A supply chain collaborative management system based on composite material sharing intelligent manufacturing

Abstract

The application relates to the technical field of supply chain management, and discloses a supply chain cooperative management system based on composite material sharing intelligent manufacturing; the system comprises a feature extraction module, which is used for extracting shared manufacturing features; a role analysis module, which is used for dividing supply roles into primary roles and secondary roles; a virtual factory module, which is used for generating a virtual factory with a shared path; and a shared upgrading module, which is used for updating and upgrading the shared path; the application can convert actual physical layer shared manufacturing into one-time all-around virtual simulation, thereby being capable of discovering and avoiding adverse reactions and supply defects existing in capacity connection, efficiency matching, visual cooperation and the like of different types of suppliers in advance, realizing level crossing of supply chain cooperation from static matching to dynamic optimization and simulation verification, and reducing the error probability of supply chain cooperation during composite material sharing intelligent manufacturing.

Description

Technical Field

[0001] This invention relates to the field of supply chain management technology, and more specifically, to a supply chain collaborative management system based on intelligent manufacturing of composite materials. Background Technology

[0002] As an emerging manufacturing paradigm, shared intelligent manufacturing dynamically integrates and coordinates dispersed design resources, material resources, manufacturing equipment, and market channels through a networked platform. This enables the social sharing and optimized allocation of manufacturing resources, which is of great positive significance for improving the overall efficiency of the composite materials industry and reducing the innovation costs of SMEs. Therefore, a supply chain collaborative management system is needed to collaboratively manage the shared manufacturing of composite materials.

[0003] Referring to patent application CN119599761A, a data labeling supply chain collaborative management system and method based on big data analysis is disclosed. The system uses a data labeling preset module to set preset data labels for any supply chain and adds the supply chain name to these preset data labels. A manufacturing progress analysis module collects the product manufacturing progress of any supply chain, analyzes the manufacturing progress, and converts it into manufacturing data labels. A supply progress analysis module collects the total sales progress of any supply chain, analyzes the total sales progress, and converts it into sales data labels. A distribution progress analysis module collects the product sales progress of any supply chain, and converts the sales progress into sales data labels. A supply chain completion analysis module summarizes and analyzes the data labels collected by the manufacturing progress analysis module, supply progress collection module, and distribution progress collection module, fills in the preset labels, and generates a unique data label for each supply chain. Existing supply chain collaborative management systems typically rely on the static qualifications of suppliers to match and set collaborative logic and rules in order to achieve the collaborative effect of shared manufacturing. However, this collaborative management method can only manage collaboratively at the actual physical level and cannot simulate and rehearse the entire supply chain collaborative management process at the virtual simulation level. As a result, it cannot discover potential anomalies and defects in shared manufacturing, leading to a high risk of failure hidden in the established supply chain collaborative scheme before actual operation, thereby increasing the probability of supply chain collaboration errors in the shared manufacturing of composite materials.

[0004] In view of this, the present invention proposes a supply chain collaborative management system based on intelligent manufacturing of composite materials to solve the above problems. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art and to achieve the above objectives, the present invention provides the following technical solution: a supply chain collaborative management system based on composite material shared intelligent manufacturing, applied to a collaborative management platform, comprising: The feature extraction module is used to extract shared manufacturing features from the user's manufacturing request. Shared manufacturing features include raw material supply credit, equipment manufacturing efficiency, and product service level. The role analysis module is used to index supply roles from suppliers based on shared manufacturing characteristics. Supply roles include material suppliers, equipment manufacturers, and product distributors. It also performs adaptation analysis on supply roles and divides them into preferred roles and secondary roles. The virtual factory module is used to establish a virtual supply scenario with supply positions based on the supply balance principle, and to import the preferred roles into the supply positions one by one to generate a virtual factory with a shared path. The shared upgrade module is used to dynamically collect the supply balance index of the preferred role in the shared path in a simulated environment, identify the collaborative attributes of the virtual factory, and replace the preferred role with the secondary role according to the collaborative attributes to update and upgrade the shared path.

[0006] Furthermore, the method for extracting shared manufacturing features is as follows: The key semantics in the manufacturing request were parsed using natural language processing technology, and then the key semantics were broken down into textual and numerical parts. The numerical parts of the key semantics of raw materials, equipment and products in the text part are divided into a first set of numbers, a second set of numbers and a third set of numbers, and the quantity of the numerical parts in the first set of numbers, the second set of numbers and the third set of numbers are queried respectively; When the number of the number part is 1, the number parts in the first number set, the second number set, and the third number set are recorded as raw material supply credit, equipment manufacturing efficiency, and product service level; When the number of numeric parts is greater than 1, retrieve the entry time of the numeric parts, and record the numeric parts of the last entry time as raw material supply credit, equipment manufacturing efficiency, and product service level.

[0007] Furthermore, the indexing method for supply roles is as follows: The system retrieves the attribute information and update information of each supplier in the supply chain, and extracts the attribute values ​​and update times from the attribute information and update information respectively. When the attribute value is S-11, the attribute information is recorded as a valid attribute; The period between the update time and the current time is recorded as the interruption period. When the duration of the interruption period is less than or equal to the supply interruption threshold, the update information is recorded as a valid update. Suppliers in the supply chain that simultaneously possess valid attributes and valid updates, and whose role semantics are materials, manufacturing, and products, are respectively denoted as material candidates, equipment candidates, and product candidates; Material suppliers with credit ratings greater than or equal to raw material supply credit ratings are designated as material suppliers; equipment suppliers with efficiency ratings greater than or equal to equipment manufacturing efficiency are designated as equipment manufacturers; and product suppliers with service ratings greater than or equal to product distributors are designated as product dealers.

[0008] Furthermore, the method for dividing the primary and secondary roles is as follows: The number of times material suppliers, equipment manufacturers, and product distributors performed safety self-checks and data updates during the interruption period were queried one by one. The number of data updates was compared with the number of safety self-checks to calculate the backup ratio. During the interruption period, work logs from material suppliers, equipment manufacturers, and product distributors participating in shared manufacturing were screened out, the quality level of the work logs was identified, and work logs with an excellent quality level were recorded as valid logs. After comparing the number of valid logs with the number of working logs, the excellent percentage value is calculated. The backup percentage value and the excellent percentage value are weighted and summed to calculate the shared performance index. Based on the shared performance index from largest to smallest, material suppliers, equipment manufacturers, and product distributors are arranged in descending order to generate the first queue, the second queue, and the third queue. The material suppliers, equipment manufacturers, and product distributors ranked first in the first, second, and third queues are designated as preferred roles, and the remaining material suppliers, equipment manufacturers, and product distributors are designated as secondary roles.

[0009] Furthermore, the supply balance criterion is: adjacent scene layers are connected through a hierarchical chain; The method for establishing a virtual supply scenario is as follows: A simulation scene is established using modeling and simulation tools. Three horizontally distributed scene layers with a closed ring structure are set in the simulation scene, and the three scene layers are respectively called the first layer, the middle layer and the last layer. B independent supply positions are simulated in the first, middle and last layers respectively, and contour lines are established between two adjacent supply positions. Establish a start port on the first layer, establish a start port and a stop port on the middle layer, and establish a stop port on the last layer. With the start port and the stop port as the two ends of the hierarchical chain, establish hierarchical chains between the first layer and the middle layer, and between the middle layer and the last layer. The hierarchical chain between the first layer and the middle layer is numbered C1, and the hierarchical chain between the middle layer and the last layer is numbered C2, thus transforming the simulation scenario into a virtual supply scenario.

[0010] Furthermore, the method for generating a virtual factory is as follows: Based on the standard of one supply position corresponding to one preferred role, the material suppliers, equipment manufacturers and product distributors in the preferred roles are respectively imported into the supply positions in the first-end layer, the middle layer and the last-end layer; The supply numbers of material suppliers, equipment manufacturers and product distributors are retrieved by blockchain. The supply numbers in the first layer, middle layer and last layer are sorted in ascending order according to the supply number from smallest to largest, generating three number groups. Establish a basic path with five path points, import three number groups into the first, third and fifth path points respectively, and import C1 and C2 into the second and fourth path points respectively, so as to convert the basic path into a shared path; Establish business rules for shared manufacturing and match corresponding sharing permissions to these rules, thereby transforming the virtual supply scenario into a virtual factory.

[0011] Furthermore, supply balance indicators include the proportion of shared constraints, the proportion of compliance efficiency, and the proportion of online visibility; collaboration attributes include high-quality collaboration and low-quality collaboration.

[0012] Furthermore, when collecting the shared constraint ratio, in a simulated environment, the shared manufacturing time periods of the D preferred roles on the shared path are determined. The time periods that overlap between the D shared manufacturing time periods are recorded as collaborative time periods. The duration of overlap between the D shared manufacturing time periods and collaborative time periods is calculated to obtain D overlap durations. After comparing the D overlap durations with the duration of collaborative time periods, the D shared constraint ratios are calculated.

[0013] Furthermore, when collecting compliance efficiency percentages, in a simulated environment, using the same duration as a standard, E sampling periods are marked at intervals within D shared manufacturing periods. The shared manufacturing efficiency of each of the E sampling periods is queried. The durations of sampling periods where the shared manufacturing efficiency is lower than the rated efficiency are accumulated to obtain the inefficient duration. The difference between the duration of the shared manufacturing period and the inefficient duration is then compared with the duration of the corresponding shared manufacturing period to calculate the D compliance efficiency percentages.

[0014] Furthermore, the method for identifying collaborative attributes is as follows: When the proportion of shared constraints is less than the proportion of standard constraints, the proportion of shared constraints will be recorded as an abnormal indicator. When the compliance efficiency ratio is less than the standard efficiency ratio, the compliance efficiency ratio will be recorded as an abnormal indicator. When the online viewing ratio is less than the standard viewing ratio, the online viewing ratio will be recorded as an abnormal indicator. When the number of abnormal indicators in the preferred role of the virtual factory is 0, the collaboration attribute of the virtual factory is recorded as high-quality collaboration. When the number of abnormal indicators in the preferred role of the virtual factory is greater than 0, the collaboration attribute of the virtual factory is recorded as low-quality collaboration.

[0015] The technical advantages of this invention's supply chain collaborative management system based on composite material shared intelligent manufacturing are as follows: (1): By analyzing the characteristics and experience data of shared manufacturing, this invention can intelligently index and select qualified primary and secondary roles from a large number of suppliers. By co-simulating the shared path and business rules with the virtual factory, the actual physical level of shared manufacturing can be transformed into a comprehensive virtual simulation. This allows for the early detection and avoidance of adverse reactions and supply defects in different types of suppliers in terms of capacity connection, efficiency matching, and visual collaboration. It realizes the hierarchical leap of supply chain collaboration from static matching to dynamic optimization and simulation verification, and reduces the probability of supply chain collaboration errors when manufacturing composite materials.

[0016] (2): By collecting and analyzing the shared constraint ratio, compliance efficiency ratio and online visibility ratio of the shared path, this invention can automatically identify the weak links in the shared path of the virtual factory and carry out targeted processing on the problem nodes corresponding to the weak links, thereby realizing the dynamic update and upgrade effect of the shared path. This enables the supply chain collaborative management system to have the ability and mechanism for diagnosis, repair and evolution, ensuring that the shared manufacturing process always maintains the optimal supply chain collaborative state, thereby ensuring the efficiency and stability of the supply chain collaborative management system. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the architecture of a supply chain collaborative management system based on shared intelligent manufacturing of composite materials, provided in Embodiment 1 of the present invention. Figure 2 A schematic diagram of the modules of the collaborative management platform provided in Embodiment 1 of the present invention; Figure 3 This is a flowchart illustrating a supply chain collaborative management method based on composite material sharing and intelligent manufacturing, as provided in Embodiment 2 of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1: Please refer to Figures 1-2As shown in this embodiment, a supply chain collaborative management system based on composite material sharing and intelligent manufacturing is applied to a collaborative management platform and includes: The feature extraction module receives manufacturing requests uploaded by the user and extracts shared manufacturing features from the manufacturing requests. Shared manufacturing features include raw material supply credit, equipment manufacturing efficiency, and product service level. The user terminal refers to the port that can receive user demand information about composite material products and transmit and interact with the collaborative management platform in two directions, making the user terminal a part of the supply chain collaborative management system. In this embodiment, the user end is a mini-program, official account, APP, etc. on a mobile terminal device.

[0020] Manufacturing requests are specific data that enable the shared manufacturing of composite materials for end users to play a role and function in the supply chain; Since the manufacturing request is the original representation of the true meaning of shared manufacturing of composite materials in the user terminal, the manufacturing request contains a lot of data types and a wide semantic dimension, making it impossible to represent the true meaning concisely. Therefore, it is necessary to simplify the manufacturing request and extract the shared manufacturing features from the manufacturing request. In this embodiment, the shared manufacturing feature is used to concisely and accurately represent the true meaning of the manufacturing request, which can lay the foundation for subsequent supply chain collaborative management.

[0021] Specifically, shared manufacturing characteristics include raw material supply credit, equipment manufacturing efficiency, and product service level; Raw material supply credit refers to the supply credit status of material suppliers when composite materials are manufactured together, which can be used as the basis for initial identification of material suppliers; Equipment manufacturing efficiency refers to the product manufacturing quality of the corresponding equipment manufacturer when composite materials are shared in manufacturing, and can be used as a basis for initial identification of product manufacturers; Product service level refers to the service quality of the product distributor when composite materials are manufactured together, and can be used as a basis for initial identification of product distributors.

[0022] Specifically, the method for extracting shared manufacturing features is as follows: The key semantics in the manufacturing request are parsed using natural language processing technology and then broken down into textual and numerical parts. Key semantics refers to a concise representation of the true meaning in the manufacturing request, and consists of textual and numerical parts. The textual part is used to distinguish the meaning and type of key semantics, while the numerical part is used to indicate the degree of key semantics. The key semantics of the text part being raw materials, equipment and products are denoted as credit semantics, efficiency semantics and grade semantics. The numerical parts in credit semantics, efficiency semantics and grade semantics are formed into a first set of numbers, a second set of numbers and a third set of numbers. The quantity of the numerical parts in the first set of numbers, the second set of numbers and the third set of numbers are queried respectively. When the number of the number part is 1, the number parts in the first number set, the second number set, and the third number set are respectively recorded as raw material supply credit, equipment manufacturing efficiency, and product service level; When the number of numeric parts is greater than 1, query the entry time of each numeric part, and record the numeric part of the last entry time as raw material supply credit, equipment manufacturing efficiency and product service level respectively.

[0023] It should be noted that the final content of raw material supply credit, equipment manufacturing efficiency, and product service level are all specific numbers, which can provide an accurate basis for the subsequent screening and identification of material suppliers, equipment manufacturers, and product distributors.

[0024] The role analysis module uses shared manufacturing characteristics as the indexing benchmark to index supply roles from suppliers and performs adaptation analysis on supply roles, dividing supply roles into preferred roles and secondary roles; Once the characteristics of shared manufacturing are obtained, raw material supply credit, equipment manufacturing efficiency, and product service level can be used as index benchmarks to select supply roles that match the characteristics of shared manufacturing from among suppliers, so that the supply roles can act as participants in the supply chain of shared manufacturing of composite materials. In this embodiment, the supply roles include material suppliers, equipment manufacturers, and product distributors; material suppliers refer to the roles in the supply chain that provide raw material supply for the shared manufacturing of composite materials, equipment manufacturers refer to the roles in the supply chain that provide specific processing equipment for the shared manufacturing of composite materials, and product distributors refer to the roles in the supply chain that provide product sales services for the shared manufacturing of composite materials.

[0025] Specifically, the indexing method for supply roles is as follows: The system retrieves the attribute information and update information of all suppliers in the supply chain, and extracts the attribute values ​​and update times from the attribute information and update times respectively. The attribute information and update times are used to represent the actual situation of the supplier's attribute dimensions and data dimensions. The attribute values ​​are the attribute results of the attribute information, and the update times are the time results of the update information. When the attribute value is S-11, it means that the supplier can meet the shared manufacturing needs of the supply chain in terms of supply attribute dimension, and the attribute information is recorded as a valid attribute. The period between the update time and the current time is recorded as the interruption period, and the duration of the interruption period is compared with the preset supply interruption threshold. The preset supply interruption threshold is a pre-set maximum data update duration that limits suppliers from participating in this shared manufacturing process, in order to avoid untimely data updates and inaccurate status monitoring when suppliers who have not updated for a long time participate in shared manufacturing. The preset supply interruption threshold is obtained by averaging the maximum data update durations of a large number of historical participants in shared manufacturing. When the duration of the interruption period is less than or equal to the supply interruption threshold, it indicates that the supplier can meet the shared manufacturing needs of the supply chain in terms of update time, and the update information is recorded as a valid update. Suppliers in the supply chain that have both valid attributes and valid updates are aggregated into a supply set. The role semantics of the suppliers in the supply set are parsed out, and suppliers whose role semantics are materials, manufacturing, and products are respectively recorded as material candidates, equipment candidates, and product candidates. Compare the credit rating of the material suppliers with the credit rating of the raw material suppliers, and record the material suppliers whose credit rating is greater than or equal to the credit rating of the raw material suppliers as material suppliers; Compare the noted efficiency of the equipment supplier with the equipment manufacturing efficiency, and record the equipment supplier whose noted efficiency is greater than or equal to the equipment manufacturing efficiency as the equipment manufacturer; Compare the remark level of the product candidate with the product service level, and record the product candidate with a remark level greater than or equal to the product service level as a product distributor.

[0026] In this embodiment, the number of material suppliers, equipment manufacturers, and product distributors indexed is not just one, but at least two. This provides at least two shared manufacturing solutions for the shared manufacturing of composite materials, thereby achieving collaborative management of various supply roles in the supply chain. Furthermore, the credit rating, efficiency rating, and level rating are all obtained through database queries.

[0027] Since there are more than one material supplier, equipment manufacturer, and product distributor listed, and each stage of the composite material shared manufacturing process requires at least one supplier, it is necessary to distinguish between material suppliers, equipment manufacturers, and product distributors and classify them into preferred and secondary roles. In this embodiment, the preferred role refers to the supply role that takes priority in participating in the shared manufacturing of composite materials, so that the preferred role is in the first tier in terms of overall performance and efficiency. The secondary role refers to the supply role that does not take priority in participating in the shared manufacturing of composite materials, so that the secondary role is in the second tier in terms of overall performance and efficiency.

[0028] The method for dividing primary and secondary characters is as follows: The number of times material suppliers, equipment manufacturers, and product distributors performed safety self-checks and data updates during the interruption period were queried one by one. The number of data updates was compared with the number of safety self-checks to calculate the backup ratio. The formula for calculating the backup percentage is: ; In the formula, For backup percentage values, For the number of times the data is updated, The number of times a safety self-check is performed; During the interruption period, work logs from material suppliers, equipment manufacturers, and product distributors participating in shared manufacturing were screened out, the quality level of the work logs was identified, and work logs with an excellent quality level were recorded as valid logs. The percentage of excellent logs is calculated by comparing the number of valid logs with the number of working logs. The formula for calculating the percentage of excellent results is: ; in, For an excellent percentage value, The number of valid logs, The number of work logs; The backup percentage and the excellent percentage are assigned different proportional coefficients and then added together to calculate the sharing performance index. The formula for calculating the shared performance index is: ; In the formula, To share performance index, , These are the ratio coefficients for the backup percentage and the excellent percentage, respectively. , All are greater than 0 and less than 1; Based on the shared performance index from largest to smallest, material suppliers, equipment manufacturers, and product distributors are arranged in descending order to generate the first queue, the second queue, and the third queue. The material suppliers, equipment manufacturers, and product distributors ranked first in the first, second, and third queues are designated as preferred roles, and the remaining material suppliers, equipment manufacturers, and product distributors are designated as secondary roles.

[0029] It should be noted that, in order to ensure the orderly and comprehensive nature of composite material shared manufacturing, the number of material suppliers, equipment manufacturers, and product distributors in the preferred roles is not unique. It needs to be determined based on the role and specific type of each supplier in composite material shared manufacturing. For example, when composite materials require two raw materials, but each specific type of material supplier can only provide one raw material, then there are two material suppliers in the preferred roles.

[0030] The virtual factory module, based on the supply balance principle, establishes a virtual supply scenario with supply positions and imports the preferred role into the supply position to generate a virtual factory with a shared path; Once the preferred role is obtained, a virtual environment can be constructed that can have a linkage effect with the preferred role in shared manufacturing, so that the virtual environment can be integrated with the preferred role at the virtual level, and this virtual environment is recorded as a virtual supply scenario. In this embodiment, the virtual supply scenario is a scenario that can be integrated with the preferred role to provide supply chain simulation for the shared manufacturing of composite materials at the virtual level.

[0031] To ensure that the established virtual supply scenarios and preferred roles are balanced in terms of quantity and supply chain distribution, it is necessary to proceed under the constraints of supply balance principles. Specifically, the supply balance criterion is that adjacent scene layers are connected through a hierarchical chain.

[0032] The method for establishing a virtual supply scenario is as follows: A simulation scene is created using modeling and simulation tools. Three horizontally distributed scene layers with a closed ring structure are set up in the simulation scene. The three scene layers are named the first layer, the middle layer, and the last layer from left to right. The horizontal distribution ensures that the scene layers maintain a neat formation, and the closed ring structure ensures that adjacent scene layers remain independent. B independent supply positions are simulated in the first, middle and last layers respectively, and contour lines are established between two adjacent supply positions. The contour lines can separate two adjacent supply positions and avoid cross interference. A start port is established at the first layer, a start port and a stop port are established at the middle layer, and a stop port is established at the last layer. The start port and the stop port are the two ends of the hierarchical chain, and hierarchical chains are established between the first layer and the middle layer, and between the middle layer and the last layer. The hierarchical chain is used to provide a data channel for data transmission and interaction in different scene layers, thereby avoiding the phenomenon of data silos in different scene layers. The hierarchical chain between the first layer and the middle layer is numbered C1, and the hierarchical chain between the middle layer and the last layer is numbered C2, thus transforming the simulation scenario into a virtual supply scenario.

[0033] Once the virtual supply scenario is obtained, the preferred role can be integrated with the virtual supply scenario. At the same time, with the coordinated combination of supply position and hierarchical chain, the virtual supply scenario can be transformed into a virtual factory, so that the virtual factory can serve as a simulation factory to realize the shared manufacturing of composite materials at the virtual level. The method for generating a virtual factory is as follows: Based on the standard of one supply position corresponding to one preferred role, the material suppliers, equipment manufacturers and product distributors in the preferred roles are respectively imported into the supply positions in the first-end layer, the middle layer and the last-end layer; The supply numbers of material suppliers, equipment manufacturers and product distributors are retrieved by blockchain. The supply numbers in the first layer, middle layer and last layer are sorted in ascending order according to the supply number from smallest to largest, generating three number groups. Establish a basic path with five path points, import three number groups into the first, third and fifth path points respectively, and import C1 and C2 into the second and fourth path points respectively, so as to convert the basic path into a shared path; Establish business rules for shared manufacturing and match corresponding sharing permissions to these rules, thereby transforming the virtual supply scenario into a virtual factory. Business rules define the business logic of shared manufacturing within the virtual factory, while sharing permissions define the operational permissions for the virtual factory simulation, ensuring that the virtual factory remains relatively consistent with the actual situation of suppliers in the supply chain.

[0034] In this embodiment, the generated virtual factory is not a physical structure in the traditional physical sense, but rather integrates various supply roles in the real-world supply chain at the virtual level to achieve intelligent supply chain collaborative management of shared manufacturing of composite materials, thereby avoiding the limitations and inconveniences of traditional physical supply chain collaborative management.

[0035] The shared upgrade module dynamically collects the supply balance indicators of the preferred role in the shared path under a simulated environment, identifies the collaborative attributes of the virtual factory, and replaces the preferred role with anomalies, prompting the shared path to be updated and upgraded. The supply balance index refers to the overall quality level of shared manufacturing corresponding to the shared path in a virtual factory. It can represent the specific situation of the virtual factory in various dimensions of supply chain collaborative management operations, and identify the collaborative attributes of the virtual factory based on the supply balance index. In this embodiment, the collaboration attribute is used to represent the degree and quality of collaboration between the preferred roles in the shared path in the shared manufacturing process; Collaboration attributes include high-quality collaboration and low-quality collaboration; high-quality collaboration refers to the high degree and quality of collaboration among the preferred roles in the shared path in shared manufacturing; low-quality collaboration refers to the low degree and quality of collaboration among the preferred roles in the shared path in shared manufacturing.

[0036] Supply balance indicators include the proportion of shared constraints, the proportion of compliance efficiency, and the proportion of online visibility; In this embodiment, when collecting supply balance indicators, it is not necessary to actually manufacture and process each preferred role on the shared path in real life. Instead, the manufacturing process of each preferred role on the shared path of the virtual factory is simulated in a simulation environment. When simulating the shared path, it is necessary to first build a simulation environment for simulation using simulation software (such as factory.io software), and import the actual parameters of each preferred role on the shared path (actual parameters include but are not limited to material delivery distance, maximum production volume, equipment failure rate, product qualification rate, etc.) into the simulation environment to realize the simulated operation of the shared path and the dynamic collection of supply balance indicators.

[0037] The shared constraint ratio refers to the duration during which each preferred role on the shared path can be simultaneously in the state of shared manufacturing of composite materials, which can be used to represent the duration of the preferred role's participation in supply chain collaboration on the shared path; When collecting the proportion of shared constraints, in the simulation environment, first determine the shared manufacturing time periods of the D preferred roles on the shared path, and record the time periods that overlap between the D shared manufacturing time periods as collaborative time periods. Calculate the duration of overlap between the D shared manufacturing time periods and collaborative time periods to obtain the D overlap durations. Then, compare the D overlap durations with the duration of the collaborative time periods to calculate the proportion of the D shared constraints. The formula for calculating the proportion of shared constraints is: ; In the formula, To share the proportion of constraints, For the duration of overlap, This refers to the duration of the coordinated period.

[0038] The compliance efficiency ratio refers to the duration during which the production efficiency of each preferred role in the shared path is in a compliant state in shared manufacturing, which can be used to represent the production efficiency performance of the preferred role in the shared path; When collecting compliance efficiency percentages, in a simulated environment, using the same duration as the standard, E sampling periods are marked at intervals within D shared manufacturing periods. The shared manufacturing efficiency of each of the E sampling periods is queried, and sampling periods with shared manufacturing efficiency lower than the rated efficiency are recorded as inefficient periods. The durations of all inefficient periods are accumulated to obtain the inefficient duration. The difference between the duration of the shared manufacturing period and the inefficient duration is calculated, and the difference is compared with the duration of the corresponding shared manufacturing period to calculate the compliance efficiency percentages of the D periods. The formula for calculating the compliance efficiency ratio is: ; In the formula, For compliance efficiency ratio, To share the duration of manufacturing periods, This is an inefficient duration.

[0039] Online visibility percentage refers to the duration during which each preferred role on the shared path remains online and visible throughout the shared manufacturing process, thus representing the online controllability of the preferred role; When collecting the online visibility percentage, in a simulated environment, the duration of D preferred roles in the online visibility state is counted and recorded as D visibility durations. The D visibility durations are then compared with the duration of the corresponding shared manufacturing period to calculate the D online visibility percentages.

[0040] After collecting the percentage of shared constraints, compliance efficiency, and online visibility, the collaborative attributes can be identified and analyzed. Specifically, the method for identifying collaborative attributes is as follows: Compare the proportions of shared constraints, compliance efficiency, and online visibility for each of the D preferred roles; When the shared constraint ratio is less than the standard constraint ratio, the duration of the shared constraint for the preferred role is shorter, and the shared constraint ratio is recorded as an abnormal indicator. The standard constraint ratio refers to the maximum value of the shared constraint ratio when it is recorded as an abnormal indicator; it is obtained through historical data analysis. When the compliance efficiency ratio is less than the standard efficiency ratio, the production efficiency of the preferred role is low, and the compliance efficiency ratio is recorded as an abnormal indicator. The standard efficiency ratio refers to the maximum value of the compliance efficiency ratio when it is recorded as an abnormal indicator; it is obtained through historical data analysis. When the online viewable percentage is less than the standard viewable percentage, the controllable time of the preferred role is shorter, and the online viewable percentage is recorded as an abnormal indicator. The standard viewable percentage refers to the maximum value of the online viewable percentage when it is recorded as an abnormal indicator; it is obtained through historical data analysis. When the number of abnormal indicators in the preferred role of the virtual factory is 0, it means that the preferred role does not need to be replaced, and the collaboration attribute of the virtual factory is recorded as high-quality collaboration. When the number of abnormal indicators in the preferred role of the virtual factory is greater than 0, it means that the preferred role needs to be replaced, and the collaboration attribute of the virtual factory is recorded as low-quality collaboration.

[0041] In this embodiment, when the collaboration attribute of the virtual factory is high-quality collaboration, each preferred role on the shared path in the virtual factory can efficiently and with high quality complete the shared manufacturing effect of composite materials, and realize the collaborative management effect of the supply chain. Conversely, when the collaboration attribute of the virtual factory is low-quality collaboration, it is necessary to replace the preferred roles on the shared path, so as to update and upgrade the shared path. In this embodiment, when updating and upgrading the shared path, the specific type of the preferred role with abnormal indicators on the shared path is first determined. When the preferred role is a material supplier, material suppliers with abnormal indicators will be removed from the shared path, and material suppliers of the same type that are second in the first queue will be imported into the shared path to achieve the update and upgrade of the shared path. When the preferred role is the equipment manufacturer, the equipment manufacturers with abnormal indicators are removed from the shared path, and the second-ranked equipment manufacturers of the same type in the second queue are imported into the shared path to achieve the update and upgrade of the shared path; When the preferred role is a product distributor, product distributors with abnormal indicators will be removed from the shared path, and product distributors of the same type that are second in the third queue will be imported into the shared path to update and upgrade the shared path.

[0042] It should be noted that the updated and upgraded shared path serves as a direct solution for supply chain collaborative management in the shared manufacturing of composite materials. Based on the shared path, the shared manufacturing of composite materials is carried out. At the same time, the updated and upgraded shared path also needs to be continuously simulated and updated to achieve dynamic management of supply chain collaboration and avoid the lag problem of unchanging collaborative management methods.

[0043] Example 2: Please refer to Figure 3 As shown, for parts not described in detail in this embodiment, please refer to the description in Embodiment 1. A supply chain collaboration method based on composite material sharing and intelligent manufacturing is applied to a collaboration management platform and implemented based on a supply chain collaboration management system based on composite material sharing and intelligent manufacturing, including: S01: Extract raw material supply credit, equipment manufacturing efficiency, and product service level from the user's manufacturing request; S02: Using shared manufacturing characteristics as the indexing benchmark, the supply roles are indexed from the suppliers, and the supply roles are adapted and analyzed to divide the supply roles into preferred roles and secondary roles; S03: Based on the supply balance principle, establish a virtual supply scenario with supply positions, and import the preferred roles into the supply positions one by one to generate a virtual factory with a shared path; S04: In a simulated environment, dynamically collect the supply balance index of the preferred role in the shared path, identify the collaborative attributes of the virtual factory, and replace the preferred role with the secondary role according to the collaborative attributes to update and upgrade the shared path.

[0044] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A supply chain collaborative management system based on intelligent manufacturing of composite materials, applied to a collaborative management platform, characterized in that: include: The feature extraction module is used to extract shared manufacturing features from the user's manufacturing request. Shared manufacturing features include raw material supply credit, equipment manufacturing efficiency, and product service level. The role analysis module is used to index supply roles from suppliers based on shared manufacturing characteristics. Supply roles include material suppliers, equipment manufacturers, and product distributors. It also performs adaptation analysis on supply roles and divides them into preferred roles and secondary roles. The virtual factory module is used to establish a virtual supply scenario with supply positions based on the supply balance principle, and to import the preferred roles into the supply positions one by one to generate a virtual factory with a shared path. The shared upgrade module is used to dynamically collect the supply balance index of the preferred role in the shared path in a simulated environment, identify the collaborative attributes of the virtual factory, and replace the preferred role with the secondary role according to the collaborative attributes to update and upgrade the shared path.

2. The supply chain collaborative management system based on composite material shared intelligent manufacturing according to claim 1, characterized in that, The method for extracting shared manufacturing features is as follows: The key semantics in the manufacturing request were parsed using natural language processing technology, and then the key semantics were broken down into textual and numerical parts. The numerical parts of the key semantics of raw materials, equipment and products in the text part are divided into a first set of numbers, a second set of numbers and a third set of numbers, and the quantity of the numerical parts in the first set of numbers, the second set of numbers and the third set of numbers are queried respectively; When the number of the number part is 1, the number parts in the first number set, the second number set, and the third number set are recorded as raw material supply credit, equipment manufacturing efficiency, and product service level; When the number of numeric parts is greater than 1, retrieve the entry time of the numeric parts, and record the numeric parts of the last entry time as raw material supply credit, equipment manufacturing efficiency, and product service level.

3. A supply chain collaborative management system based on composite material shared intelligent manufacturing according to claim 2, characterized in that, The indexing method for supply roles is as follows: The system retrieves the attribute information and update information of each supplier in the supply chain, and extracts the attribute values ​​and update times from the attribute information and update information respectively. When the attribute value is S-11, the attribute information is recorded as a valid attribute; The period between the update time and the current time is recorded as the interruption period. When the duration of the interruption period is less than or equal to the supply interruption threshold, the update information is recorded as a valid update. Suppliers in the supply chain that simultaneously possess valid attributes and valid updates, and whose role semantics are materials, manufacturing, and products, are respectively denoted as material candidates, equipment candidates, and product candidates; Material suppliers with credit ratings greater than or equal to raw material supply credit ratings are designated as material suppliers; equipment suppliers with efficiency ratings greater than or equal to equipment manufacturing efficiency are designated as equipment manufacturers; and product suppliers with service ratings greater than or equal to product distributors are designated as product dealers.

4. A supply chain collaborative management system based on composite material shared intelligent manufacturing according to claim 3, characterized in that, The method for dividing primary and secondary characters is as follows: The number of times material suppliers, equipment manufacturers, and product distributors performed safety self-checks and data updates during the interruption period were queried one by one. The number of data updates was compared with the number of safety self-checks to calculate the backup ratio. During the interruption period, work logs from material suppliers, equipment manufacturers, and product distributors participating in shared manufacturing were screened out, the quality level of the work logs was identified, and work logs with an excellent quality level were recorded as valid logs. After comparing the number of valid logs with the number of working logs, the excellent percentage value is calculated. The backup percentage value and the excellent percentage value are weighted and summed to calculate the shared performance index. Based on the shared performance index from largest to smallest, material suppliers, equipment manufacturers, and product distributors are arranged in descending order to generate the first queue, the second queue, and the third queue. The material suppliers, equipment manufacturers, and product distributors ranked first in the first, second, and third queues are designated as preferred roles, and the remaining material suppliers, equipment manufacturers, and product distributors are designated as secondary roles.

5. A supply chain collaborative management system based on composite material shared intelligent manufacturing according to claim 4, characterized in that, The supply balance criterion is: adjacent scene layers are connected through a hierarchical chain; The method for establishing a virtual supply scenario is as follows: A simulation scene is established using modeling and simulation tools. Three horizontally distributed scene layers with a closed ring structure are set in the simulation scene, and the three scene layers are respectively called the first layer, the middle layer and the last layer. B independent supply positions are simulated in the first, middle and last layers respectively, and contour lines are established between two adjacent supply positions. Establish a start port on the first layer, establish a start port and a stop port on the middle layer, and establish a stop port on the last layer. With the start port and the stop port as the two ends of the hierarchical chain, establish hierarchical chains between the first layer and the middle layer, and between the middle layer and the last layer. The hierarchical chain between the first layer and the middle layer is numbered C1, and the hierarchical chain between the middle layer and the last layer is numbered C2, thus transforming the simulation scenario into a virtual supply scenario.

6. A supply chain collaborative management system based on composite material shared intelligent manufacturing according to claim 5, characterized in that, The method for generating a virtual factory is as follows: Based on the standard of one supply position corresponding to one preferred role, the material suppliers, equipment manufacturers and product distributors in the preferred roles are respectively imported into the supply positions in the first-end layer, the middle layer and the last-end layer; The supply numbers of material suppliers, equipment manufacturers and product distributors are retrieved by blockchain. The supply numbers in the first layer, middle layer and last layer are sorted in ascending order according to the supply number from smallest to largest, generating three number groups. Establish a basic path with five path points, import three number groups into the first, third and fifth path points respectively, and import C1 and C2 into the second and fourth path points respectively, so as to convert the basic path into a shared path; Establish business rules for shared manufacturing and match corresponding sharing permissions to these rules, thereby transforming the virtual supply scenario into a virtual factory.

7. A supply chain collaborative management system based on composite material shared intelligent manufacturing according to claim 6, characterized in that, Supply balance indicators include the proportion of shared constraints, the proportion of compliance efficiency, and the proportion of online visibility; collaboration attributes include high-quality collaboration and low-quality collaboration.

8. A supply chain collaborative management system based on composite material shared intelligent manufacturing according to claim 7, characterized in that, When collecting the shared constraint ratio, in a simulated environment, the shared manufacturing time periods of D preferred roles on the shared path are determined. The time periods that overlap between the D shared manufacturing time periods are recorded as collaborative time periods. The duration of overlap between the D shared manufacturing time periods and collaborative time periods is calculated to obtain D overlap durations. The D overlap durations are then compared with the duration of collaborative time periods to calculate the D shared constraint ratios.

9. A supply chain collaborative management system based on composite material shared intelligent manufacturing according to claim 8, characterized in that, When collecting compliance efficiency percentages, in a simulated environment, using the same duration as a standard, E sampling periods are marked at intervals within D shared manufacturing periods. The shared manufacturing efficiency of each of the E sampling periods is queried. The durations of sampling periods where the shared manufacturing efficiency is lower than the rated efficiency are accumulated to obtain the inefficient duration. The difference between the duration of the shared manufacturing period and the inefficient duration is then calculated and compared with the duration of the corresponding shared manufacturing period to calculate the D compliance efficiency percentages.

10. A supply chain collaborative management system based on composite material shared intelligent manufacturing according to claim 9, characterized in that, The method for identifying collaborative attributes is as follows: When the proportion of shared constraints is less than the proportion of standard constraints, the proportion of shared constraints will be recorded as an abnormal indicator. When the compliance efficiency ratio is less than the standard efficiency ratio, the compliance efficiency ratio will be recorded as an abnormal indicator. When the online viewing ratio is less than the standard viewing ratio, the online viewing ratio will be recorded as an abnormal indicator. When the number of abnormal indicators in the preferred role of the virtual factory is 0, the collaboration attribute of the virtual factory is recorded as high-quality collaboration. When the number of abnormal indicators in the preferred role of the virtual factory is greater than 0, the collaboration attribute of the virtual factory is recorded as low-quality collaboration.

Images