Big data-based material supply chain procurement management method and system

Abstract

This invention relates to the field of procurement management technology, specifically to a big data-based material supply chain procurement management method and system. The method includes the following steps: comparing inventory and outbound frequency, classifying material response levels, generating a procurement list, calculating delivery intervals and assessing delivery risks, screening materials with conflicting schedules, eliminating irreplaceable routes, filtering out suppliers with low qualifications and poor performance, matching quotas and tasks, and generating a procurement list. In this invention, dynamic comparison of current inventory levels and average daily outbound frequency identifies materials requiring priority response, avoiding response delays caused by static inventory warnings. Combined with multi-source path registration, it effectively identifies material supply relationships with substitutable capabilities. By analyzing qualification document update times and performance behavior, it eliminates ineffective and poorly performing suppliers, achieving optimal matching of supply relationships and enhancing the target adaptability and overall coordination of procurement execution and response rhythm.

Description

Technical Field

[0001] This invention relates to the field of procurement management technology, and in particular to a material supply chain procurement management method and system based on big data. Background Technology

[0002] Procurement management technology falls at the intersection of enterprise operations management and supply chain management, encompassing multiple aspects such as procurement strategy formulation, procurement process optimization, supplier management, procurement execution and supervision, cost control, and contract management. Procurement management leverages big data analytics, artificial intelligence, the Internet of Things, and blockchain to achieve accurate forecasting of procurement plans, dynamic evaluation of supplier performance, standardization and intelligentization of procurement processes, and cross-system data collaboration and visualization. This technology is widely applied in the acquisition and management of materials and services in industries such as manufacturing, power, transportation, and construction, aiming to reduce procurement costs, shorten procurement cycles, and improve procurement quality and transparency, thereby enhancing enterprises' resource acquisition capabilities and market responsiveness in complex supply chain environments.

[0003] Among them, the materials supply chain procurement management method is a way to improve the efficiency and quality of materials procurement management and decision-making. Its main purpose is to collect, clean, model, and analyze procurement-related data throughout the entire lifecycle of materials to achieve multiple functions such as procurement demand forecasting, procurement plan optimization, intelligent supplier evaluation and selection, and inventory structure adjustment, supporting enterprises in achieving a low-cost, high-efficiency, and highly responsive procurement management model. The method can be applied to enterprise-level procurement platforms, regional collaborative procurement systems, and group-level centralized material procurement systems to improve the automation and intelligence level of procurement work.

[0004] Traditional management methods automate procurement management through data collection and analysis. However, they lack a dynamic response mechanism based on actual outbound frequency in judging outbound rhythm, resulting in slow response to high-frequency outbound materials in certain phases. In terms of supplier evaluation, they do not refine the dimensions of abnormal arrival types and arrival time, making it difficult to accurately identify delivery fluctuations. They also lack systematic analysis of the time coupling between procurement plans and warehousing windows, which can easily lead to material backlogs or gaps due to mismatches between order placement time and receiving cycle. Furthermore, in the selection of supply relationships, they neglect the joint examination of alternative paths and supplier qualification status, which can easily lead to the inclusion of supply chain nodes without alternative capabilities or with expired qualifications in procurement allocation, resulting in the risk of materials not being delivered on time. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing a big data-based material supply chain procurement management method and system.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a big data-based material supply chain procurement management method, comprising the following steps:

[0007] S1: Obtain the material records of the procurement warehouse, call the current inventory quantity field and the average daily outbound frequency field of each material, combine them with the material distribution frequency field, aggregate the material items according to the procurement response level, and generate a list of procurement materials to be distributed.

[0008] S2: Based on the material code field in the list of materials to be dispatched, determine the frequency and time span of delivery deviations of the same supplier under the current material code, aggregate the delivery anomalies of each supplier by material code and sort and classify them to generate a supply stage risk level table.

[0009] S3: Based on the aforementioned supply stage risk level table, filter out material items whose procurement time conflicts with or is disconnected from the receiving window, call the multi-source supply path registration field, filter out records of irreplaceable supply paths, and generate a supply rhythm conflict material record table.

[0010] S4: Based on the material code field in the supply rhythm conflict material record table, eliminate suppliers whose qualification updates exceed the set interval period or whose delivery date deviates from the ranking, establish a one-to-many relationship with the remaining suppliers according to the material code, and generate a material preferred supply matching table.

[0011] As a further embodiment of the present invention, the list of procurement materials to be dispatched includes material classification labels, response level groupings, and inventory consumption differences; the supply stage risk level table includes supplier risk level identifiers, arrival offset intervals, and abnormal cumulative frequency labels; the supply rhythm conflict material record table includes procurement order time offset items, receiving window conflict identifiers, and adjustable path markings; and the preferred supply matching table includes performance stability level, qualification cycle update identifiers, and material supply allocation mapping.

[0012] As a further aspect of the present invention, the step of obtaining the list of purchased materials to be distributed specifically includes:

[0013] S101: Obtain the material records of the procurement warehouse. The material records include the material inventory ledger, historical outbound details and procurement instruction execution record table. Call the current inventory quantity field of each material in the material inventory ledger and the average daily outbound frequency field of the same material in the historical outbound details to bind the fields. Establish an inventory frequency control group based on the field binding results. Filter the material items in the control group whose current inventory quantity is lower than the average daily outbound frequency multiplied by the period in days to obtain the inventory supply and demand offset material set.

[0014] S102: Based on the material code field of the inventory supply and demand offset material set, obtain the procurement instruction execution record table in the procurement management record, extract the instruction issuance timestamp field corresponding to each material in the record table, calculate the interval period length between adjacent timestamps, perform frequency statistics on materials with the same code according to the interval period length field, and perform joint mapping between the frequency results and the inventory supply and demand offset material set to obtain the issuance density label set within the period.

[0015] S103: Call the distribution density label value of each material in the distribution density label set within the period, assign the corresponding procurement response level identifier label to the material item according to the distribution level range set in the material response rules, bind the response level label to the original material code, establish a structured record set including code field, supply and demand offset attribute, and response level field, and generate a list of procurement materials to be distributed.

[0016] As a further aspect of the present invention, the steps for obtaining the supply stage risk level table are specifically as follows:

[0017] S201: Based on the material code field in the list of materials to be dispatched, obtain the delivery record table and receipt registration book of all suppliers in the last three procurement cycles, call the departure time field in the delivery record table and the receipt confirmation time field in the receipt registration book to perform field mapping, construct a time comparison set using the departure and receipt times under the same material and supplier dimensions, calculate the time difference in each record, obtain the supply and transportation cycle of each material, and establish the arrival time interval information;

[0018] S202: Based on the material and supplier fields in the delivery time interval information, call the abnormal identification field of the same period and the same material in the abnormal delivery record book, compare the abnormal identification of each material under each supplier dimension, count the number and location of abnormal records of each supplier under a single material dimension, and jointly label them with the corresponding time period in the delivery time interval information to generate a delivery deviation attribution tag set.

[0019] S203: Call the abnormal frequency label and transportation cycle value of each supplier under the same material dimension in the delivery deviation attribution label set, construct a multi-supplier record cluster indexed by material code, classify and sort the abnormal frequency and cycle values ​​in each record cluster, and group and label the delivery risk level between suppliers and material items according to the sorting level to generate a supply stage risk level table.

[0020] As a further aspect of the present invention, the steps for obtaining the supply rhythm conflict material record table are specifically as follows:

[0021] S301: Based on the supplier and material code combination marked as high risk in the supply stage risk level table, obtain the current cycle procurement plan table for the corresponding material, extract the order time field, and obtain the receiving window cycle field for the corresponding material from the warehouse scheduling window record. Associate and bind the two fields according to the material code, judge the time sequence of each record, filter out material items whose order time is later than the receiving window start time or earlier than the receiving window end time, and establish a time-disjointed material index set.

[0022] S302: Call the material code field and supplier code field of the materials in the time-disjointed material index set, obtain the supply path registration field in the multi-source path information table, retrieve the path substitution capability status value bound to each record, filter out records with path substitution capability status of non-substitutable, and retain the material and supplier joint index for the filtered records to generate an adjustable path conflict record set.

[0023] S303: Based on the material and supplier joint index information in the adjustable path conflict record set, perform intersection matching with the time-disjointed material index set, extract material items that meet the time conflict conditions and have adjustable path attributes, and construct a composite tag field including procurement time, receiving cycle and path substitution status for the material items to generate a supply rhythm conflict material record table.

[0024] As a further aspect of the present invention, the step of obtaining the preferred supply matching table of materials specifically includes:

[0025] S401: Based on the material code field and supplier number field in the supply rhythm conflict material record table, obtain the supplier qualification update records within the current valid procurement cycle, extract the qualification document update time field, call the set qualification validity interval period parameter, calculate the time difference between the update time of each record and the current date, determine whether the difference exceeds the qualification validity threshold, filter the qualified records, and generate a valid qualification supplier index set.

[0026] S402: Call the supplier number information in the valid qualified supplier index set, extract the average delivery date offset field of the corresponding supplier in this period from the performance behavior log, perform numerical normalization on the delivery date offset value, sort according to the normalization result, and remove suppliers with lower offset ranking according to the offset tolerance threshold to obtain a stable performance supplier index set.

[0027] S403: Based on the supplier IDs and bound material codes in the stable fulfillment supplier index set, aggregate the supplier IDs at the material level, construct a one-to-many supplier mapping structure for each material, construct a mapping table structure according to the material ID, and generate a material preferred supply matching table.

[0028] As a further aspect of the present invention, the method further includes the following steps:

[0029] S5: Based on the pairing information of each group of materials and suppliers in the material preferred supply matching table, call the current quota utilization rate field and the procurement task demand field of each supplier's corresponding materials in the order management record, and perform item-by-item mapping and matching in combination with the supply item name and material name in the pairing information to obtain the supplier and material combination that meets the allocation conditions and generate the periodic procurement allocation execution list.

[0030] The periodic procurement allocation execution list includes procurement available share indicators, a list of execution material numbers, and a list of allocation target suppliers.

[0031] As a further aspect of the present invention, the step of obtaining the periodic procurement allocation execution list specifically includes:

[0032] S501: Based on the pairing information of each group of materials and suppliers in the material selection and supply matching table, call the quota utilization rate field and the procurement task requirement field in the order management record, perform difference calculation on each record and compare it with the procurement capacity threshold parameter to determine whether the supplier has the procurement capacity below the limit, filter the material supply combination that meets the conditions, and generate an effective procurement capacity combination set.

[0033] S502: Based on the supplier and material combination information in the effective procurement capacity combination set, extract the supply item name field and the material name field, compare the field content item by item and construct a mapping consistency identifier, remove combinations with mapping failures, obtain a structurally stable supply pairing list, and establish a stable supply mapping pair list.

[0034] S503: Call the stable supply mapping pair for each group of material codes and supplier numbers in the list, combine the corresponding quota utilization rate and task demand data, calculate the periodic adaptation strength value between materials and suppliers, filter material supply combinations with periodic adaptation strength values ​​less than the scheduling threshold, and establish a periodic procurement and allocation execution list.

[0035] As a further aspect of the present invention, the formula for calculating the periodic compatibility strength value between materials and suppliers is specifically as follows:

[0036] ;

[0037] in, Indicates supplies With suppliers The periodic adaptation strength value between them Indicates supplier In the current cycle, materials Quota utilization rate Indicates supplier Purchasing capacity threshold Indicates supplier Materials during the current cycle The required procurement volume. Indicates supplier Materials during the current cycle The required procurement volume. Indicates supplies The total number of matching suppliers in the current cycle. Indicates supplies The normalized value of the bound supply item name's encoded value. Indicates supplier The normalized value of the coded value of the provided supply item name.

[0038] A big data-based materials supply chain procurement management system, wherein the big data-based materials supply chain procurement management system is used to implement the above-mentioned big data-based materials supply chain procurement management method, the system comprising:

[0039] The procurement demand analysis module obtains the material records of the procurement warehouse, calls the current inventory quantity field and the average daily outbound frequency field of each material, and combines them with the material distribution frequency field to aggregate the material items according to the procurement response level and generate a list of procurement materials to be distributed.

[0040] The supply risk assessment module, based on the material code field in the list of materials to be dispatched, determines the frequency and time span of delivery deviations of the same supplier under the current material code, aggregates the delivery anomalies of each supplier by material code, sorts and classifies them, and generates a supply stage risk level table.

[0041] The supply conflict identification module, based on the supply stage risk level table, filters out material items whose procurement time and receiving window conflict or are disconnected, calls the multi-source supply path registration field, filters out records of irreplaceable supply paths, and generates a supply rhythm conflict material record table.

[0042] The supplier matching module, based on the material code field in the supply rhythm conflict material record table, removes suppliers whose qualification updates exceed the set interval period or whose delivery date deviates from the ranking, establishes a one-to-many relationship with the remaining suppliers according to the material code, and generates a material preferred supply matching table.

[0043] The procurement execution and organization module, based on the pairing information of each group of materials and suppliers in the material selection and supply matching table, calls the current quota utilization rate field and the procurement task demand field of each supplier's corresponding materials in the order management record, and performs item-by-item mapping and matching with the supply item name and material name in the pairing information to obtain the supplier and material combination that meets the allocation conditions and generate the periodic procurement allocation execution list.

[0044] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0045] In this invention, materials requiring priority response are selected based on a dynamic comparison of current inventory levels and average daily outbound frequency, avoiding response delays caused by static inventory warnings. By categorizing and summarizing the frequency of procurement order issuance and combining it with procurement response levels, materials are aggregated to achieve dynamic prioritization of procurement. Delivery interval analysis is constructed based on delivery and receipt records, and supply deviation assessment is completed by combining anomaly indicators, achieving quantitative classification of risks in the material supply stage. By matching procurement time with receiving window, materials with conflicting supply rhythms are identified. By combining multi-source path registration, material supply relationships with substitutable capabilities are effectively identified. Suppliers with failures and performance deviations are eliminated based on qualification document update time and performance behavior analysis, achieving optimal matching of supply relationships. Based on quota utilization rate and procurement task requirements, the cyclical procurement capacity and task are accurately matched, enhancing the target adaptability of procurement execution and the overall coordination of response rhythm. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a schematic diagram of the workflow of the present invention;

[0048] Figure 2 This is a detailed flowchart of S1 of the present invention;

[0049] Figure 3 This is a detailed flowchart of the S2 process of the present invention;

[0050] Figure 4 This is a detailed flowchart of the S3 process of the present invention;

[0051] Figure 5 This is a detailed flowchart of the S4 process of the present invention;

[0052] Figure 6 This is a detailed flowchart of S5 of the present invention;

[0053] Figure 7 This is a system flowchart of the present invention. Detailed Implementation

[0054] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0055] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0056] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0057] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0058] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0059] Please see Figure 1 This invention provides a technical solution: a big data-based material supply chain procurement management method, comprising the following steps:

[0060] S1: Obtain the material records of the procurement warehouse. The material records include the material inventory ledger, historical outbound details and procurement instruction execution record table. Compare the current inventory quantity field of each material in the material inventory ledger with the daily average outbound frequency field of the corresponding material in the historical outbound details. Determine the material items whose current inventory quantity does not cover the recent outbound rhythm. According to the procurement instruction, classify and summarize the distribution frequency field of the same material in the record table. Aggregate the material items according to the procurement response level to generate a list of procurement materials to be dispatched.

[0061] S2: Based on the material code field in the list of materials to be dispatched, obtain the delivery record table, receipt and signing registration book and abnormal arrival record book of all suppliers for the materials in the past three cycles. Extract the departure time field from the delivery record table and the signing confirmation time field from the receipt and signing registration book, calculate the arrival time interval, and call the abnormal identification field of the corresponding materials in the abnormal arrival record book to determine the frequency and time span of the arrival deviation of the same supplier under the current material code. Aggregate the delivery abnormalities of each supplier by material code and sort and classify them to generate a supply stage risk level table.

[0062] The anomaly identification field contains standard logistics arrival anomaly registration information, including anomaly categories such as transportation delays, incorrect delivery, and damage reports;

[0063] S3: Based on the suppliers and material combinations marked as high-risk in the supply stage risk level table, obtain the order time field of the current cycle procurement plan corresponding to the material code, and extract the material receiving window cycle field from the warehouse scheduling window record. Then, judge the time sequence of the two fields one by one, filter out material items whose procurement time and receiving window conflict or are disconnected, call the multi-source supply path registration field, filter out records of irreplaceable supply paths, and generate a supply rhythm conflict material record table.

[0064] S4: Based on the material code field in the supply rhythm conflict material record table, obtain the supplier qualification update record and historical performance behavior log of each supplier in the current effective period, call the qualification document update time field in the qualification record to judge the validity, and extract the average delivery date offset field in the performance log to sort the values, remove suppliers whose qualification update exceeds the set interval period or whose delivery date offset ranks low, establish a one-to-many relationship with the remaining suppliers according to the material code, and generate a material preferred supply matching table;

[0065] The average delivery date offset field represents the average deviation between the delivery cycle of a number of recent orders and the contractually agreed delivery cycle. It is a common parameter used in enterprise material planning and management to assess supply reliability.

[0066] S5: Based on the pairing information of each group of materials and suppliers in the material selection and supply matching table, call the current quota utilization rate field and the procurement task demand field of each supplier's corresponding materials in the order management record to determine whether the supplier has the procurement capacity that has not reached the upper limit in the current period. Combine the supply item name and material name in the pairing information to perform item-by-item mapping and matching, obtain the supplier and material combination that meets the allocation conditions, and generate the periodic procurement allocation execution list.

[0067] The list of procured materials to be dispatched includes material classification labels, response level groupings, and inventory consumption differences. The supply stage risk level table includes supplier risk level identifiers, arrival offset intervals, and cumulative frequency of anomalies. The supply rhythm conflict material record table includes procurement order time offset items, receiving window conflict identifiers, and adjustable path markings. The material preferred supply matching table includes performance stability level, qualification cycle update identifiers, and material supply allocation mapping. The periodic procurement and allocation execution list includes procurement available share flags, execution material number list, and allocation target supplier list.

[0068] Please see Figure 2 The specific steps for obtaining the list of procured materials to be distributed are as follows:

[0069] S101: Obtain the material records of the procurement warehouse. The material records include the material inventory ledger, historical outbound details and procurement instruction execution record table. Call the current inventory quantity field of each material in the material inventory ledger and the average daily outbound frequency field of the same material in the historical outbound details to bind the fields. Establish an inventory frequency control group based on the field binding results. Filter the material items in the control group whose current inventory quantity is lower than the average daily outbound frequency multiplied by the period in days to obtain the inventory supply and demand offset material set.

[0070] To retrieve the procurement and warehousing records, for example, if the procurement department needs to formulate a procurement plan for bearings coded "A001", connectors coded "B002", and seals coded "C003", the first step is to retrieve the material inventory ledger from the material management system. This ledger records the real-time inventory information for each type of material. For example, the current inventory of bearings "A001" is 1500 units, connectors "B002" is 800 units, and seals "C003" is 1200 units. Next, the historical outbound details are retrieved. This detailed record shows the outbound status of each type of material over a past period. For example, by statistically analyzing the outbound history of bearings "A001" over the past 90 days... The inventory records show a total outbound volume of 27,000 pieces, so the average daily outbound frequency is calculated as 27,000 pieces / 90 days = 300 pieces / day. The outbound volume of material "B002" connectors in the past 90 days was 13,500 pieces, with an average daily outbound frequency of 13,500 pieces / 90 days = 150 pieces / day. The outbound volume of material "C003" sealing rings in the past 90 days was 18,000 pieces, with an average daily outbound frequency of 18,000 pieces / 90 days = 200 pieces / day. The current inventory of material "A001" bearings (1500 pieces) in the inventory ledger is linked to the historical outbound details of material "A001" bearings (300 pieces / day) through the material code field. Simultaneously, material "B..." The current inventory of "002" connectors (800 units) is linked to a daily outbound frequency of 150 units / day. Similarly, the current inventory of "C003" sealing rings (1200 units) is linked to a daily outbound frequency of 200 units / day. This field binding establishes a control group based on inventory frequency. For example, the current inventory of "A001" bearings is 1500 units, with a daily outbound frequency of 300 units / day. The preset cycle is 10 days, determined based on the company's production plan and safety stock strategy. This cycle represents the length of time the existing inventory can sustain production operations without new material purchases. For instance, in a quarterly procurement plan, a complete supply cycle is typically set at 90 days, but this is adjusted considering the production process. For emergency replenishment or small-batch procurement, the defined cycle days are intended to assess the short-term inventory's ability to meet demand. The control group is selected based on the current inventory level being lower than the average daily outbound frequency multiplied by the cycle days. Specifically, for material "A001" bearings, the average daily outbound frequency multiplied by the cycle days is calculated as 300 units / day × 10 days = 3000 units. Since the current inventory level of 1500 units is lower than 3000 units, material "A001" bearings are selected. For material "B002" connectors, the average daily outbound frequency multiplied by the cycle days is calculated as 150 units / day × 10 days = 1500 units. Since the current inventory level of 800 units is lower than 1500 units, material "B002" connectors are selected.For the sealing ring of material "C003", the daily average outbound frequency multiplied by the cycle number of days is 200 pieces / day × 10 days = 2000 pieces. Since the current inventory of 1200 pieces is less than 2000 pieces, the sealing ring of material "C003" is selected, resulting in an inventory supply and demand offset material set, which includes material codes "A001", "B002" and "C003".

[0071] S102: Based on the material code field in the inventory supply and demand offset material set, obtain the procurement instruction execution record table in the procurement management record, extract the instruction issuance timestamp field corresponding to each material in the record table, calculate the interval period length between adjacent timestamps, perform frequency statistics on materials with the same code according to the interval period length field, and perform joint mapping between the frequency results and the inventory supply and demand offset material set to obtain the issuance density label set within the period.

[0072] For material code "A001" in the inventory supply and demand offset material cluster, the order issuance timestamp field corresponding to this material is extracted from the procurement order execution record table. This field records the specific issuance date and time of the procurement order. The procurement order execution record table for material "A001" shows that there were three orders issued in the past year, with timestamps of 2023-01-10 10:00:00, 2023-03-15 11:30:00, and 2023-06-20 09:00:00. For material "B002", the order issuance timestamps are 2023-01-20 14:00:00 and 2023-04-25 10:00:00. For material "C003",... The instruction issuance timestamps are 2023-02-01 09:00:00, 2023-05-10 13:00:00, and 2023-07-05 16:00:00. The interval period between adjacent timestamps is calculated. For material "A001", the first interval period is the time difference between 2023-03-15 11:30:00 and 2023-01-10 10:00:00, specifically calculated as 64 days, 1 hour, and 30 minutes, which is 64.0625 days. The second interval period is the time difference between 2023-06-20 09:00:00 and 2023-03-15 11:30:00, specifically calculated as 96... The time difference between 2023-04-25 10:00:00 and 2023-01-20 14:00:00 is calculated as 95 days 20 hours 0 minutes, or 95.8958 days. For material "B002", the first time difference is between 2023-05-10 13:00:00 and 2023-02-01 09:00:00, which is calculated as 98 days 4 hours 0 minutes, or 98.1667 days. The second time difference is between 2023-07-05 16:00:00 and... The time difference between 2023-05-10 13:00:00 is specifically calculated as 56 days, 3 hours, and 0 minutes, which translates to 56.125 days. Frequency statistics are then performed on materials with the same code based on the interval period length field. This frequency statistics refers to the number of valid interval period lengths recorded within a specified analysis period. For example, if the analysis period is 180 days, the two interval period lengths for material "A001" are 64.0625 days and 96.8958 days respectively, both within the 180-day analysis period, therefore its frequency is 2. The interval period length for material "B002" is 95.8333 days, with a frequency of 1. The interval period lengths for material "C003" are 98.1667 days and 56.The frequency is 2 over 125 days. The frequency results are then jointly mapped to the inventory supply and demand offset material set. For example, the statistical frequency of 2 for material "A001", the statistical frequency of 1 for material "B002", and the statistical frequency of 2 for material "C003" are mapped to the corresponding material codes in the inventory supply and demand offset material set, respectively, to obtain the distribution density label set within the period, which includes the material code and the corresponding instruction distribution frequency.

[0073] S103: Call the distribution density label value of each material in the distribution density label set within the call cycle, assign the corresponding procurement response level label to the material item according to the distribution level range set in the material response rules, bind the response level label to the original material code, establish a structured record set including code field, supply and demand offset attribute, and response level field, and generate a list of procurement materials to be distributed.

[0074] For material "A001" with a distribution density label set within the cycle, its distribution density label value is 2; for material "B002", its distribution density label value is 1; and for material "C003", its distribution density label value is 2. Based on the distribution level range set in the material response rules, corresponding procurement response level labels are assigned to each material item. The distribution level range in the material response rules is set based on historical procurement data analysis and the company's definition of material urgency, aiming to categorize materials with different distribution densities into different procurement response levels. For example, material items with a distribution density label value between 0 and 1 (excluding 1) are defined as "low response" level; those with a distribution density label value between 1 and 2 (excluding 2) are defined as "medium response" level; and those with a distribution density label value greater than or equal to 2 are defined as "high response" level. For example, for material "A001", its distribution density label value is 2, and according to the set level range, its value is greater than or equal to 2, therefore it is assigned a "high response" level label. For material "B002", its distribution density label value is 1. Its value is between 1 and 2 (excluding 2), therefore a "Medium Response" level label is assigned. For material "C003", its distribution density label value is 2, which is greater than or equal to 2, therefore a "High Response" level label is assigned. The response level label is then bound to the original material code. For example, the "High Response" label is bound to material code "A001", the "Medium Response" label is bound to material code "B002", and the "High Response" label is bound to material code "C003". This establishes a system including the code field, supply and demand offset attribute, and response... The structured record set of the response level field, for example, the record set of material "A001" contains: code "A001", supply and demand offset attribute "Yes" (indicating that it is filtered as an inventory supply and demand offset material in S101), and response level "High Response", the record set of material "B002" contains: code "B002", supply and demand offset attribute "Yes", and response level "Medium Response", and the record set of material "C003" contains: code "C003", supply and demand offset attribute "Yes", and response level "High Response", generates a list of procurement materials to be dispatched.

[0075] Please see Figure 3 The specific steps for obtaining the supply stage risk level table are as follows:

[0076] S201: Based on the material code field in the list of materials to be dispatched, obtain the delivery record table and receipt registration book of all suppliers in the last three procurement cycles, call the departure time field in the delivery record table and the receipt confirmation time field in the receipt registration book to perform field mapping, construct a time comparison set using the departure and receipt times under the same material and supplier dimensions, calculate the time difference in each record, obtain the supply and transportation cycle of each material, and establish arrival time interval information;

[0077] To obtain all supplier delivery records and receipt logs for the past three procurement cycles, for example, if the list of procured materials to be dispatched contains material code "A001", it is necessary to obtain the delivery records and receipt logs of all suppliers supplying "A001" for the past three procurement cycles (e.g., the first, second, and third quarters of 2023). Let's define suppliers S001 and S002 as having provided goods for material "A001". The delivery records should include the supplier's delivery batch, departure time, etc. The receiving and signing register contains information such as the confirmation time of goods arrival. It maps the departure time field in the shipping record table to the confirmation time field in the receiving and signing register, using the material code and supplier code as common keys for association. For example, for a batch of material "A001" supplied by supplier S001, the shipping record table records the departure time as 2023-02-01 09:00:00, and the receiving and signing register records the confirmation time as 2023. -02-0514; 00; 00, constructing a time reference set using the departure and receipt times under the same material and supplier dimensions. For example, the time reference set includes "Material Code; A001, Supplier Code; S001, Departure Time; 2023-02-0109; 00; 00, Receipt Confirmation Time; 2023-02-0514; 00; 00", and calculating the time difference in each record. This time difference is the supply transportation cycle. For example, for the above records, the time difference is calculated as follows: Subtracting 2023-02-0109 from 2023-02-0514;00;00 gives 4 days and 5 hours, which is converted to 4.208 days. This allows us to obtain the supply and transportation cycle for each item. For example, the transportation cycle for item "A001" supplied by supplier S001 is 4.208 days, while the transportation cycle for another batch supplied by supplier S002 might be 3.8 days. We then establish arrival time interval information, including the item code, supplier code, and corresponding supply and transportation cycle value.

[0078] S202: Based on the material and supplier fields in the delivery interval information, call the abnormal identification field of the same period and the same material in the abnormal delivery record book, compare the abnormal identification of each material under each supplier dimension, count the number and location of abnormal records of each supplier under a single material dimension, and jointly label them with the corresponding time period in the delivery interval information to generate a delivery deviation attribution tag set.

[0079] In the delivery interval information, the supply and transportation cycle for material "A001" and supplier S001 is 4.208 days. The abnormal delivery record book is accessed for the same period and material, and the abnormal delivery record field is used to identify such abnormalities. This abnormal delivery record book records delivery anomalies for specific materials within a specific period, such as delays, shortages, or incorrect deliveries. It includes a Boolean abnormality identifier field. For example, querying the abnormal delivery record book reveals that in the last three procurement cycles, the record for material "A001" supplied by supplier S001 with a receipt confirmation time of 2023-02-05 14:00:00 has a "delayed delivery" abnormality identifier. However, the batch of material "A001" supplied by supplier S002 has no abnormality identifier. The abnormality identifiers for each material's delivery records at each supplier level are compared. For example, comparing the abnormality identifiers for material "A001" and supplier S001's records... The arrival record is compared with the corresponding abnormal identifier in the abnormal arrival record book. The comparison result shows that there is an abnormality, while the comparison result of the arrival record of material "A001" and supplier S002 shows no abnormality. The number of abnormal records and the location of occurrence for each supplier under a single material dimension are counted. For example, for material "A001", supplier S001 has 1 abnormal record, which occurred in the first quarter of 2023, and supplier S002 has 0 abnormal records. These are jointly labeled with the corresponding time period in the arrival time interval information. For example, in the arrival time interval information, the record of material "A001", supplier S001 and supply transportation cycle of 4.208 days are jointly labeled as "abnormal frequency: 1 time, occurrence quarter: first quarter of 2023". A delivery deviation attribution label set is generated, which includes material code, supplier code, supply transportation cycle, abnormal frequency and abnormal occurrence location.

[0080] S203: Call the abnormal frequency label and transportation cycle value of each supplier under the same material dimension in the delivery deviation attribution label set, construct a multi-supplier record cluster indexed by material code, classify and sort the abnormal frequency and cycle values ​​in each record cluster, and group and label the delivery risk level between suppliers and material items according to the sorting level to generate a supply stage risk level table.

[0081] For material "A001", supplier S001 has an anomaly frequency of 1 and a transportation cycle of 4.208 days, while supplier S002 has an anomaly frequency of 0 and a transportation cycle of 3.8 days. A multi-supplier record cluster is constructed, indexed by the material code. For example, a record cluster is built for material "A001", containing the anomaly frequency and transportation cycle data for supplier S001, as well as the anomaly frequency and transportation cycle data for supplier S002. The anomaly frequency and cycle values ​​in each record cluster are categorized and sorted. The anomaly frequency categorization and sorting... The rules are as follows: Anomalies with a frequency of 0 are marked as "low"; anomalies with a frequency of 1-2 are marked as "medium"; and anomalies with a frequency greater than 2 are marked as "high". The classification and sorting rules for transportation cycles are as follows: Based on the company's set average transportation cycle benchmark (e.g., 4 days), transportation cycles 0.5 days or less than the benchmark (i.e., 3.5 days) are marked as "short"; those between 3.5 and 4.5 days are marked as "moderate"; and those greater than 4.5 days are marked as "long". For example, for the record cluster "A001" for material: Supplier S001, ... Supplier S002 has a normal frequency of 1 (classified as "Medium") and a transportation cycle of 4.208 days (classified as "Moderate"). Supplier S002 has an abnormal frequency of 0 (classified as "Low") and a transportation cycle of 3.8 days (classified as "Moderate"). The delivery risk levels between suppliers and material items are grouped and labeled according to their ranking. The grouping of delivery risk levels is based on the combination of abnormal frequency and transportation cycle classification. For example, if the abnormal frequency is "High" or the transportation cycle is "Long," it is classified as "High Risk." If the abnormal frequency is "Medium" and the transportation cycle is "Long," it is classified as "High Risk." If the delivery period is "moderate", it is classified as "medium risk". If the frequency of anomalies is "low" and the transportation period is "moderate" or "short", it is classified as "low risk". For example, for material "A001", the frequency of anomalies of supplier S001 is "medium" and the transportation period is "moderate", so it is classified as "medium risk". The frequency of anomalies of supplier S002 is "low" and the transportation period is "moderate", so it is classified as "low risk". A supply stage risk level table is generated, which includes material code, supplier code and corresponding delivery risk level.

[0082] Please see Figure 4 The specific steps for obtaining the supply rhythm conflict material record form are as follows:

[0083] S301: Based on the supplier and material code combination marked as high risk in the supply stage risk level table, obtain the current cycle procurement plan table for the corresponding material, extract the order time field, and obtain the receiving window cycle field for the corresponding material from the warehouse scheduling window record. Associate and bind the two fields according to the material code, judge the time sequence of each record, filter material items whose order time is later than the receiving window start time or earlier than the receiving window end time, and establish a time-disjointed material index set.

[0084] The supply stage risk level table shows that the combination of material "A001" and supplier S003 is marked as "high risk". Retrieve the corresponding procurement plan for this period. The procurement plan contains the planned order time and quantity information for specific materials. For example, for material "A001", the planned order time field value in the current period's procurement plan is 2023-08-10 10:00:00. Extract the order time field and retrieve the corresponding material's receiving window period field from the warehouse scheduling window record. The warehouse scheduling window record defines the time period during which specific materials can be received in the warehouse. For example, for material "A001"... The receiving window period is from 08:00:00 on August 8, 2023 to 17:00:00 on August 12, 2023. The two fields are associated and bound by the material code. For example, the planned order time of material "A001" (2023-08-10 10:00:00) is bound to the receiving window start time (2023-08-08 08:00:00) and the receiving window end time (2023-08-12 17:00:00). The time sequence of each record is judged. The specific judgment process is as follows: First, determine whether the order time is later than the receiving window start time, i.e., if the order time > The receiving window starts at time 2023. Next, it checks if the order placement time is earlier than the receiving window end time (i.e., order placement time < receiving window end time). If both conditions are met, the timing of the material's arrangement is reasonable; otherwise, there is a time discrepancy. For example, for material "A001," its order placement time (2023-08-10 10:00:00) is later than the receiving window start time (2023-08-08 08:00:00) but earlier than the receiving window end time (2023-08-12 17:00:00). Therefore, this material was not selected. The order placement time for another material, "D004," is set to 2023-08-10 10:00:00. 8-0715;00;00, the receiving window period is from 2023-08-0808;00;00 to 2023-08-1217;00;00. Since the order time 2023-08-0715;00;00 is earlier than the receiving window start time 2023-08-0808;00;00, the material "D004" is filtered out. The system filters out material items whose order time is later than the receiving window start time or earlier than the receiving window end time. For example, it filters out material "D004" with an order time of 2023-08-0715;00;00, and establishes a time-disjointed material index set.

[0085] S302: Call the material code field and supplier code field of the material in the time-disjointed material index set, obtain the supply path registration field in the multi-source path information table, retrieve the path substitution capability status value bound to each record, filter out records with path substitution capability status of non-substitutable, and retain the material and supplier joint index for the filtered records to generate an adjustable path conflict record set.

[0086] The time-disconnected material index set contains a combination of material "D004" and supplier S004. The supply path registration field from the multi-source path information table is retrieved. This table records the available suppliers and corresponding supply paths for each material, and marks the alternative capability status of that path. For example, the path registration information for "D004" supplied by supplier S004 may include "primary path," "backup path," etc., and is bound to a path alternative capability status value. The path alternative capability status value bound to each record is retrieved. This value is a preset enumeration type, such as "substitutable," "non-substitutable," or "partially substitutable," reflecting whether there are alternative paths available when the current supply path encounters problems. Perform rapid replacements. For example, for the combination of material "D004" and supplier S004, its supply path substitution capability status is "non-substitutable". For the combination of material "E005" and supplier S005, its supply path substitution capability status is "substitutable". Filter out records with a path substitution capability status of "non-substitutable". For example, filter out the combination of material "D004" and supplier S004 because its path substitution capability status is "non-substitutable". However, retain the combination of material "E005" and supplier S005. For the filtered records, retain the composite index of the material and supplier. For example, retain the composite index of material "E005" and supplier S005. Generate an adjustable path conflict record set.

[0087] S303: Based on the material and supplier joint index information in the adjustable path conflict record set, perform intersection matching with the time-disjointed material index set, extract material items that meet the time conflict conditions and have adjustable path attributes, and construct a composite tag field including procurement time, receiving cycle and path substitution status for the material items to generate a supply rhythm conflict material record table.

[0088] The adjustable path conflict record set contains the joint index of material "E005" and supplier S005. It is then matched against the time-disjoint material index set. The time-disjoint material index set contains material items filtered in S301 whose order time and receiving window do not match. For example, the time-disjoint material index set contains the joint index of material "D004" and supplier S004, and the joint index of material "E005" and supplier S005. During the intersection matching, the system checks whether the two sets have the same joint index of material and supplier. For example, in this case, the joint index of material "E005" and supplier S005 exists in both sets. Material items that meet the time conflict condition and have the adjustable path attribute are extracted. For example, material "E005" is extracted because it simultaneously satisfies the conditions of order time and receiving window conflict (time disjointness) and its supply path is substitutable (adjustable path conflict). The construction of material items includes a composite tag field for procurement time, receiving period, and route alternative status. For example, for material "E005", its procurement plan order time (e.g., 2023-08-07 15:00:00) is obtained from S301, its receiving window period (e.g., 2023-08-08 08:00:00 to 2023-08-12 17:00:00) is obtained from the warehouse scheduling window record, and its route alternative status (e.g., "alternative") is obtained from the multi-source route information table. This information is combined to form a composite tag field, such as "Procurement time; 2023-08-07 15:00:00, Receiving period; 2023-08-08 08:00:00 ~ 2023-08-12 17:00:00, Route alternative status; Alternative", generating a supply rhythm conflict material record table, which lists materials that have both time conflicts and route adjustment potential.

[0089] Please see Figure 5 The specific steps for obtaining the material selection and supply matching table are as follows:

[0090] S401: Based on the material code field and supplier number field in the supply rhythm conflict material record table, obtain the supplier qualification update records within the current valid procurement cycle, extract the qualification document update time field, call the set qualification validity interval period parameter, calculate the time difference between the update time of each record and the current date, determine whether the difference exceeds the qualification validity threshold, filter the records with valid qualifications, and generate a valid qualification supplier index set.

[0091] The supply rhythm conflict material record table contains a combination of material code "E005" and supplier number S005. This allows for the retrieval of supplier qualification update records within the current valid procurement cycle. These records include the update dates of various supplier qualification documents, such as ISO certification and quality system certification. The update date field is extracted; for example, from supplier S005's qualification update record, the latest ISO9001 certification update date is found to be 2023-03-01. The set qualification validity interval parameter is then invoked. This parameter is set by the company according to regulatory requirements and internal risk control strategies, and is a fixed time length used to determine whether a supplier's qualification is within its validity period. For example, setting this parameter to 365 days represents the validity period from the update date. Valid for the entire year, the time difference between the update time and the current date of each record is calculated, and it is determined whether the difference exceeds the qualification validity threshold. For example, if the current date is 2023-08-15 and the qualification update time of supplier S005 is 2023-03-01, the time difference is 167 days, which is less than the qualification validity interval parameter of 365 days. Therefore, the qualification is considered valid. If the qualification update time of another supplier S006 is set to 2022-06-01 and the current date is 2023-08-15, the time difference is 440 days, which exceeds 365 days. Therefore, the qualification is considered invalid. Records with valid qualifications are filtered. For example, the combination of material code "E005" and supplier number S005 is filtered. Since supplier S005 has a valid qualification, a valid qualification supplier index set is generated.

[0092] S402: Call the supplier number information in the valid qualified supplier index set, extract the average delivery date offset field of the corresponding supplier in this period from the performance behavior log, perform numerical normalization on the delivery date offset value, sort according to the normalization result, and remove suppliers with lower offset rankings according to the offset tolerance threshold to obtain a stable performance supplier index set.

[0093] The valid supplier index set includes supplier number S005. The average delivery date offset field for the corresponding supplier within the current period is extracted from the performance behavior log. The performance behavior log records in detail the planned and actual delivery dates for each delivery by the supplier, and calculates the difference between the two. The average delivery date offset field is the arithmetic mean of the delivery date offsets of all deliveries made by the supplier within the current period. For example, supplier S005's average delivery date offset within the current period is -0.5 days (indicating an average delivery date 0.5 days early), while supplier S007's average delivery date offset is 1.2 days (indicating an average delivery date 1.2 days late). The delivery date offset values ​​are then normalized using a minimum-maximum normalization method, mapping the delivery date offset values ​​to the range of 0 to 1. For example, setting the historical maximum offset to 5 days and the minimum offset to -2 days, the normalization formula is: For S005, -0.5 days, the normalized value is For S007, 1.2 days, the normalized value is The suppliers are then sorted based on the normalized results. For example, supplier S005, with a normalized delivery date offset of 0.214, is ranked before supplier S007, which has an offset of 0.457, because a smaller normalized value represents better fulfillment stability. Suppliers with lower offset rankings are eliminated based on the offset tolerance threshold. This threshold is set by the company according to its own requirements for supply chain stability. For example, a normalized delivery date offset of 0.6 means that any supplier with a normalized delivery date offset greater than 0.6 will be eliminated. This threshold is based on historical data analysis. For example, by statistically analyzing the delivery date offset distribution of all successfully fulfilled orders in the past year, the 90th percentile is taken as the upper limit to ensure that most suppliers can meet the requirements. For example, if S008's normalized delivery date offset is 0.7, then S008 will be eliminated, resulting in a stable fulfillment supplier index set, which includes supplier number S005.

[0094] S403: Based on the supplier IDs and bound material codes in the stable fulfillment supplier index set, aggregate the supplier IDs at the material level, construct a one-to-many supplier mapping structure for each material, construct a mapping table structure according to the material ID, and generate a material preferred supply matching table.

[0095] In the stable fulfillment supplier index set, supplier S005 is bound to material code "E005". Supplier numbers are aggregated under the material dimension. For example, for material "E005", all stable fulfillment supplier numbers corresponding to it are collected. If S009 also meets the condition and supplies material "E005" in addition to S005, then S005 and S009 are aggregated under material "E005". A one-to-many supplier mapping structure is constructed for each material. For example, for material "E005", the constructed mapping structure is: E005->[S005, S009]. A mapping table structure is constructed according to the material number. This mapping table structure uses the material code as the primary key and its value is a list of supplier numbers. For example, the following mapping table structure is constructed.

[0096] Table 1: Material Optimization and Supply Matching Table (Example)

[0097] ;

[0098] As shown in Table 1, this table records each material and its corresponding list of stable fulfilling suppliers, generating a material preferred supply matching table.

[0099] Please see Figure 6 The specific steps for obtaining the periodic procurement allocation execution list are as follows:

[0100] S501: Based on the pairing information of each group of materials and suppliers in the material selection and supply matching table, call the quota utilization rate field and the procurement task requirement field in the order management record, perform difference calculation on each record and compare it with the procurement capacity threshold parameter to determine whether the supplier has the procurement capacity below the limit, filter the material supply combination that meets the conditions, and generate an effective procurement capacity combination set.

[0101] In the material selection and supply matching table, the pairing information between material "E005" and supplier S005 is retrieved from the quota utilization rate and procurement task demand fields in the order management record. The order management record contains the procurement quota allocated to the supplier and its actual usage. The quota utilization rate is calculated by dividing the supplier's executed quota in the current period by its total allocated quota. The procurement task demand field indicates the current procurement task's demand for this material. For example, if supplier S005's quota utilization rate for material "E005" in the current period is 0.70 (i.e., 70%), and the current procurement task's demand for material "E005" is 500 units, a difference calculation is performed on each record and compared with the procurement capacity threshold parameter to determine whether the supplier has procurement capacity below the limit. Indicates supplier The purchasing capacity threshold is set based on the supplier's historical maximum capacity, production line load, raw material supply stability, and the company's assessment parameters of its production capacity. For example, for supplier S005, its purchasing capacity threshold is... The value is set to 0.90, which means that the upper limit of supplier S005's capacity is 90% of its total quota. The comparison process is as follows: First, calculate the current quota utilization rate of supplier S005. With purchasing capacity threshold The difference, i.e. This difference indicates that supplier S005 still has... The quota space can be used to undertake new procurement tasks, and this difference is greater than This indicates that supplier S005 has purchasing power below the limit. Select material supply combinations that meet the conditions. For example, the combination of material "E005" and supplier S005 meets the conditions and is selected, generating a set of effective purchasing power combinations.

[0102] S502: Based on the supplier and material combination information in the effective procurement capacity combination set, extract the supply item name field and the material name field, compare the field content item by item and construct a mapping consistency identifier, remove combinations with mapping failures, obtain a structurally stable supply pairing list, and establish a stable supply mapping pair list.

[0103] The effective procurement capability combination set includes the combination of material "E005" and supplier S005. The system extracts the supply item name field and the material name field. The supply item name field is a standardized name obtained from the supplier's product catalog or service list, while the material name field is a standardized name obtained from the enterprise's internal material master data. For example, for material "E005," its internal material name is "die-cast aluminum alloy bracket," while the supply item name provided by supplier S005 might be "customized aluminum bracket." The system compares the field content item by item and constructs a mapping consistency identifier. The comparison process includes string similarity calculation and keyword matching to determine whether the two names refer to the same item. For example, the system compares "die-cast aluminum alloy..." with the corresponding material name. Keyword extraction and comparison were performed on "bracket" and "customized aluminum bracket". It was found that "aluminum" and "bracket" are common keywords. After semantic analysis, they were considered to have a high degree of consistency, so a "consistent" mapping consistency identifier was constructed. If the two names are significantly different, for example, the material name is "high-strength bolt" while the supply item name is "plastic gasket", then an "inconsistent" mapping consistency identifier is constructed, and the combination with failed mapping is eliminated. For example, if the mapping consistency identifier of a combination is "inconsistent", the combination will be eliminated, and a list of structurally stable supply pairs is obtained. For example, the combination of material "E005" and supplier S005 is retained because the mapping consistency is "consistent", and a list of stable supply mapping pairs is established.

[0104] S503: Call the stable supply mapping to calculate the periodic fit strength value between materials and suppliers for each group of material codes and supplier numbers in the list, and combine the corresponding quota utilization rate and task demand data. Filter the material supply combinations with periodic fit strength values ​​less than the scheduling threshold and establish a periodic procurement and allocation execution list.

[0105] The specific formula for calculating the periodic compatibility strength value between materials and suppliers is as follows:

[0106] ;

[0107] in, Indicates supplies With suppliers The periodic adaptation strength value between them Indicates supplier In the current cycle, materials The quota utilization rate is calculated by dividing the supplier's executed quota in the current period by its total allocated quota. Indicates supplier The procurement capacity threshold is determined based on the supplier's capacity configuration parameters. Indicates supplier Materials during the current cycle The required procurement volume. Indicates supplier Materials during the current cycle The required procurement volume. Indicates supplies The total number of matching suppliers in the current cycle. Indicates supplies The normalized value of the bound supply item name's encoded value is extracted from the name mapping table as an integer and then processed according to the minimum-maximum normalization rule. Indicates supplier The normalized value of the code for the provided supply item name, and the scheduling threshold are set by multiplying the average fit strength value of the actual successful allocation records of the same type of materials and supplier combinations in the historical period by an adjustment factor. This is an experience-based system threshold, and the value is maintained within an adjustable range.

[0108] In the list of stable supply mapping pairs, materials The supplier is designated as "E005". For "S005", the supplier In the current cycle, materials Quota utilization rate for supplies Procurement task demand for Items, supplier Purchasing capacity threshold for supplies Total number of matching suppliers in the current period for (S005 and S009) Set the procurement requirements of supplier S009 for material "E005". for Items, materials The normalized value of the coded value for the bound supply item name "Die-cast Aluminum Alloy Bracket" for ,supplier The normalized value of the code for the supplied item name "Custom Aluminum Bracket" for The normalized value of this code is achieved by mapping the material name and supply item name to a preset integer code (e.g., encoding "die-cast aluminum alloy bracket" as 80 and "custom aluminum bracket" as 70 using a dictionary or coding table), and then applying a minimum-maximum normalization rule. Convert to a value between 0 and 1. For example, if the encoding range is 0-100, then... , The formula used is:

[0109] ;

[0110] The calculation yields a periodic fit strength value between materials and suppliers. This formula quantifies the degree of matching between materials and suppliers within the current procurement cycle. Indicates supplies With suppliers The periodicity of the fit is a value; the lower the value, the stronger the fit. Indicates supplier In the current cycle, materials The quota utilization rate is calculated by dividing the supplier's executed quota in the current period by its total allocated quota. For example, the executed quota is... Items, total quota is Item, then , Indicates supplier The procurement capacity threshold is determined based on the supplier's acceptance capacity configuration parameters. For example, the acceptance capacity configuration parameters for S005 are... ,but , Indicates supplier Materials during the current cycle The procurement task demand, for example, the current procurement task demand is... Item, Indicates supplier Materials during the current cycle The procurement task requirements, for example, S009 for materials. The demand is Item, Indicates supplies The total number of suppliers that can be matched in the current cycle, for example, S005 and S009 match material "E005", then , Indicates supplies The normalized value of the bound supply item name's encoded value is extracted from the name mapping table as an integer and then processed according to the minimum-maximum normalization rule. Indicates supplier The normalized value of the coded value of the provided supply item name, the normalization method and Similarly, the advantage of the formula is that it comprehensively considers the remaining purchasing power of suppliers. The relative importance of the tasks currently undertaken by suppliers And the degree of matching between the names of the materials and the items supplied by the supplier. By multiplying these three factors, the compatibility strength between materials and suppliers is precisely quantified, making scheduling decisions more comprehensive and accurate. For example, the periodic compatibility strength value between material "E005" and supplier "S005" is calculated:

[0111] ;

[0112] The scheduling threshold is set by multiplying the average fit strength value calculated by the system based on the actual successful allocation records of the same type of materials and supplier combinations within a historical period by an adjustment factor. This is an experience-based system threshold, and the value is maintained within an adjustable range. For example, the system calculates its average fit strength value by analyzing the procurement records of similar materials successfully allocated in the past 12 months. And set the adjustment factor as Therefore, the scheduling threshold is Select supply combinations of materials whose periodicity fit strength value is less than the scheduling threshold. For example, the periodicity fit strength value between material "E005" and supplier S005 is less than the threshold value. Less than the scheduling threshold Therefore, this combination was selected. The result shows that material "E005" is highly compatible with supplier S005 and should be given priority for allocation. This result directly corresponds to an effective combination in the periodic procurement allocation execution list, and the periodic procurement allocation execution list is established.

[0113] Please see Figure 7 A big data-based supply chain procurement management system is used to execute the aforementioned big data-based supply chain procurement management method. The system includes:

[0114] The procurement demand analysis module obtains the material records of the procurement warehouse, calls the current inventory quantity field and the average daily outbound frequency field of each material, and combines them with the material distribution frequency field to aggregate the material items according to the procurement response level and generate a list of procurement materials to be distributed.

[0115] The supply risk assessment module, based on the material code field in the list of materials to be dispatched, determines the frequency and time span of delivery deviations of the same supplier under the current material code, aggregates the delivery anomalies of each supplier by material code, sorts and classifies them, and generates a supply stage risk level table.

[0116] The supply conflict identification module filters out material items whose procurement time and receiving window conflict or are disconnected based on the supply stage risk level table, calls the multi-source supply path registration field, filters out records of irreplaceable supply paths, and generates a supply rhythm conflict material record table.

[0117] The supplier matching module, based on the material code field in the supply rhythm conflict material record table, removes suppliers whose qualification updates exceed the set interval period or whose delivery date deviates from the ranking, establishes a one-to-many relationship with the remaining suppliers according to the material code, and generates a material preferred supply matching table.

[0118] The procurement execution and organization module, based on the pairing information of each group of materials and suppliers in the material selection and supply matching table, calls the current quota utilization rate field and the procurement task demand field of each supplier's corresponding materials in the order management record, and performs item-by-item mapping and matching with the supply item name and material name in the pairing information to obtain the supplier and material combination that meets the allocation conditions and generate the periodic procurement allocation execution list.

[0119] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0120] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0121] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0122] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0123] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0124] In the several embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0125] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0126] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0127] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0128] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A big data-based material supply chain procurement management method, characterized in that, Includes the following steps: S1: Obtain the material records of the procurement warehouse, call the current inventory quantity field and the average daily outbound frequency field of each material, combine them with the material distribution frequency field, aggregate the material items according to the procurement response level, and generate a list of procurement materials to be distributed. S2: Based on the material code field in the list of materials to be dispatched, determine the frequency and time span of delivery deviations of the same supplier under the current material code, aggregate the delivery anomalies of each supplier by material code and sort and classify them to generate a supply stage risk level table. S3: Based on the aforementioned supply stage risk level table, filter out material items whose procurement time conflicts with or is disconnected from the receiving window, call the multi-source supply path registration field, filter out records of irreplaceable supply paths, and generate a supply rhythm conflict material record table. S4: Based on the material code field in the supply rhythm conflict material record table, eliminate suppliers whose qualification updates exceed the set interval period or whose delivery date deviates from the ranking, establish a one-to-many relationship with the remaining suppliers according to the material code, and generate a material preferred supply matching table.

2. The material supply chain procurement management method based on big data according to claim 1, characterized in that, The list of procurement materials to be dispatched includes material classification labels, response level groupings, and inventory consumption differences. The supply stage risk level table includes supplier risk level identifiers, arrival offset intervals, and abnormal cumulative frequency labels. The supply rhythm conflict material record table includes procurement order time offset items, receiving window conflict identifiers, and adjustable path markings. The preferred supply matching table includes performance stability level, qualification cycle update identifiers, and material supply allocation mapping.

3. The material supply chain procurement management method based on big data according to claim 2, characterized in that, The specific steps for obtaining the list of procured materials to be distributed are as follows: S101: Obtain the material records of the procurement warehouse. The material records include the material inventory ledger, historical outbound details and procurement instruction execution record table. Call the current inventory quantity field of each material in the material inventory ledger and the average daily outbound frequency field of the same material in the historical outbound details to bind the fields. Establish an inventory frequency control group based on the field binding results. Filter the material items in the control group whose current inventory quantity is lower than the average daily outbound frequency multiplied by the period in days to obtain the inventory supply and demand offset material set. S102: Based on the material code field of the inventory supply and demand offset material set, obtain the procurement instruction execution record table in the procurement management record, extract the instruction issuance timestamp field corresponding to each material in the record table, calculate the interval period length between adjacent timestamps, perform frequency statistics on materials with the same code according to the interval period length field, and perform joint mapping between the frequency results and the inventory supply and demand offset material set to obtain the issuance density label set within the period. S103: Call the distribution density label value of each material in the distribution density label set within the period, assign the corresponding procurement response level identifier label to the material item according to the distribution level range set in the material response rules, bind the response level label to the original material code, establish a structured record set including code field, supply and demand offset attribute, and response level field, and generate a list of procurement materials to be distributed.

4. The material supply chain procurement management method based on big data according to claim 3, characterized in that, The specific steps for obtaining the supply stage risk level table are as follows: S201: Based on the material code field in the list of materials to be dispatched, obtain the delivery record table and receipt registration book of all suppliers in the last three procurement cycles, call the departure time field in the delivery record table and the receipt confirmation time field in the receipt registration book to perform field mapping, construct a time comparison set using the departure and receipt times under the same material and supplier dimensions, calculate the time difference in each record, obtain the supply and transportation cycle of each material, and establish the arrival time interval information; S202: Based on the material and supplier fields in the delivery time interval information, call the abnormal identification field of the same period and the same material in the abnormal delivery record book, compare the abnormal identification of each material under each supplier dimension, count the number and location of abnormal records of each supplier under a single material dimension, and jointly label them with the corresponding time period in the delivery time interval information to generate a delivery deviation attribution tag set. S203: Call the abnormal frequency label and transportation cycle value of each supplier under the same material dimension in the delivery deviation attribution label set, construct a multi-supplier record cluster indexed by material code, classify and sort the abnormal frequency and cycle values ​​in each record cluster, and group and label the delivery risk level between suppliers and material items according to the sorting level to generate a supply stage risk level table.

5. The material supply chain procurement management method based on big data according to claim 4, characterized in that, The specific steps for obtaining the supply rhythm conflict material record table are as follows: S301: Based on the supplier and material code combination marked as high risk in the supply stage risk level table, obtain the current cycle procurement plan table for the corresponding material, extract the order time field, and obtain the receiving window cycle field for the corresponding material from the warehouse scheduling window record. Associate and bind the two fields according to the material code, judge the time sequence of each record, filter out material items whose order time is later than the receiving window start time or earlier than the receiving window end time, and establish a time-disjointed material index set. S302: Call the material code field and supplier code field of the materials in the time-disjointed material index set, obtain the supply path registration field in the multi-source path information table, retrieve the path substitution capability status value bound to each record, filter out records with path substitution capability status of non-substitutable, and retain the material and supplier joint index for the filtered records to generate an adjustable path conflict record set. S303: Based on the material and supplier joint index information in the adjustable path conflict record set, perform intersection matching with the time-disjointed material index set, extract material items that meet the time conflict conditions and have adjustable path attributes, and construct a composite tag field including procurement time, receiving cycle and path substitution status for the material items to generate a supply rhythm conflict material record table.

6. The material supply chain procurement management method based on big data according to claim 5, characterized in that, The specific steps for obtaining the preferred supply matching table for the materials are as follows: S401: Based on the material code field and supplier number field in the supply rhythm conflict material record table, obtain the supplier qualification update records within the current valid procurement cycle, extract the qualification document update time field, call the set qualification validity interval period parameter, calculate the time difference between the update time of each record and the current date, determine whether the difference exceeds the qualification validity threshold, filter the qualified records, and generate a valid qualification supplier index set. S402: Call the supplier number information in the valid qualified supplier index set, extract the average delivery date offset field of the corresponding supplier in this period from the performance behavior log, perform numerical normalization on the delivery date offset value, sort according to the normalization result, and remove suppliers with lower offset ranking according to the offset tolerance threshold to obtain a stable performance supplier index set. S403: Based on the supplier IDs and bound material codes in the stable fulfillment supplier index set, aggregate the supplier IDs at the material level, construct a one-to-many supplier mapping structure for each material, construct a mapping table structure according to the material ID, and generate a material preferred supply matching table.

7. The material supply chain procurement management method based on big data according to claim 6, characterized in that, The method further includes the following steps: S5: Based on the pairing information of each group of materials and suppliers in the material preferred supply matching table, call the current quota utilization rate field and the procurement task demand field of each supplier's corresponding materials in the order management record, and perform item-by-item mapping and matching in combination with the supply item name and material name in the pairing information to obtain the supplier and material combination that meets the allocation conditions and generate the periodic procurement allocation execution list. The periodic procurement allocation execution list includes procurement available share indicators, a list of execution material numbers, and a list of allocation target suppliers.

8. The material supply chain procurement management method based on big data according to claim 7, characterized in that, The specific steps for obtaining the periodic procurement allocation execution list are as follows: S501: Based on the pairing information of each group of materials and suppliers in the material selection and supply matching table, call the quota utilization rate field and the procurement task requirement field in the order management record, perform difference calculation on each record and compare it with the procurement capacity threshold parameter to determine whether the supplier has the procurement capacity below the limit, filter the material supply combination that meets the conditions, and generate an effective procurement capacity combination set. S502: Based on the supplier and material combination information in the effective procurement capacity combination set, extract the supply item name field and the material name field, compare the field content item by item and construct a mapping consistency identifier, remove combinations with mapping failures, obtain a structurally stable supply pairing list, and establish a stable supply mapping pair list. S503: Call the stable supply mapping pair for each group of material codes and supplier numbers in the list, combine the corresponding quota utilization rate and task demand data, calculate the periodic adaptation strength value between materials and suppliers, filter material supply combinations with periodic adaptation strength values ​​less than the scheduling threshold, and establish a periodic procurement and allocation execution list.

9. The material supply chain procurement management method based on big data according to claim 8, characterized in that, The formula for calculating the periodic compatibility strength value between materials and suppliers is as follows: ； in, Indicates supplies With suppliers The periodic adaptation strength value between them Indicates supplier In the current cycle, materials Quota utilization rate Indicates supplier Purchasing capacity threshold Indicates supplier Materials during the current cycle The required procurement volume. Indicates supplier Materials during the current cycle The required procurement volume. Indicates supplies The total number of suppliers that can be matched in the current period. Indicates supplies The normalized value of the coded value of the bound supply item name. Indicates supplier The normalized value of the coded value of the provided supply item name.

10. A big data-based materials supply chain procurement management system, characterized in that: The system is used to implement the big data-based material supply chain procurement management method according to any one of claims 1-9, and the system includes: The procurement demand analysis module obtains the material records of the procurement warehouse, calls the current inventory quantity field and the average daily outbound frequency field of each material, and combines them with the material distribution frequency field to aggregate the material items according to the procurement response level and generate a list of procurement materials to be distributed. The supply risk assessment module, based on the material code field in the list of materials to be dispatched, determines the frequency and time span of delivery deviations of the same supplier under the current material code, aggregates the delivery anomalies of each supplier by material code, sorts and classifies them, and generates a supply stage risk level table. The supply conflict identification module, based on the supply stage risk level table, filters out material items whose procurement time and receiving window conflict or are disconnected, calls the multi-source supply path registration field, filters out records of irreplaceable supply paths, and generates a supply rhythm conflict material record table. The supplier matching module, based on the material code field in the supply rhythm conflict material record table, removes suppliers whose qualification updates exceed the set interval period or whose delivery date deviates from the ranking, establishes a one-to-many relationship with the remaining suppliers according to the material code, and generates a material preferred supply matching table. The procurement execution and organization module, based on the pairing information of each group of materials and suppliers in the material selection and supply matching table, calls the current quota utilization rate field and the procurement task demand field of each supplier's corresponding materials in the order management record, and performs item-by-item mapping and matching with the supply item name and material name in the pairing information to obtain the supplier and material combination that meets the allocation conditions and generate the periodic procurement allocation execution list.

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