Order adjustment management method and system based on rule request

Abstract

The invention provides an order adjustment management method and system based on a rule request, and relates to the field of order management, and the method comprises the steps: obtaining first new order information according to real-time material order information; judging whether the first newly-added order information has a first trigger identification feature or not, inputting the first newly-added order information into a transaction quantification level analysis model when the first newly-added order information has the first trigger identification feature to obtain a first quantification level, and analyzing the first quantification level according to a request generation rule to obtain a first priority adjustment request; when the rule module receives the first priority adjustment request, first decision output information is obtained according to an order adjustment decision rule, and a first adjustment instruction is generated; and according to the first adjustment instruction, carrying out sequence adjustment on the first newly-added order. The technical problems that in the prior art, the intelligent level of arrangement and adjustment of newly-added material orders is not high, order management flexibility is poor, order adjustment is not timely, and order processing efficiency is low are solved.

Description

Technical Field

[0001] The present invention relates to the field of order management, and in particular to an order adjustment management method and system based on rule requests. Background Art

[0002] Materials are the material basis for all human production and life, and new materials are the cornerstone of the development of emerging industries. As my country's research and development capabilities and production capabilities for new materials continue to improve, and there are also strong downstream application industries, it has provided a huge impetus for the development of my country's materials industry. This has led to a surge in orders for material processing companies. The current order management system can improve the efficiency of logistics operations by managing and tracking orders placed by customers and dynamically grasping the progress and completion of orders. However, it has little effect on improving the efficiency of material production and processing and alleviating order pressure.

[0003] However, the inventors of this application found that the above technology has at least the following technical problems in the process of implementing the technical solution of the invention in the embodiment of this application:

[0004] The existing technology has technical problems such as low intelligence level in arranging and adjusting new material orders, poor flexibility in order management, untimely order adjustments, and low order processing efficiency. Summary of the invention

[0005] The embodiment of the present application provides an order adjustment management method and system based on rule requests, which solves the technical problems of the prior art in that the arrangement and adjustment of new material orders is not intelligent, the order management flexibility is poor, the order adjustment is not timely, and the order processing efficiency is low. The technical effect of digitizing and quantifying order information by establishing mathematical logic rules, exchanging the priority order of new orders in a reasonable order, optimizing the order management process, improving the intelligence of order adjustment, and enhancing management flexibility, thereby improving the efficiency of order processing, is achieved.

[0006] In view of the above problems, an embodiment of the present application provides an order adjustment management method and system based on rule requests.

[0007] In a first aspect, an embodiment of the present application provides an order adjustment management method based on rule requests, wherein the method comprises: obtaining first newly added order information based on real-time material order information; determining whether the first newly added order information has a first trigger identification feature, wherein the first trigger identification feature is a feature that triggers order sequence replacement; when the first newly added order information has the first trigger identification feature, inputting the first newly added order information into a transaction quantitative level analysis model for transaction quantitative level analysis to obtain a first quantitative level; analyzing the first quantitative level according to a request generation rule to obtain a first priority adjustment request; when the rule module receives the first priority adjustment request, obtaining first decision output information according to the order adjustment decision rule in the rule module; generating a first adjustment instruction based on the first decision output information; and performing sequence adjustment on the first newly added order according to the first adjustment instruction.

[0008] On the other hand, an embodiment of the present application provides an order adjustment management system based on rule requests, wherein the system includes: an order information acquisition unit, the order information acquisition unit is used to obtain first newly added order information according to real-time material order information; a trigger identification judgment unit, the trigger identification judgment unit is used to judge whether the first newly added order information has a first trigger identification feature, wherein the first trigger identification feature is a feature that triggers the order exchange; a quantitative level analysis unit, the quantitative level analysis unit is used to input the first newly added order information into a transaction quantitative level analysis model to perform transaction quantitative level analysis when the first newly added order information has the first trigger identification feature, and obtain a first quantitative level; a priority adjustment unit, the priority adjustment unit is used to analyze the first quantitative level according to a request generation rule to obtain a first priority adjustment request; a decision output unit, the decision output unit is used to obtain first decision output information according to the order adjustment decision rule in the rule module when the rule module receives the first priority adjustment request; an adjustment instruction generation unit, the adjustment instruction generation unit is used to generate a first adjustment instruction according to the first decision output information; an order adjustment unit, the order adjustment unit is used to adjust the order of the first newly added order according to the first adjustment instruction.

[0009] In a third aspect, an embodiment of the present application provides an order adjustment management system based on rule requests, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any one of the methods described in the first aspect when executing the program.

[0010] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0011] Due to the adoption of obtaining the first newly added order information according to the real-time material order information; judging whether the first newly added order information has the first trigger identification feature, wherein the first trigger identification feature is a feature that triggers the order exchange; when the first newly added order information has the first trigger identification feature, inputting the first newly added order information into the transaction quantitative level analysis model for transaction quantitative level analysis to obtain the first quantitative level; analyzing the first quantitative level according to the request generation rule to obtain the first priority adjustment request; when the rule module receives the first priority adjustment request, obtaining the first decision output information according to the order adjustment decision rule in the rule module; generating the first adjustment instruction according to the first decision output information; and adjusting the order of the first newly added order according to the first adjustment instruction, the embodiment of the present application provides an order adjustment management method and system based on rule requests, which solves the technical problems of the prior art that the arrangement and adjustment of the newly added material orders are not intelligent at a high level, the order management flexibility is poor, the order adjustment is not timely, and the order processing efficiency is low. The technical effect of digitizing and quantifying the order information by establishing mathematical logic rules, exchanging the priority order of the newly added orders in a reasonable order, optimizing the order management process, improving the intelligence of order adjustment, and enhancing the management flexibility, thereby improving the efficiency of order processing, is achieved.

[0012] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 A flowchart of an order adjustment management method based on rule requests according to an embodiment of the present application;

[0014] Figure 2 A schematic diagram of a process of performing transaction quantitative level analysis in an order adjustment management method based on rule requests according to an embodiment of the present application;

[0015] Figure 3 A schematic diagram of a flow chart of constructing a request generation rule of an order adjustment management method based on a rule request according to an embodiment of the present application;

[0016] Figure 4 A flowchart of a line order cycle analysis of an order adjustment management method based on rule requests according to an embodiment of the present application;

[0017] Figure 5 A schematic diagram of a flow chart of first decision output information of a rule module of an order adjustment management method based on rule request according to an embodiment of the present application;

[0018] Figure 6 A schematic diagram of a flow chart of obtaining order adjustment failure information of an order adjustment management method based on rule request according to an embodiment of the present application;

[0019] Figure 7 A schematic diagram of a flow chart of order material category analysis of an order adjustment management method based on rule requests according to an embodiment of the present application;

[0020] Figure 8 This is a structural diagram of an order adjustment management system based on rule requests according to an embodiment of the present application;

[0021] Fig. 9 It is a schematic diagram of the structure of an exemplary electronic device according to an embodiment of the present application.

[0022] Explanation of the accompanying drawings: order information acquisition unit 11, trigger identification and judgment unit 12, quantitative level analysis unit 13, priority adjustment unit 14, decision output unit 15, adjustment instruction generation unit 16, order adjustment unit 17, electronic device 300, memory 301, processor 302, communication interface 303, bus architecture 304. DETAILED DESCRIPTION

[0023] The embodiment of the present application provides an order adjustment management method and system based on rule requests, which solves the technical problems of the prior art in that the arrangement and adjustment of new material orders is not intelligent, the order management flexibility is poor, the order adjustment is not timely, and the order processing efficiency is low. The technical effect of digitizing and quantifying order information by establishing mathematical logic rules, exchanging the priority order of new orders in a reasonable order, optimizing the order management process, improving the intelligence of order adjustment, and enhancing management flexibility, thereby improving the efficiency of order processing, is achieved.

[0024] Application Overview

[0025] Materials are the material basis for all human production and life, and new materials are the cornerstone of the development of emerging industries. As my country's research and development capabilities and production capabilities for new materials continue to improve, and there are also strong downstream application industries, it has provided a huge impetus for the development of my country's materials industry. This has led to a surge in orders for material processing companies. The current order management system can improve the efficiency of logistics operations by managing and tracking orders placed by customers and dynamically grasping the progress and completion of orders. However, it has little effect on improving the efficiency of material production and processing and alleviating order pressure. The technical problems of the existing technology, such as the low level of intelligence in the arrangement and adjustment of new material orders, poor order management flexibility, untimely order adjustments, and low order processing efficiency, are solved.

[0026] In response to the above technical problems, the overall idea of ​​the technical solution provided by this application is as follows:

[0027] An embodiment of the present application provides an order adjustment management method based on rule requests, wherein the method includes: obtaining first newly added order information based on real-time material order information; determining whether the first newly added order information has a first trigger identification feature, wherein the first trigger identification feature is a feature that triggers order sequence replacement; when the first newly added order information has the first trigger identification feature, inputting the first newly added order information into a transaction quantitative grade analysis model for transaction quantitative grade analysis to obtain a first quantitative grade; analyzing the first quantitative grade according to a request generation rule to obtain a first priority adjustment request; when the rule module receives the first priority adjustment request, obtaining first decision output information according to the order adjustment decision rule in the rule module; generating a first adjustment instruction based on the first decision output information; and performing sequence adjustment on the first newly added order according to the first adjustment instruction.

[0028] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically described below in conjunction with the drawings in the specification.

[0029] Embodiment 1

[0030] like Figure 1 As shown, an embodiment of the present application provides an order adjustment management method based on rule requests, wherein the method is applied to an order adjustment management system based on rule requests, the system includes a rule module, and the method includes:

[0031] S100: Obtaining first newly added order information according to the real-time material order information;

[0032] Specifically, the order adjustment management system can collect material order information in real time, including order work status, order deadline, ordered material category, order quantity, order amount, delivery address and logistics distribution information, etc. The order work status includes processed orders, orders being processed and new orders. The first new order refers to any new order, and the order information such as the deadline, ordered material category, quantity and delivery address of the first new order can be obtained from the order adjustment management system. It can achieve the effect of timely processing of material orders and reducing omissions.

[0033] S200: Determine whether the first newly added order information has a first trigger identification feature, wherein the first trigger identification feature is a feature that triggers order sequence change;

[0034] S300: When the first newly added order information has the first trigger identification feature, the first newly added order information is input into a transaction quantitative grade analysis model to perform transaction quantitative grade analysis to obtain a first quantitative grade;

[0035] Specifically, the first newly added order information is analyzed to determine whether there are features that trigger the order sequence change, that is, the first trigger identification features, such as the large amount of new order tasks, the approaching delivery time, or the complex material production and long construction period of the new order, which can trigger the order adjustment. When the first newly added order information has the first trigger identification feature, the first newly added order information is input into the transaction quantitative grade analysis model to perform transaction quantitative grade analysis on the order. The transaction quantitative grade analysis model covers the historical transaction information and grade label data of the materials industry, and can perform grade analysis and grade matching after quantifying the input information. The higher the grade, the higher the importance and urgency of the order. The transaction quantitative grade analysis model can accurately perform quantitative grade analysis on the first newly added order information.

[0036] Further, such as Figure 2 As shown, when the first newly added order information has the first trigger identification feature, the first newly added order information is input into the transaction quantification level analysis model to perform transaction quantification level analysis to obtain a first quantification level, and step S300 includes:

[0037] S310: Obtain multiple transaction data according to the first newly added order information, wherein the multiple transaction data includes transaction amount data, transaction cycle data, and transaction material data;

[0038] S320: acquiring multiple quantitative indicators by performing quantitative data collection on the multiple transaction data;

[0039] S330: Obtaining a multi-mean quantitative index according to the real-time material order information;

[0040] S340: normalizing the multiple quantitative indicators and performing proportion calculation based on the multiple mean quantitative indicators to obtain a first proportion coefficient;

[0041] S350: Inputting the first proportion coefficient into the transaction quantitative grade analysis model to generate the first quantitative grade.

[0042] Specifically, in order to conduct transaction quantitative level analysis, multiple transaction data in the first newly added order information are analyzed, and the multiple transaction data include transaction amount data, transaction cycle data and transaction material data. Further, the profit of the newly added order, production delivery cycle, whether the raw materials are sufficient, and the complexity of the material production and processing technology are analyzed. Each type of data in the multiple transaction data is quantified through the transaction quantitative level analysis model, and quantitative data is collected. The transaction quantitative level analysis model is supervised and learned through multiple sets of training data until it is trained to a convergence state, which can ensure the accuracy of quantification and obtain multiple quantitative indicators. Quantitative indicators refer to indicators that can be reflected by specific data, and reflect the state of the subject with linearly transformed data within a certain range. Multi-quantitative indicators can use multiple quantitative data to reflect the order status of the first newly added order. The larger the multi-quantitative indicator, the more important the order is, and the corresponding production needs to be carried out as soon as possible.

[0043] According to the real-time material order information, a multi-mean quantitative index is obtained. The real-time material order information includes a large number of material order information of the enterprise. The quantitative data of different orders are averaged to obtain a multi-mean quantitative index, which reflects the average level of the enterprise's material orders. The multi-quantitative index is normalized, the index is dimensionless, and the data is mapped to the range of 0 to 1. The proportion is further calculated based on the multi-mean quantitative index to obtain a first proportion coefficient. The first quantitative level is determined according to the first proportion coefficient, and the first proportion coefficient is proportional to the first quantitative level. By quantifying the order information and performing calculations with the multi-mean quantitative index, the order information can be digitized and quantified, and the digitization and scientificity of order management can be realized.

[0044] S400: Analyze the first quantization level according to a request generation rule to obtain a first priority adjustment request;

[0045] Specifically, further, a request generation rule is formulated, and the request generation rule can analyze and evaluate the priority of each level in the first quantitative level, so as to obtain the first priority adjustment request according to the importance and priority, and make adjustment requests for the order of material orders according to the order level and request rules, thereby improving the scientific nature of the adjustment and achieving the effect of optimizing the order management process.

[0046] Further, such as Figure 3 As shown, before analyzing the first quantization level according to the request generation rule to obtain the first priority adjustment request, step S400 also includes:

[0047] S410: Determine a preset quantitative level by performing quantitative data threshold analysis on historical material order information;

[0048] S420: constructing a first mapping structure according to the preset quantization levels, wherein the preset quantization levels in the first mapping structure correspond one to one to preset priorities;

[0049] S430: Constructing the request generation rule according to the first mapping structure.

[0050] Specifically, the quantitative data of historical materials are analyzed, the threshold of the quantitative data is determined, the preset quantitative level is determined according to the threshold, and a first mapping structure is constructed to correspond the preset quantitative level to the preset priority one by one, and the level and priority are corresponded. The request generation rule is constructed according to the first mapping structure. The request rule covers the priority and quantitative level of historical materials. Since the historical data covers the material order completion rules and business data logic rules of the enterprise, the rule can be better applied to the new orders of the enterprise, so that the generated adjustment request has good accuracy and reliability.

[0051] S500: When the rule module receives the first priority adjustment request, first decision output information is obtained according to the order adjustment decision rule in the rule module;

[0052] Further, such as Figure 4 As shown, when the rule module receives the first priority adjustment request, first decision output information is obtained according to the order adjustment decision rule in the rule module, and step S500 further includes:

[0053] S510: Obtaining N period time nodes greater than or equal to a preset period by performing order cycle analysis on the real-time material order information;

[0054] S520: By performing real-time work efficiency calculation on the process flow of the material processing plant, M efficiency process nodes with a preset efficiency or less are obtained;

[0055] S530: Obtain a first adjustable node according to the N cycle time nodes and the M efficiency process nodes;

[0056] S540: Input the first adjustable node into the node matching block of the rule module for storage.

[0057] Specifically, the order cycle is analyzed, and the order cycle includes production, packaging, logistics distribution, and customer receipt. According to the analysis results of real-time material order information, a time period is preset, and N cycle time nodes greater than or equal to the preset period are obtained, and each time node corresponds to each workflow node for completing the order. In this way, sufficient time periods for the completion of new orders can be guaranteed. Further, the work efficiency of the material processing process of the material processing plant is calculated, and the comprehensive work efficiency of the machine and labor in each process is calculated. An average work efficiency is preset, and M efficiency process nodes less than or equal to the preset efficiency are obtained, so that new orders can be completed on time. According to the N cycle time nodes and the M efficiency process nodes, the first adjustable node is obtained, which is stored in the node matching block of the rule module, and the output result of the node matching block can be adjusted. Achieving an in-depth analysis of the order cycle, thereby comprehensively controlling the completion process of the enterprise's material orders and achieving the effect of optimizing the order management solution.

[0058] Further, such as Figure 5 As shown, the first adjustable node is input into the node matching block of the rule module for storage, and step S540 includes:

[0059] S541: Performing process demand analysis according to the first newly added order information to obtain n required cycle time nodes and m efficiency process nodes;

[0060] S542: Inputting the n cycle time nodes and the m efficiency process nodes into the node matching block for intersection matching to obtain a first matching result;

[0061] S543: Generate the first decision output information of the rule module according to the first matching result.

[0062] Specifically, the process demand analysis is performed on the first newly added order information, and similar processes are matched in the historical data to obtain n cycle time nodes and m efficiency process nodes of the demand. The n cycle time nodes and the m efficiency process nodes are input into the node matching block and the intersection matching operation is performed with the first adjustable node. The intersection node obtained is the first matching result, and the minimum work efficiency and time cycle required for the order are obtained. According to the matching result of the first newly added order, the first decision output information of the rule module is generated. The node matching block can summarize the completion rules of historical material orders and make reasonable predictions on the completion cycle of new orders, so as to achieve the technical effect of real-time supervision of the production cycle of material orders, reasonable evaluation of new orders, and reasonable adjustment of the insertion order.

[0063] Further, such as Figure 6As shown, the n cycle time nodes and the m efficiency process nodes are input into the node matching block for intersection matching to obtain a first matching result, and step S542 further includes:

[0064] S5421: Obtaining a first intersection coefficient for intersection matching of the node matching block;

[0065] S5422: Determine whether the first intersection coefficient is less than a preset intersection coefficient;

[0066] S5423: When the first intersection coefficient is less than the preset intersection coefficient, obtain a first coefficient difference;

[0067] S5424: Obtaining a first excess overflow coefficient of the material processing plant;

[0068] S5425: When the first coefficient difference is not within the first excess overflow coefficient, obtain first reminder information, wherein the first reminder information is information about order adjustment failure.

[0069] Specifically, an intersection coefficient is preset, and the intersection coefficient is used to describe the degree of intersection size. The preset coefficient is the intersection coefficient during normal production. The first intersection coefficient after the first newly added order information is intersection matched in the node matching block is obtained, and it is determined whether the first intersection coefficient is less than the preset intersection coefficient. When it is less than, the first coefficient difference is obtained, indicating that the work task of the first newly added order is within the tolerance range of the factory. Further, the first excess overflow coefficient of the factory is obtained, which is the maximum overflow coefficient. Generally, in order to complete the order, the factory will continue to work outside the normal production time to improve production efficiency. The intersection coefficient matched by the intersection of the cycle time node and the efficiency process node outside the normal production time is called the overflow coefficient. The maximum overflow coefficient refers to the maximum overflow coefficient, that is, the intersection coefficient corresponding to the highest production efficiency that the factory can bear. When the first coefficient difference is not in the first excess overflow coefficient, the first reminder information is obtained, that is, the first order can be completed under normal working conditions, then the first reminder information is obtained to remind the order not to adjust the order. It can avoid the wrong adjustment of orders and disrupt the normal production order of the enterprise.

[0070] S600: Generate a first adjustment instruction according to the first decision output information;

[0071] S700: Sequentially adjust the first newly added order according to the first adjustment instruction.

[0072] Specifically, after the order adjustment management system generates the first priority adjustment request, the rule module in the system receives the request, analyzes the historical data and real-time data of the company's production materials and processing orders, and makes a decision on the request based on the analysis results through the order adjustment decision rules in the rule module to determine whether the request is reasonable. After obtaining the information after the decision, an adjustment instruction is generated according to the output decision information, thereby reminding the user that there is an adjustment optimization plan, further adjusting the order of the newly added orders, adjusting the order of the material orders, enhancing management flexibility, thereby optimizing the order management process, improving the efficiency of processing orders, and further improving the benefits of the enterprise.

[0073] Further, such as Figure 7 As shown, the first newly added order information is obtained according to the real-time material order information, the system further includes a merging unit, and step S100 further includes:

[0074] S110: Obtaining a first material category by performing order material category analysis on the first newly added order information;

[0075] S120: generating a first block to be adjusted according to the first material category;

[0076] S130: Performing merging rule judgment on all newly added order information in the block according to the merging unit in the first block to be adjusted to obtain first merged order information;

[0077] S140: Complete the merging order adjustment according to the first merging order information.

[0078] Specifically, the materials in the new orders are classified and processed. Since the material processing plant can divide the processing technology according to the material category, the first block to be adjusted is generated according to the first material category. The first block to be adjusted contains a merging unit, which can judge the merging rules of all new orders according to the material category to determine whether they can be merged. If they can be merged, the first merged order information is obtained and the merging order is adjusted. By merging orders, the efficiency of order processing can be improved, the efficiency of material processing can be improved, and the request rules for order adjustment management can be more complete and scientific.

[0079] In summary, the order adjustment management method and system based on rule requests provided by the embodiments of the present application have the following technical effects:

[0080] 1. Due to the adoption of obtaining first newly added order information according to real-time material order information; judging whether the first newly added order information has a first trigger identification feature, wherein the first trigger identification feature is a feature that triggers order sequence replacement; when the first newly added order information has the first trigger identification feature, inputting the first newly added order information into a transaction quantitative level analysis model for transaction quantitative level analysis to obtain a first quantitative level; analyzing the first quantitative level according to a request generation rule to obtain a first priority adjustment request; when the rule module receives the first priority adjustment request, obtaining first decision output information according to an order adjustment decision rule in the rule module; generating a first adjustment instruction according to the first decision output information; and adjusting the order of the first newly added order according to the first adjustment instruction, the embodiment of the present application provides an order adjustment management method and system based on rule requests, thereby achieving the technical effect of digitizing and quantifying order information by establishing mathematical logic rules, exchanging the priority order of newly added orders in a reasonable order, optimizing the order management process, improving the intelligence of order adjustment, and enhancing management flexibility, thereby improving the efficiency of processing orders.

[0081] 2. Due to the use of node matching blocks to summarize the historical material order completion rules and make reasonable predictions on the completion cycle of new orders, the technical effect of real-time supervision of the production cycle of material orders, reasonable evaluation of new orders, and reasonable adjustment is achieved.

[0082] Embodiment 2

[0083] Based on the same inventive concept as the order adjustment management method based on rule request in the above embodiment, Figure 8 As shown, an embodiment of the present application provides an order adjustment management system based on rule requests, wherein the system includes:

[0084] An order information acquisition unit 11, wherein the order information acquisition unit 11 is used to obtain first newly added order information according to the real-time material order information;

[0085] A trigger identification judgment unit 12, the trigger identification judgment unit 12 is used to judge whether the first newly added order information has a first trigger identification feature, wherein the first trigger identification feature is a feature that triggers order sequence replacement;

[0086] A quantitative level analysis unit 13, wherein the quantitative level analysis unit 13 is configured to input the first newly added order information into a transaction quantitative level analysis model to perform transaction quantitative level analysis to obtain a first quantitative level when the first newly added order information has the first trigger identification feature;

[0087] A priority adjustment unit 14, the priority adjustment unit 14 is used to analyze the first quantization level according to a request generation rule to obtain a first priority adjustment request;

[0088] A decision output unit 15, wherein the decision output unit 15 is configured to obtain first decision output information according to the order adjustment decision rule in the rule module when the rule module receives the first priority adjustment request;

[0089] an adjustment instruction generating unit 16, wherein the adjustment instruction generating unit 16 is configured to generate a first adjustment instruction according to the first decision output information;

[0090] The order adjustment unit 17 is used to sequentially adjust the first newly added order according to the first adjustment instruction.

[0091] Furthermore, the system comprises:

[0092] A transaction data obtaining unit, the transaction data obtaining unit being used to obtain multiple transaction data according to the first newly added order information, wherein the multiple transaction data includes transaction amount data, transaction cycle data and transaction material data;

[0093] A quantitative index analysis unit, the quantitative index analysis unit is used to obtain multiple quantitative indexes by performing quantitative data collection on the multiple transaction data;

[0094] A mean quantization unit, the mean quantization unit is used to obtain multiple mean quantization indicators according to the real-time material order information;

[0095] A proportion calculation unit, the proportion calculation unit is used to obtain a first proportion coefficient by normalizing the multiple quantitative indicators and performing proportion calculation based on the multiple mean quantitative indicators;

[0096] A quantitative grade analysis unit, wherein the quantitative grade analysis unit is used to generate the first quantitative grade according to the first proportion coefficient input into the transaction quantitative grade analysis model.

[0097] Furthermore, the system comprises:

[0098] A data threshold analysis unit, the data threshold analysis unit is used to determine a preset quantitative level by performing quantitative data threshold analysis on historical material order information;

[0099] A mapping analysis unit, the mapping analysis unit being configured to construct a first mapping structure according to the preset quantization levels, wherein the preset quantization levels in the first mapping structure correspond one-to-one to preset priorities;

[0100] A rule construction unit, wherein the rule construction unit is used to construct the request generation rule according to the first mapping structure.

[0101] Furthermore, the system comprises:

[0102] An order cycle analysis unit, the order cycle analysis unit is used to obtain N cycle time nodes greater than or equal to a preset cycle by performing order cycle analysis on the real-time material order information;

[0103] A work efficiency calculation unit, the work efficiency calculation unit is used to obtain M efficiency process nodes less than or equal to a preset efficiency by performing real-time work efficiency calculation on the process flow of the material processing plant;

[0104] An adjustment node output unit, the adjustment node output unit being used to obtain a first adjustable node according to the N cycle time nodes and the M efficiency process nodes;

[0105] A node matching unit is used to input the first adjustable node into a node matching block of the rule module for storage.

[0106] Furthermore, the system comprises:

[0107] A process requirement analysis unit, wherein the process requirement analysis unit is used to perform process requirement analysis according to the first newly added order information to obtain n cycle time nodes and m efficiency process nodes of the requirement;

[0108] An intersection matching unit, the intersection matching unit is used to input the n period time nodes and the m efficiency process nodes into the node matching block for intersection matching to obtain a first matching result;

[0109] A decision output unit, wherein the decision output unit is used to generate the first decision output information of the rule module according to the first matching result.

[0110] Furthermore, the system comprises:

[0111] An intersection coefficient calculation unit, the intersection coefficient calculation unit is used to obtain a first intersection coefficient for intersection matching of the node matching block;

[0112] An intersection coefficient determination unit, the intersection coefficient determination unit is used to determine whether the first intersection coefficient is less than a preset intersection coefficient;

[0113] a coefficient difference obtaining unit, the coefficient difference obtaining unit being used to obtain a first coefficient difference when the first intersection coefficient is less than the preset intersection coefficient;

[0114] An excess analysis unit, the excess analysis unit is used to obtain a first excess overflow coefficient of the material processing plant;

[0115] An overflow reminder unit, wherein the overflow reminder unit is used to obtain first reminder information when the first coefficient difference is not within the first excess overflow coefficient, wherein the first reminder information is information about order adjustment failure.

[0116] Furthermore, the system comprises:

[0117] A material category analysis unit, the material category analysis unit is used to obtain a first material category by performing an order material category analysis on the first newly added order information;

[0118] An analysis unit to be adjusted, the analysis unit to be adjusted is used to generate a first block to be adjusted according to the first material category;

[0119] a merging rule judgment unit, the merging rule judgment unit being used to perform merging rule judgment on all newly added order information in the block according to the merging unit in the first block to be adjusted, to obtain first merged order information;

[0120] A merge order adjustment unit, wherein the merge order adjustment unit is used to complete the merge order adjustment according to the first merge order information.

[0121] Exemplary Electronic Devices

[0122] Reference below Fig. 9 To describe the electronic device of the embodiment of the present application,

[0123] Based on the same inventive concept as the order adjustment management method based on rule request in the aforementioned embodiment, the embodiment of the present application also provides an order adjustment management system based on rule request, including: a processor, the processor is coupled to a memory, the memory is used to store a program, when the program is executed by the processor, the system executes the method described in any one of the first aspects

[0124] The electronic device 300 includes: a processor 302, a communication interface 303, and a memory 301. Optionally, the electronic device 300 may also include a bus architecture 304. The communication interface 303, the processor 302, and the memory 301 may be interconnected via the bus architecture 304; the bus architecture 304 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus architecture 304 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig. 9 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0125] The processor 302 may be a CPU, a microprocessor, an ASIC, or one or more integrated circuits for controlling the execution of the program of the present application.

[0126] The communication interface 303 uses any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), wired access networks, etc.

[0127] The memory 301 may be a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, an optical disc storage (including a compressed optical disc, a laser disc, an optical disc, a digital versatile disc, a Blu-ray disc, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory may exist independently and be connected to the processor via a bus architecture 304. The memory may also be integrated with the processor.

[0128] The memory 301 is used to store computer-executable instructions for executing the solution of the present application, and the execution is controlled by the processor 302. The processor 302 is used to execute the computer-executable instructions stored in the memory 301, thereby realizing an order adjustment management method based on rule requests provided in the above embodiment of the present application.

[0129] Optionally, the computer-executable instructions in the embodiments of the present application may also be referred to as application code, which is not specifically limited in the embodiments of the present application.

[0130] An embodiment of the present application provides an order adjustment management method based on rule requests, wherein the method includes: obtaining first newly added order information based on real-time material order information; determining whether the first newly added order information has a first trigger identification feature, wherein the first trigger identification feature is a feature that triggers order sequence replacement; when the first newly added order information has the first trigger identification feature, inputting the first newly added order information into a transaction quantitative grade analysis model for transaction quantitative grade analysis to obtain a first quantitative grade; analyzing the first quantitative grade according to a request generation rule to obtain a first priority adjustment request; when the rule module receives the first priority adjustment request, obtaining first decision output information according to the order adjustment decision rule in the rule module; generating a first adjustment instruction based on the first decision output information; and performing sequence adjustment on the first newly added order according to the first adjustment instruction.

[0131] Those of ordinary skill in the art will appreciate that the various digital numbers such as the first and second involved in the present application are only for the convenience of description, and are not used to limit the scope of the embodiments of the present application, nor do they represent the order of precedence. "And / or" describes the association relationship of the associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are in an "or" relationship. "At least one" refers to one or more. At least two refers to two or more. "At least one", "any one" or similar expressions refer to any combination of these items, including any combination of single items (individuals) or plural items (individuals). For example, at least one item (individual, kind) of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0132] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server, data center, etc. that includes one or more available media integrated. The available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)), etc.

[0133] The various illustrative logic units and circuits described in the embodiments of the present application can be implemented or operated by a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic, a discrete hardware component, or the design of any combination of the above functions. The general-purpose processor can be a microprocessor, and optionally, the general-purpose processor can also be any traditional processor, controller, microcontroller or state machine. The processor can also be implemented by a combination of computing devices, such as a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration to implement.

[0134] The steps of the method or algorithm described in the embodiments of the present application can be directly embedded in hardware, a software unit executed by a processor, or a combination of the two. The software unit can be stored in a RAM memory, a flash memory, a ROM memory, an EPROM memory, an EEPROM memory, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium in the art. Exemplarily, the storage medium can be connected to the processor so that the processor can read information from the storage medium and can write information to the storage medium. Optionally, the storage medium can also be integrated into the processor. The processor and the storage medium can be arranged in an ASIC, and the ASIC can be arranged in a terminal. Optionally, the processor and the storage medium can also be arranged in different components in the terminal. These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are performed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0135] Although the present application has been described in conjunction with specific features and embodiments thereof, it is obvious that various modifications and combinations may be made thereto without departing from the spirit and scope of the present application. Accordingly, this specification and the drawings are merely exemplary illustrations of the present application as defined by the appended claims, and are deemed to have covered any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include these modifications and variations.

Claims

1. A method for managing order adjustment based on rule requests, wherein: The method is applied to an order adjustment management system based on rule requests, the system includes a rule module, and the method includes: According to the real-time material order information, the first newly added order information is obtained; Determining whether the first newly added order information has a first trigger identification feature, wherein the first trigger identification feature is a feature that triggers order sequence change; When the first newly added order information has the first trigger identification feature, inputting the first newly added order information into a transaction quantitative grade analysis model to perform transaction quantitative grade analysis to obtain a first quantitative grade; Analyzing the first quantization level according to a request generation rule to obtain a first priority adjustment request; When the rule module receives the first priority adjustment request, first decision output information is obtained according to the order adjustment decision rule in the rule module; generating a first adjustment instruction according to the first decision output information; The first newly added order is sequentially adjusted according to the first adjustment instruction.

2. The method according to claim 1, wherein when the first newly added order information has the first trigger identification feature, the first newly added order information is input into a transaction quantification grade analysis model to perform transaction quantification grade analysis to obtain a first quantification grade, the method further comprising: According to the first newly added order information, multiple transaction data are obtained, wherein the multiple transaction data include transaction amount data, transaction cycle data and transaction material data; By performing quantitative data collection on the multiple transaction data, multiple quantitative indicators are obtained; Obtaining a multi-mean quantitative index according to the real-time material order information; By normalizing the multiple quantitative indicators and performing a proportion calculation based on the multiple mean quantitative indicators, a first proportion coefficient is obtained; The first quantitative grade is generated by inputting the first proportion coefficient into the transaction quantitative grade analysis model.

3. The method according to claim 1, before analyzing the first quantization level according to the request generation rule to obtain the first priority adjustment request, the method further comprises: Determine the preset quantitative level by conducting quantitative data threshold analysis on historical material order information; According to the preset quantization levels, constructing a first mapping structure, wherein the preset quantization levels in the first mapping structure correspond one to one to the preset priorities; The request generation rule is constructed according to the first mapping structure.

4. The method of claim 2, wherein when the rule module receives the first priority adjustment request, first decision output information is obtained according to the order adjustment decision rule in the rule module, and the method further comprises: By performing order cycle analysis on the real-time material order information, N cycle time nodes greater than or equal to a preset cycle are obtained; By calculating the real-time work efficiency of the process flow of the material processing plant, M efficiency process nodes with a preset efficiency are obtained; Obtaining a first adjustable node according to the N cycle time nodes and the M efficiency process nodes; The first adjustable node is input into the node matching block of the rule module for storage.

5. The method according to claim 4, wherein the first adjustable node is input into the node matching block of the rule module for storage, and the method further comprises: Performing process demand analysis according to the first newly added order information to obtain n cycle time nodes and m efficiency process nodes required; Inputting the n cycle time nodes and the m efficiency process nodes into the node matching block for intersection matching to obtain a first matching result; The first decision output information of the rule module is generated according to the first matching result.

6. The method according to claim 5, wherein the n cycle time nodes and the m efficiency process nodes are input into the node matching block for intersection matching to obtain a first matching result, the method further comprising: Obtaining a first intersection coefficient for intersection matching of the node matching block; Determining whether the first intersection coefficient is less than a preset intersection coefficient; When the first intersection coefficient is less than the preset intersection coefficient, obtaining a first coefficient difference; Obtaining a first excess overflow coefficient of the material processing plant; When the first coefficient difference is not within the first excess overflow coefficient, a first reminder message is obtained, wherein the first reminder message is information of order adjustment failure.

7. The method of claim 1, wherein: The first newly added order information is obtained according to the real-time material order information, the system further includes a merging unit, and the method further includes: Obtaining a first material category by performing order material category analysis on the first newly added order information; generating a first block to be adjusted according to the first material category; Performing merging rule judgment on all newly added order information in the block according to the merging unit in the first block to be adjusted to obtain first merged order information; The merging order adjustment is completed according to the first merging order information.

8. An order adjustment management system based on rule requests, wherein: The system comprises: An order information acquisition unit, the order information acquisition unit is used to obtain first newly added order information according to the real-time material order information; a trigger identification judgment unit, the trigger identification judgment unit being used to judge whether the first newly added order information has a first trigger identification feature, wherein the first trigger identification feature is a feature that triggers order sequence exchange; a quantitative level analysis unit, wherein when the first newly added order information has the first trigger identification feature, the quantitative level analysis unit is used to input the first newly added order information into a transaction quantitative level analysis model to perform transaction quantitative level analysis to obtain a first quantitative level; a priority adjustment unit, configured to analyze the first quantization level according to a request generation rule to obtain a first priority adjustment request; a decision output unit, the decision output unit being configured to obtain first decision output information according to the order adjustment decision rule in the rule module when the rule module receives the first priority adjustment request; an adjustment instruction generating unit, the adjustment instruction generating unit being configured to generate a first adjustment instruction according to the first decision output information; An order adjustment unit, wherein the order adjustment unit is used to sequentially adjust the first newly added order according to the first adjustment instruction.

9. An order adjustment management system based on rule requests, comprising: A processor, the processor is coupled to a memory, the memory is used to store a program, when the program is executed by the processor, the system is enabled to execute the method according to any one of claims 1 to 7.

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