CN116227835A - Product production control method and system based on supply chain control system - Google Patents
Product production control method and system based on supply chain control system Download PDFInfo
- Publication number
- CN116227835A CN116227835A CN202211708758.1A CN202211708758A CN116227835A CN 116227835 A CN116227835 A CN 116227835A CN 202211708758 A CN202211708758 A CN 202211708758A CN 116227835 A CN116227835 A CN 116227835A
- Authority
- CN
- China
- Prior art keywords
- data
- product
- supply chain
- bill
- node
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000195 production control method Methods 0.000 title claims abstract description 21
- 239000000463 material Substances 0.000 claims abstract description 101
- 238000012545 processing Methods 0.000 claims abstract description 92
- 238000004519 manufacturing process Methods 0.000 claims abstract description 87
- 238000000034 method Methods 0.000 claims abstract description 71
- 230000008569 process Effects 0.000 claims abstract description 42
- 239000000306 component Substances 0.000 claims description 52
- 238000013461 design Methods 0.000 claims description 23
- 239000008358 core component Substances 0.000 claims description 13
- 238000004891 communication Methods 0.000 claims description 11
- 238000004590 computer program Methods 0.000 claims description 10
- 230000003993 interaction Effects 0.000 claims description 10
- 230000000007 visual effect Effects 0.000 claims description 10
- 238000003860 storage Methods 0.000 claims description 8
- 239000000047 product Substances 0.000 description 194
- 238000010586 diagram Methods 0.000 description 15
- 238000007726 management method Methods 0.000 description 10
- 239000000203 mixture Substances 0.000 description 8
- 230000006870 function Effects 0.000 description 7
- 239000002994 raw material Substances 0.000 description 7
- 238000004364 calculation method Methods 0.000 description 6
- 230000008676 import Effects 0.000 description 6
- 238000004088 simulation Methods 0.000 description 4
- 230000002776 aggregation Effects 0.000 description 3
- 238000004220 aggregation Methods 0.000 description 3
- 239000003814 drug Substances 0.000 description 3
- 229940079593 drug Drugs 0.000 description 3
- 230000003137 locomotive effect Effects 0.000 description 3
- 230000005180 public health Effects 0.000 description 3
- 238000011156 evaluation Methods 0.000 description 2
- 238000012946 outsourcing Methods 0.000 description 2
- 230000004044 response Effects 0.000 description 2
- 239000004576 sand Substances 0.000 description 2
- 239000011265 semifinished product Substances 0.000 description 2
- 230000001502 supplementing effect Effects 0.000 description 2
- 238000012384 transportation and delivery Methods 0.000 description 2
- PCTMTFRHKVHKIS-BMFZQQSSSA-N (1s,3r,4e,6e,8e,10e,12e,14e,16e,18s,19r,20r,21s,25r,27r,30r,31r,33s,35r,37s,38r)-3-[(2r,3s,4s,5s,6r)-4-amino-3,5-dihydroxy-6-methyloxan-2-yl]oxy-19,25,27,30,31,33,35,37-octahydroxy-18,20,21-trimethyl-23-oxo-22,39-dioxabicyclo[33.3.1]nonatriaconta-4,6,8,10 Chemical compound C1C=C2C[C@@H](OS(O)(=O)=O)CC[C@]2(C)[C@@H]2[C@@H]1[C@@H]1CC[C@H]([C@H](C)CCCC(C)C)[C@@]1(C)CC2.O[C@H]1[C@@H](N)[C@H](O)[C@@H](C)O[C@H]1O[C@H]1/C=C/C=C/C=C/C=C/C=C/C=C/C=C/[C@H](C)[C@@H](O)[C@@H](C)[C@H](C)OC(=O)C[C@H](O)C[C@H](O)CC[C@@H](O)[C@H](O)C[C@H](O)C[C@](O)(C[C@H](O)[C@H]2C(O)=O)O[C@H]2C1 PCTMTFRHKVHKIS-BMFZQQSSSA-N 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 238000000802 evaporation-induced self-assembly Methods 0.000 description 1
- 239000012467 final product Substances 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 239000013067 intermediate product Substances 0.000 description 1
- 230000013011 mating Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 238000013439 planning Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
- 238000000547 structure data Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
- G06Q10/0875—Itemisation or classification of parts, supplies or services, e.g. bill of materials
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/103—Workflow collaboration or project management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/04—Manufacturing
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Development Economics (AREA)
- Game Theory and Decision Science (AREA)
- Educational Administration (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Data Mining & Analysis (AREA)
- Manufacturing & Machinery (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application belongs to the technical field of supply chain control, and particularly relates to a product production control method and system based on a supply chain control system. And establishing a supply chain model associated among the processing nodes in the product circulation process according to the bill of materials data of the processing nodes by acquiring the bill of materials data of the processing nodes in the product circulation process. And acquiring the influence data of the current emergency on each processing node of the product, inputting the influence data into a supply chain model, and finally outputting recommended data corresponding to each processing node. The method and the device can meet the control requirement of the emergency on the production of the product, and realize intelligent regulation and control in the production.
Description
Technical Field
The embodiment of the application belongs to the technical field of supply chain control, and particularly relates to a product production control method and system based on a supply chain control system.
Background
The supply chain control system is an organic whole with specific functions formed by combining a plurality of components which interact and are mutually dependent. The method has the main function of helping enterprises to realize automation of business operation.
The supply chain control system in the prior art can only realize the production management of products under the conventional condition, for example, when a certain component quantity in a production processing node is insufficient, the prior control system reminds an administrator of supplementing the component according to the current product reserve.
However, the existing supply chain control system has a single function, and cannot adapt to the management requirement of the emergency on the production of the product.
Disclosure of Invention
In order to solve the above problems in the prior art, that is, in order to solve the problem that the existing supply chain control system has a single function and cannot adapt to the management requirement of an emergency on the production of a product, the embodiment of the application provides a product production control method and a control system based on the supply chain control system.
In a first aspect, embodiments of the present application provide a product production control method based on a supply chain control system, including:
acquiring bill of materials data of each processing node in the product circulation process;
establishing a supply chain model associated among the processing nodes in the product circulation process according to the bill of materials data of the processing nodes;
and acquiring influence data of the current emergency on each processing node of the product, inputting the influence data into the supply chain model, and outputting recommended data corresponding to each processing node.
In a preferred embodiment of the above method for controlling production of a product based on a supply chain control system, the bill of materials data includes: product design node bill of materials data, product purchase node bill of materials data, product production node bill of materials data, and product after-market node bill of materials data;
the step of establishing a supply chain model associated with each processing node in the product circulation process according to the bill of materials data of each processing node comprises the following steps:
according to the product design node bill of materials data, a first map of the association between components used by the product is established;
establishing a second map of the association between the components used by the product and the suppliers according to the product purchasing node bill of materials data;
establishing a third map of the association between the production flows of the products according to the bill of materials of the production nodes of the products;
establishing a fourth map of the association between the product and the sales client according to the product after-sales node bill of materials data;
and establishing a supply chain model associated among all the processing nodes in the product circulation process according to the first map, the second map, the third map and the fourth map.
In the above preferred technical solution of the product production control method based on the supply chain control system, the components in the bill of materials data are coded and identified, and the components after coded and identified are classified according to a preset classification rule.
In the above preferred technical solution of the product production control method based on the supply chain control system, the obtaining the impact data of the current emergency on each processing node of the product includes:
and acquiring demand degree data, crisis data existing in product production and product performance influence data, which are caused by the current emergency event input by a user in the product circulation process.
In a preferred embodiment of the above product production control method based on a supply chain control system, the inputting the influence data into the supply chain model and outputting recommended data corresponding to each processing node includes:
setting initialization parameters of the supply chain model;
determining influence result data of the current emergency on each processing node according to the initialization parameters, the demand data, the crisis data and the performance influence data;
evaluating the accuracy of the influence result data according to a preset prediction strategy to obtain prediction result data;
and outputting recommended data corresponding to each processing node according to the predicted result data.
In the above preferred technical solution of the product production control method based on a supply chain control system, the evaluating the accuracy of the influence result data according to a preset prediction policy to obtain prediction result data includes:
and generating a radar chart containing the predicted result data according to the preset prediction strategy and the influence result data.
In a second aspect, embodiments of the present application provide a supply chain control system for product production, comprising:
the basic resource layer is used for acquiring bill of materials data of each processing node in the product circulation process;
the core component layer is used for establishing a supply chain model associated with each processing node in the product circulation process according to the bill of materials data of each processing node;
and the visual interaction layer is used for acquiring the influence data of the current emergency on each processing node of the product, inputting the influence data into the supply chain model and outputting recommended data corresponding to each processing node.
In a third aspect, an embodiment of the present application provides an electronic device, including:
a processor, a memory, a communication interface;
the memory is used for storing executable instructions of the processor;
wherein the processor is configured to execute the supply chain control system-based product production control method of any one of the first aspects via execution of the executable instructions.
In a fourth aspect, embodiments of the present application provide a readable storage medium having stored thereon a computer program which, when executed by a processor, implements the supply chain control system-based product production control method of any one of the first aspects.
In a fifth aspect, embodiments of the present application provide a computer program product comprising a computer program for implementing the supply chain control system-based product production control method of any one of the first aspects when executed by a processor.
One skilled in the art can appreciate that the embodiment of the present application provides a product production control method and control system based on a supply chain control system. And establishing a supply chain model associated among the processing nodes in the product circulation process according to the bill of materials data of the processing nodes by acquiring the bill of materials data of the processing nodes in the product circulation process. And acquiring the influence data of the current emergency on each processing node of the product, inputting the influence data into a supply chain model, and finally outputting recommended data corresponding to each processing node. The method can meet the control requirement of the emergency on the production of the product, and realize intelligent regulation and control.
Drawings
Preferred embodiments of a product production control method and control system based on a supply chain control system of the present application are described below with reference to the accompanying drawings. The attached drawings are as follows:
FIG. 1 is a schematic flow chart of a product production control method based on a supply chain control system according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a supply chain control system for product production according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a basic resource layer according to an embodiment of the present application;
FIG. 4 is a flowchart of a method for creating a supply chain model according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a core component layer according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a visual interaction layer according to an embodiment of the present application;
FIG. 7 is a flowchart of a method for outputting recommended data corresponding to each processing node according to an embodiment of the present disclosure;
FIG. 8 is a schematic structural diagram of a supply chain model building module according to an embodiment of the present disclosure;
FIG. 9 is a schematic illustration of a radar chart provided herein;
FIG. 10 is a schematic diagram of a complete configuration of a supply chain control system for product production according to an embodiment of the present application;
fig. 11 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
First, it should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present application, and are not intended to limit the scope of the present application. Those skilled in the art can make adjustments as needed to suit a particular application.
Further, it should be noted that, in the description of the embodiments of the present application, terms such as directions or positional relationships indicated by the terms "inner", "outer", and the like are based on the directions or positional relationships shown in the drawings, which are merely for convenience of description, and do not indicate or imply that the apparatus or the component must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present application.
Furthermore, it should be noted that, in the description of the embodiments of the present application, unless explicitly specified and limited otherwise, the terms "connected," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be the communication between the two components. The specific meaning of the above terms in the embodiments of the present application will be understood by those skilled in the art according to the specific circumstances.
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
The supply chain control system is used for surrounding a core enterprise, starting from purchasing raw materials, producing intermediate products and final products through control of information flow and the like, and finally sending the products to a user through a sales network, wherein the supply chain control system is used for connecting suppliers, manufacturers and sellers into an integral functional network chain structure mode, and the main function of the supply chain control system is to help the enterprise to realize automation of business operation.
The supply chain control system in the prior art can only realize the production management of products under the conventional condition, for example, when a certain component quantity in a production node is insufficient, the prior control system reminds an administrator of supplementing the component according to the current product reserve.
However, the existing supply chain control system has a single function, and cannot adapt to the management requirement of the emergency on the production of the product.
In recent years, due to the influence of some external factors, emergency events are frequent, and the emergency events easily cause the interruption of a supply chain, so that the stability of the supply chain of some product manufacturers is influenced. Therefore, it is important to improve the dynamic regulation capability of the enterprise supply chain in emergency.
By way of example, in the rail traffic industry, more than ten thousand parts of the locomotive body are required, the structural composition and the manufacturing process are complex, the materials used are various, and the manufacturing period is long. If some emergencies with larger influence on locomotive production are met, uncontrollable situations occur in product design nodes, purchasing nodes, production nodes, sales nodes and the like of the locomotive, and the production efficiency is seriously influenced.
Therefore, in view of the above technical problems in the prior art, the present application provides a product production control method and control system based on a supply chain control system. And establishing a supply chain model associated among the processing nodes in the product circulation process according to the bill of materials data of the processing nodes by acquiring the bill of materials data of the processing nodes in the product circulation process. And acquiring the influence data of the current emergency on each processing node of the product, inputting the influence data into a supply chain model, and finally outputting recommended data corresponding to each processing node.
The supply chain control system has the capabilities of quick response, accurate decision and cooperative response, and is high in intelligent degree. The production of the product under the emergency can be dealt with, and the normal production of the product is ensured.
The following describes the technical solutions of the present application and how the technical solutions of the present application solve the above technical problems in detail with specific embodiments. The following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.
Fig. 1 is a schematic flow chart of a product production control method based on a supply chain control system according to an embodiment of the present application, and an execution subject of the method may be the supply chain control system, where the method in the embodiment may be implemented by software, hardware, or a combination of software and hardware. As shown in fig. 1, the method specifically includes the following steps:
s101, acquiring bill of materials data of each processing node in the product circulation process.
The supply chain control system in this embodiment can be built according to a sand table deduction mode, the supply chain is a complex network, the whole body is pulled and started, the stability of the supply chain control system under an emergency can be accurately estimated by utilizing the sand table deduction mode, and timely adjustment of each processing node in product production is facilitated.
FIG. 2 is a schematic structural diagram of a supply chain control system for product production according to an embodiment of the present application, as shown in FIG. 2, the supply chain control system includes: a basic resource layer, a core component layer and a visual interaction layer. The core component layer is respectively connected with the basic resource layer and the visual interaction layer.
The basic resource layer is used for acquiring bill of materials data of each processing node in the product circulation process, and the bill of materials data comprises: product design node bill of materials data, product procurement node bill of materials data, product production node bill of materials data, and product after-market node bill of materials data.
A Bill of materials (BOM) is a file for describing a product structure, and is a product structure data file that can be recognized by a computer. In the production process of an enterprise's products, the types of bill of materials include, but are not limited to: product design node BOM, product purchasing node BOM, product production node BOM, product after-sales node BOM, and the like.
The content in the product design node BOM includes, but is not limited to: designing a bill of materials and a bill of process materials. The design bill of materials includes a list of components used and the assembly relationship between the components of the product, and the list displays the basic information of the components and the supplier information of the components. The components comprise a general component, a standard component, a self-made component, an outsourcing component and the like. The assembly relationship includes a clearance fit, an interference fit, a transition fit, etc.
The content in the product procurement node BOM includes, but is not limited to: raw material information for outsourcing, component information, and vendor information corresponding to the raw material, component, and the like.
The content in the product production node BOM includes, but is not limited to: technological process of product production, tooling resources, raw materials, semi-finished products and other information. The technological process can indicate the manufacturing method and the assembly sequence of the product, and also can indicate processing equipment, tool fixtures, tool aids and the like corresponding to the manufacturing and assembly procedures of the product. The product production node BOM may describe the manufacturing process of the product in detail.
The content in the product after-market node BOM includes, but is not limited to: basic information of components used for the product, dealer information for selling the product, and the like.
S102, according to bill of materials data of each processing node, establishing a supply chain model associated among the processing nodes in the product circulation process.
The core component layer is used for establishing a supply chain model associated among the product design node, the purchasing node, the production node and the sales node according to the bill of materials data of each processing node. The supply chain model ties together the processing nodes in the product circulation process.
S103, obtaining influence data of the current emergency on each processing node of the product, inputting the influence data into a supply chain model, and outputting recommended data corresponding to each processing node.
The visual interaction layer is used for acquiring influence data of the current emergency on each processing node of the product production, inputting the influence data into the supply chain model, and outputting a production recommendation scheme corresponding to each processing node after the supply chain model is calculated.
The emergency event can be a natural disaster, a public health event, an accident disaster, a social security event and the like, and the event can have a certain influence on the production of products of enterprises.
Impact data includes, but is not limited to: demand data caused by the current emergency on the production of the product, crisis data existing in the production of the product, product performance influence data and the like.
With this embodiment, for example, by quickly finding an alternative resource party, the resource party may be a supplier of a component, etc., and the capacity adjustment is performed to complete the production. Meanwhile, according to the existing capacity conditions, the maximum capacity achievable by the product and the number of users capable of being served are predicted, and the research and development period of the product for realizing marketing is predicted. Therefore, under the emergency, the accurate matching of the enterprise supply chain is realized, the adjustment and control of the production plan are realized, the energy efficiency is improved, and the product reserves and the enterprise crisis are reduced.
For ease of understanding the present application, the following examples are set forth. The background can be: c enterprises and D enterprises of motor car motors are provided for a certain high-speed railway vehicle, and after receiving the production requirement of the motor car motors, the C enterprises start to purchase a bearing with a certain key model. And C, the enterprise distributes the order of the material to the suppliers A, B and C according to a certain proportion according to the signed delivery protocol.
The first provider feeds back the product which can not be delivered in quantity on time in the order confirmation link due to the emergency. In order not to affect the delivery schedule of the final product, the enterprise C needs to increase the supply ratio from the other two suppliers, but the other suppliers have limited capacity increase, and cannot fully meet the supply gap of the first supplier due to the reduced yield.
Therefore, through the method, the input influence data of the first, second and third parts, namely the capacity data, is acquired, the capacity data is input into the supply chain model, and after simulation calculation, the output recommended data is that the similar key type bearing can be purchased from the D enterprise.
Therefore, the C enterprise can purchase the similar key type bearing from the D enterprise, so that the purchase gap is complemented.
In the above embodiment of the present application, the supply chain model associated between the processing nodes in the product circulation process is established by acquiring the bill of materials data of the processing nodes in the product circulation process, and further according to the bill of materials data of the processing nodes. And acquiring the influence data of the current emergency on each processing node of the product, inputting the influence data into a supply chain model, and finally outputting recommended data corresponding to each processing node. According to the method, the system and the equipment, the bill of materials data are obtained, the supply chain model is built, and efficient and intelligent analysis of each processing node in the product circulation process under an emergency can be achieved, so that general research and decision support is provided for enterprise production regulation, management, product formulation and the like, and intelligent regulation is achieved.
Further, on the basis of the above embodiment, the structural composition of the basic resource layer is described below by using fig. 3, and fig. 3 is a schematic structural diagram of the basic resource layer according to the embodiment of the present application, where, as shown in fig. 3, the structural composition includes a data acquisition module and a data sharing module.
The data acquisition module is used for acquiring product design node bill of materials data, product purchasing node bill of materials data, product production node bill of materials data and product after-sale node bill of materials data.
The data sharing module is used for transmitting the product design node bill of materials data, the product purchasing node bill of materials data, the product production node bill of materials data and the product after-sale node bill of materials data to the core component layer.
The data acquired by the data acquisition module can be shared and streamed by the data sharing module, so that resources used in the production process of the product are coordinated.
In one possible implementation, the data acquisition module includes a vendor information acquisition interface, a material acquisition module.
The supplier information acquisition interface is used for accessing a plurality of suppliers related to product production and acquiring supplier information.
Suppliers in this application include, but are not limited to: raw material suppliers, component manufacturers, equipment manufacturers, product distributors and the like, and the supplier information acquisition interfaces provide communication data interfaces for enterprises accessing the suppliers, so that the supplier information is acquired. Wherein the vendor information includes, but is not limited to: the types of raw materials, components, equipment, and sales products that can be provided by suppliers for product production.
It will be appreciated that the above-described vendor information is merely exemplary and is not intended to be limiting of the present application.
It should be noted that, the provider information acquisition interface accesses the provider and the obtained provider information, and the provider has authorized storage and use.
The material collection module is used for collecting product design node material list data, product purchasing node material list data, product production node material list data and product after-sale node material list data, and establishing a matching relation between the material list data and supplier information.
The material information of related products among different enterprises can be obtained through the material acquisition module, so that the data flow and sharing among enterprises are realized.
In the above embodiments of the present application, the structural composition of the base resource layer includes a data acquisition module and a data sharing module. The data acquisition module is used for acquiring product design node bill of materials data, product purchasing node bill of materials data, product production node bill of materials data and product after-sale node bill of materials data. The data sharing module is used for transmitting the product design node bill of materials data, the product purchasing node bill of materials data, the product production node bill of materials data and the product after-sale node bill of materials data to the core component layer. The basic resource layer provides a large amount of data for the core component layer, and the obtained bill of materials data is sent to the core component layer to prepare for the core component layer to create a supply chain model, so that the created supply chain model is more accurate.
Further, on the basis of the above embodiment, a process of establishing a supply chain model associated between the processing nodes in the product circulation process according to bill of materials data of the processing nodes will be described below with reference to fig. 4. Fig. 4 is a flowchart of a method for building a supply chain model according to an embodiment of the present application, where the method includes the following steps:
s401, according to product design node bill of materials data, a first map of the association between components used by the product is established.
The method can be realized through a core component layer in a supply chain control system, and fig. 5 is a schematic structural diagram of the core component layer provided in the embodiment of the present application, and as shown in fig. 5, the structural composition includes a data aggregation management module, a knowledge graph creation module, and a supply chain model creation module.
The data aggregation management module is used for managing and storing product design node bill of materials data, product purchasing node bill of materials data, product production node bill of materials data and product after-sale node bill of materials data.
Optionally, the data aggregation management module may aggregate the bill of materials data sent by the data sharing module, and perform collection, cleaning, storage, processing and the like on the data to implement unified management on the data, so as to provide the required data for the knowledge graph creation module. In addition, the various maps established below and the supply chain model established and the like can be stored and managed.
The knowledge graph creation module is used for creating a first graph, and a second graph, a third graph and a fourth graph which are described below.
S402, establishing a second map of the association between the components used by the product and the suppliers according to the bill of materials data of the product purchasing node.
S403, establishing a third map of the correlation between the product production flows according to the product production node bill of materials data.
S404, according to the after-sale node bill of materials data of the product, a fourth map of the association between the product and the sales client is established.
It may be understood that the knowledge graph creation module may also create other related graphs according to the obtained bill of materials data, which is not limited in this application.
Optionally, the knowledge graph creation module may further perform coding identification on the components in the bill of materials data, and rank the components after coding identification according to a preset classification rule.
By way of example only, and not by way of limitation,
the knowledge graph creation module can split key components used by the product, wherein the components can be important materials in the product design BOW, the product purchase BOW, the product manufacturing BOW and the product after-sale BOW. And carrying out unified coding identification on the split components and parts, and grading according to importance degrees, for example, according to ABCD and the like, wherein A is the most important key material, and the importance degrees corresponding to letters are gradually decreased. The components in the bill of materials data are coded, identified and classified, so that the data can be managed better.
S405, establishing a supply chain model associated among all the processing nodes in the product circulation process according to the first map, the second map, the third map and the fourth map.
The supply chain model building module is used for building a supply chain model related to the product design node, the purchasing node, the production node and the sales node according to the first map, the second map, the third map and the fourth map.
The processing nodes in the product circulation process can be connected through the supply chain model building module, and the relevance among the nodes is enhanced.
In the above embodiment of the present application, a first map of the association between the components used in the product is established according to the product design node bill of materials data, a second map of the association between the components used in the product and the suppliers is established according to the product purchasing node bill of materials data, a third map of the association between the product production processes is established according to the product production node bill of materials data, and a fourth map of the association between the product and the sales customers is established according to the product after-sales node bill of materials data, and further, a supply chain model of the association between the processing nodes in the product circulation process is established according to the first map, the second map, the third map and the fourth map. By the method and the device, the supply chain model associated among the processing nodes in the established product circulation process is more accurate.
Further, on the basis of the above embodiment, the structural composition of the visual interaction layer is described below through fig. 6, and fig. 6 is a schematic structural diagram of the visual interaction layer according to the embodiment of the present application, as shown in fig. 6, where the structural composition includes an incident import module, a deduction control module, and a display module.
The emergency import module is used for acquiring influence data of the current emergency on production of products.
The emergency event may be a natural disaster, public health event, accident disaster, social security event, etc. which may affect the production of the enterprise product.
Optionally, the impact data includes, but is not limited to, data of demand caused by the current emergency on the production of the product, crisis data of the production existence of the product, data of impact on the performance of the product, and the like.
It will be appreciated that the above-described impact data are for illustration only and are not intended as limitations of the present application.
By way of example only, and not by way of limitation,
because of certain public health events, the temperature requirement for a certain product, such as a drug storage cabinet, becomes above 56 ℃ for 30min. Therefore, the emergency import module can acquire the temperature demand data and the time demand data of the product.
The deduction control module is used for inputting the influence data into the supply chain model.
Taking the above example as an example, the deduction control module inputs the obtained temperature demand data and time demand data of the product into the established supply chain model, and the supply chain model performs deduction simulation to obtain the influence result data, where the influence result data may be, for example, that an original component cannot meet the above requirement, and needs to find other replaceable components.
The display module is used for displaying recommended data corresponding to each processing node, which is output after the influence data is calculated by the supply chain model.
Taking the above example as an example, because an original component cannot meet the above requirement, it is necessary to find an alternative component, and replacement of the component affects each processing node in the product circulation process, so the display module may display recommended data corresponding to each processing node.
In the above embodiment of the present application, the structural components of the visual interaction layer include an incident import module, a deduction control module, and a display module. The emergency import module is used for obtaining influence data of the current emergency on the production of the product, wherein the influence data comprise, but are not limited to, demand data caused in the process of product circulation, crisis data existing in the production of the product and product performance influence data, the deduction control module is used for inputting the influence data into the supply chain model, and the display module is used for displaying recommended data corresponding to each processing node which is outputted after the influence data is calculated by the supply chain model. According to the implementation, the influence data of the emergency event is obtained, so that the supply chain model is convenient to analyze, and further intelligent regulation and control of the production process of the product are realized.
Further, on the basis of the above embodiment, a process of inputting the influence data into the supply chain model and outputting the recommended data corresponding to each processing node is described below by referring to fig. 7, and fig. 7 is a flowchart of a method for outputting the recommended data corresponding to each processing node according to the embodiment of the present application, as shown in fig. 7, and the method includes the following steps:
s701, setting initialization parameters of a supply chain model.
The method may be implemented by a supply chain model building module in a supply chain control system. Fig. 8 is a schematic structural diagram of a supply chain model building module according to an embodiment of the present application, and as shown in fig. 8, the supply chain model building module includes: the device comprises an initialization module, a deduction calculation module, a result prediction module and a result recommendation module.
The initialization module is used for setting initialization parameters of the supply chain model.
The parameters may be supply and demand data of the product, planning data of product production, production energy consumption data, production order data, production capacity data, product reserve data of related materials for producing each node, existing semi-finished product data, product reserve data of the finished product, capacity data of enterprises associated with product production, and the like in the current production state. It is to be understood that the above data is not to be taken as limiting the present application.
The initialization module performs initial data setting according to the parameters, such as setting initial basic parameters of the supply chain model, setting initial dynamic parameters of the supply chain model, setting initial prediction parameters, and the like.
S702, determining influence result data of the current emergency on each processing node according to the initialization parameters, the demand data, the crisis data and the performance influence data.
The deduction calculation module is used for carrying out simulation calculation processing by utilizing various established patterns according to the initialization parameters, the demand data, the crisis data and the performance influence data, and determining influence result data of the current emergency on the product design node, the purchasing node, the production node and the sales node.
S703, evaluating the accuracy of the influence result data according to a preset prediction strategy to obtain the prediction result data.
The result prediction module is used for evaluating the accuracy of the influence result data according to a preset prediction strategy to obtain the prediction result data.
Optionally, the result prediction module may generate a radar chart including predicted result data according to a preset prediction policy and influence result data.
Fig. 9 is a schematic diagram of a radar chart provided in the present application, and as shown in fig. 9, a preset prediction strategy may include the following aspects, namely, basic resources, design coordination, production coordination, supply-demand matching, resource evaluation, market feedback, crisis coverage, early warning accuracy, and the like, and evaluation result data of the aspects are shown in the form of scores in fig. 9.
It can be understood that the preset prediction strategy can also comprise other aspects, the application is not limited, and the prediction result data can be displayed visually and intuitively by setting the radar chart.
S704, according to the prediction result data, recommendation data corresponding to each processing node is output.
And the result recommending module is used for outputting recommending data corresponding to each processing node in the product circulation process to the user according to the predicted result data.
By way of example only, and not by way of limitation,
taking the drug storage cabinet of the above embodiment as an example, the temperature requirement is changed to be above 56 ℃ and the time requirement is changed to be 30min, the emergency import module of the visual interaction layer obtains the temperature requirement data and the time requirement data of the product and sends the temperature requirement data and the time requirement data to the deduction control module, and the deduction control module inputs the temperature requirement data and the time requirement data into the supply chain model.
The deduction calculation module in the supply chain model building module carries out simulation calculation processing by utilizing various built maps according to the temperature demand data, the time demand data and the initialization parameters, and the obtained influence result is that the original A component cannot meet the requirements, and an alternative B component needs to be searched, wherein the alternative components are B1, B2, B3 and the like. The result prediction module may display the scores corresponding to B1, B2, and B3 under the preset prediction policy in the radar chart, as shown in fig. 9, where the determination with the highest score is assumed to be B2 as the production recommendation scheme. And then outputting and producing the resources required by the drug storage cabinet in the product design node, the purchasing node, the production node and the sales node according to the B2. Such as the required raw materials, the required mating components, etc.
In the above embodiment of the present application, by setting an initialization parameter of a supply chain model, according to the initialization parameter, the demand data, the crisis data and the performance impact data, the impact result data of the current emergency on each processing node is determined, further, according to a preset prediction policy, the accuracy of the impact result data is evaluated, the prediction result data is obtained, and finally, according to the prediction result data, the recommended data corresponding to each processing node is output. According to the embodiment, the influence data and the initialization parameters of the current emergency on the production of the product are obtained, the recommended data corresponding to each processing node in the output product circulation process is more accurate, and the intelligent regulation and control of the production process of the product are realized.
In summary, fig. 10 is a schematic diagram of a complete structure of a supply chain control system for product production according to the embodiment of the present application, and the specific structural components and functions of the supply chain control system are shown in the above embodiment, which is not repeated herein.
Fig. 11 is a schematic structural diagram of an electronic device according to an embodiment of the present application, as shown in fig. 11, where the device may include: at least one processor 1101 and a memory 1102.
A memory 1102 for storing programs. In particular, the program may include program code including computer operation instructions, or executable instructions of the processor 1101, or the like.
The processor 1101 is configured to execute computer-executable instructions stored in the memory 1102 to implement the methods described in the foregoing method embodiments. The processor 1101 may be a central processing unit (Central Processing Unit, abbreviated as CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, abbreviated as ASIC), or one or more integrated circuits configured to implement embodiments of the present application.
Optionally, the electronic device may also include a communication interface 1103. In a specific implementation, if the communication interface 1103, the memory 1102, and the processor 1101 are implemented independently, the communication interface 1103, the memory 1102, and the processor 1101 may be connected to each other and perform communication with each other through buses. The bus may be an industry standard architecture (Industry Standard Architecture, abbreviated ISA) bus, an external device interconnect (Peripheral Component, abbreviated PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, abbreviated EISA) bus, among others. Buses may be divided into address buses, data buses, control buses, etc., but do not represent only one bus or one type of bus.
Alternatively, in a specific implementation, if the communication interface 1103, the memory 1102, and the processor 1101 are implemented integrally on a single chip, the communication interface 1103, the memory 1102, and the processor 1101 may complete communication through internal interfaces.
The electronic device provided in this embodiment is configured to execute the method executed in the foregoing embodiment, and its implementation principle is similar to that of the technical effect, which is not described herein.
The embodiment of the application also provides a readable storage medium, on which a computer program is stored, which when executed by a processor implements the technical solution provided by any of the foregoing embodiments.
The embodiment of the application also provides a computer program product, which comprises a computer program, and the computer program is used for realizing the technical scheme provided by any one of the method embodiments when being executed by a processor.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.
Claims (10)
1. A method of product production control based on a supply chain control system, comprising:
acquiring bill of materials data of each processing node in the product circulation process;
establishing a supply chain model associated among the processing nodes in the product circulation process according to the bill of materials data of the processing nodes;
and acquiring influence data of the current emergency on each processing node of the product, inputting the influence data into the supply chain model, and outputting recommended data corresponding to each processing node.
2. The method of claim 1, wherein the bill of materials data comprises: product design node bill of materials data, product purchase node bill of materials data, product production node bill of materials data, and product after-market node bill of materials data;
the step of establishing a supply chain model associated with each processing node in the product circulation process according to the bill of materials data of each processing node comprises the following steps:
according to the product design node bill of materials data, a first map of the association between components used by the product is established;
establishing a second map of the association between the components used by the product and the suppliers according to the product purchasing node bill of materials data;
establishing a third map of the association between the production flows of the products according to the bill of materials of the production nodes of the products;
establishing a fourth map of the association between the product and the sales client according to the product after-sales node bill of materials data;
and establishing a supply chain model associated among all the processing nodes in the product circulation process according to the first map, the second map, the third map and the fourth map.
3. The method of claim 2, wherein the components in the bill of materials data are coded and identified, and the components after coded and identified are classified according to a preset classification rule.
4. A method according to claim 3, wherein the obtaining the impact data of the current emergency on each processing node of the product comprises:
and acquiring demand degree data, crisis data existing in product production and product performance influence data, which are caused by the current emergency event input by a user in the product circulation process.
5. The method of claim 4, wherein inputting the impact data into the supply chain model and outputting recommendation data corresponding to the processing nodes comprises:
setting initialization parameters of the supply chain model;
determining influence result data of the current emergency on each processing node according to the initialization parameters, the demand data, the crisis data and the performance influence data;
evaluating the accuracy of the influence result data according to a preset prediction strategy to obtain prediction result data;
and outputting recommended data corresponding to each processing node according to the predicted result data.
6. The method according to claim 5, wherein evaluating the accuracy of the impact result data according to a preset prediction strategy to obtain prediction result data comprises:
and generating a radar chart containing the predicted result data according to the preset prediction strategy and the influence result data.
7. A supply chain control system for product production, comprising:
the basic resource layer is used for acquiring bill of materials data of each processing node in the product circulation process;
the core component layer is used for establishing a supply chain model associated with each processing node in the product circulation process according to the bill of materials data of each processing node;
and the visual interaction layer is used for acquiring the influence data of the current emergency on each processing node of the product, inputting the influence data into the supply chain model and outputting recommended data corresponding to each processing node.
8. An electronic device, comprising:
a processor, a memory, a communication interface;
the memory is used for storing executable instructions of the processor;
wherein the processor is configured to execute the supply chain control system-based product production control method of any one of claims 1 to 6 via execution of the executable instructions.
9. A readable storage medium having stored thereon a computer program, which when executed by a processor implements the supply chain control system based product production control method of any one of claims 1 to 6.
10. A computer program product comprising a computer program for implementing the supply chain control system-based product production control method of any one of claims 1 to 6 when executed by a processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211708758.1A CN116227835A (en) | 2022-12-29 | 2022-12-29 | Product production control method and system based on supply chain control system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211708758.1A CN116227835A (en) | 2022-12-29 | 2022-12-29 | Product production control method and system based on supply chain control system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116227835A true CN116227835A (en) | 2023-06-06 |
Family
ID=86581505
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211708758.1A Pending CN116227835A (en) | 2022-12-29 | 2022-12-29 | Product production control method and system based on supply chain control system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116227835A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116402480A (en) * | 2023-06-07 | 2023-07-07 | 成都普朗克科技有限公司 | Method and system for outputting inventory based on association rule self-built model |
| CN117114384A (en) * | 2023-09-08 | 2023-11-24 | 深圳达普信科技有限公司 | Multi-dimensional digital supply chain process optimization method based on big data |
| CN117151449A (en) * | 2023-10-30 | 2023-12-01 | 国网浙江省电力有限公司 | Data platform chain information interaction method based on full-scenario linkage |
-
2022
- 2022-12-29 CN CN202211708758.1A patent/CN116227835A/en active Pending
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116402480A (en) * | 2023-06-07 | 2023-07-07 | 成都普朗克科技有限公司 | Method and system for outputting inventory based on association rule self-built model |
| CN116402480B (en) * | 2023-06-07 | 2023-09-19 | 成都普朗克科技有限公司 | Method and system for outputting inventory based on association rule self-built model |
| CN117114384A (en) * | 2023-09-08 | 2023-11-24 | 深圳达普信科技有限公司 | Multi-dimensional digital supply chain process optimization method based on big data |
| CN117151449A (en) * | 2023-10-30 | 2023-12-01 | 国网浙江省电力有限公司 | Data platform chain information interaction method based on full-scenario linkage |
| CN117151449B (en) * | 2023-10-30 | 2024-02-06 | 国网浙江省电力有限公司 | Data platform chain information interaction method based on full-scenario linkage |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN116227835A (en) | Product production control method and system based on supply chain control system | |
| US11030709B2 (en) | Method and system for automatically creating and assigning assembly labor activities (ALAs) to a bill of materials (BOM) | |
| JP5875794B2 (en) | Method for managing quality of service for network participants in a networked business process and machine-readable medium storing instructions for performing such a method | |
| US11816715B2 (en) | Cloud computing smart solar configurator | |
| KR20180068174A (en) | contractor selection server for carrying out at construction work and method | |
| JP2012069098A (en) | Method and system for managing service quality of networked business process associated with network participant | |
| CN113034143A (en) | Block chain carbon transaction system and method considering load side carbon emission reduction | |
| CN110210980A (en) | A kind of driving behavior appraisal procedure, device and storage medium | |
| DE112020006969T5 (en) | Information processing device and information processing system | |
| CN112613724A (en) | Compliance assessment method and device for enterprise, storage medium and electronic equipment | |
| CN111429237A (en) | Order price determining method and device, server and storage medium | |
| CN111353671B (en) | Supply chain management method, device and system | |
| CN113159849B (en) | Carbon transaction system based on green coin and blue coin system | |
| CN106202542A (en) | A kind of method and device generating Vehicular battery fault job order | |
| CN110189185A (en) | A kind of rough house fitting-out work standard quotation system | |
| CN105260926A (en) | System for selectively purchasing fittings of mixing plant | |
| CN103562896B (en) | Apparatus for minimizing communication and integration complexity between software applications | |
| Hassan et al. | Blockchain networks for solar PV electric vehicles charging station to support and foster clean energy transition | |
| CN113487085B (en) | Method and device for predicting service life of equipment based on joint learning framework, computer equipment and computer readable storage medium | |
| CN116258557A (en) | Network distribution system based on chemical safety product channel | |
| Ye | Information infrastructure of engineering collaboration in a distributed virtual enterprise | |
| Amit et al. | Advances in Digital Manufacturing Systems | |
| CN114124977A (en) | Cross-tenant data sharing method and device and electronic equipment | |
| CN114138532A (en) | Remote fault diagnosis system based on project scheme simulation software architecture design | |
| Azhar et al. | Electric vehicle consumption dataset tailored to malaysian situation and implemented using rapid miner auto-model |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |