A data management system, method, electronic device and storage medium

Abstract

This invention discloses a data management system, method, electronic device, and storage medium, relating to the field of manufacturing technology. The system includes: a data integration module, a data synchronization module, a data training module, and a data maintenance module; wherein, the data integration module is used for data integration with third-party systems; the data synchronization module is used for data synchronization between modules performing different business requirements; the data training module is used for learning and training based on data from the data integration module and the data synchronization module; and the data maintenance module is used for maintaining the system's built-in data pool and updating the stored data in a timely manner. This invention can improve data interaction efficiency.

Description

Technical Field

[0001] This invention relates to the field of manufacturing technology, and in particular to a data management system, method, electronic device, and storage medium. Background Technology

[0002] As production technology develops and progresses, the requirements for product manufacturing are becoming increasingly stringent, especially regarding production efficiency. In recent years, the integration of "information technology + manufacturing" has deepened, and in order to improve production efficiency, automated production technology has been gradually applied to the production of actual products. The use of automated production equipment reduces manual operation and thus improves production efficiency.

[0003] However, the problems of information silos and data silos are very prominent in manufacturing enterprises, making it impossible to effectively exchange data between different tasks in the system. Summary of the Invention

[0004] The purpose of this invention is to provide a data management system, method, electronic device, and storage medium that can improve data interaction efficiency.

[0005] To achieve the above objectives, the present invention provides the following solution:

[0006] A data management system, comprising:

[0007] The data integration module is used for data integration with third-party systems;

[0008] The data synchronization module is used to synchronize data between modules that perform different business requirements.

[0009] A data training module is used to perform learning and training based on the data from the data integration module and the data synchronization module;

[0010] The data maintenance module is used to maintain the data in the system's built-in data pool and update the stored data in a timely manner.

[0011] Optionally, the data training module includes a data reading unit, a data analysis unit, and a data training unit.

[0012] Optionally, the data reading unit is used to read data from the data integration module and the data synchronization module; the data analysis unit is used to analyze one or more of the customer information, supplier information, product information, inventory information, employee information, and process data in the data to determine the relevant influencing factors affecting enterprise management and process optimization; the data training unit is used to train the data based on the relevant influencing factors to determine the suggestions for enterprise management optimization and the path for process optimization.

[0013] Optionally, the data maintenance module is used to cooperate with process management and business management to implement data-driven operations, so as to maintain the overall data pool of the manufacturing enterprise.

[0014] Optionally, the form data of the business management is connected to the data maintenance module to realize automatic filling and correction of the form data.

[0015] The present invention also provides a data management method, comprising:

[0016] The system integrates data with third-party systems and synchronizes data between modules that perform different business requirements. Then, it learns and trains based on the data from the data integration module and the data synchronization module, thereby maintaining the data pool built into the system and updating the stored data in a timely manner.

[0017] The present invention also provides an electronic device, including a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to cause the electronic device to perform the data management method described above.

[0018] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the data management method described above.

[0019] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0020] This invention discloses a data management system, method, electronic device, and storage medium. The system includes a data integration module, a data synchronization module, a data training module, and a data maintenance module. The data integration module is used for data integration with third-party systems; the data synchronization module is used for data synchronization between modules performing different business requirements; the data training module is used for learning and training based on data from the data integration module and the data synchronization module; and the data maintenance module is used for maintaining the system's built-in data pool and updating the stored data in a timely manner. This invention can improve data interaction efficiency. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of the composition of the data management system in this embodiment.

[0023] Figure label:

[0024] 1. Data integration module; 2. Data synchronization module; 3. Data training module; 4. Data maintenance module. Detailed Implementation

[0025] 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.

[0026] The purpose of this invention is to provide a data management system, method, electronic device, and storage medium that can improve data interaction efficiency.

[0027] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0028] like Figure 1 As shown, the present invention provides a data management system, including:

[0029] The data integration module is used for data integration with third-party systems;

[0030] The data synchronization module is used to synchronize data between modules that perform different business requirements.

[0031] A data training module is used to perform learning and training based on the data from the data integration module and the data synchronization module;

[0032] The data maintenance module is used to maintain the data in the system's built-in data pool and update the stored data in a timely manner.

[0033] Based on the above technical solution, the following embodiments are provided.

[0034] As an application environment, it is equipped with a management system, which includes: a process management system, a business management system, a task management system, an edge computing system, and a data management system.

[0035] The process management system is used to determine business processes and corresponding control instructions; the business management system is used to execute different business modules according to the control instructions; the business modules include order business modules, production business modules, warehousing business modules, quality business modules, and process business modules; the task management system is used to schedule and manage specific tasks in each of the business modules; the edge computing system is used to manufacture equipment according to demand; the demand is determined according to the scheduling of business processes or specific tasks; the data management system in this embodiment is used to synchronize data in the form of internal sharing and / or external sharing; the internal sharing is to share the data generated during the manufacturing of equipment in the management system; the external sharing is to share the data generated during the manufacturing of equipment in a third-party system.

[0036] As described above, the data management system is used for the communication and interaction between the underlying systems of various system modules and the data communication and interaction with the factory's third-party systems. It includes a data integration module 1, a data synchronization module 2, a data training module 3, and a data maintenance module 4. The data training module 3 includes a data reading unit, a data analysis unit, and a data training unit.

[0037] In one or more embodiments, the data integration module 1 is used, for example, to implement the data integration step, integrating data from third-party systems, such as ERP systems, with the data from various applications of the management system itself. For example, the data format of the ERP system is modified to make it compatible with the management system and to be extracted and stored in the enterprise's overall data pool.

[0038] Data synchronization module 2, for example, is used to implement the data synchronization steps, synchronize the data of various modules between the business management systems, and realize data synchronization with the business process system.

[0039] Data training module 3, for example, is used to implement the data training steps, and learns and trains based on various data information from data integration module 1 and data synchronization module 2.

[0040] The data reading unit, for example, is used to implement the data reading step. It obtains relevant information in a specific task by reading data such as the task of the process execution unit in the business process system.

[0041] The data analysis unit, for example, is used to implement data analysis steps. It analyzes one or more of the following information: customer information, supplier information, product information, inventory information, employee information, process data, etc., to identify the relevant influencing factors affecting enterprise management and process optimization.

[0042] The data training unit, for example, is used to implement the data training steps, training a large amount of sample data based on influencing factors, in order to provide optimization suggestions for enterprise management and optimization paths for process upgrades.

[0043] In one or more embodiments, based on datasets from one or more third-party or proprietary overall data pools, machine learning algorithms can discover and derive patterns and relationships among several independent and interdependent variables from the data. Continuous updates to these variables or those derived from the algorithm, as well as ongoing consideration of other learned variables, allow the machine learning algorithm to probabilistically determine, for example, the status of people or equipment in specific roles, such as classification, judgment, and / or prediction. As examples, the machine learning algorithm can be configured to employ any one or more of Bayesian, random forest, decision tree, linear regression, deep learning, neural networks, and / or dimensionality reduction techniques. In some instances, applying machine learning algorithms to the results of data analysis can, for example, achieve intelligent task-to-position matching and assignment by analyzing task characteristics and specific job skill requirements and workload, or identify improvement opportunities for specific tasks in specific roles by acquiring interaction data from business processes to achieve intelligent assistance for specific tasks in specific roles.

[0044] Data maintenance module 4, for example, is used for data maintenance of the overall data pool of the factory, enabling timely data updates.

[0045] In one or more embodiments, the data management system enables data integration with third-party systems and various modules of the management system to collect data. Through the data maintenance module 4, it establishes an overall data pool for the enterprise. During the operation of the business process system and the business management system, it coordinates to achieve data-driven operation and utilizes the data training module to achieve data analysis and application, thereby realizing overall task-driven operation of the entire factory process.

[0046] In one or more embodiments, taking the data analysis of process optimization for a certain part in a manufacturing enterprise as an example, some of the process steps of the data management system and data management method disclosed herein are as follows:

[0047] First, obtain all relevant process parameters and workpiece quality parameters during the process.

[0048] Secondly, by analyzing the process parameters, we can obtain the key parameter indicators that affect product quality.

[0049] Finally, through the data training unit, combined with a large amount of process parameters and product quality data, the correlation between process parameters and product quality is obtained.

[0050] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0051] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A data management system, characterized in that, include: The data integration module is used for data integration with third-party systems; The data integration module is used to implement the data integration steps, which integrate the data from third-party systems with the management system's own applications. Specifically, it modifies the data format of third-party systems to make them compatible with the management system and can be extracted and stored in the enterprise's overall data pool. The data synchronization module is used to synchronize data between modules that perform different business requirements. The data synchronization module is used to implement the data synchronization steps, synchronize the data of each module between the business management systems, and realize data synchronization with the business process system. A data training module is used to perform learning and training based on the data from the data integration module and the data synchronization module; The data training module includes a data reading unit, a data analysis unit, and a data training unit. These units implement data training steps, learning and training based on various data information from the data integration module and the data synchronization module. The data reading unit reads task data from the process execution units in the business process system to obtain relevant information for specific tasks. The data analysis unit analyzes one or more of customer information, supplier information, product information, inventory information, employee information, and process data to identify relevant influencing factors affecting enterprise management and process optimization. The data training unit trains on a large amount of sample data based on these influencing factors to provide optimization suggestions for enterprise management and optimization paths for process upgrades. Specifically, based on data from... Learning from datasets of one or more third-party or proprietary overall data pools, machine learning algorithms can discover patterns and relationships among several independent and interdependent variables derived from the data. Continuous updates to these variables or those derived from the algorithm, as well as ongoing consideration of other learned variables, allow the machine learning algorithm to probabilistically determine the patterns. The machine learning algorithm is configured to employ any one or more of Bayesian, random forest, decision tree, linear regression, deep learning, neural networks, and / or dimensionality reduction techniques. The results of applying the machine learning algorithm to the data enable intelligent matching and assignment of tasks and specific positions by analyzing task characteristics and skill requirements and workload attributes of specific roles. By acquiring interaction data from business processes, the improvement space for specific tasks in specific roles can be determined to achieve intelligent assistance for specific tasks in specific roles. The data maintenance module is used to maintain the data in the system's built-in data pool and update the stored data in a timely manner. The data maintenance module is used for the overall data pool maintenance of the factory, enabling timely data updates. The aforementioned data management system enables data integration with third-party systems and various modules of this management system, achieving data collection. Through the data maintenance module, it establishes an overall data pool for the enterprise, cooperating with the business process system and business management system to drive data during operation, and utilizing the data training module to achieve data analysis and application, thereby realizing overall task-driven operation of the entire factory process.

2. A data management method, based on the system of claim 1, characterized in that, include: The system integrates data with third-party systems and synchronizes data between modules that perform different business requirements. Then, it learns and trains based on the data from the data integration module and the data synchronization module, thereby maintaining the data pool built into the system and updating the stored data in a timely manner.

3. An electronic device, characterized in that, It includes a memory and a processor, the memory being used to store a computer program, and the processor running the computer program to cause the electronic device to perform the data management method according to claim 2.

4. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the data management method as described in claim 2.

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