Intelligent logistics supply chain management system and risk early warning method thereof

Abstract

The invention relates to the technical field of supply chain management, and discloses an intelligent logistics supply chain management system and a risk early warning method thereof, and the system comprises a data standardization module, a system integration platform module, a data center and cloud service module, and a visual management tool module. According to the intelligent logistics supply chain management system and the risk early warning method thereof, scientific decision support can be provided for a management layer through provided data analysis and prediction results, and making of a more reasonable strategic plan and an operation strategy is helped; the application of the information sharing and collaboration and information sharing module promotes the information transparency and collaboration work efficiency of all parties of the supply chain, reduces the problems caused by information asymmetry, and reduces the operation cost of the supply chain as a whole by optimizing the flow of the supply chain, reducing unnecessary inventory and logistics cost and avoiding excessive production through a prediction model. By monitoring and optimizing the whole process of the supply chain, resource waste and environmental influence are reduced, and sustainable development of supply chain management is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of supply chain management, and in particular to an intelligent logistics supply chain management system and a risk early warning method thereof. Background Art

[0002] Supply chain management refers to the management method of product manufacturing, transportation, distribution and sales by effectively organizing suppliers, manufacturers, warehouses, distribution centers and channel dealers to minimize the cost of the entire supply chain system while meeting a certain level of customer service. Moreover, in the intelligent logistics supply chain management system, risk warning methods are also crucial.

[0003] However, due to the inconsistent data formats and standards of different systems and suppliers, the existing intelligent logistics supply chain management systems cannot directly exchange data between different systems. Data transmission and processing require additional conversion work, which increases the complexity and cost of system integration. Data cannot flow freely between systems, resulting in the inability to share information in various links of the supply chain, reducing the overall operational efficiency and leading to information islands. Therefore, an intelligent logistics supply chain management system and its risk warning method are proposed to solve the above problems. Summary of the invention

[0004] 1. Technical issues to be resolved In view of the shortcomings of the prior art, the present invention provides an intelligent logistics supply chain management system and a risk warning method thereof, which have the advantages of improving the interoperability between systems, and solve the problems of the existing intelligent logistics supply chain management system, such as the inconsistency of data formats and standards between different systems and suppliers, the inability to directly exchange data between different systems, the need for additional conversion work for data transmission and processing, which increases the complexity and cost of system integration, and the inability of data to flow freely between systems, resulting in the inability to share information in various links in the supply chain, reducing the overall operational efficiency, and causing the problem of information islands.

[0005] (II) Technical solution To achieve the above objectives, the present invention provides the following technical solutions: an intelligent logistics supply chain management system, including a data standardization module, a system integration platform module, a data center and cloud service module, a visual management tool module, a collaboration and information sharing module, and a security and privacy protection module.

[0006] Preferably, the data standardization module includes a data format standardization unit, a data dictionary unit and a standard protocol formulation unit, and the system integration platform module includes an API management unit, an enterprise service bus unit and a data mapping unit.

[0007] Preferably, the data center and cloud service module includes a data storage unit, a data processing unit and a cloud service management unit, and the visual management tool module includes a data integration unit, a report generation unit and a data dashboard unit.

[0008] Preferably, the collaboration and information sharing module includes an order management unit, an inventory management unit, a transportation management unit and a supply chain event management unit, and the security and privacy protection module includes an access control unit, an encryption unit, an identity authentication unit and a security monitoring unit.

[0009] Preferably, the data standardization module is used to solve the problem of inconsistent data formats among different systems and suppliers and to formulate unified data exchange standards. The system integration platform module is responsible for integrating information systems in various links of the supply chain, breaking through data silos and achieving information interconnection.

[0010] Preferably, the data center and cloud service module are used to provide unified data storage and computing resources to achieve centralized management of supply chain data, and the visual management tool module is used to provide managers with a data visualization interface to assist in supply chain decision support.

[0011] Preferably, the collaboration and information sharing module is used to establish an information sharing mechanism among all parties in the supply chain, promote information sharing and collaboration between upstream and downstream enterprises in the supply chain, and improve response speed and decision-making efficiency. The security and privacy protection module is used to formulate data access control and authority management policies, ensure the security of sensitive information, and use encryption and identity authentication technologies to protect the security of data during transmission and storage.

[0012] A risk warning method for an intelligent logistics supply chain management system comprises the following steps: S1. Data collection and standardization: The data standardization module collects the raw data from each system and converts it into a unified format standard. The system integration platform module is responsible for transmitting the standardized data to the data center and cloud service module. S2. Real-time monitoring and anomaly detection: The data center and cloud service modules analyze real-time data and use machine learning algorithms to detect anomalies in the supply chain. The anomaly detection module pushes potential risk information to the collaboration and information sharing module. S3. Risk assessment and prediction: The collaboration and information sharing module will analyze the detected risk information and historical data, and use the prediction model provided by the data center to predict and evaluate the risks that may occur in the future; S4. Automatic early warning and coordinated response: The visual management tool module generates an intuitive risk matrix and early warning information based on the risk assessment results. The collaboration and information sharing module pushes risk warnings to all parties in the supply chain, triggering a coordinated response from suppliers and logistics providers. S5. Execution and continuous optimization of emergency plans: The security and privacy protection module ensures the security of risk information during transmission and storage. All parties in the supply chain take corresponding response measures based on pre-established emergency plans, and optimize and improve the entire risk warning system through continuous risk assessment and simulation exercises.

[0013] (III) Beneficial effects Compared with the prior art, the present invention provides an intelligent logistics supply chain management system and a risk warning method thereof, which has the following beneficial effects: 1. The intelligent logistics supply chain management system and its risk warning method can provide scientific decision-making support for the management through the data analysis and prediction results provided, and help formulate more reasonable strategic planning and operation strategies. The application of information sharing and collaboration and information sharing modules promotes the information transparency and collaborative work efficiency of all parties in the supply chain, reduces the problems caused by information asymmetry, and reduces the overall operating costs of the supply chain by optimizing the supply chain process, reducing unnecessary inventory and logistics costs, and avoiding overproduction through predictive models. By monitoring and optimizing the entire supply chain process, it reduces resource waste and environmental impact, and promotes the sustainable development of supply chain management.

[0014] 2. The intelligent logistics supply chain management system and its risk warning method, through real-time monitoring and automatic warning, can enable each link of the supply chain to quickly identify and respond to potential risks, shorten the reaction time, improve the agility of the overall supply chain, predict and warn of risk events in advance, enable enterprises to take countermeasures in advance, and reduce losses caused by emergencies such as supply disruptions, inventory backlogs, logistics delays, etc. Risk warning can provide a variety of response strategies and alternative plans when the supply chain faces shocks, thereby enhancing the supply chain's risk resistance and recovery capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a structural diagram of an intelligent logistics supply chain management system of the present invention; Figure 2 The present invention is a flowchart of a risk early warning method for an intelligent logistics supply chain management system. DETAILED DESCRIPTION

[0016] 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.

[0017] See also Figure 1-2 , an intelligent logistics supply chain management system, including a data standardization module, a system integration platform module, a data center and cloud service module, a visual management tool module, a collaboration and information sharing module, and a security and privacy protection module.

[0018] Specifically, the data standardization module includes a data format standardization unit, a data dictionary unit and a standard protocol formulation unit, and the system integration platform module includes an API management unit, an enterprise service bus unit and a data mapping unit.

[0019] Furthermore, the data format standardization unit is responsible for defining and maintaining data format standards, such as XML and JSON; the data dictionary unit is used to maintain and update the definitions and interpretations of data fields; and the standard protocol formulation unit is used to negotiate and formulate data exchange protocols with industry partners.

[0020] Furthermore, the API management unit is used to manage and provide API interfaces between systems; the enterprise service bus unit is used to process message transmission and data conversion between systems; and the data mapping unit maps and converts data formats of different systems.

[0021] Specifically, the data center and cloud service module includes a data storage unit, a data processing unit and a cloud service management unit, and the visual management tool module includes a data integration unit, a report generation unit and a data dashboard unit.

[0022] Furthermore, the data storage unit provides large-scale data storage solutions; the data processing unit is used for data cleaning, conversion and analysis; and the cloud service management unit is used to manage the allocation and use of cloud resources.

[0023] Furthermore, the data integration unit is used to collect and integrate data from various systems; the report generation unit is used to automatically generate various business reports; and the data dashboard unit is used to provide an interface for real-time data display and analysis.

[0024] Specifically, the collaboration and information sharing module includes an order management unit, an inventory management unit, a transportation management unit and a supply chain event management unit, and the security and privacy protection module includes an access control unit, an encryption unit, an identity authentication unit and a security monitoring unit.

[0025] Furthermore, the order management unit is used to handle the sharing and collaboration of order data; the inventory management unit is used to share inventory information in real time; the transportation management unit is used to coordinate and share transportation information; and the supply chain event management unit is used to monitor and share event information in the supply chain.

[0026] Furthermore, the access control unit is used to manage user permissions and data access control; the encryption unit is used for encryption services for data transmission and storage; the identity authentication unit is used to process user identity authentication and authorization; and the security monitoring unit is used to monitor the system security status and detect abnormal activities.

[0027] Specifically, the data standardization module is used to solve the problem of inconsistent data formats among different systems and suppliers and to formulate unified data exchange standards. The system integration platform module is responsible for integrating the information systems of various links in the supply chain, breaking through data silos and achieving information interconnection and interoperability.

[0028] Furthermore, the data standardization module is closely connected with the system integration platform module and the data center and cloud service module to ensure that data can be smoothly transmitted and shared between systems. The system integration platform module collaborates with the data standardization module to use unified data standards for system integration. At the same time, the system integration platform module is also connected with the data center and cloud service module to aggregate the data of each system to the cloud for centralized management and analysis.

[0029] Specifically, the data center and cloud service module is used to provide unified data storage and computing resources to achieve centralized management of supply chain data. The visual management tool module is used to provide managers with a data visualization interface to assist in supply chain decision support.

[0030] Furthermore, the data center and cloud service module connects the data standardization module and the system integration platform module, receives standardized data from each system, and provides data services for other modules. At the same time, the data center and cloud service module also supports the data requirements of the visualization management tool module and the collaboration and information sharing module. The visualization management tool module needs to obtain unified data resources from the data center and cloud service module, and use the collaborative functions provided by the collaboration and information sharing module.

[0031] Specifically, the collaboration and information sharing module is used to establish an information sharing mechanism among all parties in the supply chain, promote information sharing and collaboration between upstream and downstream enterprises in the supply chain, and improve response speed and decision-making efficiency. The security and privacy protection module is used to formulate data access control and authority management policies, ensure the security of sensitive information, and use encryption and identity authentication technologies to protect the security of data during transmission and storage.

[0032] Furthermore, the collaboration and information sharing module is connected to the data center and cloud service module, using cloud data to support collaboration between supply chain partners. At the same time, the collaboration and information sharing module also provides collaborative function support for the visual management tool module. The security and privacy protection module must collaborate with all other modules mentioned above to ensure the security of the entire system.

[0033] A risk warning method for an intelligent logistics supply chain management system comprises the following steps: S1. Data collection and standardization: The data standardization module collects the raw data from each system and converts it into a unified format standard. The system integration platform module is responsible for transmitting the standardized data to the data center and cloud service module. S2. Real-time monitoring and anomaly detection: The data center and cloud service modules analyze real-time data and use machine learning algorithms to detect anomalies in the supply chain. The anomaly detection module pushes potential risk information to the collaboration and information sharing module. S3. Risk assessment and prediction: The collaboration and information sharing module will analyze the detected risk information and historical data, and use the prediction model provided by the data center to predict and evaluate the risks that may occur in the future; S4. Automatic early warning and coordinated response: The visual management tool module generates an intuitive risk matrix and early warning information based on the risk assessment results. The collaboration and information sharing module pushes risk warnings to all parties in the supply chain, triggering a coordinated response from suppliers and logistics providers. S5. Execution and continuous optimization of emergency plans: The security and privacy protection module ensures the security of risk information during transmission and storage. All parties in the supply chain take corresponding response measures based on pre-established emergency plans, and optimize and improve the entire risk warning system through continuous risk assessment and simulation exercises.

[0034] In summary, the intelligent logistics supply chain management system and its risk warning method can provide scientific decision-making support for management through the data analysis and prediction results provided, help formulate more reasonable strategic planning and operation strategies, and the application of information sharing and collaboration and information sharing modules promotes information transparency and collaborative work efficiency among all parties in the supply chain, reduces problems caused by information asymmetry, and reduces the overall operating cost of the supply chain by optimizing supply chain processes, reducing unnecessary inventory and logistics costs, and avoiding overproduction through predictive models. By monitoring and optimizing the entire supply chain process, it reduces resource waste and environmental impact, and promotes the sustainable development of supply chain management.

[0035] Moreover, through real-time monitoring and automatic early warning, each link in the supply chain can quickly identify and respond to potential risks, shorten the reaction time, improve the agility of the overall supply chain, predict and warn of risk events in advance, enable enterprises to take countermeasures in advance, and reduce losses caused by emergencies, such as supply disruptions, inventory backlogs, logistics delays, etc. Risk early warning can provide a variety of response strategies and alternative plans when the supply chain faces shocks, enhance the risk resistance and recovery capabilities of the supply chain, and solve the existing intelligent logistics supply chain management system. Due to the inconsistent data formats and standards of different systems and suppliers, different systems cannot directly exchange data, and data transmission and processing require additional conversion work, which increases the complexity and cost of system integration. Data cannot flow freely between systems, resulting in the inability of various links in the supply chain to share information, reducing overall operational efficiency and leading to information islands.

[0036] 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 also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0037] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent logistics supply chain management system, characterized by: It includes data standardization module, system integration platform module, data center and cloud service module, visual management tool module, collaboration and information sharing module, and security and privacy protection module.

2. The intelligent logistics supply chain management system according to claim 1, characterized in that: The data standardization module includes a data format standardization unit, a data dictionary unit and a standard protocol formulation unit, and the system integration platform module includes an API management unit, an enterprise service bus unit and a data mapping unit.

3. The intelligent logistics supply chain management system according to claim 1, characterized in that: The data center and cloud service module includes a data storage unit, a data processing unit and a cloud service management unit, and the visual management tool module includes a data integration unit, a report generation unit and a data dashboard unit.

4. The intelligent logistics supply chain management system according to claim 1, characterized in that: The collaboration and information sharing module includes an order management unit, an inventory management unit, a transportation management unit and a supply chain event management unit, and the security and privacy protection module includes an access control unit, an encryption unit, an identity authentication unit and a security monitoring unit.

5. The intelligent logistics supply chain management system according to claim 1, characterized in that: The data standardization module is used to solve the problem of inconsistent data formats among different systems and suppliers and to formulate unified data exchange standards. The system integration platform module is responsible for integrating information systems in various links of the supply chain, breaking through data silos and achieving information interconnection.

6. The intelligent logistics supply chain management system according to claim 1, characterized in that: The data center and cloud service module is used to provide unified data storage and computing resources to achieve centralized management of supply chain data. The visual management tool module is used to provide managers with a data visualization interface to assist in decision support for the supply chain.

7. The intelligent logistics supply chain management system according to claim 1, characterized in that: The collaboration and information sharing module is used to establish an information sharing mechanism among all parties in the supply chain, promote information sharing and collaboration between upstream and downstream enterprises in the supply chain, and improve response speed and decision-making efficiency. The security and privacy protection module is used to formulate data access control and authority management policies, ensure the security of sensitive information, and use encryption and identity authentication technologies to protect the security of data during transmission and storage.

8. A risk warning method for an intelligent logistics supply chain management system, applicable to an intelligent logistics supply chain management system according to any one of claims 1 to 7, characterized in that: The following steps are involved: S1. Data collection and standardization: The data standardization module collects the raw data from each system and converts it into a unified format standard. The system integration platform module is responsible for transmitting the standardized data to the data center and cloud service module. S2. Real-time monitoring and anomaly detection: The data center and cloud service modules analyze real-time data and use machine learning algorithms to detect anomalies in the supply chain. The anomaly detection module pushes potential risk information to the collaboration and information sharing module. S3. Risk assessment and prediction: The collaboration and information sharing module will analyze the detected risk information and historical data, and use the prediction model provided by the data center to predict and evaluate the risks that may occur in the future; S4. Automatic early warning and coordinated response: The visual management tool module generates an intuitive risk matrix and early warning information based on the risk assessment results. The collaboration and information sharing module pushes risk warnings to all parties in the supply chain, triggering a coordinated response from suppliers and logistics providers. S5. Execution and continuous optimization of emergency plans: The security and privacy protection module ensures the security of risk information during transmission and storage. All parties in the supply chain take corresponding response measures based on pre-established emergency plans, and optimize and improve the entire risk warning system through continuous risk assessment and simulation exercises.

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