CN115829190A - Supply chain management system and method based on big data - Google Patents
Supply chain management system and method based on big data Download PDFInfo
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Abstract
The invention relates to the technical field of big data, in particular to a supply chain management system and a supply chain management method based on big data, which comprises the steps of respectively capturing all production accessory information needing to be purchased in a production process flow for each production business; extracting characteristic information from each target production accessory in each production business; respectively identifying and extracting the target production accessories with storage association relation in all the target production accessories of each production business branch line; performing association verification in each association accessory set, and performing warehousing planning on each warehousing space area for accessory storage in the target enterprise based on the distribution information of the association accessory sets obtained after the association verification; and bringing the plans into the same storage space area for storing all the digital supply chains corresponding to the target production accessories, and returning the digital supply chains to the same management center for supply chain information management.
Description
Technical Field
The invention relates to the technical field of big data, in particular to a supply chain management system and a supply chain management method based on big data.
Background
For some manufacturing enterprises, in the process of producing and processing a product, raw materials to be purchased are often in various types, and different raw materials often have different required storage conditions, if different raw materials are allocated to different storage intervals based on different storage conditions according to a conventional method, the maximum utilization of storage space cannot be realized, and the workload of storage management personnel in warehousing and ex-warehouse management of the raw materials is increased to a certain extent;
the digital supply chain is characterized in that all links in the supply chain are completed on an internet platform, efficiency improvement is realized by depending on timeliness and bidirectionality of the internet, if the digital supply chain constructed by raw materials and production processes participated by the raw materials are comprehensively considered, flexible scheduling management of an effective storage space area is realized, a plurality of storage problems can be solved for most manufacturing enterprises, and storage cost is reduced.
Disclosure of Invention
The present invention is directed to a supply chain management system and method based on big data, so as to solve the problems mentioned in the background art.
In order to solve the technical problems, the invention provides the following technical scheme: a big data-based supply chain management method comprises the following steps:
step S100: respectively collecting historical production and processing flow information of production branches corresponding to various production services in a target enterprise, and respectively capturing all production accessory information needing to be purchased in the production and processing flow for the various production services; respectively setting all production accessories in each production business, which need to occupy the internal storage space of a target enterprise, as target production accessories in each production business, and respectively extracting characteristic information from each target production accessory in each production business;
step S200: respectively extracting the characteristic information corresponding to each target production accessory in each production business branch line, and respectively identifying and extracting the target production accessories with storage association relation in all the target production accessories of each production business branch line on the basis of the characteristic information corresponding to each target production accessory;
step S300: information input is carried out on each warehousing space area used for accessory storage in the target enterprise; collecting all target production accessories in each production business, wherein the target production accessories have storage association relation with each other, and obtaining a plurality of association accessory sets corresponding to each production business; all the target production accessories in each associated accessory set have a warehousing association relationship with each other; performing association verification in each association accessory set, and performing storage planning on each storage space area for accessory storage in the target enterprise based on the distribution information of the association accessory sets obtained after the association verification;
step S400: respectively collecting information of each link of various target production accessories in the process from each historical order application to warehousing, and respectively constructing and obtaining a plurality of historical digital supply chains corresponding to the various target production accessories; and incorporating the plans into all the digital supply chains corresponding to the target production accessories stored in the same storage space area, and integrating the supply chains into the same management center for supply chain information management.
Further, step S100 includes:
step S101: when various production services are developed, all production procedures forming the corresponding production processing flow are subjected to procedure information extraction; the process information corresponding to each production process comprises execution sequence information, object information before process execution and intermediate product information obtained after process execution; respectively capturing production processes participated by target production accessories in each production business, acquiring process information corresponding to the production processes, and taking the process information as first characteristic information of each target production accessory in each production business;
step S102: respectively collecting storage and keeping requirements made by management personnel on each target production accessory in each production business based on the production process requirements of each production business; and extracting storage keywords respectively for storage and keeping requirements corresponding to each target production accessory in each production business, and taking the storage keyword set obtained by extraction and collection as second characteristic information of each target production accessory in each production business.
Further, step S200 includes:
step S201: respectively extracting first characteristic information and second characteristic information of each target production accessory in each production business; the method comprises the steps of setting a target production part a and a target production part B, wherein the production process in which the target production part a participates is A, and the production process in which the target production part B participates is B; when the production process A and the production process B belong to the production process flow corresponding to a certain production business, turning to step S202;
step S202: extracting and obtaining the execution sequence corresponding to the production process A based on the first characteristic information of the target production part a and the target production part b in the corresponding certain production business, and setting the execution sequence as P A Extracting the execution sequence corresponding to the production process B, and setting the execution sequence as P B (ii) a Simultaneously extracting object information before the production process A is executed, intermediate product information obtained after the production process A is executed, object information before the production process B is executed and intermediate product information obtained after the production process B is executed; extracting and obtaining a storage keyword set corresponding to the target production accessory a based on second characteristic information of the target production accessory a and the target production accessory b in the corresponding certain production business, and setting the storage keyword set as Q a Extracting a storage keyword set corresponding to the target production accessory b, and setting the storage keyword set as Q b ；
Step S203: when P is present A And P B Satisfies | P A -P B |=1,Q a =Q b Preliminarily judging that a storage association relation exists between the target production accessory a and the target production accessory b; when | P A -P B I =1, and P A <P B If the intermediate product obtained after the production process A is executed is the object before the production process B is executed, judging that the production process A and the production process B have process association in a certain production service, and finally judging that a storage association relationship exists between a target production accessory a and a target production accessory B; when | P A -P B I =1, and P A >P B If the intermediate product obtained after the production process B is executed is the object before the production process A is executed, judging that the production process A and the production process B have process association in a certain production service, and finally judging that a storage association relationship exists between a target production accessory a and a target production accessory B;
in the processing flow of some products, if execution sequence association exists in some processes and corresponding storage management requirements are the same, the flexible and mobile acquisition and storage plan can be adopted when production accessories corresponding to the processes are acquired and purchased, namely the accessories can be stored in the same storage space, the time for acquiring, purchasing and warehousing the accessories is staggered based on supply chain information, and the storage management of various production accessories on the same storage space is realized.
Further, step S300 includes:
step S301: a feedback manager evaluates the sorting difficulty value between every two target production accessories with storage association; traversing the types of the target production accessories contained in each associated accessory set and the sorting difficulty value between every two types of target production accessories;
step S302: if the number of types of target production accessories contained in a certain associated accessory set is 2, selecting the same storage space area for storing the two types of target production accessories when the sorting difficulty value between the two types of target production accessories is smaller than the difficulty threshold value; when the sorting difficulty value between the two target production accessories is larger than or equal to the difficulty threshold value, respectively selecting different storage space areas for storing the two target production accessories;
step S303: if the number of types of target production accessories contained in a certain associated accessory set is greater than 2, when the sorting difficulty value between two types of target production accessories G1 and G2 is greater than a difficulty threshold value, accumulating the sorting difficulty values between G1 and other target production accessories except G2 in the certain associated accessory set to obtain a sorting difficulty accumulated value G1, accumulating the sorting difficulty values between G2 and other target production accessories except G1 in the certain associated accessory set to obtain a sorting difficulty accumulated value G2, comparing G1 with G2 in a numerical value manner, removing the target production accessories with the large corresponding sorting difficulty accumulated value from the certain associated accessory set, and selecting the same storage space region H1 for storage for all target production accessories in the removed associated accessory set; and selecting storage space areas except H1 for each rejected target production accessory for storage.
Further, step S400 includes:
step S401: capturing all suppliers responding to various historical order applications of a certain target production accessory in all historical digital supply chains of the certain target production accessory, acquiring the average period duration from the response order application to warehousing of each supplier based on all the historical digital supply chains, and calculating the delayed delivery rate K = x/m of each supplier; wherein m represents the total times of transaction of each supplier selected by the target enterprise; x represents the total number of delayed deliveries of each supplier;
step S402: respectively setting minimum storage amounts for various target production accessories, preferentially pushing a supplier with the shortest average period time to a corresponding management center when the storage amount of a certain target production accessory reaches the corresponding minimum storage amount monitored by the same management center, preferentially pushing the supplier with the smallest delayed delivery rate to the corresponding management center when the average period time difference between two suppliers is smaller than a threshold value, and storing a new digital supply chain based on the finally selected supplier in the corresponding management center;
the method can ensure that the phenomenon of production flow interruption can not be caused when production consumption is abnormal in the branch line of the corresponding production business.
The system comprises an information acquisition module, a characteristic information extraction module, a storage association relation identification and judgment module, a storage planning management module and a supply chain information management module;
the information acquisition module is used for respectively acquiring historical production and processing flow information of production branches corresponding to various production services in a target enterprise and respectively capturing all production accessory information needing to be purchased in the production and processing flow for the various production services;
the characteristic information extraction module is used for respectively setting all production accessories which correspond to all production businesses and relate to planning, storing and managing the internal storage space of the target enterprise as target production accessories in all production businesses; extracting characteristic information from each target production accessory in each production business;
the storage association relation identification and judgment module is used for receiving the data in the characteristic information extraction module, and identifying and extracting the target production accessories with the storage association relation in all the target production accessories of each production business branch line based on the characteristic information corresponding to each target production accessory;
the warehousing planning management module is used for inputting information into each warehousing space area for accessory storage in the target enterprise; collecting all target production accessories in each production business, wherein the target production accessories have storage association relation with each other, and obtaining a plurality of association accessory sets corresponding to each production business; performing association verification in each associated accessory set, and performing warehousing planning on each warehousing space area for accessory storage in the target enterprise;
the supply chain information management module is used for respectively acquiring information of each link of various target production accessories in the process from each historical order application to warehousing, and respectively constructing and obtaining a plurality of historical digital supply chains corresponding to the various target production accessories; and bringing the plans into the same storage space area for storing all the digital supply chains corresponding to the target production accessories, and returning the digital supply chains to the same management center for supply chain information management.
Further, the storage incidence relation identification and judgment module comprises a storage incidence relation preliminary judgment unit and a storage incidence relation verification and judgment unit;
the storage incidence relation primary judging unit is used for receiving the data in the characteristic information extraction module and performing primary judgment and identification on the storage incidence relation in all target production accessories of each production business branch line;
and the storage incidence relation checking and judging unit is used for receiving the data in the characteristic information extraction module and the data in the storage incidence relation primary judging unit and checking the result obtained by the primary judging and identifying.
Further, the warehousing planning management module comprises a set association checking unit and a warehousing planning management unit;
the system comprises a set association checking unit, a storage association checking unit and a storage association checking unit, wherein the set association checking unit is used for collecting all target production accessories in each production business, which have storage association relations with each other, so as to obtain a plurality of association accessory sets corresponding to each production business; performing association check in each association accessory set;
and the warehousing planning management unit is used for receiving the data in the set association check unit and performing warehousing planning management on each warehousing space area for accessory storage in the target enterprise.
Compared with the prior art, the invention has the following beneficial effects: the invention can realize the maximum utilization value of the storage space region with limited area; the invention can realize the elastic storage of different production accessories to be stored in the same storage space region in the storage space region with limited area based on the relation between the production processes participated by each production accessory to be stored and the storage condition requirement required by each production accessory to be stored, and improves the storage management efficiency by effectively staggering the purchasing and storage time of the production accessories.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic flow chart of a big data based supply chain management method of the present invention;
fig. 2 is a schematic structural diagram of a big data-based supply chain management system according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-2, the present invention provides a technical solution: a big data-based supply chain management method comprises the following steps:
step S100: respectively collecting historical production and processing flow information of production branches corresponding to various production services in a target enterprise, and respectively capturing all production accessory information needing to be purchased in the production and processing flow for the various production services; respectively setting all production accessories in each production business, which need to occupy the internal storage space of a target enterprise, as target production accessories in each production business, and respectively extracting characteristic information from each target production accessory in each production business;
wherein, step S100 includes:
step S101: when various production services are developed, all production procedures forming the corresponding production processing flow are subjected to procedure information extraction; the process information corresponding to each production process comprises execution sequence information, object information before process execution and intermediate product information obtained after process execution; respectively capturing production processes participated by target production accessories in each production business, acquiring process information corresponding to the production processes, and taking the process information as first characteristic information of each target production accessory in each production business;
for example, a production service corresponds to a flow line or a production line for processing a certain product;
step S102: respectively collecting storage and keeping requirements made by management personnel on each target production accessory in each production business based on the production process requirements of each production business; extracting storage keywords respectively for storage and keeping requirements corresponding to target production accessories in each production business, and taking a storage keyword set obtained by extraction and collection as second characteristic information of each target production accessory in each production business;
step S200: respectively extracting the characteristic information corresponding to each target production accessory in each production business branch line, and respectively identifying and extracting the target production accessories with storage association relation in all the target production accessories of each production business branch line on the basis of the characteristic information corresponding to each target production accessory;
wherein, step S200 includes:
step S201: respectively extracting first characteristic information and second characteristic information of each target production accessory in each production business; the method comprises the steps of setting a target production part a and a target production part B, wherein the production process in which the target production part a participates is A, and the production process in which the target production part B participates is B; when the production process A and the production process B belong to the production process flow corresponding to a certain production business, turning to step S202;
step S202: extracting and obtaining the execution sequence corresponding to the production process A based on the first characteristic information of the target production part a and the target production part b in the corresponding certain production business, and setting the execution sequence as P A Extracting the execution sequence corresponding to the production process B, and setting the execution sequence as P B (ii) a Simultaneously extracting object information before the production process A is executed, intermediate product information obtained after the production process A is executed, object information before the production process B is executed and intermediate product information obtained after the production process B is executed; extracting and obtaining a storage keyword set corresponding to the target production accessory a based on second characteristic information of the target production accessory a and the target production accessory b in the corresponding certain production business, and setting the storage keyword set as Q a Extracting to obtain a storage keyword set corresponding to the target production part b, and setting the storage keyword set as Q b ；
Step S203: when P is present A And P B Satisfies | P A -P B |=1,Q a =Q b Preliminarily judging that a storage association relation exists between the target production accessory a and the target production accessory b; when | P A -P B I =1, and P A <P B If the intermediate product obtained after the production process A is executed is the object before the production process B is executed, judging that the production process A and the production process B have process association in a certain production service, and finally judging that a storage association relationship exists between a target production accessory a and a target production accessory B; when | P A -P B I =1, and P A >P B If the intermediate product obtained after the production process B is executed is the object before the production process A is executed, the intermediate product is judged to have process association between the production process A and the production process B in a corresponding production business, and finally the target production accessory a and the target are judgedThe production accessories b have storage association relation;
step S300: information input is carried out on each warehousing space area used for accessory storage in the target enterprise; collecting all target production accessories in each production business, wherein the target production accessories have storage association relation with each other, and obtaining a plurality of association accessory sets corresponding to each production business; all the target production accessories in each associated accessory set have a warehousing association relationship with each other; performing association verification in each association accessory set, and performing warehousing planning on each warehousing space area for accessory storage in the target enterprise based on the distribution information of the association accessory sets obtained after the association verification;
wherein, step S300 includes:
step S301: a feedback manager evaluates the sorting difficulty value between every two target production accessories with storage association; traversing the types of the target production accessories contained in each associated accessory set and the sorting difficulty value between every two types of target production accessories;
step S302: if the number of types of target production accessories contained in a certain associated accessory set is 2, selecting the same storage space area for storing the two types of target production accessories when the sorting difficulty value between the two types of target production accessories is smaller than the difficulty threshold value; when the sorting difficulty value between the two target production accessories is larger than or equal to the difficulty threshold value, respectively selecting different storage space areas for storing the two target production accessories;
step S303: if the number of types of target production accessories contained in a certain associated accessory set is greater than 2, when the sorting difficulty value between two types of target production accessories G1 and G2 is greater than a difficulty threshold value, accumulating the sorting difficulty values between G1 and other target production accessories except G2 in the certain associated accessory set to obtain a sorting difficulty accumulated value G1, accumulating the sorting difficulty values between G2 and other target production accessories except G1 in the certain associated accessory set to obtain a sorting difficulty accumulated value G2, comparing G1 with G2 in a numerical value mode, removing the target production accessories with the corresponding sorting difficulty accumulated value from the certain associated accessory set, and selecting the same storage space region H1 for storing all target production accessories in the removed associated accessory set; selecting storage space areas except H1 for all the removed target production accessories for storage;
step S400: respectively collecting information of each link of various target production accessories in the process from each historical order application to warehousing, and respectively constructing and obtaining a plurality of historical digital supply chains corresponding to the various target production accessories; all the digital supply chains corresponding to the target production accessories which are planned to be brought into the same storage space area for storage are integrated into the same management center for supply chain information management;
wherein, step S400 includes:
step S401: capturing all suppliers responding to each historical order application of a certain target production accessory in all historical digital supply chains of the certain target production accessory, acquiring the average cycle time from the response order application to warehousing of each supplier based on all historical digital supply chains, and calculating the deferred delivery rate K = x/m of each supplier, wherein m represents the total times of selecting each supplier for trading by a target enterprise; x represents the total number of delayed deliveries of each supplier;
step S402: respectively setting minimum storage amounts for various target production accessories, preferentially pushing a supplier with the shortest average period time to a corresponding management center when the storage amount of a certain target production accessory reaches the corresponding minimum storage amount monitored by the same management center, preferentially pushing the supplier with the smallest delayed delivery rate to the corresponding management center when the average period time difference between two suppliers is smaller than a threshold value, and storing a new digital supply chain based on the finally selected supplier in the corresponding management center;
for example, in a management center corresponding to a storage space region, it is monitored that the storage amount of the target production part x1 reaches the minimum storage amount of the target production part x 1; preferentially pushing the supplier with the shortest average period time length to the corresponding management center, and preferentially selecting the supplier with the smallest delay delivery rate between the two suppliers as a final supplier to initiate order application to the final supplier when the difference value between the average period time lengths of the two suppliers is only 1 day so as to avoid the material shortage phenomenon;
the system comprises an information acquisition module, a characteristic information extraction module, a storage association relation identification and judgment module, a storage planning management module and a supply chain information management module;
the information acquisition module is used for respectively acquiring historical production and processing flow information of production branches corresponding to various production services in a target enterprise and respectively capturing all production accessory information needing to be purchased in the production and processing flow for the various production services;
the characteristic information extraction module is used for respectively setting all production accessories related to planning, storing and managing the internal storage space of the target enterprise, which correspond to each production business, as target production accessories in each production business; extracting characteristic information from each target production accessory in each production business;
the storage association relation identification and judgment module is used for receiving the data in the characteristic information extraction module, and identifying and extracting the target production accessories with the storage association relation in all the target production accessories of each production business branch line based on the characteristic information corresponding to each target production accessory;
the storage incidence relation identification and judgment module comprises a storage incidence relation preliminary judgment unit and a storage incidence relation verification and judgment unit;
the storage incidence relation primary judging unit is used for receiving the data in the characteristic information extraction module and performing primary judgment and identification on the storage incidence relation in all target production accessories of each production business branch line;
the storage association relation checking and judging unit is used for receiving the data in the characteristic information extraction module and the data in the storage association relation primary judging unit and checking a result obtained by primary judging and identifying;
the warehousing planning management module is used for inputting information into each warehousing space area for accessory storage in the target enterprise; collecting all target production accessories in each production business, wherein the target production accessories have storage association relation with each other, and obtaining a plurality of association accessory sets corresponding to each production business; performing correlation verification in each correlation accessory set, and performing storage planning on each storage space area for accessory storage in the target enterprise;
the warehousing planning management module comprises a set association checking unit and a warehousing planning management unit;
the system comprises a set association checking unit, a storage association checking unit and a storage association checking unit, wherein the set association checking unit is used for collecting all target production accessories in each production business, which have storage association relation with each other, so as to obtain a plurality of association accessory sets corresponding to each production business; performing association check in each association accessory set;
the warehousing planning management unit is used for receiving the data in the set association check unit and performing warehousing planning management on each warehousing space area for accessory storage in the target enterprise;
the supply chain information management module is used for respectively acquiring information of each link of various target production accessories in the process from each historical order application to warehousing, and respectively constructing and obtaining a plurality of historical digital supply chains corresponding to the various target production accessories; and bringing the plans into the same storage space area for storing all the digital supply chains corresponding to the target production accessories, and returning the digital supply chains to the same management center for supply chain information management.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A big data based supply chain management method, the method comprising:
step S100: respectively collecting historical production and processing flow information of production branches corresponding to various production services in a target enterprise, and respectively capturing all production accessory information needing to be purchased in the production and processing flow for the various production services; respectively setting all production accessories in each production business, which need to occupy the internal storage space of the target enterprise, as target production accessories in each production business, and respectively extracting characteristic information from each target production accessory in each production business;
step S200: respectively extracting the characteristic information corresponding to each target production accessory in each production business branch line, and respectively identifying and extracting the target production accessories with storage association relation in all the target production accessories of each production business branch line on the basis of the characteristic information corresponding to each target production accessory;
step S300: inputting information into each warehousing space area for accessory storage in the target enterprise; collecting all target production accessories in each production business, wherein the target production accessories have storage association relation with each other, and obtaining a plurality of association accessory sets corresponding to each production business; all the target production accessories in each associated accessory set have a warehousing association relationship with each other; performing association verification in each association accessory set, and performing warehousing planning on each warehousing space area for accessory storage in the target enterprise based on the distribution information of the association accessory sets obtained after the association verification;
step S400: respectively collecting information of each link of various target production accessories in the process from each historical order application to warehousing, and respectively constructing and obtaining a plurality of historical digital supply chains corresponding to the various target production accessories; and incorporating the plans into all the digital supply chains corresponding to the target production accessories stored in the same storage space area, and integrating the supply chains into the same management center for supply chain information management.
2. The big data based supply chain management method according to claim 1, wherein step S100 comprises:
step S101: when various production services are developed, all production procedures forming the corresponding production processing flow are subjected to procedure information extraction; the process information corresponding to each production process comprises execution sequence information, object information before process execution and intermediate product information obtained after process execution; respectively capturing production processes participated by target production accessories in each production business, acquiring process information corresponding to the production processes, and taking the process information as first characteristic information of each target production accessory in each production business;
step S102: respectively collecting storage and keeping requirements made by management personnel on each target production accessory in each production business based on the production process requirements of each production business; and extracting storage keywords from the storage and keeping requirements corresponding to the target production accessories in the production services respectively, and taking the storage keyword set obtained by extraction and collection as second characteristic information of the target production accessories in the production services.
3. The big data based supply chain management method according to claim 2, wherein the step S200 comprises:
step S201: respectively extracting first characteristic information and second characteristic information of each target production accessory in each production business; the method comprises the steps of setting a target production part a and a target production part B, wherein the production process in which the target production part a participates is A, and the production process in which the target production part B participates is B; when the production process A and the production process B belong to the production process flow corresponding to a certain production business, turning to step S202;
step S202: extracting and obtaining the execution sequence corresponding to the production process A based on the first characteristic information of the target production part a and the target production part b in the corresponding certain production business, and setting the execution sequence as P A Extracting the execution sequence corresponding to the production process B, and setting the execution sequence as P B (ii) a Simultaneously extracting object information before the production process A is executed, intermediate product information obtained after the production process A is executed, object information before the production process B is executed and intermediate product information obtained after the production process B is executed; extracting and obtaining a storage keyword set corresponding to the target production accessory a based on second characteristic information of the target production accessory a and the target production accessory b in the corresponding certain production business, and setting the storage keyword set as Q a Extracting a storage keyword set corresponding to the target production accessory b, and setting the storage keyword set as Q b ；
Step S203: when P is present A And P B Satisfies | P A -P B |=1,Q a =Q b Preliminarily judging that a storage association relation exists between the target production accessory a and the target production accessory b; when | P A -P B I =1, and P A <P B If the intermediate product obtained after the production process A is executed is the object before the production process B is executed, judging that the production process A and the production process B have process association in a certain production service, and finally judging that a storage association relationship exists between a target production accessory a and a target production accessory B; when | P A -P B I =1, and P A >P B If the intermediate product obtained after the production process B is executed is the object before the production process A is executed, the process association between the production process A and the production process B in the corresponding certain production business is judged, and finally the warehousing association relationship between the target production accessory a and the target production accessory B is judged.
4. The big data-based supply chain management method according to claim 3, wherein step S300 comprises:
step S301: a feedback manager evaluates the sorting difficulty value between every two target production accessories with storage association; traversing the types of the target production accessories contained in each associated accessory set and the sorting difficulty value between every two types of target production accessories;
step S302: if the number of types of target production accessories contained in a certain associated accessory set is 2, selecting the same storage space area for storing two types of target production accessories when the sorting difficulty value between the two types of target production accessories is smaller than the difficulty threshold value; when the sorting difficulty value between the two target production accessories is larger than or equal to the difficulty threshold value, respectively selecting different storage space areas for storing the two target production accessories;
step S303: if the number of types of target production accessories contained in a certain associated accessory set is greater than 2, when the sorting difficulty value between two types of target production accessories G1 and G2 is greater than a difficulty threshold value, accumulating the sorting difficulty values between G1 and other target production accessories except G2 in the certain associated accessory set to obtain a sorting difficulty accumulated value G1, accumulating the sorting difficulty values between G2 and other target production accessories except G1 in the certain associated accessory set to obtain a sorting difficulty accumulated value G2, comparing G1 with G2 in a numerical value manner, removing the target production accessories with the corresponding sorting difficulty accumulated values from the certain associated accessory set, and selecting and storing the same storage space region H1 for all target production accessories in the associated accessory set obtained after removal; and selecting storage space areas except H1 for each rejected target production accessory for storage.
5. The big data-based supply chain management method according to claim 4, wherein the step S400 comprises:
step S401: capturing all suppliers responding to various historical order applications of a certain target production accessory in all historical digital supply chains of the certain target production accessory, acquiring the average cycle time from the response order application to warehousing of each supplier based on all the historical digital supply chains, and calculating the deferred delivery rate K = x/m of each supplier, wherein m represents the total times of selecting each supplier for trading by a target enterprise; x represents the total number of delayed deliveries of each supplier;
step S402: the method comprises the steps of setting the lowest storage quantity for various target production accessories respectively, when monitoring that the storage quantity of a certain target production accessory reaches the corresponding lowest storage quantity in the same management center, preferentially pushing a supplier with the shortest average period time to the corresponding management center, when the difference value of the average period time between the two suppliers is smaller than a threshold value, preferentially pushing the supplier with the smallest delayed delivery rate to the corresponding management center, and storing a new digital supply chain based on the finally selected supplier in the corresponding management center.
6. A big data-based supply chain management system is applied to the big data-based supply chain management method of any one of claims 1 to 5, and is characterized by comprising an information acquisition module, a characteristic information extraction module, a warehousing association relation identification and judgment module, a warehousing planning management module and a supply chain information management module;
the information acquisition module is used for respectively acquiring historical production and processing flow information of production branches corresponding to various production services in a target enterprise and respectively capturing all production accessory information needing to be purchased externally in the production and processing flow for the various production services;
the characteristic information extraction module is used for respectively setting all production accessories related to planning, storing and managing the internal storage space of the target enterprise, which correspond to each production business, as target production accessories in each production business; extracting characteristic information from each target production accessory in each production business;
the storage association relation identification and judgment module is used for receiving the data in the characteristic information extraction module, and respectively identifying and extracting the target production accessories with the storage association relation in all the target production accessories of each production business branch line based on the characteristic information corresponding to each target production accessory;
the warehousing planning management module is used for inputting information into each warehousing space area for accessory storage in the target enterprise; collecting all target production accessories in each production business, wherein the target production accessories have storage association relation with each other, and obtaining a plurality of association accessory sets corresponding to each production business; performing association verification in each associated accessory set, and performing warehousing planning on each warehousing space area for accessory storage in the target enterprise;
the supply chain information management module is used for respectively acquiring information of each link of various target production accessories in the process from each historical order application to warehousing, and respectively constructing and obtaining a plurality of historical digital supply chains corresponding to the various target production accessories; and incorporating the plans into all the digital supply chains corresponding to the target production accessories stored in the same storage space area, and integrating the supply chains into the same management center for supply chain information management.
7. The big data-based supply chain management system according to claim 6, wherein the warehousing incidence relation identification and judgment module comprises a warehousing incidence relation preliminary judgment unit and a warehousing incidence relation verification and judgment unit;
the storage incidence relation primary judging unit is used for receiving the data in the characteristic information extraction module and performing primary judgment and identification on the storage incidence relation in all target production accessories of each production business branch line;
and the warehousing incidence relation checking and judging unit is used for receiving the data in the characteristic information extraction module and the data in the warehousing incidence relation preliminary judging unit and checking the result obtained by preliminary judgment and identification.
8. The big data-based supply chain management system according to claim 6, wherein the warehousing plan management module comprises a set association checking unit, a warehousing plan management unit;
the set association checking unit is used for collecting all target production accessories in each production business, which have storage association relation with each other, so as to obtain a plurality of association accessory sets corresponding to each production business; performing association check in each association accessory set;
and the warehousing planning management unit is used for receiving the data in the set association checking unit and performing warehousing planning management on each warehousing space area for accessory storage in the target enterprise.
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