Data fusion deployment system based on material management platform

Abstract

The invention discloses a data fusion deployment system based on a material management platform, and the system comprises a material management module which is used for obtaining the multi-source data of a potential supply point from the material management platform, and the multi-source data of the potential supply point comprises material inventory data, purchasing data and material supply data; the data fusion module is used for carrying out data fusion on the obtained multi-source data of the potential supply points based on a multi-modal database and carrying out quality inspection on the fused data; the data allocation module is used for performing adaptation degree evaluation on the fused multi-source data of the potential supply points, and constructing a material allocation target function taking the maximum scheduling adaptation coefficient as a target to obtain the maximum scheduling adaptation coefficient; and the user interaction module is used for sending the multi-source data of the potential supply point corresponding to the maximum scheduling adaptation coefficient. According to the data fusion deployment system based on the material management platform, the effect of improving the accuracy of the data fusion deployment system is achieved, and the problem that the accuracy of the data fusion deployment system is low due to the quality problem of a data source in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of data fusion and deployment, and in particular to a data fusion and deployment system based on a material management platform. Background Art

[0002] As the level of informationization of material management continues to improve, the material management platform is also changing with each passing day. The key to the material management platform's data processing and analysis capabilities lies in the platform's data fusion and deployment capabilities. Through real-time inventory information and logistics tracking, it can ensure that materials are delivered on time and meet users' needs for fast and reliable services. In addition, the data fusion and deployment system can ensure the timely supply of materials and high-quality services, which helps to improve customer satisfaction.

[0003] With the rapid changes and increasing complexity of material management platforms, enterprises need to adjust production and supply strategies more quickly. Data fusion and deployment systems can help enterprises share information with users and help users at potential supply points quickly respond to each other's material deployment needs. However, the data sources of data fusion and deployment systems in existing technologies may have inconsistent quality, inconsistent formats, or lack of standardization, which may lead to errors and deviations in the data integration and analysis process of the data fusion and deployment system, affecting the accuracy and reliability of the data fusion and deployment system. Summary of the invention

[0004] The embodiment of the present application solves the problem of low accuracy of the data fusion and deployment system in the prior art by providing a data fusion and deployment system based on a material management platform, thereby improving the accuracy of the data fusion and deployment system.

[0005] An embodiment of the present application provides a data fusion and allocation system based on a material management platform, including a material management module, a data fusion module, a data allocation module, and a user interaction module; the material management module is used to obtain multi-source data of potential supply points from the material management platform, and the multi-source data of the potential supply points includes material inventory data, procurement data, and material supply data; the data fusion module is used to perform data fusion on the acquired multi-source data of potential supply points based on a multimodal database, and perform quality inspection on the fused data; the data allocation module is used to evaluate the fitness of the fused multi-source data of potential supply points, construct a material allocation objective function with the maximum scheduling adaptation coefficient as the target, and obtain the maximum scheduling adaptation coefficient; the user interaction module is used to send the multi-source data of the potential supply points corresponding to the maximum scheduling adaptation coefficient to the allocation demander.

[0006] Furthermore, the method for acquiring multi-source data of the potential supply point is as follows: determine the source of the material inventory data, and use data integration tools to extract data from various systems to obtain the current material inventory of the potential supply point from different data sources, and record the restricted use date of each batch of materials before the materials are put into storage; save the electronic version of the purchase invoice generated when purchasing materials in the storage device in slices, record the detailed information of each material allocation, including the allocation time, material number, and purchase quantity, and combine the allocation time with the purchase quantity to form the historical demand; design a layout diagram for the warehouse where the materials are stored, mark the shelf number of each shelf, the shelf number includes the shelf location and shelf number, obtain and record the supplier information, the supplier information includes the company name of the supplier company and the name and category of the materials provided, obtain and record the monthly supply of the supplier company, and convert the shelf number and supplier information into hot encoded variables.

[0007] Furthermore, the multi-source data of the acquired potential supply points are fused based on a multimodal database, specifically: an entity-relationship diagram is established to describe the relationship and attributes between the multi-source data of each potential supply point; the entity includes material inventory data, procurement data, and material supply data; fields are added to the entity, and the fields include material name, material category, current inventory, and restricted use date; non-null constraints are set for all fields; a primary key constraint is set for the material name field; and foreign key constraints are set for the current inventory field and the restricted use date field.

[0008] Furthermore, the quality check of the fused data is specifically: data integrity, including checking whether there are null values ​​and abnormal data in the multi-source data of potential supply points; data consistency, including checking whether the data naming specifications, data units, and data formats are unified; Data timeliness, including checking whether multi-source data from potential supply points is regularly updated.

[0009] Furthermore, the data integrity check method is as follows: for material names with default values, check whether these default values ​​are correctly applied in the data; check for missing values ​​in material inventory data, procurement data, and material supply data, and accumulate and record the missing values; for the material name field of the same potential supply point, verify the uniqueness to avoid duplication or conflict.

[0010] Furthermore, the data consistency is checked in the following way: comparing multi-source data of the same potential supply point in different data sources, and adding an exclamation mark to the multi-source data with inconsistent data.

[0011] Furthermore, the user interaction module is specifically as follows: first, the allocation application of the allocation demand party is obtained, and the multi-source data of the potential supply points that meet the demand points are retrieved; the scheduling adaptation coefficients of the multi-source data of the potential supply points that meet the demand points are compared to obtain a maximum scheduling adaptation coefficient; the complete information of the multi-source data of the potential supply points with the maximum scheduling adaptation coefficient is retrieved, and the multi-source data of the potential supply points of the allocation demand party are integrated, and the multi-source data of the potential supply points of the allocation demand party and the maximum scheduling adaptation coefficient are updated; the updated multi-source data of the potential supply points are returned to the data fusion module.

[0012] Furthermore, a material date time series diagram is established to compare the current date with the historical date in pairs from bottom to top; and the number of multi-source data of potential supply points that exceed the restricted use date range of the material is recorded.

[0013] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Through the data fusion and deployment system based on the material management platform, the accuracy of the data fusion and deployment system is improved, which effectively solves the problem of low accuracy of the data fusion and deployment system in the existing technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 A flow chart of a data fusion and deployment system based on a material management platform provided in an embodiment of the present application; DETAILED DESCRIPTION The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0015] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or still includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "include..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0016] Material management module: used to obtain multi-source data of potential supply points from the material management platform, wherein the multi-source data of potential supply points includes material inventory data, procurement data and material supply data.

[0017] The material inventory data includes the current material inventory of potential supply points and the limited use period of materials, the procurement data includes the procurement date and historical demand, and the material supply data includes the shelf number where the materials are placed and the supplier information; The method for obtaining the material inventory data is as follows: Determine the source of material inventory data, which includes a logistics transportation system, a cooperative supply chain system, and a public security filing system; Use data integration tools to extract data from various systems to obtain the current inventory of potential supply points from different data sources; Before materials are put into storage, the restricted use date of each batch of materials shall be recorded.

[0018] The importance of obtaining material inventory data includes the following points: Optimized management: Through material inventory data, managers can accurately understand the current material inventory of each potential supply point, which can help managers effectively control and optimize inventory. Through inventory data, they can replenish shortage materials in time and avoid excessive inventory backlogs, thereby reducing capital occupation and storage costs; Improve efficiency: Material inventory data can help supply chain managers better predict and plan the purchase and distribution of materials to ensure the efficient operation of the supply chain. Therefore, knowing the inventory status of each material can reduce supply chain disruptions or cost increases caused by out-of-stock or excess inventory. Ensure the quality of materials: Data on the limited use period of materials is crucial to ensuring the quality and safety of materials. Knowing the use period of materials in a timely manner can help avoid using expired materials and reduce the health risks and safety hazards that may be caused by using expired materials.

[0019] The method for obtaining the procurement data is as follows: The electronic version of the purchase invoice generated when purchasing materials is stored in the storage device in pieces; Record detailed information for each material allocation, including allocation time, material number, and purchase quantity, and combine the allocation time with the purchase quantity to form the historical demand.

[0020] The importance of obtaining procurement data includes the following points: Arrange procurement plans: historical demand can be used to predict future demand, determine the best replenishment cycle and order quantity, and understand when and how much material is needed, thereby helping the procurement team adjust the procurement schedule and quantity to ensure timely supply of materials; Traceability of product quality issues: When product quality issues or recalls occur, the purchase date of materials can help companies quickly trace the affected batches or suppliers, which is essential for taking timely measures, reducing risks, and protecting user interests; Tracking expiration: The purchase date of materials can help accurately track the shelf life of materials. By comparing the purchase date and the shelf life of materials, you can promptly identify which materials are about to expire or have expired, so that you can take corresponding treatment measures, such as accelerating consumption, giving priority to processing, etc. Optimize inventory management: Knowing the purchase date of materials helps optimize inventory management. Through the purchase date, the management team can implement a first-in, first-out or first-in, last-out strategy to ensure that the materials in the inventory always maintain freshness and a reasonable turnover rate, reducing losses caused by aging of materials.

[0021] The method for obtaining the material supply data is as follows: Design a layout of the warehouse where materials are stored, and mark the shelf number of each shelf, which includes the shelf position and shelf number; Obtain and record supplier information, including the company name of the supplier company and the name and category of the materials provided; Obtain and record the monthly supply output of the supplier company; Convert shelf number and supplier information into hot-encoded variables.

[0022] The importance of obtaining material supply data includes the following points: Accurately enter inventory data: During the warehousing and outbound process, accurately recording the shelf numbers of materials can reduce the problem of inaccurate inventory data caused by data entry errors; Avoid damage and expiration: For perishable or time-sensitive materials, knowing their storage location can ensure that they are properly handled and managed in inventory to avoid expiration or damage; Precisely locate supplies: Shelf numbers can help warehouse staff quickly and accurately find the storage location of specific supplies. In large warehouses or multiple warehouses, shelf numbers can effectively organize and manage inventory and reduce the time required to find supplies; Fast picking: During the material distribution and delivery process, knowing the shelf number of the material can significantly shorten the picking time. The staff can quickly find and take out the required materials, thereby speeding up the material processing speed.

[0023] Data fusion module: used to fuse the multi-source data of potential supply points based on the multi-modal database, and perform quality checks on the fused data; The multi-source data of the potential supply points are fused based on the multi-modal database, and the multi-source data of the potential supply points are fused at the feature level through the database management tool, specifically: Establish an entity-relationship diagram to describe the relationships and attributes between multi-source data of each potential supply point; The entities include material inventory data, procurement data, and material supply data; Add fields to the entity, including material name, material category, current inventory, and limited use date; Set not null constraints on all fields; Set a primary key constraint on the material name field; Set foreign key constraints on the current inventory field, the product quality inspection report field, and the restricted use date field.

[0024] It should be noted that the non-null constraint ensures that the field is not empty, which can avoid data incompleteness and ensure the data integrity of each record. Setting a primary key constraint on the material name field ensures the uniqueness of each record in the entity and prevents duplicate material name records, which helps data uniqueness and query efficiency. The foreign key constraint ensures that the field value in one entity has a corresponding value in the primary key of another related entity, maintaining the referential integrity between entities. For example, the current inventory may refer to the inventory in the material inventory data.

[0025] As the basis of data organization in relational databases, database table structures effectively support the needs of data management, query, and operation in modern applications through their structured and standardized characteristics. The main uses of database table structures include: Data storage and organization: used to store and organize large amounts of data and ensure data structure and consistency; Data query and retrieval: quickly query and retrieve data through structured tables to improve retrieval efficiency; Establishing data relationships: Establishing relationships between different tables through primary keys and foreign keys to support data association queries and integrity maintenance; Data constraints and integrity: Ensure data integrity and consistency by defining column-level constraints and table-level constraints.

[0026] It should be noted that the column-level constraints include unique constraints and non-null constraints; the table-level constraints include foreign key constraints and check constraints.

[0027] The quality inspection has the following requirements: Data integrity, including checking for null values ​​and abnormal data in multi-source data of potential supply points; Data consistency, including checking whether the data naming conventions, data units, and data formats are unified; Data timeliness, including checking whether multi-source data from potential supply points is regularly updated.

[0028] The data integrity ensures that all necessary fields in the multi-source data of the potential supply point exist and are not missing, including checking whether there are null values ​​and abnormal data in the multi-source data of the potential supply point. Checking the data integrity has the following important significance: Data quality assurance: Data integrity checks can ensure that data is of high quality and that all necessary fields are present and not missing. Missing data may lead to analysis errors or wrong decisions, affecting the company's operations and services. Accurate basis for decision making: Only complete data can provide accurate information and insights. When managing materials, ensuring that all necessary information is complete can help management make decisions based on real situations; Avoid incorrect operations: If there are empty values ​​or abnormal data in the data, it may cause system errors or unpredictable behaviors. In material management, if the quantity of a certain material is empty or abnormal, it may affect inventory management, procurement plans or customer service.

[0029] The data integrity is checked in the following ways: for material names with default values, check whether these default values ​​are correctly applied in the data; check for missing values ​​in material inventory data, procurement data, and material supply data, and accumulate and record the missing values; for the material name field of the same potential supply point, verify the uniqueness to avoid duplication or conflict The integrity of the data is verified and calculated using the following formula:

[0030] Where: P is the data completeness, m is the total number of multi-source data of potential supply points involved in the inspection, g is the number of missing data identified by the quality inspection, h is the number of multi-source data of potential supply points that are abnormally repeated, and c is the number of data that needs to be refilled.

[0031] The data consistency ensures that the multi-source data of the same potential supply point is consistent between different data sources and different time points, including checking whether the data naming specifications, data units, and data formats are unified. Checking data consistency has the following important significance: Support data integration and analysis: In the environment of big data fusion and data integration, data consistency is the basis for ensuring that data can be correctly integrated and analyzed. Consistent data formats and units can simplify the data integration process and make data integration more accurate and reliable; Help with data standardization: Data consistency checks help ensure that data complies with predefined standards and specifications. These standards can include data naming specifications, unit standards, and data format requirements, thereby ensuring that data is interoperable and understandable in different environments and systems; Reduce maintenance costs: Consistent data management and maintenance can reduce system maintenance costs, reduce the time and resources required to handle and resolve problems caused by data inconsistency, and thus improve system stability and reliability.

[0032] The data consistency is checked as follows: Compare the multi-source data of the same potential supply point from different data sources, and add an exclamation mark to the multi-source data with inconsistent data.

[0033] Data timeliness ensures that the multi-source data of potential supply points are the latest information in the historical time series, including checking whether the multi-source data of potential supply points are regularly updated data. Checking data timeliness has the following important significance: Improve the usefulness and value of data: As time goes by, the usefulness and value of old data will gradually decrease. By keeping data current, you can ensure that the data always has the highest usefulness and value, whether it is used for internal business analysis or external information release; Timely decision-making and planning: For decision-making and planning processes that require real-time data support, data timeliness is critical. Ensuring data timeliness means that decision makers and planners can analyze and make decisions based on the latest data, thereby more accurately responding to current and future needs and challenges; By updating data regularly, the efficiency of data management can be improved. Automated data timeliness checking and updating processes can reduce manual intervention and management costs while ensuring data quality and timeliness.

[0034] The timeliness of the data is checked as follows: Establish a material date time series diagram, compare the current date with the historical date in pairs from bottom to top; and record the number of multi-source data of potential supply points that exceed the restricted use date range of the material.

[0035] The database table structure refers to a structured form used to organize and store data in a relational database. The database table structure is mainly composed of tables, columns, rows, and keys, which are used to define and describe the organization and relationship of data.

[0036] The timeliness of the data is checked and calculated, and the calculation formula is as follows:

[0037] Where: N is the data timeliness, f is the number of multi-source data of potential supply points with valid data format, s is the number of multi-source data of potential supply points with correct data type, is the number of multi-source data of potential supply points within the restricted use date of the materials, and m is the total number of multi-source data of potential supply points involved in the inspection.

[0038] Data allocation module: used to evaluate the adaptability of the fused multi-source data of potential supply points, construct a material allocation objective function with the maximum scheduling adaptation coefficient as the goal, and obtain the maximum scheduling adaptation coefficient; When a data allocation application appears on the material management platform, the system evaluates the adaptability of the multi-source data of the potential supply points after integration. The material allocation objective function with the maximum scheduling adaptation coefficient as the target is constructed, and the calculation formula is as follows:

[0039] Where: W is the objective function of material allocation, q is the current inventory of the material, d is the current month, p is the month with limited use period, r is the historical demand, t is the number of days converted from the purchase date, β is the hot code of the supplier information, ℷ is the hot code of the shelf number, P is the data completeness, and N is the data timeliness.

[0040] It should be noted that when the scheduling adaptation coefficient value is larger, it indicates that the match between the potential supply point and the allocation demand party is very good, and the allocation of resources is very close to the actual demand of the demand point, that is, the current potential supply point is most suitable as the allocation object, and the material allocation will be very efficient, reducing resource waste and over-allocation. When the scheduling adaptation coefficient value is smaller, it indicates that the match between the potential supply point and the demand point is poor, and the allocation of resources does not match the actual demand of the allocation demand party. Due to demand mismatch, selecting the current potential supply point may increase additional transportation costs and storage costs.

[0041] The maximum scheduling adaptation coefficient can be used as an objective function to provide a data-driven basis for decision-making. By evaluating the adaptability of different scheduling schemes, the optimal scheme can be selected, thereby making more accurate and effective decisions in actual operations.

[0042] User interaction module: used to send multi-source data of potential supply points corresponding to the maximum scheduling adaptation coefficient to the scheduling demander.

[0043] The user interaction module includes a user interface, a parameter adjustment interface and a detail interface; The user interface is used to display the material name and material category, the shelf number where the material is stored, the scheduling adaptation coefficient, and the update time; The parameter adjustment interface facilitates the user to interact with the system, including adjusting the priority of the requirements and ensuring that the system can give priority to meeting high-priority requirements when resources are limited or the requirements are urgent; The details interface allows users to view detailed information about specific materials, including shelf distribution maps, restricted use dates, and quality inspection reports.

[0044] The user interaction module is specifically: First, obtain the allocation application of the allocation demander and retrieve multi-source data of potential supply points that meet the demand points; Compare the scheduling adaptation coefficients of the multi-source data of the potential supply points that meet the demand points to obtain a maximum scheduling adaptation coefficient; Retrieve the complete information of multi-source data of the potential supply point with the maximum scheduling adaptation coefficient, integrate it with the multi-source data of the potential supply point of the allocation demand side, and update the multi-source data of the allocation demand side and the potential supply point with the maximum scheduling adaptation coefficient; The updated multi-source data of potential supply points are returned to the data fusion module.

[0045] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0046] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0047] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0048] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0049] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0050] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. The data fusion and deployment system based on the material management platform is characterized by: include: Material management module: used to obtain multi-source data of potential supply points from the material management platform, wherein the multi-source data of potential supply points includes material inventory data, procurement data and material supply data; Data fusion module: used to fuse the multi-source data of potential supply points based on the multi-modal database, and perform quality checks on the fused data; Data allocation module: used to evaluate the adaptability of the fused multi-source data of potential supply points, construct a material allocation objective function with the maximum scheduling adaptation coefficient as the goal, and obtain the maximum scheduling adaptation coefficient; User interaction module: used to send multi-source data of potential supply points corresponding to the maximum scheduling adaptation coefficient to the scheduling demander.

2. The data fusion and deployment system based on the material management platform as claimed in claim 1, characterized in that: The method for acquiring the multi-source data of the potential supply point is as follows: Determine the source of material inventory data and use data integration tools to extract data from various systems to obtain the current material inventory of potential supply points from different data sources. Before the materials are put into storage, record the restricted use date of each batch of materials; The electronic version of the purchase invoice generated when purchasing materials is stored in the storage device in pieces, and the detailed information of each material allocation is recorded, including the allocation time, material number, and purchase quantity. The allocation time is combined with the purchase quantity to form the historical demand; Design a layout diagram for the warehouse where materials are stored, mark the shelf number of each shelf, which includes the shelf location and shelf number, obtain and record supplier information, which includes the company name of the supplier company and the name and category of the materials provided, obtain and record the monthly supply output of the supplier company, and convert the shelf number and supplier information into hot encoded variables.

3. The data fusion and deployment system based on the material management platform as claimed in claim 2 is characterized in that: The multi-source data of the potential supply points are fused based on the multi-modal database, specifically: Establish an entity-relationship diagram to describe the relationships and attributes between multi-source data of each potential supply point; The entities include material inventory data, procurement data, and material supply data; Add fields to the entity, including material name, material category, current inventory, and limited use date; Set not null constraints on all fields; Set a primary key constraint for the material name field; Set foreign key constraints on the Current Inventory Quantity field and the Limited Use Date field.

4. The data fusion and deployment system based on the material management platform as claimed in claim 3 is characterized in that: The quality check of the fused data is specifically as follows: Data integrity checks, including checking whether there are null values ​​or abnormal data in the multi-source data of potential supply points; Data consistency check, including checking whether the data naming conventions, data units, and data formats are unified; Data timeliness check, including checking whether the multi-source data of potential supply points are regularly updated.

5. The data fusion and deployment system based on the material management platform as claimed in claim 4 is characterized in that: The material allocation objective function is calculated as follows: Where: W is the material allocation objective function, q is the current inventory of the material, d is the current month, p is the month with a limited use period, r is the historical demand, t is the number of days from the purchase date, β is the hot code of the supplier information, is the hot code of the shelf number, P is the data completeness, and N is the data timeliness.

6. The data fusion and deployment system based on the material management platform as claimed in claim 5, characterized in that: The data integrity check is specifically as follows: For material names with default values, check whether these default values ​​are correctly applied in the data; Check missing values ​​for material inventory data, procurement data, and material supply data, and accumulate and record missing values; For the material name field of the same potential supply point, verify the uniqueness to avoid duplication or conflict; After completing the data integrity check, the data integrity is verified and calculated.

7. The data fusion and deployment system based on the material management platform as claimed in claim 6, characterized in that: The data timeliness check is specifically as follows: Establish a material date time series diagram, and compare the current date with the historical date from bottom to top; And record the number of multi-source data of potential supply points that exceed the restricted use date range of the materials; After completing the data timeliness check, the timeliness of the data is verified and calculated.

8. The data fusion and deployment system based on the material management platform as claimed in claim 7, characterized in that: The user interaction module is specifically: First, obtain the allocation application of the allocation demander and retrieve multi-source data of potential supply points that meet the demand points; Compare the scheduling adaptation coefficients of the multi-source data of the potential supply points that meet the demand points to obtain a maximum scheduling adaptation coefficient; Retrieve the complete information of multi-source data of the potential supply point with the maximum scheduling adaptation coefficient, integrate it with the multi-source data of the potential supply point of the allocation demand side, and update the multi-source data of the allocation demand side and the potential supply point with the maximum scheduling adaptation coefficient; The updated multi-source data of potential supply points are returned to the data fusion module.

9. The data fusion and deployment system based on the material management platform as claimed in claim 8, characterized in that: The specific calculation formula for the data integrity is as follows: Where: P is the data completeness, m is the total number of multi-source data of potential supply points involved in the inspection, g is the number of missing data identified by the quality inspection, h is the number of multi-source data of potential supply points that are abnormally repeated, and c is the number of data that needs to be refilled.

10. The data fusion and deployment system based on the material management platform as claimed in claim 9, characterized in that: The specific calculation formula of the data timeliness is as follows: Where: N is the data timeliness, f is the number of multi-source data of potential supply points with valid data format, s is the number of multi-source data of potential supply points with correct data type, is the number of multi-source data of potential supply points within the restricted use date of the materials, and m is the total number of multi-source data of potential supply points involved in the inspection.

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