, such as setting parameters based on operator experience, which results in fixed parameters and a lack of flexibility. However, in actual production, different cables have different characteristics and are also affected by the environment, leading to inconsistent cable quality and unstable or substandard finished product quality.

[0004] Therefore, existing cable production management methods are insufficient to achieve precise and differentiated control of parameters based on the characteristics of different cable models, resulting in a dilemma between maintaining quality stability and production efficiency. Summary of the Invention

[0005] The purpose of this application is to provide cable production management methods, systems, equipment, and storage media to improve the efficiency of managing production parameters during the cable production management process, thereby enhancing the stability of the quality of finished cable products.

[0006] A first aspect of this application provides a cable production management method, including:

[0007] Obtain the cable model number of the target cable, and match the cable type from the cable type classification table based on the cable model number; the target cable is the cable to be manufactured, and the cable type classification table includes a one-to-one correspondence between cable model numbers and cable types.

[0008] If the target cable is a Class I cable, the initial cable production parameters are determined based on the cable model and production parameter lookup table. The initial cable production parameters are then adjusted based on the raw material data and production environment data of the target cable to obtain the target cable production parameters. The production parameter lookup table includes a one-to-one correspondence between cable model and cable production parameters.

[0009] If the target cable is a Class II cable, the initial cable production parameters are determined based on the cable model and production parameter lookup table of the target cable, and are used as the production parameters of the target cable. The environmental sensitivity coefficient of Class I cable is greater than that of Class II cable, and the raw material data fluctuation coefficient of Class I cable is greater than that of Class II cable.

[0010] A second aspect of this application provides a cable production management system, including:

[0011] The cable classification module is used to obtain the cable model of the target cable and match the cable type from the cable type classification table based on the cable model to obtain the cable type of the target cable. The target cable is the cable to be manufactured, and the cable type classification table includes a one-to-one correspondence between cable model and cable type.

[0012] The first cable management module is used to determine the initial cable production parameters based on the cable model and production parameter lookup table if the target cable belongs to Class I cable; and to adjust the initial cable production parameters based on the cable production raw material data and production environment data of the target cable to obtain the target cable production parameters; the production parameter lookup table includes a one-to-one correspondence between cable model and cable production parameters;

[0013] The second cable management module is used to determine the initial cable production parameters based on the cable model and production parameter lookup table of the target cable if the target cable is a Class II cable. The environmental sensitivity coefficient of Class I cables is greater than that of Class II cables, and the raw material data fluctuation coefficient of Class I cables is greater than that of Class II cables.

[0014] A third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of the cable production management method described above.

[0015] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the cable production management method described above.

[0016] The beneficial effects of the cable production management method, system, equipment, and storage medium provided in this application are as follows:

[0017] This application's embodiments, by classifying cables into Class I and Class II and implementing differentiated production parameter management, can balance production quality stability and management efficiency. For Class I cables, after determining initial parameters based on the model, adjustments are further made in conjunction with raw material and environmental data to ensure that the parameters adapt to fluctuations in raw material characteristics and environmental changes. This avoids quality defects (such as substandard insulation performance) caused by fluctuations in raw materials or the environment, significantly improving the finished product qualification rate of this type of cable. For Class II cables, parameters are directly called based on the model, eliminating redundant adjustment steps, reducing the time cost and operational complexity of parameter setting, improving production preparation efficiency, and reducing management resource consumption.

[0018] The classification and control logic of this application embodiment can accurately adapt parameters for cable models that are sensitive to raw materials and environment, and simplify the process for cable models with strong tolerance, thus solving the problem that it is difficult to balance quality stability and production efficiency under the unified parameter management mode. Attached Figure Description

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

[0020] Figure 1 A schematic flowchart of a cable production management method provided in an embodiment of this application;

[0021] Figure 2 A structural block diagram of a cable production management system provided in an embodiment of this application;

[0022] Figure 3 This is a schematic block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0023] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0024] To make the objectives, technical solutions, and advantages of this application clearer, the following description will be provided in conjunction with the accompanying drawings and specific embodiments.

[0025] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating a cable production management method according to an embodiment of this application. The method can be executed by an electronic device, and specifically, the method may include S101 to S103.

[0026] S101: Obtain the cable model of the target cable, and match the cable type of the target cable from the cable type classification table based on the cable model; the target cable is the cable to be manufactured, and the cable type classification table includes a one-to-one correspondence between cable model and cable type.

[0027] In this embodiment, the target cable refers to the cable product planned for production. A cable model number is a combination of characters used to uniquely identify a type of cable product; it can be classified based on attributes such as conductor material, insulation type, voltage rating, and number of cores. The cable type classification table is a data table storing the correspondence between cable models and cable types. Cable types are categories based on cable characteristics; for example, different cable types can be classified based on raw material sensitivity and environmental sensitivity. A one-to-one correspondence means that each cable model uniquely corresponds to one cable type, ensuring the determinacy of the classification.

[0028] In this embodiment, a pre-established cable type classification table is used to associate the model number and type of the cable to be produced. Before production, the corresponding cable type can be directly obtained through model number retrieval. The consideration behind this embodiment is that different models of cables have different structural material performance requirements, resulting in different production management needs. Establishing a correspondence between model number and type in advance allows for rapid determination of management strategies during the production preparation stage, avoiding inefficiencies caused by complex model number parsing. At the same time, standardized classification ensures consistency in subsequent production parameter management.

[0029] For example, the specific implementation process of obtaining the cable model of the target cable and matching it with the cable type classification table based on the cable model may include:

[0030] (1) In this embodiment, a cable type classification table can be pre-built. Specifically, in this embodiment, the cable production management system can be used to obtain all historical and planned cable models produced by the factory. By analyzing the production characteristics corresponding to each model, the cable type to which each cable model belongs can be determined, and a one-to-one correspondence between cable models and cable types can be established. In this embodiment, this correspondence can be entered into the database of the production management system to form a structured cable type classification table, which can be maintained regularly according to the updates of newly added cable models or type classification standards.

[0031] (2) This embodiment can obtain the cable model of the target cable. Specifically, when a production task is generated, the target cable is the cable to be produced. This embodiment can automatically obtain the cable model of the target cable from the cable production management system; if the automatic acquisition fails, the operator shall input the cable model of the target cable into the operation interface of the cable production management system.

[0032] (3) This embodiment can match cable type based on cable model. Specifically, this embodiment can call the cable type classification table in the database, use the cable model of the target cable as the search keyword, search in the cable type classification table, find the record corresponding to the cable model through precise matching, and extract the cable type of the target cable from the record. Finally, this embodiment uses the matched cable type of the target cable as the basis for subsequently determining the production parameter management strategy.

[0033] S102: If the target cable is a Class I cable, the initial cable production parameters are determined based on the cable model and production parameter lookup table of the target cable; the initial cable production parameters are adjusted based on the cable production raw material data and production environment data of the target cable to obtain the target cable production parameters; the production parameter lookup table includes a one-to-one correspondence between the cable model and the cable production parameters.

[0034] In this embodiment, the execution order between S103 and S102 is not limited. S102 can be executed first and then S103, or S103 can be executed first and then S102.

[0035] In this embodiment, "Cable Class I" refers to a cable category sensitive to fluctuations in raw material properties and changes in the production environment. The production parameter lookup table is a data table storing the correspondence between cable models and production parameters, used for quickly retrieving the baseline production parameters for the corresponding cable. Initial cable production parameters are production parameters initially determined based on the cable model, such as extrusion temperature, traction speed, and cooling water temperature. Cable production raw material data are the characteristic data of the raw materials used in production, such as copper hardness and insulation melt index. Production environment data are environmental characteristic data of the production site, such as workshop temperature, humidity, and dust concentration. Target cable production parameters are the final parameters adjusted for actual production. A one-to-one correspondence means that each cable model uniquely corresponds to a set of production parameters, used to ensure the determinism of parameter retrieval.

[0036] In this embodiment, initial cable production parameters are first determined based on a cable model and production parameter lookup table for a certain type of cable. Then, these initial parameters are adjusted by combining data on the raw materials and production environment of the target cable to obtain the target cable's production parameters. The underlying consideration for this embodiment is that, due to its structure, materials, or performance requirements, this type of cable is highly sensitive to fluctuations in raw material characteristics and changes in the production environment; relying solely on fixed parameters is insufficient to guarantee production quality. The production parameter lookup table provided in this embodiment offers a unified benchmark of initial parameters, ensuring that parameter settings are based on standardized criteria and improving parameter management efficiency. Simultaneously, to improve the stability and pass rate of the finished product quality of this type of cable, this embodiment further adjusts the initial cable production parameters by combining real-time raw material and environmental data. This allows the parameters to adapt to actual production conditions, avoiding quality defects caused by fluctuations, and improving the accuracy of production control through standardized processes.

[0037] For example, if the target cable belongs to a Class I cable type, the specific implementation process for determining the target cable production parameters may include:

[0038] (1) In this embodiment, a production parameter query table can be pre-built. Specifically, in this embodiment, the cable models of all cables in the factory can be obtained through the cable production management system, the historical qualified production data of each model can be analyzed, and the initial cable production parameters corresponding to each cable model can be determined based on the production parameters corresponding to the high finished product qualification rate. A one-to-one correspondence between cable models and initial parameters can be established. In this embodiment, a structured production parameter query table can be formed based on this correspondence, and it can be updated and maintained regularly according to the addition of new cable models or production experience.

[0039] (2) In this embodiment, the initial cable production parameters can be determined based on the cable model and the production parameter lookup table. Specifically, when the production task of the target cable is generated, this embodiment can obtain the cable model of the target cable through the cable production management system, and then call the production parameter lookup table in the database to extract the corresponding initial cable production parameters based on the model.

[0040] (3) In this embodiment, the cable type of the target cable can be determined by the cable model. If the target cable is a Class I cable, the raw material data and production environment data of the target cable are collected. Specifically, in this embodiment, raw material data of cable production, such as copper resistivity and insulation density, can be obtained through raw material testing equipment; and production environment data, such as real-time temperature and humidity, can be collected through sensors deployed in the workshop.

[0041] (4) In this embodiment, the initial cable production parameters can be adjusted based on the collected data to obtain the target cable production parameters. Specifically, in this embodiment, the initial parameters can be correlated with raw material data and environmental data through the cable production management system, and the initial parameters can be optimized according to the preset adjustment rules. For example, the extrusion temperature can be adjusted according to the melt index deviation of the insulation material, and the cooling water temperature can be adjusted according to the temperature deviation of the workshop. Finally, the target cable production parameters are obtained as the basis for actual production.

[0042] S103: If the target cable is a Class II cable, the initial cable production parameters are determined based on the cable model and production parameter lookup table of the target cable and used as the target cable production parameters; the environmental sensitivity coefficient of Class I cable is greater than that of Class II cable, and the raw material data fluctuation coefficient of Class I cable is greater than that of Class II cable.

[0043] In this embodiment, the cable production parameters are directly determined by looking up a table of cable models and production parameters for Category II cables. The rationale behind this embodiment is that Category II cables are less sensitive to fluctuations in raw materials and the environment, requiring no complex adjustments. Directly accessing the parameters simplifies the process and thus improves production efficiency.

[0044] For example, if the target cable is a Class II cable, the specific implementation process for determining the cable production parameters may include:

[0045] (1) In this embodiment, a production parameter query table can be pre-built. Specifically, in this embodiment, the cable production management system can collect all cable models of Class II cables, determine the cable production parameters corresponding to each model based on historical stable production data, establish the correspondence between models and parameters, and enter the data into the system database to form a structured table.

[0046] (2) In this embodiment, the cable production parameters can be determined based on the cable model of the target cable (Category II cable) and a lookup table. Specifically, in this embodiment, the production parameter lookup table can be called, and the corresponding cable production parameters can be matched based on the cable model of the target cable. The cable production parameters can then be used as the basis for production execution.

[0047] As can be seen from the above, the embodiments of this application, by classifying cable models into Class I and Class II cables and implementing differentiated production parameter management, can balance production quality stability and management efficiency. For Class I cables, after determining the initial parameters based on the model, further adjustments are made in conjunction with raw material and environmental data to ensure that the parameters can adapt to fluctuations in raw material characteristics and environmental changes, avoiding quality defects (such as substandard insulation performance) caused by fluctuations in raw materials or the environment, and significantly improving the finished product qualification rate of this type of cable. For Class II cables, parameters are directly called based on the model, eliminating redundant adjustment steps, reducing the time cost and operational complexity of parameter setting, improving production preparation efficiency, and reducing management resource consumption.

[0048] The classification and control logic of this application embodiment can accurately adapt parameters for cable models that are sensitive to raw materials and environment, and simplify the process for cable models with strong tolerance, thus solving the problem that it is difficult to balance quality stability and production efficiency under the unified parameter management mode.

[0049] In one embodiment of this application, before obtaining the cable model of the target cable, the method further includes:

[0050] Obtain the cable model number for all historically manufactured cables;

[0051] Determine the cable type corresponding to each cable model, and construct a cable type classification table based on the cable models of all historically produced cables and the cable types corresponding to each cable model;

[0052] The method for determining the cable type corresponding to each historically produced cable model includes:

[0053] Based on the historical production data corresponding to this cable model, determine the raw material data fluctuation coefficient and environmental sensitivity coefficient corresponding to this cable model;

[0054] If the raw material data fluctuation coefficient is greater than the first fluctuation coefficient threshold, or the environmental sensitivity coefficient is greater than the first environmental sensitivity threshold, then the cable type corresponding to this cable model is determined to be a Class I cable.

[0055] If the raw material data fluctuation coefficient is less than or equal to the first fluctuation coefficient threshold, and the environmental sensitivity coefficient is less than or equal to the first environmental sensitivity coefficient threshold, then the cable type corresponding to the cable model is determined to be a Class II cable.

[0056] In this embodiment, the historical production data of the cable model includes the first cable production data corresponding to each of multiple historical production batches; the first cable production data includes historical cable production raw material data; the historical cable production raw material data includes historical conductor raw material data, historical insulation raw material data, historical shielding raw material data, and historical sheath raw material data; determining the raw material data fluctuation coefficient of the cable model based on the historical production data of the cable model includes: calculating the raw material data fluctuation coefficient of the cable model based on the historical conductor raw material data, historical insulation raw material data, historical shielding raw material data, and historical sheath raw material data corresponding to each of multiple historical production batches of the cable model.

[0057] In this embodiment, "historical production cable" refers to cable products that have been manufactured in the past. "Historical production data" refers to relevant data generated during the production process of historically produced cables. "Multiple historical production batches" refers to multiple production units of historically produced cables divided by production period or batch. "First cable production data" refers to the set of production data corresponding to a historical production batch. "Historical conductor raw material data" refers to the characteristic data of conductor raw materials in historical production, such as the resistivity of copper rods and the hardness of aluminum rods. "Historical insulation raw material data" refers to the characteristic data of insulation raw materials in historical production, such as the melt flow index of XLPE granules and the density of PVC. "Historical shielding raw material data" refers to the characteristic data of shielding raw materials in historical production, such as the volume resistivity of semiconducting tapes. "Historical sheathing raw material data" refers to the characteristic data of sheathing raw materials in historical production, such as the tensile strength of PE materials. "Raw material data fluctuation coefficient" refers to an index characterizing the degree of fluctuation in the raw material characteristics of this cable model. "First fluctuation coefficient threshold" refers to a critical value used to determine whether the raw material data fluctuation is significant. "First environmental sensitivity coefficient threshold" refers to a critical value used to determine whether the environmental sensitivity is significant.

[0058] In this embodiment, the cable models of all historically produced cables are obtained. For each cable model, a raw material data fluctuation coefficient and an environmental sensitivity coefficient are calculated based on its historical production data. These coefficients are then compared with corresponding thresholds to classify the cable into either Category I or Category II, ultimately constructing a cable type classification table. The underlying consideration for this embodiment is that different cable models have varying degrees of sensitivity to raw material characteristic fluctuations and environmental changes due to differences in raw material composition and structural design. This embodiment objectively distinguishes the sensitive characteristics by quantifying the raw material data fluctuation coefficient and environmental sensitivity coefficient. Classifying cable types using a first fluctuation coefficient threshold and a first environmental sensitivity coefficient threshold clarifies which cable models require fine-tuning parameters (Category I cables) and which can be simplified in management (Category II cables). The cable type classification table constructed in this embodiment provides a unified basis for subsequent production parameter management, avoiding control errors caused by subjective judgment and balancing quality stability and production efficiency.

[0059] For example, the specific implementation process of constructing a cable type classification table may include:

[0060] (1) This embodiment can obtain the cable models of all historically produced cables. Specifically, this embodiment can obtain all cable models that the factory has produced in the past through the cable production management system to form a historical model list to ensure that nothing is omitted.

[0061] (2) In this embodiment, the historical production data corresponding to each historically produced cable model can be obtained through the cable production management system. Specifically, for each cable model in the historical model list, the first cable production data corresponding to each of its multiple historical production batches can be retrieved from the database of the cable production management system. The historical conductor raw material data, historical insulation raw material data, historical shielding raw material data, and historical sheath raw material data are extracted, such as the hardness of copper materials and the melt index of insulation materials in each batch, and then organized and archived by batch.

[0062] (3) This embodiment can calculate the raw material data fluctuation coefficient of the cable model based on historical raw material data. Specifically, this embodiment can integrate the raw material data of conductors, insulation, shielding and sheath of all historical production batches for each model, calculate the fluctuation degree of various raw material characteristics through statistical analysis, and obtain the raw material data fluctuation coefficient of the model. The calculation process of environmental sensitivity coefficient is the same.

[0063] (4) In this embodiment, the cable type can be determined based on the comparison between the coefficient and the threshold. Specifically, in this embodiment, the calculated raw material data fluctuation coefficient can be compared with the first fluctuation coefficient threshold, and the environmental sensitivity coefficient can be compared with the first environmental sensitivity coefficient threshold. If the raw material data fluctuation coefficient exceeds the threshold or the environmental sensitivity coefficient exceeds the threshold, it is determined to be a Class I cable; if neither exceeds the threshold, it is determined to be a Class II cable.

[0064] (5) This embodiment can construct a cable type classification table. Specifically, this embodiment can associate all historically produced cable models with their corresponding determined cable types, enter them into the production management system database, form a structured cable type classification table, and regularly update and maintain it based on newly added historical production data.

[0065] This embodiment quantifies raw material data fluctuation coefficients and environmental sensitivity coefficients based on historical production data, and objectively classifies cable types using thresholds. This avoids the bias of subjective judgment based on experience, making the correspondence between cable models and types more accurate. This embodiment clarifies that Category I cables require fine-tuning of parameters, while Category II cables can be managed more simply, achieving differentiated control. This ensures quality stability for sensitive models while simplifying processes for more robust models, improving production efficiency. The cable type classification table constructed in this embodiment provides a unified standard for subsequent production parameter management, ensuring consistency and standardization of management strategies, reducing quality problems or efficiency losses caused by improper control, and balancing production quality and management economy.

[0066] In one embodiment of this application, the historical production data of the cable model includes second cable production data corresponding to multiple historical production batches; the second cable production data includes historical cable production raw material data, historical cable production parameter data, historical cable quality assessment data, and historical production environment data; determining the environmental sensitivity coefficient of the cable model based on the historical production data includes:

[0067] Based on historical cable quality assessment data, the historical production data of this cable model is divided into multiple historical data subsets; each historical data subset includes second cable production data corresponding to at least one historical production batch; the range of raw material data variation is determined based on all historical cable production raw material data in the historical production data of this cable model, and the range of production parameter variation is determined based on all historical cable production parameter data in the historical production data of this cable model.

[0068] For each historical data subset, the second cable production data corresponding to each historical production batch in the historical data subset is filtered based on the range of changes in raw material data and the range of changes in production parameters to obtain the filtered historical data subset; the correlation coefficient between historical cable quality assessment data and historical production environment data is calculated based on all filtered historical data subsets, and the environmental sensitivity coefficient of the cable model is determined based on the correlation coefficient.

[0069] In this embodiment, based on the range of changes in raw material data and the range of changes in production parameters, the second cable production data corresponding to each of the historical production batches in the historical data subset are filtered to obtain the filtered historical data subset, which specifically includes:

[0070] The range of raw material data variation is narrowed based on the first proportional coefficient to obtain the narrowed range of raw material data variation; the range of production parameter variation is narrowed based on the first proportional coefficient to obtain the narrowed range of production parameter variation; the second cable production data corresponding to each of all historical production batches in the historical data subset is filtered based on the narrowed range of raw material data variation and the narrowed range of production parameter variation to obtain the filtered historical data subset.

[0071] In this embodiment, the second cable production data refers to a set of production data containing multiple types of data corresponding to a historical production batch. Historical cable quality assessment data refers to evaluation data on the quality of historically produced cables, which may include, for example, finished product pass rate and quality assessment scores. Historical data subsets refer to groups of historical production data divided based on historical cable quality assessment data, with each subset containing second cable production data for at least one batch. Raw material data variation range refers to the fluctuation range of historical cable production raw material data within the historical data subset, such as the difference between the maximum and minimum values ​​of copper hardness. Production parameter variation range refers to the fluctuation range of historical cable production parameter data within the historical data subset, such as the difference between the maximum and minimum values ​​of extrusion temperature. The correlation coefficient is an indicator characterizing the degree of correlation between historical cable quality assessment data and historical production environment data.

[0072] In this embodiment, the first proportionality coefficient is a preset value used to narrow the range of changes in raw material data and production parameters. The function of the first proportionality coefficient is to increase the rigor of data screening by narrowing the range of changes in raw material data and production parameters, thereby accurately eliminating interference from fluctuations in raw material characteristics and adjustments in production parameters on quality assessment. Specifically, the original ranges of changes in raw material data and production parameters contain anomalous data with large fluctuations, making it difficult to ensure the stability of raw materials and parameters in the data when used directly for data analysis. However, by narrowing the range using the first proportionality coefficient, historical production batch data with more gradual fluctuations in raw materials and parameters can be retained. This allows the filtered subset of historical data to focus more on the independent impact of environmental factors on quality, providing a cleaner sample for subsequent calculation of the correlation coefficient between historical cable quality assessment data and historical production environment data, ensuring that the environmental sensitivity coefficient truly reflects the degree of environmental impact on quality.

[0073] In this embodiment, historical cable quality assessment data is divided into multiple historical data subsets to distinguish production batches with different quality levels. For each subset, the range of changes in raw materials and production parameters is calculated, and the data is filtered after being reduced by a first proportional coefficient to eliminate the interference of fluctuations in raw materials and parameters. The correlation coefficient between historical cable quality assessment data and historical production environment data in each subset is then calculated to comprehensively determine the environmental sensitivity coefficient of the cable model.

[0074] The consideration behind this embodiment is that by dividing historical production data into multiple historical data subsets based on historical cable quality assessment data, it is possible to longitudinally compare the characteristics of historical production environment data in different quality batches. For example, as the quality assessment data increases, does the environmental data in the corresponding data subset exhibit a specific distribution? Or, as the quality assessment data decreases, do the environmental data in the corresponding data subset exhibit common fluctuations? This embodiment can control the stability of raw materials and parameters within the same quality level, and more clearly observe the correlation between quality changes and environmental data changes, such as whether the quality assessment data fluctuates when the ambient temperature changes. The correlation coefficient calculated after data screening can accurately reflect the trend of the environment's impact on quality under different quality levels, ensuring that the environmental sensitivity coefficient truly quantifies the degree of correlation between the environment and quality, and providing a reliable basis for subsequent classification.

[0075] For example, the specific implementation process for determining the environmental sensitivity coefficient based on historical production data of this cable model may include:

[0076] (1) This embodiment can divide historical data subsets based on historical cable quality assessment data. Specifically, this embodiment can extract all second cable production data for this cable model through the cable production management system, and then extract historical cable quality assessment data, such as historical finished product qualification rate and / or historical quality assessment score. For example, this embodiment can divide the data into three levels according to the quality assessment score (such as 90 points and above, 80-90 points and below 80 points), and this embodiment can group the historical production batches corresponding to each level into a historical data subset.

[0077] (2) This embodiment can determine the range of changes in raw material data and the range of changes in production parameters. Specifically, this embodiment can, for each subset of historical data, count the maximum and minimum values ​​of all historical cable production raw material data (such as copper resistivity and insulation melt index) and calculate the difference to obtain the range of changes in raw material data; this embodiment can, count the maximum and minimum values ​​of all historical cable production parameter data (such as extrusion temperature and traction speed) and calculate the difference to obtain the range of changes in production parameters.

[0078] (3) This embodiment can narrow down the scope and filter the data. Specifically, in this embodiment, the first proportional coefficient can be set to 0.7, the range of raw material data variation can be multiplied by 0.7 to obtain the range of raw material data variation, and the range of production parameter variation can be multiplied by 0.7 to obtain the range of production parameter variation. From this historical data subset, the second cable production data in which both the historical cable production raw material data and the historical cable production parameter data are within the corresponding narrowed range can be filtered to form the filtered historical data subset.

[0079] (4) This embodiment can calculate the correlation coefficient and determine the environmental sensitivity coefficient. Specifically, this embodiment can calculate the correlation coefficient between historical cable quality assessment data and historical production environment data (such as workshop temperature and humidity) for all filtered historical data subsets, and take the weighted average of the correlation coefficients between the environmental parameters such as workshop temperature and humidity and the historical cable quality assessment data as the environmental sensitivity coefficient of the cable model, so as to quantify the degree of influence of the environment on quality.

[0080] In this embodiment, based on the reduced range of raw material data variation and the reduced range of production parameter variation, the second cable production data corresponding to each of all historical production batches in the historical data subset are filtered to obtain the filtered historical data subset, which specifically includes:

[0081] For the second cable production data corresponding to each historical production batch in the historical data subset: if the historical cable production raw material data in the second cable production data is within the range of variation of the reduced raw material data, and the historical cable production parameter data is within the range of variation of the reduced production parameters, then the second cable production data is added to the filtered historical data subset.

[0082] In this embodiment, historical cable quality assessment data includes historical finished product pass rate data and historical quality assessment score data; based on the historical cable quality assessment data, the historical production data of this cable model is divided into multiple historical data subsets, which may specifically include:

[0083] Based on historical finished product pass rate data, multiple finished product pass rate intervals are determined, and multiple quality assessment levels are divided based on historical quality assessment score data. Based on multiple finished product pass rate intervals and multiple quality assessment levels, the historical production data of this cable model is divided into multiple historical data subsets.

[0084] In this embodiment, historical finished product pass rate data refers to the proportion of qualified finished products in historical production batches out of the total finished products. Historical quality assessment score data refers to the quantitative scoring data of the quality of cables produced in history. Finished product pass rate range refers to the range divided according to historical finished product pass rate data, such as 98% and above, 95%-98%, etc. Quality assessment level refers to the level divided according to historical quality assessment score data, such as Grade A, Grade B, and Grade C, etc.

[0085] In this embodiment, the underlying consideration is that historical production data for the same cable model may show differences in quality levels, which could mask the true impact of the environment on quality. By dividing the data into subsets based on pass rate ranges and quality levels, it is possible to ensure that the historical cable quality assessment data within each subset has similar characteristics. This reduces the interference of quality fluctuations on subsequent calculations of environmental sensitivity coefficients, making the divided subsets more suitable for analyzing the correlation between environmental factors and quality, thus laying the foundation for accurate calculation of environmental sensitivity coefficients.

[0086] For example, the specific implementation process of dividing the historical production data of this cable model into multiple historical data subsets based on historical cable quality assessment data may include:

[0087] (1) This embodiment can determine the range of finished product pass rate and the classification criteria for quality assessment level. Specifically, this embodiment can analyze the historical finished product pass rate data of the cable model and set the range according to the distribution characteristics (such as 98% and above, 95%-98% and below 95%); this embodiment can analyze the historical quality assessment score data and classify the level according to the score range (such as 90 points and above is level A, 80-90 points is level B, and below 80 points is level C).

[0088] (2) This embodiment can associate historical production batches with quality indicators. Specifically, this embodiment can extract the second cable production data corresponding to each historical production batch of the cable model, and determine the range of historical finished product qualification rate and the level of historical quality assessment score for each batch.

[0089] (3) This embodiment can divide historical data into subsets. Specifically, this embodiment can group the second cable production data corresponding to all historical production batches that belong to the same finished product qualification rate range and the same quality assessment level into a historical data subset to ensure that the quality assessment data characteristics within each subset are consistent.

[0090] This embodiment divides production batches into subsets based on historical finished product pass rate data and historical quality assessment score data. This allows for precise differentiation of production batches at different quality levels, enabling longitudinal comparison of historical production environment data characteristics across different quality batches. This avoids the overall quality fluctuations masking the true correlation between environment and quality, laying the foundation for subsequent analysis. This embodiment narrows the range of raw material data and production parameter variations and filters the data using a first proportionality coefficient. This effectively eliminates interference from raw material characteristic fluctuations and production parameter adjustments on quality assessment, ensuring that the filtered dataset focuses more on the independent impact of environmental factors on quality, thus improving the purity of the environment-quality correlation analysis. Based on the filtered subsets, this embodiment calculates correlation coefficients and determines environmental sensitivity coefficients. This objectively quantifies the degree of environmental impact on cable quality, making the environmental sensitivity coefficients more accurately reflect the actual correlation. This provides a reliable basis for subsequent cable model classification, improving the stability and scientific management of cable production quality.

[0091] In one embodiment of this application, before obtaining the cable model of the target cable, the method further includes:

[0092] Obtain the cable model number for all historically manufactured cables;

[0093] For each historically produced cable model, if the cable model belongs to a certain type of cable, then perform the first operation to obtain the reference cable production parameters corresponding to that cable model:

[0094] The first operation includes:

[0095] Obtain the third-party cable production data corresponding to each of the multiple historical production batches of this cable model. The third-party cable production data includes historical cable production raw material data, historical cable production parameter data, historical cable quality assessment data, and historical production environment data.

[0096] Based on the first screening condition, the third cable production data of the target historical production batch is determined from the third cable production data corresponding to each of the multiple historical production batches of this cable model; the first screening condition is that the historical cable quality assessment data is higher than the first quality assessment threshold.

[0097] Based on the production data of the third cable from the target historical production batch, the reference cable production parameters corresponding to this cable model are determined; the reference cable production parameters are used to construct a production parameter lookup table.

[0098] In this embodiment, after obtaining the cable models of all historically manufactured cables, the method further includes:

[0099] For each historically produced cable model, if the cable model belongs to Category II cable, then perform the second operation to obtain the reference cable production parameters corresponding to that cable model.

[0100] A production parameter lookup table is constructed based on the benchmark cable production parameters corresponding to the cable models of each historically produced cable.

[0101] The second operation includes:

[0102] Obtain the fourth cable production data corresponding to each of the multiple historical production batches of this cable model. The fourth cable production data includes historical cable production parameter data and historical cable quality assessment data.

[0103] Based on the second screening criteria, the fourth cable production data of the target historical production batch is determined from the fourth cable production data corresponding to each of the multiple historical production batches of this cable model; the second screening criteria is that the cable quality assessment data is higher than the second quality assessment threshold, and the second quality assessment threshold is higher than the first quality assessment threshold.

[0104] The production parameters of the reference cable corresponding to this cable model are determined based on the production data of the fourth cable from the target historical production batch.

[0105] In this embodiment, the third cable production data refers to the set of historical production data for Class I cables. The fourth cable production data refers to the set of historical production data for Class II cables. The first screening condition refers to the condition used to screen high-quality batches of Class I cables, with historical cable quality assessment data exceeding a first quality assessment threshold as the standard. The second screening condition refers to the condition used to screen high-quality batches of Class II cables, with cable quality assessment data exceeding a second quality assessment threshold as the standard. The first quality assessment threshold refers to the critical value for Class I cable quality qualification, and the second quality assessment threshold refers to the critical value for Class II cable quality qualification that is higher than the first threshold. The benchmark cable production parameters refer to the standard production parameters corresponding to each cable model, serving as the benchmark for subsequent production.

[0106] In this embodiment, for Class I cables, batches with historical quality assessment data higher than the first quality assessment threshold are selected, and benchmark parameters are determined based on third cable production data including raw materials, parameters, and environment. For Class II cables, batches with quality assessment data higher than the second quality assessment threshold are selected, and benchmark parameters are determined based on fourth cable production data including parameters and quality. Finally, a production parameter lookup table is constructed.

[0107] The considerations behind this embodiment are as follows: First-class cables are sensitive to raw materials and the environment, requiring the determination of baseline parameters based on high-quality batches containing multiple types of data to provide a foundation for subsequent adjustments; second-class cables are more resilient, simplifying data dimensions (only parameters and quality) and setting a higher second threshold to ensure more stable and reliable baseline parameters. This embodiment ensures the validity of baseline parameters by classifying and screening high-quality batch data, and the constructed lookup table provides a unified standard for setting production parameters for different types of cables, balancing accuracy and efficiency.

[0108] For example, the specific implementation process of constructing a production parameter query table may include:

[0109] (1) This embodiment can handle the determination of the benchmark parameters of a type of cable. Specifically, this embodiment can obtain the third cable production data of multiple historical production batches for each cable model belonging to a type of cable through the production management system; this embodiment can set a first quality assessment threshold (such as a quality assessment score of 85 points) and filter out target historical production batches whose historical cable quality assessment data is higher than the threshold; this embodiment can integrate the historical cable production parameter data of these batches and take the mean or mode as the benchmark cable production parameters corresponding to the model.

[0110] (2) This embodiment can handle the determination of the benchmark parameters for Category II cables. Specifically, this embodiment can obtain the fourth cable production data of multiple historical production batches for each cable model that belongs to Category II cables; this embodiment can set a second quality assessment threshold (such as a quality assessment score of 90 points, which is higher than the first threshold) and filter out target historical production batches whose cable quality assessment data is higher than the threshold; this embodiment can integrate the historical cable production parameter data of these batches and take the mean or mode as the benchmark cable production parameters corresponding to the model.

[0111] (3) This embodiment can construct a production parameter lookup table. Specifically, this embodiment can associate all historically produced cable models with the corresponding determined benchmark cable production parameters to form a structured production parameter lookup table.

[0112] This embodiment determines benchmark parameters by classifying cables into Category I and Category II, taking into account the characteristic requirements of different cable types. For Category I cables, benchmarks are determined based on high-quality batches containing multi-category data, providing a comprehensive reference for subsequent parameter adjustments. For Category II cables, data dimensions are simplified and higher quality thresholds are set to ensure more stable and reliable benchmark parameters. This embodiment selects high-quality batch data as the benchmark source, ensuring the validity and rationality of the benchmark cable production parameters. The production parameter lookup table constructed in this embodiment provides a unified parameter standard for all types of cables, reducing the subjectivity of parameter setting and improving the standardization of production parameter management. This ensures a solid foundation for quality adjustments for Category I cables while improving the production efficiency of Category II cables, balancing production quality and management economy.

[0113] Corresponding to the cable production management method in the above embodiment, Figure 2 This is a structural block diagram of a cable production management system provided according to an embodiment of this application. For ease of explanation, only the parts relevant to the embodiment of this application are shown. References Figure 2The cable production management system 20 includes: a cable classification module 21, a first cable management module 22, and a second cable management module 23.

[0114] The cable classification module 21 is used to obtain the cable model of the target cable and match the cable type of the target cable from the cable type classification table based on the cable model. The target cable is the cable to be produced, and the cable type classification table includes a one-to-one correspondence between cable model and cable type.

[0115] The first cable management module 22 is used to determine the initial cable production parameters based on the cable model and production parameter lookup table if the target cable belongs to Class I cable; and to adjust the initial cable production parameters based on the cable production raw material data and production environment data of the target cable to obtain the target cable production parameters; the production parameter lookup table includes a one-to-one correspondence between cable model and cable production parameters;

[0116] The second cable management module 23 is used to determine the initial cable production parameters based on the cable model and production parameter lookup table of the target cable if the cable type of the target cable belongs to Class II cable, and use them as the target cable production parameters; the environmental sensitivity coefficient of Class I cable is greater than that of Class II cable, and the raw material data fluctuation coefficient of Class I cable is greater than that of Class II cable.

[0117] In one embodiment of this application, the cable production management system 20 further includes:

[0118] The cable type analysis module is used for:

[0119] Obtain the cable model number for all historically manufactured cables;

[0120] Determine the cable type corresponding to each cable model, and construct a cable type classification table based on the cable models of all historically produced cables and the cable types corresponding to each cable model;

[0121] The method for determining the cable type corresponding to each historically produced cable model includes:

[0122] Based on the historical production data corresponding to this cable model, determine the raw material data fluctuation coefficient and environmental sensitivity coefficient corresponding to this cable model;

[0123] If the raw material data fluctuation coefficient is greater than the first fluctuation coefficient threshold, or the environmental sensitivity coefficient is greater than the first environmental sensitivity threshold, then the cable type corresponding to this cable model is determined to be a Class I cable.

[0124] If the raw material data fluctuation coefficient is less than or equal to the first fluctuation coefficient threshold, and the environmental sensitivity coefficient is less than or equal to the first environmental sensitivity coefficient threshold, then the cable type corresponding to the cable model is determined to be a Class II cable.

[0125] In one embodiment of this application, the historical production data of the cable model includes first cable production data corresponding to multiple historical production batches; the first cable production data includes historical cable production raw material data; the historical cable production raw material data includes historical conductor raw material data, historical insulation raw material data, historical shielding raw material data, and historical sheath raw material data; the cable type analysis module is specifically used for:

[0126] The raw material data fluctuation coefficient of this cable model is calculated based on the historical conductor raw material data, historical insulation raw material data, historical shielding raw material data, and historical sheath raw material data corresponding to multiple historical production batches.

[0127] In one embodiment of this application, the historical production data of the cable model includes second cable production data corresponding to multiple historical production batches; the second cable production data includes historical cable production raw material data, historical cable production parameter data, historical cable quality assessment data, and historical production environment data; the cable type analysis module is further used for:

[0128] Based on historical cable quality assessment data, the historical production data of this cable model is divided into multiple historical data subsets; each historical data subset includes the second cable production data corresponding to at least one historical production batch.

[0129] The range of raw material data variation is determined based on all historical cable production raw material data in the historical production data of this cable model, and the range of production parameter variation is determined based on all historical cable production parameter data in the historical production data of this cable model.

[0130] For each historical data subset, the second cable production data corresponding to each historical production batch in the historical data subset is filtered based on the range of changes in raw material data and the range of changes in production parameters to obtain the filtered historical data subset.

[0131] The correlation coefficient between historical cable quality assessment data and historical production environment data is calculated based on all filtered historical data subsets, and the environmental sensitivity coefficient of the cable model is determined based on the correlation coefficient.

[0132] In one embodiment of this application, the cable type analysis module is further used for:

[0133] The range of raw material data variation is narrowed based on the first proportional coefficient to obtain the narrowed range of raw material data variation; the range of production parameter variation is narrowed based on the first proportional coefficient to obtain the narrowed range of production parameter variation; the second cable production data corresponding to each of all historical production batches in the historical data subset is filtered based on the narrowed range of raw material data variation and the narrowed range of production parameter variation to obtain the filtered historical data subset.

[0134] In one embodiment of this application, the cable production management system 20 further includes:

[0135] The production parameter analysis module is used to obtain the cable model of all historically produced cables;

[0136] For each historically produced cable model, if the cable model belongs to a certain type of cable, then perform the first operation to obtain the reference cable production parameters corresponding to that cable model:

[0137] The first operation includes:

[0138] Obtain the third-party cable production data corresponding to each of the multiple historical production batches of this cable model. The third-party cable production data includes historical cable production raw material data, historical cable production parameter data, historical cable quality assessment data, and historical production environment data.

[0139] Based on the first screening condition, the third cable production data of the target historical production batch is determined from the third cable production data corresponding to each of the multiple historical production batches of this cable model; the first screening condition is that the historical cable quality assessment data is higher than the first quality assessment threshold.

[0140] Based on the production data of the third cable from the target historical production batch, the reference cable production parameters corresponding to this cable model are determined; the reference cable production parameters are used to construct a production parameter lookup table.

[0141] In one embodiment of this application, the production parameter analysis module is further configured to:

[0142] For each historically produced cable model, if the cable model belongs to Category II cable, then perform the second operation to obtain the reference cable production parameters corresponding to that cable model.

[0143] A production parameter lookup table is constructed based on the benchmark cable production parameters corresponding to the cable models of each historically produced cable.

[0144] The second operation includes:

[0145] Obtain the fourth cable production data corresponding to each of the multiple historical production batches of this cable model. The fourth cable production data includes historical cable production parameter data and historical cable quality assessment data.

[0146] Based on the second screening criteria, the fourth cable production data of the target historical production batch is determined from the fourth cable production data corresponding to each of the multiple historical production batches of this cable model; the second screening criteria is that the cable quality assessment data is higher than the second quality assessment threshold, and the second quality assessment threshold is higher than the first quality assessment threshold.

[0147] The production parameters of the reference cable corresponding to this cable model are determined based on the production data of the fourth cable from the target historical production batch.

[0148] See Figure 3 , Figure 3 This is a schematic block diagram of an electronic device provided according to an embodiment of this application. Figure 3 The electronic device 300 in this embodiment may include one or more processors 301, one or more input devices 302, one or more output devices 303, and one or more memories 304. The processors 301, input devices 302, output devices 303, and memories 304 communicate with each other via a communication bus 305. The memories 304 store computer programs, including program instructions. The processors 301 execute the program instructions stored in the memories 304. Specifically, the processors 301 are configured to invoke the program instructions to perform the functions of the modules in the aforementioned system embodiments, for example... Figure 2 The functions of the cable classification module 21, the first cable management module 22, and the second cable management module 23 are shown.

[0149] It should be understood that, in the embodiments of this application, the processor 301 may be a central processing unit (CPU), but it may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0150] Input device 302 may include a touchpad, a fingerprint sensor (for collecting the user's fingerprint information and fingerprint orientation information), a microphone, etc., and output device 303 may include a display (LCD, etc.), a speaker, etc.

[0151] The memory 304 may include read-only memory and random access memory, and provides instructions and data to the processor 301. A portion of the memory 304 may also include non-volatile random access memory. For example, the memory 304 may also store cable type information.

[0152] In specific implementations, the processor 301, input device 302, and output device 303 described in the embodiments of this application can execute the implementation methods described in the embodiments of the cable production management method provided in this application, or they can execute the implementation methods of the electronic device 300 described in the embodiments of this application, which will not be repeated here.

[0153] In another embodiment of this application, a computer-readable storage medium is provided. This computer-readable storage medium stores a computer program, which includes program instructions. When executed by a processor, the program instructions implement all or part of the processes in the methods described above. Alternatively, the computer program can instruct related hardware to complete the process. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0154] The computer-readable storage medium can be an internal storage unit of the electronic device in any of the foregoing embodiments, such as a hard disk or memory of the electronic device. The computer-readable storage medium can also be an external storage device of the electronic device, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD) card, flash card, etc., equipped on the electronic device. Furthermore, the computer-readable storage medium can include both internal and external storage units of the electronic device. The computer-readable storage medium is used to store computer programs and other programs and data required by the electronic device. The computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0155] Those skilled in the art will recognize that the modules / units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0156] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the electronic devices and units described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0157] In the embodiments provided in this application, it should be understood that the disclosed electronic devices and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For instance, the division of modules / units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules, units, or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces or modules / units, or it may be an electrical, mechanical, or other form of connection.

[0158] The modules / units described as separate components may or may not be physically separate. Similarly, the components shown as modules / units may or may not be physical modules / units; they may be located in one place or distributed across multiple network modules / units. Some or all of the modules / units can be selected to achieve the purpose of the embodiments of this application, depending on actual needs.

[0159] Furthermore, the functional modules / units in the various embodiments of this application can be integrated into one processing module / unit, or each module / unit can exist physically separately, or two or more modules / units can be integrated into one module / unit. The integrated modules / units described above can be implemented in hardware or in the form of software functional modules / units.

[0160] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A cable production management method, characterized in that, include: Obtain the cable model number for all historically manufactured cables; Determine the cable type corresponding to each cable model, and construct a cable type classification table based on the cable models of all historically produced cables and the cable types corresponding to each cable model; Among them, for each historically produced cable model, the method for determining the cable type corresponding to that cable model includes: determining the raw material data fluctuation coefficient and environmental sensitivity coefficient corresponding to that cable model based on the historical production data corresponding to that cable model; If the raw material data fluctuation coefficient is greater than the first fluctuation coefficient threshold, or the environmental sensitivity coefficient is greater than the first environmental sensitivity threshold, then the cable type corresponding to this cable model is determined to be a Class I cable. If the raw material data fluctuation coefficient is less than or equal to the first fluctuation coefficient threshold, and the environmental sensitivity coefficient is less than or equal to the first environmental sensitivity threshold, then the cable type corresponding to the cable model is determined to be a Class II cable. Obtain the cable model number of the target cable, and match the cable type of the target cable from the cable type classification table based on the cable model number; the target cable is the cable to be manufactured, and the cable type classification table includes a one-to-one correspondence between cable model numbers and cable types; If the target cable is a Class I cable, the initial cable production parameters are determined based on the cable model and production parameter lookup table of the target cable; the initial cable production parameters are adjusted based on the cable production raw material data and production environment data of the target cable to obtain the target cable production parameters; the production parameter lookup table includes a one-to-one correspondence between cable model and cable production parameters; If the target cable is a Class II cable, the initial cable production parameters are determined based on the cable model and production parameter lookup table of the target cable, and are used as the production parameters of the target cable; the environmental sensitivity coefficient of the Class I cable is greater than that of the Class II cable, and the raw material data fluctuation coefficient of the Class I cable is greater than that of the Class II cable. The historical production data for this cable model includes production data for the second cable corresponding to each of multiple historical production batches; the second cable production data includes historical cable production raw material data, historical cable production parameter data, historical cable quality assessment data, and historical production environment data; the historical cable quality assessment data includes historical finished product pass rate data and historical quality assessment score data. The environmental sensitivity coefficient of this cable model is determined based on historical production data, including: Based on historical finished product pass rate data, multiple finished product pass rate intervals are determined, and multiple quality assessment levels are divided based on historical quality assessment score data. Based on multiple finished product pass rate intervals and multiple quality assessment levels, the historical production data of this cable model is divided into multiple historical data subsets. Each historical data subset includes at least one historical production batch corresponding to the second cable production data. The range of raw material data variation is determined based on all historical cable production raw material data in the historical production data of this cable model, and the range of production parameter variation is determined based on all historical cable production parameter data in the historical production data of this cable model. For each historical data subset, the range of raw material data variation is narrowed based on a first proportional coefficient to obtain a narrowed range of raw material data variation; the range of production parameter variation is also narrowed based on a first proportional coefficient to obtain a narrowed range of production parameter variation; for the second cable production data corresponding to each historical production batch in the historical data subset: if the historical cable production raw material data in the second cable production data is within the narrowed range of raw material data variation, and the historical cable production parameter data is within the narrowed range of production parameter variation, then the second cable production data is added to the filtered historical data subset; The correlation coefficient between historical cable quality assessment data and historical production environment data is calculated based on all filtered historical data subsets, and the environmental sensitivity coefficient of the cable model is determined based on the correlation coefficient.

2. The cable production management method as described in claim 1, characterized in that, The historical production data for this cable model includes production data for the first cable corresponding to each of multiple historical production batches; the first cable production data includes historical cable production raw material data; the historical cable production raw material data includes historical conductor raw material data, historical insulation raw material data, historical shielding raw material data, and historical sheath raw material data; The raw material data fluctuation coefficient for this cable model is determined based on historical production data, including: The raw material data fluctuation coefficient of this cable model is calculated based on the historical conductor raw material data, historical insulation raw material data, historical shielding raw material data, and historical sheath raw material data corresponding to multiple historical production batches.

3. The cable production management method as described in claim 1, characterized in that, Before obtaining the cable type of the target cable, the process also includes: Obtain the cable model number for all historically manufactured cables; For each historically produced cable model, if the cable model belongs to a certain type of cable, then perform the first operation to obtain the reference cable production parameters corresponding to that cable model: The first operation includes: Obtain the third cable production data corresponding to each of the multiple historical production batches of this cable model. The third cable production data includes historical cable production raw material data, historical cable production parameter data, historical cable quality assessment data, and historical production environment data. Based on the first screening condition, the third cable production data of the target historical production batch is determined from the third cable production data corresponding to each of the multiple historical production batches of this cable model; the first screening condition is that the historical cable quality assessment data is higher than the first quality assessment threshold. Based on the third cable production data of the target historical production batch, the reference cable production parameters corresponding to the cable model are determined; the reference cable production parameters are used to construct a production parameter lookup table.

4. The cable production management method as described in claim 3, characterized in that, After obtaining the cable model numbers of all historically manufactured cables, the process also includes: For each historically produced cable model, if the cable model belongs to Category II cable, then perform the second operation to obtain the reference cable production parameters corresponding to that cable model. A production parameter lookup table is constructed based on the benchmark cable production parameters corresponding to the cable models of each historically produced cable. The second operation includes: Obtain the fourth cable production data corresponding to each of the multiple historical production batches of this cable model. The fourth cable production data includes historical cable production parameter data and historical cable quality assessment data. Based on the second screening criteria, the fourth cable production data of the target historical production batch is determined from the fourth cable production data corresponding to each of the multiple historical production batches of this cable model; the second screening criteria is that the cable quality assessment data is higher than the second quality assessment threshold, and the second quality assessment threshold is higher than the first quality assessment threshold. The reference cable production parameters corresponding to the cable model are determined based on the fourth cable production data of the target historical production batch.

5. A cable production management system, characterized in that, include: The cable type analysis module is used to obtain the cable model of all historically manufactured cables; Determine the cable type corresponding to each cable model, and construct a cable type classification table based on the cable models of all historically produced cables and the cable types corresponding to each cable model; Among them, for each historically produced cable model, the method for determining the cable type corresponding to that cable model includes: determining the raw material data fluctuation coefficient and environmental sensitivity coefficient corresponding to that cable model based on the historical production data corresponding to that cable model; If the raw material data fluctuation coefficient is greater than the first fluctuation coefficient threshold, or the environmental sensitivity coefficient is greater than the first environmental sensitivity threshold, then the cable type corresponding to this cable model is determined to be a Class I cable. If the raw material data fluctuation coefficient is less than or equal to the first fluctuation coefficient threshold, and the environmental sensitivity coefficient is less than or equal to the first environmental sensitivity threshold, then the cable type corresponding to the cable model is determined to be a Class II cable. The historical production data for this cable model includes production data for the second cable corresponding to each of multiple historical production batches; the second cable production data includes historical cable production raw material data, historical cable production parameter data, historical cable quality assessment data, and historical production environment data; the historical cable quality assessment data includes historical finished product pass rate data and historical quality assessment score data. The cable type analysis module is specifically used to determine multiple finished product pass rate intervals based on historical finished product pass rate data, and to divide multiple quality assessment levels based on historical quality assessment score data; based on multiple finished product pass rate intervals and multiple quality assessment levels, the historical production data of the cable model is divided into multiple historical data subsets; each historical data subset includes at least one historical production batch corresponding to the second cable production data. The range of raw material data variation is determined based on all historical cable production raw material data in the historical production data of this cable model, and the range of production parameter variation is determined based on all historical cable production parameter data in the historical production data of this cable model. For each historical data subset, the range of raw material data variation is narrowed based on a first proportional coefficient to obtain a narrowed range of raw material data variation; the range of production parameter variation is also narrowed based on a first proportional coefficient to obtain a narrowed range of production parameter variation; for the second cable production data corresponding to each historical production batch in the historical data subset: if the historical cable production raw material data in the second cable production data is within the narrowed range of raw material data variation, and the historical cable production parameter data is within the narrowed range of production parameter variation, then the second cable production data is added to the filtered historical data subset; Based on all filtered historical data subsets, the correlation coefficient between historical cable quality assessment data and historical production environment data is calculated, and the environmental sensitivity coefficient of the cable model is determined based on the correlation coefficient. The cable classification module is used to obtain the cable model of the target cable and match the cable type of the target cable from the cable type classification table based on the cable model; the target cable is the cable to be manufactured, and the cable type classification table includes a one-to-one correspondence between cable model and cable type; The first cable management module is used to determine the initial cable production parameters based on the cable model and production parameter lookup table of the target cable if the cable type of the target cable belongs to Class I cable; and to adjust the initial cable production parameters based on the cable production raw material data and production environment data of the target cable to obtain the target cable production parameters; the production parameter lookup table includes a one-to-one correspondence between cable model and cable production parameters; The second cable management module is used to determine the initial cable production parameters based on the cable model and production parameter lookup table of the target cable if the cable type of the target cable belongs to Class II cable, and use these parameters as the production parameters of the target cable; the environmental sensitivity coefficient of Class I cable is greater than that of Class II cable, and the raw material data fluctuation coefficient of Class I cable is greater than that of Class II cable.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 4.

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