CN116562588A - Enterprise supply chain analysis system, method and equipment based on ERP - Google Patents

Enterprise supply chain analysis system, method and equipment based on ERP Download PDF

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CN116562588A
CN116562588A CN202310623294.2A CN202310623294A CN116562588A CN 116562588 A CN116562588 A CN 116562588A CN 202310623294 A CN202310623294 A CN 202310623294A CN 116562588 A CN116562588 A CN 116562588A
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童文
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Quanhou Guangzhou Information Technology Co ltd
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Abstract

The invention relates to the technical field of supply chain management, and discloses an enterprise supply chain analysis system, method and equipment based on ERP. The system comprises a data type dividing module, a relevance calculating module, a business report monitoring module, an enterprise supply chain optimizing module and an enterprise resource adjusting strategy generating module, wherein a business report can be constructed according to a business process of a supply chain, ERP nodes can be generated according to the business report, and an ERP model can be further generated; and real-time monitoring is carried out on data in the supply chain by utilizing the ERP model, the original supply chain is optimized according to the monitored supply chain data, real-time monitoring is carried out according to the optimized supply chain data, and an enterprise resource adjustment strategy is generated according to the monitored optimized supply chain data. The invention can improve the accuracy of the enterprise in carrying out the analysis of the supply chain resources.

Description

Enterprise supply chain analysis system, method and equipment based on ERP
Technical Field
The invention relates to the technical field of supply chain management, in particular to an ERP-based enterprise supply chain analysis system, method and equipment.
Background
In the age of rapid development of technology and continuous change of demand, ERP (Enterprise Resource Planning) has been widely applied in enterprises, and the idea of supply chain management is also being more and more emphasized by enterprises. However, in order to increase the management level of the enterprise supply chain, analysis optimization is required for the enterprise supply chain to increase the enterprise competitiveness.
Most of the existing enterprise supply chain analysis systems analyze the business processes of the supply chain, and the data generated by the supply chain cannot be reflected in time. In practical application, integrated management of all data generated in an enterprise supply chain is required to be realized, only data analysis is considered to be performed on a single flow node of the supply chain, and real-time supply chain data cannot be mastered, so that the accuracy of the enterprise in performing supply chain resource analysis is low.
Disclosure of Invention
The invention provides an ERP-based enterprise supply chain analysis system, method and equipment, and mainly aims to solve the problem of low accuracy in supply chain resource analysis of enterprises.
In order to achieve the above object, the ERP-based enterprise supply chain analysis system provided by the invention is characterized in that the system comprises a data type dividing module, a relevance calculating module, a business report monitoring module, an enterprise supply chain optimizing module and an enterprise resource adjusting strategy generating module, wherein,
the data type dividing module is used for acquiring a business process of a target enterprise supply chain, extracting real-time node data of a supply chain node in the business process, and dividing the data types of the real-time node data through preset data attributes to obtain real-time node data types;
The node association degree calculation module is used for constructing a business report of the business process according to the real-time node data type and preset business parameters, generating ERP nodes corresponding to the target enterprise supply chain according to the business report, and calculating association degrees among the ERP nodes by using a preset iterative association degree algorithm;
the business report monitoring module is used for generating an ERP model according to the association degree and the business report, and real-time monitoring the business report according to preset business requirements by utilizing the ERP model to obtain real-time business report data;
the enterprise supply chain optimizing module is configured to perform value evaluation on the real-time business report data through a pre-constructed supply chain evaluation model to obtain a business report evaluation value, optimize the target enterprise supply chain according to the business report evaluation value to obtain a target optimized enterprise supply chain, where the optimizing the target enterprise supply chain according to the business report evaluation value is specifically configured to, when obtaining the target optimized enterprise supply chain:
when the service report evaluation value is smaller than a preset evaluation threshold value, extracting service node data corresponding to the service report evaluation value;
Calculating the data optimization value of the service node data by using the following optimization value calculation formula;
wherein Y is the data optimization value, tau is an optimization factor, X is actual service data in the service node data, S is real-time service demand data, and Z is demand service data in the service node data;
optimizing the service node data according to the data optimization value to obtain optimized node data;
adding the optimized node data into ERP nodes corresponding to the target enterprise supply chain to obtain optimized ERP nodes, and updating the optimized ERP nodes into the target enterprise supply chain to obtain a target optimized enterprise supply chain;
the enterprise resource adjustment strategy generation module is used for monitoring real-time data in the target optimization enterprise supply chain according to the business requirements by utilizing the ERP model to obtain supply chain optimization data, and generating an enterprise resource adjustment strategy according to the supply chain optimization data.
Optionally, the data type dividing module is specifically configured to, when performing data type division on the real-time node data by using a preset data attribute to obtain a real-time node data type:
Generating a data type table according to the data attribute;
classifying the data attribute of the real-time node data to obtain the real-time node data attribute;
and adding the real-time node data into the data type table according to the real-time node data attribute to obtain a real-time node data type.
Optionally, the node association calculation module is specifically configured to, when constructing a service report of the service flow according to the real-time node data type and a preset service parameter:
encapsulating the real-time node data of the business process according to the real-time node data type to obtain a report header field;
determining a service field according to the service parameter;
and packaging the report header field and the service field into a service report of the service flow.
Optionally, the node relevance calculating module is specifically configured to, when calculating the relevance between the ERP nodes by using a preset iterative relevance algorithm:
determining node association relations among the ERP nodes according to the business flow;
calculating node association factors of the ERP nodes according to the node association relations, wherein the node association factor calculation formula is as follows:
wherein ,mij Is the node association factor between ERP node i and ERP node j, beta ij The method comprises the steps of obtaining node association coefficients corresponding to node association relations between ERP nodes i and ERP nodes j, wherein n is the node number of the ERP nodes;
calculating the relevance between the ERP nodes according to the node relevance factors by using an iterative relevance algorithm as follows:
wherein ,pij For the association degree between the ERP node i and the ERP node j, n is the node number of the ERP node, d is the iterative optimization coefficient, m ij For the node association factor, p, between ERP node i and ERP node j ik The association degree between the ERP node i and the ERP node k is obtained.
Optionally, the business report monitoring module is specifically configured to, when generating an ERP model according to the association degree and the business report:
generating an ERP business process according to the association degree;
adding the business report to an ERP node corresponding to the ERP business flow according to a preset business type to obtain an ERP business node template;
and combining the ERP service node templates according to the ERP service flow to obtain the ERP model.
Optionally, the business report monitoring module is specifically configured to, when using the ERP model to monitor the business report in real time according to a preset business requirement to obtain real-time business report data:
Extracting service demand data in the service demand;
monitoring the business demand data by utilizing ERP business data in the ERP model to obtain a data monitoring value, wherein the calculation formula of the data monitoring value is as follows:
E k ＝α k ×(A-B k )
wherein ,Ek Data monitoring value alpha for kth ERP business data k A data monitoring factor for kth ERP business data, A is a quantized value of the business demand data, B k A quantized value of kth ERP business data;
and selecting the minimum ERP business data in the data monitoring value as the real-time business report data.
Optionally, before performing value evaluation on the real-time business report data through a pre-constructed supply chain evaluation model, the enterprise supply chain optimization module is specifically configured to:
acquiring a service data factor, and determining a service index according to the service data factor;
determining model parameters according to the business indexes, and constructing a supply chain evaluation model equation through the model parameters, wherein the supply chain evaluation equation is as follows:
wherein ,for the supply chain evaluation value, γ is the first regression coefficient, β is the second regression coefficient, a is the extrinsic latent variable in the model parameter, b is the intrinsic latent variable in the model parameter, ρ is the model error;
The supply chain evaluation model equation is determined as the supply chain evaluation model.
Optionally, the enterprise resource adjustment policy generation module is specifically configured to, when generating an enterprise resource adjustment policy according to the supply chain optimization data:
acquiring initial enterprise resources, and optimizing the initial enterprise resources according to the supply chain optimization data to obtain optimized enterprise resources;
and generating an enterprise resource adjustment strategy according to the optimized enterprise resource and the preset business resource requirement.
In order to solve the above problems, the present invention further provides a method for operating an ERP-based enterprise supply chain analysis system, the method comprising:
acquiring a business process of a target enterprise supply chain, extracting real-time node data of a supply chain node in the business process, and dividing the real-time node data into data types through preset data attributes to obtain real-time node data types;
constructing a business report of the business process according to the real-time node data type and preset business parameters, generating ERP nodes corresponding to the target enterprise supply chain according to the business report, and calculating the association degree between the ERP nodes by using a preset iterative association degree algorithm;
Generating an ERP model according to the association degree and the business report, and carrying out real-time monitoring on the business report by utilizing the ERP model according to preset business requirements to obtain real-time business report data;
performing value evaluation on the real-time business report data through a pre-constructed supply chain evaluation model to obtain a business report evaluation value, and optimizing the target enterprise supply chain according to the business report evaluation value to obtain a target optimized enterprise supply chain;
and real-time monitoring is carried out on real-time data in the target optimization enterprise supply chain according to the business requirements by utilizing the ERP model, supply chain optimization data are obtained, and enterprise resource adjustment strategies are generated according to the supply chain optimization data.
In order to solve the above-mentioned problems, the present invention also provides an electronic apparatus including:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of operating the ERP-based enterprise supply chain analysis system described above.
According to the method and the device, the business report is built through the business process of the enterprise supply chain, ERP nodes are generated according to the business report, and the association degree between the ERP nodes is calculated, so that an ERP model is built, the combination of the supply chain and the ERP model is realized, the maximization of the benefit of the supply chain is realized, and meanwhile, the benefit distribution of the enterprise on the supply chain can be balanced; real-time monitoring is carried out on data in a supply chain by utilizing an ERP model to obtain supply chain optimization data, and then the original supply chain is optimized according to the supply chain optimization data to obtain an optimized supply chain, so that the competitiveness of the supply chain is improved; the data of the optimized supply chain is monitored in real time, and an enterprise resource adjustment strategy is generated according to the optimized data in the optimized supply chain, so that the product supply and demand balance can be adjusted timely. Therefore, the ERP-based enterprise supply chain analysis system, method and equipment provided by the invention can solve the problem of lower accuracy when an enterprise performs supply chain resource analysis.
Drawings
FIG. 1 is a functional block diagram of an ERP-based enterprise supply chain analysis system according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method of operating an ERP-based enterprise supply chain analysis system according to an embodiment of the present invention;
Fig. 3 is a schematic structural diagram of an electronic device for implementing the operation method of the ERP-based enterprise supply chain analysis system according to an embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise, the "plurality" generally includes at least two.
The words "if", as used herein, may be interpreted as "at … …" or "at … …" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrase "if determined" or "if detected (stated condition or event)" may be interpreted as "when determined" or "in response to determination" or "when detected (stated condition or event)" or "in response to detection (stated condition or event), depending on the context.
In addition, the sequence of steps in the method embodiments described below is only an example and is not strictly limited.
In practice, a server device deployed by an ERP-based enterprise supply chain analysis system may be made up of one or more devices. The enterprise supply chain analysis system based on ERP can be realized as follows: service instance, virtual machine, hardware device. For example, the ERP-based enterprise supply chain analysis system may be implemented as a business instance deployed on one or more devices in a cloud node. Briefly, the ERP-based enterprise supply chain analysis system may be understood as a software deployed on cloud nodes to provide an ERP-based enterprise supply chain analysis system for each user. Alternatively, the ERP-based enterprise supply chain analysis system may also be implemented as a virtual machine deployed on one or more devices in the cloud node. The virtual machine is provided with application software for managing each user side. Alternatively, the ERP-based enterprise supply chain analysis system may be implemented as a server consisting of a plurality of hardware devices of the same or different types, where one or more of the hardware devices are configured to provide an ERP-based enterprise supply chain analysis system for each user.
In an implementation form, the ERP-based enterprise supply chain analysis system and the user side are mutually adapted. Namely, the enterprise supply chain analysis system based on ERP is used as an application installed on the cloud service platform, and the user side is used as a client side for establishing communication connection with the application; or the enterprise supply chain analysis system based on ERP is realized as a website, and the user side is realized as a webpage; and then or the enterprise supply chain analysis system based on ERP is realized as a cloud service platform, and the user side is realized as an applet in the instant messaging application.
Referring to FIG. 1, a functional block diagram of an ERP-based enterprise supply chain analysis system is shown, in accordance with one embodiment of the present invention.
The ERP-based enterprise supply chain analysis system 100 of the present invention may be disposed in a cloud server, and in implementation form, may be used as one or more service devices, may be installed as an application on a cloud (e.g., a server of a mobile service operator, a server cluster, etc.), or may be developed as a website. Depending on the functions implemented, the ERP-based enterprise supply chain analysis system 100 may include a data type partitioning module 101, a node relevance calculation module 102, a business report monitoring module 103, a real enterprise supply chain optimization module 104, and an enterprise resource adjustment policy generation module 105. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.
In the enterprise supply chain analysis system based on ERP, each module can be independently realized and called with other modules. A call herein is understood to mean that a module may connect to a plurality of modules of another type and provide corresponding services to the plurality of modules to which it is connected. For example, the sharing evaluation module can call the same information acquisition module to acquire the information acquired by the information acquisition module based on the characteristics, and in the ERP-based enterprise supply chain analysis system provided by the embodiment of the invention, the application range of the ERP-based enterprise supply chain analysis system architecture can be adjusted by adding the module and directly calling the module without modifying the program codes, so that the cluster-type horizontal expansion is realized, and the purpose of rapidly and flexibly expanding the ERP-based enterprise supply chain analysis system is achieved. In practical applications, the modules may be disposed in the same device or different devices, or may be service instances disposed in virtual devices, for example, in a cloud server.
The following description is directed to various components and specific workflows of an ERP-based enterprise supply chain analysis system, respectively, in connection with specific embodiments:
The data type dividing module 101 is configured to obtain a business process of a supply chain of a target enterprise, extract real-time node data of a supply chain node in the business process, and perform data type division on the real-time node data through a preset data attribute to obtain a real-time node data type.
In the embodiment of the invention, the business process is set by the target enterprise supply chain for realizing planning, organization and control of supply chain logistics, fund flow and information flow, and the business process comprises purchasing, producing, storing, selling, logistics and product development, wherein the business process of the target enterprise supply chain can be obtained by carrying out questionnaire investigation on the supply chain business process of the target enterprise.
Further, corresponding business data is generated at each business process stage of the target enterprise supply chain, and data analysis is required to be performed on the business data, so that supply and demand balance is realized through information sharing.
In the embodiment of the present invention, the real-time node data refers to taking each process stage in the business process as a supply chain node, for example, taking a purchasing stage as a supply chain node, and taking a production stage as a supply chain node, so as to obtain real-time node data of each supply chain node, namely, purchasing data in the purchasing stage, production data in the production stage, sales data in the sales stage, and the like.
In detail, real-time node data in the supply chain nodes may be obtained from a pre-stored data storage area including, but not limited to, a database, a blockchain, using computer statements (e.g., java statements, python statements, etc.) having a data crawling function.
Further, in order to construct a business report for a business process, the data in the business process needs to be classified so as to avoid disorder of the data and make the business report clearer.
In the embodiment of the invention, the real-time node data types comprise character type, text type and numerical type, and the data types of each real-time node data are divided to construct a clearer business report.
In the embodiment of the present invention, the data type dividing module 101 is specifically configured to, when performing data type division on the real-time node data according to a preset data attribute to obtain a real-time node data type:
generating a data type table according to the data attribute;
classifying the data attribute of the real-time node data to obtain the real-time node data attribute;
and adding the real-time node data into the data type table according to the real-time node data attribute to obtain a real-time node data type.
In detail, the data attribute refers to the original data type in each real-time node data, including character type, text type and numerical value type; the data type table is a blank table which generates a data field as a data type according to the data attribute and comprises a character type data table, a text type data table and a numerical type data table. And classifying the data in the real-time node data according to character type, text type and numerical type in the data attribute to obtain real-time node data attribute corresponding to the data in the real-time node data, and adding the real-time node data attribute and the real-time node data thereof into a corresponding data type table to obtain the real-time node data type corresponding to the real-time node data.
When the real-time node data is purchasing data, the purchasing data comprises the purchased articles, the amount of the purchased articles, the quantity of the articles, the purchasing provider area and the like, the purchasing articles and the purchasing provider area are divided into text types according to the closest data attributes, the amount of the articles and the quantity of the articles are divided into numerical types, and the divided data corresponding to the node data attributes are used as data fields, namely the real-time node data and the real-time node data attributes corresponding to the real-time node data are added into a data type table together, so that the real-time node data type corresponding to each data in the real-time node data is obtained.
Further, in order to achieve the supply-demand balance, the corresponding business report needs to be constructed through the business process in the target enterprise supply chain so as to run through the target enterprise supply chain.
The node association calculation module 102 is configured to construct a business report of the business process according to the real-time node data type and a preset business parameter, generate an ERP node corresponding to the target enterprise supply chain according to the business report, and calculate association between the ERP nodes by using a preset iterative association algorithm.
In the embodiment of the invention, the business report refers to that business data generated in each business stage in a business process is stored in the form of a report. The business parameters include business control, other control, credit control, availability control and price control.
In the embodiment of the present invention, when the node association calculation module 102 constructs a service report of the service flow according to the real-time node data type and a preset service parameter, the node association calculation module is specifically configured to:
encapsulating the real-time node data of the business process according to the real-time node data type to obtain a report header field;
Determining a service field according to the service parameter;
and packaging the report header field and the service field into a service report of the service flow.
In detail, the real-time node data is subjected to data encapsulation according to the real-time node data type to obtain a data packet in the real-time node data, a business process stage corresponding to the data packet is used as a header field of a business report, if the real-time node data is purchasing data, the purchasing data is respectively encapsulated according to the node data type, finally the purchasing data is encapsulated into a data packet of the real-time node data, and a purchasing stage to which the data packet belongs is used as a report header field, wherein the report header field is a business process stage node and comprises a purchasing stage, a production stage, a stock stage and a sales stage.
Specifically, service control, credit control, other control, available quantity control and price control in the service parameters are used as service fields, the overall service usage of the service report is determined according to the report header fields, specific data details of each service stage are determined according to the service fields, the report header fields and the service fields are further packaged into service reports of service flows, and service data generated in each flow stage in the service flows are further added into the corresponding service report.
Further, in order to realize data interconnection and interworking between related services, the requirement information needs to be grasped, and each process stage in the service process needs to be associated, so that the degree of data association of each process stage needs to be analyzed.
In the embodiment of the invention, the ERP (Enterprise Resource Planning ) node divides a supply chain system module in the original ERP into a plurality of sub-module nodes according to the business flow and function division of a target enterprise supply chain, and the ERP nodes comprise a purchasing node, a production node, a sales node, an inventory node, a product development node and the like.
In the embodiment of the present invention, when the node association degree calculation module 102 generates the ERP node corresponding to the target enterprise supply chain according to the business report, the node association degree calculation module is specifically configured to:
determining an ERP node type according to the report type of the business report;
and generating ERP nodes corresponding to the target enterprise supply chain according to the ERP node types and preset initial blank nodes.
In detail, the report type of the business report refers to the type of the header field of the report, including purchasing, production, selling, inventory and product development, and the report type is taken as the node type of the ERP node, and the ERP node type includes purchasing, producing, selling, inventory and product development, so that the preset blank node is taken as the ERP node corresponding to the target enterprise supply chain according to the ERP node type.
Furthermore, the cooperation of ERP and supply chain management requires the core enterprise on the supply chain to play an important role, ERP nodes are designed according to the characteristics of the enterprise, and data interconnection and interworking among related businesses are realized, so that the competitiveness of the supply chain is improved, and therefore, the degree of association among different ERP nodes needs to be calculated, and the data interconnection and interworking are realized.
In the embodiment of the invention, the association degree refers to the association relationship between each ERP node, such as the association between a purchasing node and a production node, and the association between the production node and a sales node.
In the embodiment of the present invention, when the node association degree calculation module 102 calculates the association degree between the ERP nodes by using a preset iterative association degree algorithm, the node association degree calculation module is specifically configured to:
determining node association relations among the ERP nodes according to the business flow;
calculating node association factors of the ERP nodes according to the node association relations, wherein the node association factor calculation formula is as follows:
wherein ,mij Is the node association factor between ERP node i and ERP node j, beta ij The method comprises the steps of obtaining node association coefficients corresponding to node association relations between ERP nodes i and ERP nodes j, wherein n is the node number of the ERP nodes;
Calculating the relevance between the ERP nodes according to the node relevance factors by using an iterative relevance algorithm as follows:
wherein ,pij For the association degree between the ERP node i and the ERP node j, n is the node number of the ERP node, d is the iterative optimization coefficient, m ij For the node association factor, p, between ERP node i and ERP node j ik The association degree between the ERP node i and the ERP node k is obtained.
In detail, the node association relationship includes a direct association and an indirect association, and when the business process is purchase-product development-production-inventory-sales, the purchase and product development are directly associated, the product development and production are directly associated, and the purchase and production are indirectly associated, and the production and sales are indirectly associated. And then, a preset analytic hierarchy process is utilized to carry out index self-definition according to the node association relationship to determine the node association coefficient, the node association relationship is a direct association relationship, and the node association coefficient is larger; the node association relationship is an indirect association relationship, so that the node association coefficient is smaller, the node association factor of the ERP node is determined according to the node association relationship, and the ERP node association degree is determined according to the node association factor.
Specifically, according to the iterative optimization coefficient d in the iterative relevance algorithm, the next ERP node relevance calculation cannot be performed when the iterative initial value is zero, so that the node relevance cannot be accurately calculated, the iterative optimization coefficient is required to push the calculation of the relevance, the relevance between the initial ERP nodes is determined according to the node relevance factor, and the relevance between the ERP nodes is more accurately calculated according to the iterative relevance algorithm.
Further, the ERP nodes are associated according to the association degree to generate an ERP model, integration of supplier information and an upstream supplier is achieved through the ERP model, the supply information is mastered, information sharing of data is guaranteed, the enterprise is helped to adjust supply and demand balance, and maximum benefits of the enterprise are achieved.
The business report monitoring module 103 is configured to generate an ERP model according to the association degree and the business report, and monitor the business report in real time according to a preset business requirement by using the ERP model to obtain real-time business report data.
In the embodiment of the invention, the ERP model is formed by associating all ERP nodes through the association degree and the business report corresponding to each ERP node, so that the data generated by a supply chain can be conveniently and quickly stored and queried.
In the embodiment of the present invention, when the business report monitoring module 103 generates an ERP model according to the association degree and the business report, the business report monitoring module is specifically configured to:
generating an ERP business process according to the association degree;
adding the business report to an ERP node corresponding to the ERP business flow according to a preset business type to obtain an ERP business node template;
And combining the ERP service node templates according to the ERP service flow to obtain the ERP model.
In detail, the ERP business process is formed according to the association degree between ERP nodes, if the association degree between the purchasing node and the product development node is 0.8, a direct business data stream is arranged between the purchasing node and the product development node, and if the association degree between the purchasing node and the production node is 0.6, an indirect business data stream is arranged between the purchasing node and the production node through the product development node, and then the ERP business process is determined according to the association degree between each ERP node.
Specifically, if the service type is the service node type corresponding to the ERP node, if the service type of the service report is purchasing, the service report is added into the corresponding ERP node in the ERP service flow, so as to obtain an ERP service node template, and the ERP service node templates are combined in the service flow according to the ERP service flow, so that an ERP model is obtained.
Furthermore, the convenient and quick data storage and data query can be performed according to the ERP model, so that the data generated by the supply chain can be monitored in real time according to the ERP model, the supply chain can be adjusted in time, and the competitiveness of the supply chain is improved.
In the embodiment of the invention, the real-time business report data is obtained by monitoring the business report in real time, and the data in the business report is increased or reduced, for example, the obtained real-time business report data is obtained by monitoring the purchased business report in real time.
In the embodiment of the present invention, when the business report monitoring module 103 monitors the business report in real time according to a preset business requirement by using the ERP model, the business report monitoring module is specifically configured to:
extracting service demand data in the service demand;
monitoring the business demand data by utilizing ERP business data in the ERP model to obtain a data monitoring value, wherein the calculation formula of the data monitoring value is as follows:
E k ＝α k ×(A-B k )
wherein ,Ek Data monitoring value alpha for kth ERP business data k A data monitoring factor for kth ERP business data, A is a quantized value of the business demand data, B k A quantized value of kth ERP business data;
and selecting the minimum ERP business data in the data monitoring value as the real-time business report data.
In detail, the business requirement refers to the business requirement of the manufacturer or the supplier for generating or selling the products, the business requirement data refers to the specific number of the products in the business requirement, and if the business requirement is that the number of the produced products A is 50, the business requirement data refers to the number of the products in the production stage 50.
Specifically, the data monitoring comparison is performed on the service demand data by utilizing the ERP data originally stored in the ERP model to obtain a data monitoring value, wherein the data monitoring value refers to determining one ERP service data consistent with the service demand data in the ERP node in the ERP model in the current service demand according to the service demand, namely, the service demand data are compared one by one, and a negative value of a data quantization value is prevented by a data monitoring factor, when the comparison value is a negative value, the data monitoring factor takes a value of 0, and when the comparison value is a positive value, the data monitoring factor takes a value of 1.
For example, when the quantized purchasing requirement value of the service requirement data is a and the ERP service data in each ERP node in the ERP model is B, C, D, comparing a with B, C, D, and obtaining that the service data of a and B are closest through calculation, taking the ERP service data corresponding to B as the real-time service report data corresponding to the current service requirement.
Further, in order to improve the competitiveness of the target enterprise supply chain, it is necessary to evaluate the data of the products in the supply chain, so that the supply chain can be optimized, and the competitiveness of the supply chain is improved.
The enterprise supply chain optimization module 104 is configured to perform value evaluation on the real-time business report data through a pre-constructed supply chain evaluation model to obtain a business report evaluation value, and optimize the target enterprise supply chain according to the business report evaluation value to obtain a target optimized enterprise supply chain.
In the embodiment of the invention, the service report evaluation value refers to an evaluation value of real-time service report data obtained after real-time monitoring of data generated by a supply chain, and further the supply chain can be optimized according to the evaluation value so as to improve the competitiveness of the supply chain.
In the embodiment of the present invention, before the value evaluation is performed on the real-time business report data by using the pre-constructed supply chain evaluation model, the enterprise supply chain optimization module 104 is specifically configured to:
acquiring a service data factor, and determining a service index according to the service data factor;
determining model parameters according to the business indexes, and constructing a supply chain evaluation model equation through the model parameters, wherein the supply chain evaluation equation is as follows:
wherein ,for the supply chain evaluation value, γ is the first regression coefficient, β is the second regression coefficient, a is the extrinsic latent variable in the model parameter, b is the intrinsic latent variable in the model parameter, ρ is the model error;
The supply chain evaluation model equation is determined as the supply chain evaluation model.
In detail, the supply chain evaluation model represents the impact value of the business report data on the overall operation of the supply chain, and the overall evaluation of the data generated in the supply chain is obtained. The business data factors refer to influence factors on the whole shadow operation of the supply chain, including quantity influence factors of product data, efficiency influence factors of product production, sales influence factors of product sales data and the like, and the business indexes refer to influence degrees corresponding to each business data factor in the supply chain flow to determine business indexes, and influence factors in the business indexes are used as model parameters in a supply chain evaluation model, wherein the business data factors can be determined through the business flow of the supply chain.
Specifically, an equation of a supply chain evaluation model is built through model parameters, and the equation of the supply chain evaluation model is used as the supply chain evaluation model to evaluate the value of the real-time business report data. The first regression coefficient gamma in the supply chain evaluation equation is a parameter of the influence magnitude of an external potential variable in the model parameters and a parameter of the influence magnitude of an internal potential variable in the model parameters when the second regression coefficient beta is used, the external potential variable is the potential influence of an external client on the change amount of the product demand, the internal potential variable is the data of an enterprise in each flow node of the supply chain, namely, all the data in the supply chain are called internal potential variables, the model error is the parameter for correcting the model, and the model error can be set in a self-defining way when the effect of the model is the best.
Further, the value evaluation is carried out on the real-time business report data according to the supply chain evaluation model so as to evaluate the generated data in the supply chain, and the supply chain can be optimized in time.
In the embodiment of the present invention, when the enterprise supply chain optimization module 104 performs value evaluation on the real-time service report data through a pre-constructed supply chain evaluation model, the method is specifically used for:
extracting service report indexes in the real-time service report;
performing factor division on the service report indexes to obtain service report exogenous parameters and service report endogenous parameters;
and carrying out value evaluation on the real-time business report data by utilizing the supply chain evaluation model to obtain a business report evaluation value.
In detail, the data in the real-time business report is analyzed, the data in the business report index is divided according to the data, the external real-time business requirement is used as a business report exogenous parameter, the data in the supply chain is used as a business report endogenous parameter, and the business report exogenous parameter a and the business report endogenous parameter b are input into a supply chain evaluation model equation, so that a business report evaluation value is obtained.
Further, the supply chain is optimized according to the business report evaluation value, so that the supply chain is evaluated again, and the competitiveness of the supply chain is improved.
In the embodiment of the invention, the target optimization enterprise supply chain optimizes the data of the original enterprise supply chain on the basis of the original enterprise supply chain, so as to obtain the target enterprise optimization supply chain.
In the embodiment of the present invention, when the enterprise supply chain optimization module 104 optimizes the target enterprise supply chain according to the business report evaluation value to obtain a target optimized enterprise supply chain, the method is specifically used for:
when the service report evaluation value is smaller than a preset evaluation threshold value, extracting service node data corresponding to the service report evaluation value;
calculating the data optimization value of the service node data by using the following optimization value calculation formula;
wherein Y is the data optimization value, tau is an optimization factor, X is actual service data in the service node data, S is real-time service demand data, and Z is demand service data in the service node data;
optimizing the service node data according to the data optimization value to obtain optimized node data;
And adding the optimized node data into the ERP node corresponding to the target enterprise supply chain to obtain an optimized ERP node, and updating the optimized ERP node into the target enterprise supply chain to obtain a target optimized enterprise supply chain.
In detail, when the evaluation value of the service report is smaller than a preset evaluation threshold, the service node data in the supply chain is extracted, and then the service node data and the service demand data are compared according to the service node data, so that a required data optimization value is obtained, the optimization factor τ in the optimization value calculation formula is a factor for supplementing the service data when the actual service data and the real-time service demand data do not meet the demand service data, and the optimization factor can be self-defined to take a value of 0 when the service data optimization is not required.
Specifically, business node data is increased or decreased according to the data optimization value to obtain optimized node data, the optimized node data is further added to ERP nodes corresponding to a target enterprise supply chain to be optimized, and the original ERP nodes are updated by the optimized ERP nodes to obtain the target optimized enterprise supply chain.
Further, real-time monitoring is performed on real-time business data in the target optimization enterprise supply chain, so that the enterprise supply chain can be timely adjusted, enterprise resource strategies are generated, and the supply chain competitiveness is improved.
The enterprise resource adjustment policy generation module 105 is configured to monitor real-time data in the target optimization enterprise supply chain in real time according to the service requirement by using the ERP model, obtain supply chain optimization data, and generate an enterprise resource adjustment policy according to the supply chain optimization data.
In the embodiment of the invention, the supply chain optimization data refers to adding or reducing product data in the supply chain in time according to some business requirements so as to improve the benefit maximization of the supply chain, and further carrying out real-time monitoring on the optimized data of the product in the supply chain through an ERP model so as to obtain the monitored supply chain optimization data.
In detail, the step of performing real-time monitoring on the real-time data in the target optimization enterprise supply chain by using the ERP model according to the service requirement is consistent with the step of performing real-time monitoring on the service report by using the ERP model in the service report monitoring module 103 according to the preset service requirement to obtain the real-time service report data, which is not described herein again. And updating the business report to real-time data, and further monitoring the real-time data in real time to obtain supply chain optimization data.
Further, the allocation of enterprise resources can be adjusted according to the supply chain optimization data, so that the reasonable utilization of the resources is improved, and the enterprise benefit is maximized.
In the embodiment of the invention, the enterprise resource adjustment policy refers to a resource utilization policy for an enterprise to adjust enterprise product resources according to purchasing data, production data or inventory data in supply chain optimization data.
In the embodiment of the present invention, when the enterprise resource adjustment policy generation module 105 generates the enterprise resource adjustment policy according to the supply chain optimization data, the enterprise resource adjustment policy generation module is specifically configured to:
acquiring initial enterprise resources, and optimizing the initial enterprise resources according to the supply chain optimization data to obtain optimized enterprise resources;
and generating an enterprise resource adjustment strategy according to the optimized enterprise resource and the preset business resource requirement.
In detail, the initial enterprise resource refers to an initial product resource requirement determined by an enterprise according to a product production requirement, but there may be new service requirements in a product production process, and the product quantity may be increased or decreased, so that supply chain optimization data may be obtained, and further supply chain data in the initial enterprise resource is optimized according to the supply chain optimization data to obtain an optimized enterprise resource, and the enterprise resource is readjusted according to the optimized enterprise resource and a current preset service resource requirement to obtain an enterprise resource adjustment policy.
For example, when the initial enterprise resources are 100 products, and in the process of product production, 50 products need to be added by a customer, the business process data of the supply chain need to be optimized, the procurement data need to be readjusted, the supply chain optimizing data are 50 purchasing data, 50 production data are added at the moment, and then the product production requirements in the initial enterprise resources are optimized, the product production requirements are 150 at the moment, so as to obtain optimized enterprise resources, and then an enterprise resource adjusting strategy is generated according to the optimized enterprise resources and the real-time business resource requirements, wherein the enterprise resource adjusting strategy is 150 products production requirements at the moment.
According to the method and the device, the business report is built through the business process of the enterprise supply chain, ERP nodes are generated according to the business report, and the association degree between the ERP nodes is calculated, so that an ERP model is built, the combination of the supply chain and the ERP model is realized, the maximization of the benefit of the supply chain is realized, and meanwhile, the benefit distribution of the enterprise on the supply chain can be balanced; real-time monitoring is carried out on data in a supply chain by utilizing an ERP model to obtain supply chain optimization data, and then the original supply chain is optimized according to the supply chain optimization data to obtain an optimized supply chain, so that the competitiveness of the supply chain is improved; the data of the optimized supply chain is monitored in real time, and an enterprise resource adjustment strategy is generated according to the optimized data in the optimized supply chain, so that the product supply and demand balance can be adjusted timely. Therefore, the ERP-based enterprise supply chain analysis system, method and equipment provided by the invention can solve the problem of lower accuracy when an enterprise performs supply chain resource analysis.
Referring to fig. 2, a flow chart of an operation method of an ERP-based enterprise supply chain analysis system according to an embodiment of the present invention is shown. In this embodiment, the method for operating the ERP-based enterprise supply chain analysis system includes:
s1, acquiring a business process of a target enterprise supply chain, extracting real-time node data of a supply chain node in the business process, and dividing the real-time node data into data types by a preset data attribute to obtain real-time node data types;
s2, constructing a business report of the business process according to the real-time node data type and preset business parameters, generating ERP nodes corresponding to the target enterprise supply chain according to the business report, and calculating the association degree between the ERP nodes by using a preset iterative association degree algorithm;
s3, generating an ERP model according to the association degree and the business report, and monitoring the business report in real time by utilizing the ERP model according to preset business requirements to obtain real-time business report data;
s4, performing value evaluation on the real-time business report data through a pre-constructed supply chain evaluation model to obtain a business report evaluation value, and optimizing the target enterprise supply chain according to the business report evaluation value to obtain a target optimized enterprise supply chain;
And S5, real-time monitoring is carried out on the real-time data in the target optimization enterprise supply chain according to the business requirements by utilizing the ERP model, supply chain optimization data are obtained, and enterprise resource adjustment strategies are generated according to the supply chain optimization data.
Fig. 3 is a schematic structural diagram of an electronic device implementing an operation method of an ERP-based enterprise supply chain analysis system according to an embodiment of the present invention.
The electronic device may include a processor 10, a memory 11, a communication bus 12, and a communication interface 13, and may also include computer programs stored in the memory 11 and executable on the processor 10, such as ERP-based enterprise supply chain analysis system programs.
The processor 10 may be formed by an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be formed by a plurality of integrated circuits packaged with the same function or different functions, including one or more central processing units (Central Processing Unit, CPU), a microprocessor, a digital processing chip, a graphics processor, a combination of various control chips, and so on. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various components of the entire electronic device using various interfaces and lines, executes or executes programs or modules stored in the memory 11 (e.g., executes ERP-based enterprise supply chain analysis method programs, etc.), and invokes data stored in the memory 11 to perform various functions of the electronic device and process data.
The memory 11 includes at least one type of readable storage medium including flash memory, a removable hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device, such as a mobile hard disk of the electronic device. The memory 11 may in other embodiments also be an external storage device of the electronic device, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the electronic device. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device. The memory 11 may be used to store not only application software installed in an electronic device and various types of data, such as code of an ERP-based enterprise supply chain analysis system program, but also temporarily store data that has been output or is to be output.
The communication bus 12 may be a peripheral component interconnect standard (Peripheral Component Interconnect, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. The bus is arranged to enable a connection communication between the memory 11 and at least one processor 10 etc.
The communication interface 13 is used for communication between the electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), typically used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a Display (Display), an input unit such as a Keyboard (Keyboard), or alternatively a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the electronic device and for displaying a visual user interface.
Fig. 3 shows only an electronic device with components, and it will be understood by those skilled in the art that the structure shown in fig. 3 is not limiting of the electronic device and may include fewer or more components than shown, or may combine certain components, or a different arrangement of components.
For example, although not shown, the electronic device may further include a power source (such as a battery) for supplying power to the respective components, and preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management, and the like are implemented through the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The electronic device may further include various sensors, bluetooth modules, wi-Fi modules, etc., which are not described herein.
It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.
The ERP-based enterprise supply chain analysis system program stored by the memory 11 in the electronic device is a combination of instructions that, when executed in the processor 10, may implement:
acquiring a business process of a target enterprise supply chain, extracting real-time node data of a supply chain node in the business process, and dividing the real-time node data into data types through preset data attributes to obtain real-time node data types;
Constructing a business report of the business process according to the real-time node data type and preset business parameters, generating ERP nodes corresponding to the target enterprise supply chain according to the business report, and calculating the association degree between the ERP nodes by using a preset iterative association degree algorithm;
generating an ERP model according to the association degree and the business report, and carrying out real-time monitoring on the business report by utilizing the ERP model according to preset business requirements to obtain real-time business report data;
performing value evaluation on the real-time business report data through a pre-constructed supply chain evaluation model to obtain a business report evaluation value, and optimizing the target enterprise supply chain according to the business report evaluation value to obtain a target optimized enterprise supply chain;
and real-time monitoring is carried out on real-time data in the target optimization enterprise supply chain according to the business requirements by utilizing the ERP model, supply chain optimization data are obtained, and enterprise resource adjustment strategies are generated according to the supply chain optimization data.
In particular, the specific implementation method of the above instructions by the processor 10 may refer to the description of the relevant steps in the corresponding embodiment of the drawings, which is not repeated herein.
Further, the electronic device integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM).
In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus, system and method may be implemented in other manners. For example, the system embodiments described above are merely illustrative, e.g., the division of the modules is merely a logical function division, and other manners of division may be implemented in practice.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. Multiple units or systems as set forth in the system claims may also be implemented by means of one unit or system in software or hardware. The terms first, second, etc. are used to denote a name, but not any particular order.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.

Claims (10)

1. An ERP-based enterprise supply chain analysis system is characterized by comprising a data type dividing module, a relevance calculating module, a business report monitoring module, an enterprise supply chain optimizing module and an enterprise resource adjusting strategy generating module, wherein,
the data type dividing module is used for acquiring a business process of a target enterprise supply chain, extracting real-time node data of a supply chain node in the business process, and dividing the data types of the real-time node data through preset data attributes to obtain real-time node data types;
the node association degree calculation module is used for constructing a business report of the business process according to the real-time node data type and preset business parameters, generating ERP nodes corresponding to the target enterprise supply chain according to the business report, and calculating association degrees among the ERP nodes by using a preset iterative association degree algorithm;
The business report monitoring module is used for generating an ERP model according to the association degree and the business report, and real-time monitoring the business report according to preset business requirements by utilizing the ERP model to obtain real-time business report data;
the enterprise supply chain optimizing module is configured to perform value evaluation on the real-time business report data through a pre-constructed supply chain evaluation model to obtain a business report evaluation value, optimize the target enterprise supply chain according to the business report evaluation value to obtain a target optimized enterprise supply chain, where the optimizing the target enterprise supply chain according to the business report evaluation value is specifically configured to, when obtaining the target optimized enterprise supply chain:
when the service report evaluation value is smaller than a preset evaluation threshold value, extracting service node data corresponding to the service report evaluation value;
calculating the data optimization value of the service node data by using the following optimization value calculation formula;
wherein Y is the data optimization value, tau is an optimization factor, X is actual service data in the service node data, S is real-time service demand data, and Z is demand service data in the service node data;
Optimizing the service node data according to the data optimization value to obtain optimized node data;
adding the optimized node data into ERP nodes corresponding to the target enterprise supply chain to obtain optimized ERP nodes, and updating the optimized ERP nodes into the target enterprise supply chain to obtain a target optimized enterprise supply chain;
the enterprise resource adjustment strategy generation module is used for monitoring real-time data in the target optimization enterprise supply chain according to the business requirements by utilizing the ERP model to obtain supply chain optimization data, and generating an enterprise resource adjustment strategy according to the supply chain optimization data.
2. The ERP-based enterprise supply chain analysis system of claim 1, wherein the data type classification module is specifically configured to, when performing data type classification on the real-time node data by using a preset data attribute to obtain a real-time node data type:
generating a data type table according to the data attribute;
classifying the data attribute of the real-time node data to obtain the real-time node data attribute;
and adding the real-time node data into the data type table according to the real-time node data attribute to obtain a real-time node data type.
3. The ERP-based enterprise supply chain analysis system of claim 1, wherein the node association calculation module is specifically configured to, when constructing a business report of the business process according to the real-time node data type and a preset business parameter:
encapsulating the real-time node data of the business process according to the real-time node data type to obtain a report header field;
determining a service field according to the service parameter;
and packaging the report header field and the service field into a service report of the service flow.
4. The ERP-based enterprise supply chain analysis system of claim 1, wherein the node relevance calculation module is configured to, when calculating the relevance between the ERP nodes using a preset iterative relevance algorithm:
determining node association relations among the ERP nodes according to the business flow;
calculating node association factors of the ERP nodes according to the node association relations, wherein the node association factor calculation formula is as follows:
wherein ,mij Is the node association factor between ERP node i and ERP node j, beta ij The method comprises the steps of obtaining node association coefficients corresponding to node association relations between ERP nodes i and ERP nodes j, wherein n is the node number of the ERP nodes;
Calculating the relevance between the ERP nodes according to the node relevance factors by using an iterative relevance algorithm as follows:
wherein ,pij For the association degree between the ERP node i and the ERP node j, n is the node number of the ERP node, d is the iterative optimization coefficient, m ij For the node association factor, p, between ERP node i and ERP node j ik The association degree between the ERP node i and the ERP node k is obtained.
5. The ERP-based enterprise supply chain analysis system of claim 1, wherein the business report monitoring module is configured to, when generating an ERP model according to the association degree and the business report:
generating an ERP business process according to the association degree;
adding the business report to an ERP node corresponding to the ERP business flow according to a preset business type to obtain an ERP business node template;
and combining the ERP service node templates according to the ERP service flow to obtain the ERP model.
6. The ERP-based enterprise supply chain analysis system of claim 1, wherein the business report monitoring module is configured to, when using the ERP model to monitor the business report in real time according to a preset business requirement, obtain real-time business report data, specifically:
Extracting service demand data in the service demand;
monitoring the business demand data by utilizing ERP business data in the ERP model to obtain a data monitoring value, wherein the calculation formula of the data monitoring value is as follows:
E k ＝α k ×(A-B k )
wherein ,Ek Data monitoring value alpha for kth ERP business data k A data monitoring factor for kth ERP business data, A is a quantized value of the business demand data, B k A quantized value of kth ERP business data;
and selecting the minimum ERP business data in the data monitoring value as the real-time business report data.
7. The ERP-based enterprise supply chain analysis system of claim 1, wherein the enterprise supply chain optimization module is configured to, prior to performing value evaluation on the real-time business report data by using a pre-constructed supply chain evaluation model, obtain a business report evaluation value:
acquiring a service data factor, and determining a service index according to the service data factor;
determining model parameters according to the business indexes, and constructing a supply chain evaluation model equation through the model parameters, wherein the supply chain evaluation equation is as follows:
wherein ,for the supply chain evaluation value, γ is the first regression coefficient, β is the second regression coefficient, a is the extrinsic latent variable in the model parameter, b is the intrinsic latent variable in the model parameter, ρ is the model error;
The supply chain evaluation model equation is determined as the supply chain evaluation model.
8. The ERP-based enterprise supply chain analysis system of claim 1, wherein the enterprise resource adjustment policy generation module, when generating an enterprise resource adjustment policy from the supply chain optimization data, is specifically configured to:
acquiring initial enterprise resources, and optimizing the initial enterprise resources according to the supply chain optimization data to obtain optimized enterprise resources;
and generating an enterprise resource adjustment strategy according to the optimized enterprise resource and the preset business resource requirement.
9. An operation method of an enterprise supply chain analysis system based on ERP is characterized in that the method is suitable for the enterprise supply chain analysis system based on ERP, the system comprises a data type dividing module, a relevance calculating module, a business report monitoring module, an enterprise supply chain optimizing module and an enterprise resource adjustment strategy generating module, and the method comprises the following steps:
acquiring a business process of a target enterprise supply chain, extracting real-time node data of a supply chain node in the business process, and dividing the real-time node data into data types through preset data attributes to obtain real-time node data types;
Constructing a business report of the business process according to the real-time node data type and preset business parameters, generating ERP nodes corresponding to the target enterprise supply chain according to the business report, and calculating the association degree between the ERP nodes by using a preset iterative association degree algorithm;
generating an ERP model according to the association degree and the business report, and carrying out real-time monitoring on the business report by utilizing the ERP model according to preset business requirements to obtain real-time business report data;
performing value evaluation on the real-time business report data through a pre-constructed supply chain evaluation model to obtain a business report evaluation value, and optimizing the target enterprise supply chain according to the business report evaluation value to obtain a target optimized enterprise supply chain;
and real-time monitoring is carried out on real-time data in the target optimization enterprise supply chain according to the business requirements by utilizing the ERP model, supply chain optimization data are obtained, and enterprise resource adjustment strategies are generated according to the supply chain optimization data.
10. An electronic device, the electronic device comprising:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,
The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of operating the ERP-based enterprise supply chain analysis system of claim 9.
CN202310623294.2A 2023-05-29 2023-05-29 Enterprise supply chain analysis system, method and equipment based on ERP Withdrawn CN116562588A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117495019A (en) * 2023-11-14 2024-02-02 扬州市职业大学(扬州开放大学) Agricultural product cooperative scheduling method and system based on agricultural product supply chain

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117495019A (en) * 2023-11-14 2024-02-02 扬州市职业大学(扬州开放大学) Agricultural product cooperative scheduling method and system based on agricultural product supply chain

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