A plastic industry plastic supply chain risk early warning method

Abstract

The application discloses a kind of plastic industry plastic supply chain risk early warning method, it is related to data analysis field, including: obtaining supply chain basic information and order history information, setting supply chain order history information cleaning logic, based on supply chain order history information cleaning logic to supply chain order history information is cleaned;Upload order demand information, based on order demand information preliminary screening compatible supply chain;According to supply chain order history information and the compatible supply chain obtained by preliminary screening, the final adaptation degree of each compatible supply chain obtained by preliminary screening relative to order demand information is analyzed;The application is by accurately obtaining supply chain multidimensional information and establishing cleaning logic, eliminate incomplete and do not meet the conditions of historical data, guarantee the effectiveness of analysis basis, based on service range and actual service point position construction topological structure, combined with capacity data to evaluate basic adaptation degree, accurately screen compatible supply chain.

Description

Technical Field

[0001] This invention relates to the field of data analysis technology, specifically to a method for early warning of risks in the chemical and plastics supply chain in the chemical and plastics industry. Background Technology

[0002] The chemical and plastics supply chain is a link connecting chemical raw materials, plastics production, and downstream applications, encompassing procurement, production, warehousing, logistics, and distribution. By integrating upstream and downstream resources and optimizing inventory and transportation, it ensures a stable supply of raw materials and helps industries such as packaging and building materials operate efficiently.

[0003] Patent application number 202510304972.8 discloses a supply chain health assessment and risk warning method based on a graph database, comprising the following steps: S1, extracting and integrating historical supply chain data and historical event data through a historical data ETL module to construct a standardized database; S2, constructing a three-layer hypernetwork model based on the standardized database, including enterprise financial relationship subnetwork, enterprise supply relationship subnetwork, and national trade relationship subnetwork, and storing the structured data in the graph database; S3, collecting multi-source event data in real time, extracting event types and attributes through natural language processing, and generating a real-time event dataset; S4, inputting the real-time event dataset into the AIGC database. The model predicts data changes, dynamically updates the scores of hypernetwork model nodes and edges based on the prediction results, calculates enterprise supply chain health indicators, and then obtains the assessment results of enterprise comprehensive health score and supply chain network score based on the enterprise supply chain health indicators; S5, dynamically warns of the assessment results based on preset risk thresholds, and displays the supply chain network status in real time in conjunction with the visualization module. This application aims to solve the problem that "in the existing technology, the existing supply chain risk assessment in the VUCA era has shortcomings: knowledge graphs that rely on historical data are difficult to reflect the situation in real time, and the risk measurement is inaccurate; the ability to handle complex dynamic relationships is limited, and the health status of the supply network is not comprehensively assessed; compared with advanced AIGC models, knowledge graph and data mining technologies have obvious limitations."

[0004] However, in the context of the chemical and plastics industry supply chain, due to the large size of the supply chain, buyers often find it difficult to understand the real-time risks of the supply chain, making it difficult to make reasonable choices when selecting a supply chain.

[0005] To address this, a risk early warning method for the chemical and plastics supply chain in the chemical and plastics industry is proposed. Summary of the Invention

[0006] In view of the above-mentioned shortcomings of the existing technology, the present invention provides a method for risk early warning of the chemical and plastic supply chain in the chemical and plastic industry, which can effectively solve the problems of the existing technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions; This invention discloses a method for early warning of risks in the chemical and plastics supply chain in the chemical and plastics industry, including: The system acquires basic supply chain information and order history information, sets up a logic for cleaning the supply chain order history information, and cleans the supply chain order history information based on this logic. It then uploads order demand information and initially filters suitable supply chains based on this information. Based on the supply chain order history information and the initially filtered suitable supply chains, it analyzes the final fit of each initially filtered suitable supply chain with respect to the order demand information. The system acquires supply chain product quality information and corrects the matching analysis results based on this information. It sets an output threshold, compares the output threshold with the corrected analysis results, and outputs the supply chains corresponding to the corrected analysis results that meet the output threshold. Finally, it creates a supply chain list and marks the associated information for each supply chain in the list.

[0008] Furthermore, the basic supply chain information includes: the service scope of the supply chain, the current actual service scope of the supply chain, the average daily order volume of the supply chain, and the theoretical maximum daily output of products of the supply chain; The historical supply chain order information includes: order product unit price, order product quantity, order origin and destination, estimated and actual delivery time, and order damage percentage. The supply chain order history information cleaning logic is used to extract order history information from the supply chain order history information that will participate in subsequent analysis steps; Among them, the maximum daily output of products in the supply chain theory is determined based on the production equipment of the supply chain products, the estimated delivery time of orders is determined based on the order dispatch time and delivery time estimated by the supply chain back-end, and the actual delivery time of orders is determined based on the actual order dispatch time and delivery time of the supply chain. The acquisition of basic supply chain information and order history information corresponds to no less than three supply chain objectives. During the acquisition of basic supply chain information, a cloud database is created simultaneously for the differentiated storage of basic supply chain information. The user terminal can manually delete, store, and modify the basic supply chain information in the cloud database in real time.

[0009] Furthermore, the basic supply chain information and order history information are sourced from supply chain service users, and the supply chain order history information cleaning logic is as follows: Traverse the historical supply chain order information, identify incomplete information in the historical supply chain order information, and use the incomplete historical supply chain order information as the first target for cleaning, and delete it from all the acquired historical supply chain order information; The user client sets exclusion criteria based on one or more of the following: order product unit price, order product quantity, order origin and destination, order estimated delivery time and actual delivery time, and order damage percentage. Based on these exclusion criteria, the historical information of supply chain orders is cleaned. The criteria for determining incomplete supply chain order history information are: any one or more of the following are missing: order product unit price, order product quantity, order origin and destination, order estimated delivery time and actual delivery time, and order damage percentage.

[0010] Furthermore, the order demand information includes: the quantity of products required for the order, the time required for the order, and the destination of the order. In the initial screening stage of the supply chain, a supply chain service topology is created based on the service scope of each supply chain and the current actual service scope of the supply chain. Based on the supply chain service topology, the basic adaptability of the supply chain is evaluated in conjunction with the average daily order quantity of each supply chain and the theoretical maximum daily output of the supply chain. An adaptability judgment threshold is set, and all supply chains that meet the basic adaptability judgment threshold are used as the initial screening results and directed to the supply chain.

[0011] Furthermore, the supply chain service topology is determined by defining a closed area on an electronic map based on the supply chain service range, then determining points based on the current actual service range of the supply chain, and finally determining the supply chain service topology by connecting adjacent points. The current actual service range of the supply chain is a data packet consisting of the location coordinates of several order destinations. The basic adaptability evaluation operation for each supply chain is as follows: ; In the formula: For basic supply chain adaptability; This represents the average distance from the location of the supply chain in the topology corresponding to each candidate supply chain to the order receiving destination. For the supply chain The distance from its location in the corresponding topology to the order receiving destination; For the supply chain The shortest distance from the corresponding topological boundary to the order receiving destination; For the supply chain The shortest distance from each point on each path in the corresponding topology to the order receiving destination; For the supply chain The total number of paths in the corresponding topology; The coordinates of the destination for receiving the order; This is the i-th path; This is a decision function; if the condition inside the parentheses is true, it takes the value 1; otherwise, it takes the value 0. Here is the constraint function, and its value is: , Indicates the value of an expression within parentheses; This represents the maximum daily output of products according to supply chain theory. This refers to the average daily order volume within the supply chain. This refers to the quantity of products required for the order. Among them, based on supply chain basic adaptability Compared with the adaptation judgment threshold, the basic adaptation degree of the supply chain that exceeds the adaptation judgment threshold will be considered. The source supply chain serves as the initial screening result.

[0012] Furthermore, the paths in the supply chain topology, when determined, follow the following rules: Each route has been used at least once by the supply chain distribution department, and there is no overlap between the routes; When it is determined that there is only one suitable supply chain, the current output result is deemed invalid. The matching determination threshold is continuously lowered proportionally until at least two suitable supply chains are determined. At this point, the matching determination threshold is stopped, and the preliminary screening result of the supply chain is output.

[0013] Furthermore, the final fit analysis logic of each initially screened suitable supply chain relative to order demand information is expressed as follows: ; In the formula: For the initial screening of suitable supply chains The final fit; The average historical unit price of products across all supply chain order history information; For the supply chain The current unit price of the product; For the supply chain The historical average percentage of order losses; To define a custom minimum value and avoid a denominator of zero; For the supply chain Total historical order volume; , For the v-th historical order, the estimated delivery time and the actual delivery time are given. Configure the weight for the v-th order; ; For order demand timestamps; This is the current timestamp; For the supply chain The estimated delivery time for the order has been confirmed. Wherein, the configuration weight of the v-th order According to the supply chain The daily average order volume is determined from the order history information: , This represents the quantity of products corresponding to the v-th historical order. Indicates supply chain The daily average orders in the order history information include the total cumulative supply of products in the supply chain with a defined product quantity.

[0014] Furthermore, the correction logic for the final fit between the initially screened suitable supply chains and the order demand information is as follows: ; In the formula: The final result of the supply chain fit adjustment; This represents the percentage of loss for the v-th historical order.

[0015] Furthermore, the supply chains in the supply chain list are arranged based on their final fit correction results, with the supply chains with larger final fit correction results placed at the top of the list. The associated information for each supply chain in the supply chain list includes: basic supply chain information, the percentage of the latest three order losses in the historical information corresponding to the recent orders of the supply chain, and the unit price of the order products.

[0016] Compared with the known prior art, the technical solution provided by this invention has the following beneficial effects: This invention provides a method for early warning of supply chain risks in the chemical and plastics industry. During execution, this method accurately acquires multi-dimensional supply chain information and establishes a data cleaning logic to eliminate incomplete or unsuitable historical data, ensuring the effectiveness of the analysis foundation. It constructs a topology based on service scope and actual service points, and assesses basic compatibility using capacity data to accurately screen suitable supply chains, avoiding the problem of invalid single compatibility results. The final compatibility is calculated by weighting data such as historical unit price, loss rate, and timeliness deviation, and then corrected with product quality information to improve the accuracy of compatibility analysis. Finally, a list of supply chains sorted by the corrected results and annotated with key information intuitively presents high-quality options, helping users efficiently identify suitable supply chains, reducing cooperation risks caused by incomplete information and compatibility deviations, enhancing the scientific nature and reliability of supply chain selection, and providing precise decision support for supply chain management in the chemical and plastics industry. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0018] Figure 1This is a flowchart illustrating a risk warning method for the chemical and plastics supply chain in the chemical and plastics industry. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0020] The present invention will be further described below with reference to embodiments.

[0021] Example: This embodiment presents a method for early warning of risks in the chemical and plastics supply chain in the chemical and plastics industry, such as... Figure 1 As shown, it includes: Obtain basic supply chain information and order history information, set up supply chain order history information cleaning logic, and clean the supply chain order history information based on the supply chain order history information cleaning logic; Basic supply chain information includes: supply chain service scope, current actual service scope of the supply chain, average daily order volume of the supply chain, and theoretical maximum daily output of products in the supply chain; Supply chain order history information includes: order product unit price, order product quantity, order origin and destination, estimated delivery time and actual delivery time, and order damage percentage; The supply chain order history information cleaning logic is used to extract order history information from the supply chain order history information that will be used in subsequent analysis steps; Among them, the maximum daily output of products in the supply chain theory is determined based on the production equipment of the supply chain products, the estimated delivery time of orders is determined based on the order dispatch time and delivery time estimated by the supply chain back-end, and the actual delivery time of orders is determined based on the actual order dispatch time and delivery time of the supply chain. The acquisition of basic supply chain information and order history information corresponds to no less than three supply chain objectives. During the acquisition of basic supply chain information, a cloud database is created simultaneously for the differentiated storage of basic supply chain information. On the user side, the basic supply chain information can be manually deleted, newly stored, and modified in real time in the cloud database. Basic supply chain information and order history information come from supply chain service users. The logic for cleaning supply chain order history information is as follows: Traverse the historical supply chain order information, identify incomplete information in the historical supply chain order information, and use the incomplete historical supply chain order information as the first target for cleaning, and delete it from all the acquired historical supply chain order information; The user client sets exclusion criteria based on one or more of the following: order product unit price, order product quantity, order origin and destination, order estimated delivery time and actual delivery time, and order damage percentage. Based on these exclusion criteria, the historical information of supply chain orders is cleaned. The criteria for determining incomplete supply chain order history information are: any one or more of the following are missing: order product unit price, order product quantity, order origin and destination, order estimated delivery time and actual delivery time, and order damage percentage. Upload order demand information, and initially screen suitable supply chains based on the order demand information; Order demand information includes: order demand product quantity, order demand time, and order receiving destination. In the initial supply chain screening stage, a supply chain service topology is created based on the supply chain service scope and the current actual service scope of each supply chain in the basic information of each supply chain. Based on each supply chain service topology, the basic adaptability of the supply chain is evaluated in conjunction with the average daily order product quantity of each supply chain and the theoretical maximum daily product output of the supply chain. An adaptability judgment threshold is set, and all supply chains that meet the basic adaptability judgment threshold are used as the initial screening results and directed to the supply chain. The supply chain service topology is determined by defining a closed area on an electronic map based on the supply chain service scope, then determining points based on the current actual service scope of the supply chain, and finally determining the supply chain service topology by connecting adjacent points. The current actual service scope of the supply chain is a data packet consisting of the location coordinates of several order destinations. The basic adaptability assessment operation for each supply chain is as follows: ; In the formula: For basic supply chain adaptability; This represents the average distance from the location of the supply chain in the topology corresponding to each candidate supply chain to the order receiving destination. For the supply chain The distance from its location in the corresponding topology to the order receiving destination; For the supply chain The shortest distance from the corresponding topological boundary to the order receiving destination; For the supply chain The shortest distance from each point on each path in the corresponding topology to the order receiving destination; For the supply chain The total number of paths in the corresponding topology; The coordinates of the destination for receiving the order; This is the i-th path; This is a decision function; if the condition inside the parentheses is true, it takes the value 1; otherwise, it takes the value 0. Here is the constraint function, and its value is: , Indicates the value of an expression within parentheses; This represents the maximum daily output of products according to supply chain theory. This refers to the average daily order volume within the supply chain. This refers to the quantity of products required for the order. Among them, based on supply chain basic adaptability Compared with the adaptation judgment threshold, the basic adaptation degree of the supply chain that exceeds the adaptation judgment threshold will be considered. The source supply chain serves as an initial screening result; The above formula achieves basic fit assessment by integrating the spatial characteristics and capacity data of the supply chain service topology. Spatially, based on the closed area formed by the supply chain service scope, it calculates the average distance from the location within the topology to the order destination, the shortest distance at the boundary, and the shortest distance for each path. Combined with the total number of paths, it constructs distance-related indicators to reflect the spatial matching degree between the supply chain service coverage and the order destination. In terms of capacity, it introduces the correlation between the theoretical maximum daily output, the average daily order product quantity, and the order demand product quantity, quantifying the capacity fulfillment capability through constraint functions. Overall, through the comprehensive calculation of distance and capacity indicators, a basic fit is formed, ensuring that supply chains that meet the basic needs of orders in terms of service coverage and capacity supply are initially selected. When the paths in the supply chain topology are determined, they follow the following rules: Each route has been used at least once by the supply chain distribution department, and there is no overlap between the routes; When it is determined that there is only one suitable supply chain, the current output result is deemed invalid. The suitable supply chain determination threshold is continuously lowered proportionally until at least two suitable supply chains are determined. Then, the adjustment of the suitable supply chain determination threshold is stopped, and the preliminary screening result of the supply chain is output. The final fit analysis logic for each initially screened suitable supply chain relative to order demand information is expressed as follows: ; In the formula: For the initial screening of suitable supply chains The final fit; The average historical unit price of products across all supply chain order history information; For the supply chain The current unit price of the product; For the supply chain The historical average percentage of order losses; To define a custom minimum value and avoid a denominator of zero; For the supply chain Total historical order volume; , For the v-th historical order, the estimated delivery time and the actual delivery time are given. Configure the weight for the v-th order; ; For order demand timestamps; This is the current timestamp; For the supply chain The estimated delivery time for the order has been confirmed. Wherein, the configuration weight of the v-th order According to the supply chain The daily average order volume is determined from the order history information: , This represents the quantity of products corresponding to the v-th historical order. Indicates supply chain The daily average orders in the order history information include the total cumulative supply of products in the supply chain with a defined product quantity. The above formula refines the adaptation assessment from multiple dimensions, including cost, quality, timeliness, and capacity utilization. At the cost level, it reflects price rationality by comparing the historical average product unit price with the current unit price. At the quality level, it introduces the average percentage of historical order damage to quantify the stability of supply chain product quality. At the timeliness level, it calculates timeliness reliability by weighting the deviation between the expected and actual delivery times of historical orders, combined with configuration weights determined by the average daily order volume. Simultaneously, it incorporates the correlation between order demand timestamps, the current timestamp, and the expected delivery time, as well as capacity utilization ratios, comprehensively calculating the final adaptation degree based on multiple dimensions to more accurately reflect the overall matching degree between the supply chain and order demand.

[0022] The correction logic for the final fit between the initially screened suitable supply chains and the order demand information is as follows: ; In the formula: The final result of the supply chain fit adjustment; This represents the percentage of loss for the v-th historical order. The above formula optimizes the final fit by incorporating damage data from specific historical orders. Based on the initial final fit calculation, the actual damage percentage of the v-th historical order is included in the correction process. By refining the consideration of historical quality performance, the fit result is adjusted. This correction mechanism reduces the bias that may arise from using only the average damage percentage, better reflecting the actual quality performance of the supply chain under different order scenarios. This allows the corrected fit result to more accurately reflect the impact of supply chain quality stability on overall fit.

[0023] Based on historical supply chain order information and the initially selected suitable supply chains, analyze the final fit of each initially selected suitable supply chain with respect to the order demand information. Obtain product quality information from the supply chain and revise the adaptation analysis results based on the supply chain product quality information; Set an output threshold, compare the output threshold with the corrected analysis results, and output the supply chain corresponding to the corrected analysis results that meet the output threshold. Create a supply chain list and label the associated information for each supply chain in the list; The supply chains in the supply chain list are arranged based on their final fit adjustment results, with the supply chains with larger final fit adjustment results placed at the top of the list; The associated information for each supply chain in the supply chain list includes: basic supply chain information, the percentage of the three most recent order losses in the historical information corresponding to the supply chain's recent orders, and the unit price of the order products.

[0024] In this embodiment, the method described above precisely cleans historical supply chain order data, constructs topology-based screening of suitable supply chains based on service scope and capacity, and then combines multi-dimensional analysis of price, timeliness, and damage to correct the fit, ultimately outputting a list of high-quality supply chains. This ensures data accuracy, improves the precision of supply chain matching, and reduces the risks caused by insufficient capacity, time delays, and excessive damage, helping enterprises efficiently select reliable supply chains and avoid risky supply chains.

[0025] The following is an application example of the method described in the above embodiments: A chemical and plastics manufacturing company plans to purchase a batch of polyethylene raw materials and needs to select suitable supply chain partners through supply chain risk warning methods. The specific application process is as follows: I. Information Acquisition and Data Cleaning The company first identified three potential supply chain targets (denoted as Supply Chain A, B, and C) and collected basic information and order history data for each supply chain. The basic supply chain information included: Supply Chain A's service area is East China, currently covering five cities including Shanghai and Hangzhou, with an average daily order volume of 50 tons and a theoretical maximum daily output of 80 tons; Supply Chain B's service area is South China, currently covering four cities including Guangzhou and Shenzhen, with an average daily order volume of 40 tons and a theoretical maximum daily output of 70 tons; and Supply Chain C's service area is East China, currently covering six cities including Shanghai and Nanjing, with an average daily order volume of 60 tons and a theoretical maximum daily output of 90 tons. The order history data covered the unit price, quantity, origin and destination, estimated and actual delivery time, and percentage of damage for each supply chain over the past six months.

[0026] Subsequently, the company processed the historical information according to the set cleaning logic: first, incomplete information was deleted, removing three order records that lacked "actual delivery time"; second, based on the user-defined exclusion criteria (orders with a damage percentage exceeding 5%), two historical orders with excessive damage were deleted, ultimately retaining valid historical data for subsequent analysis. Simultaneously, the company stored three basic supply chain information entries in its cloud database for convenient real-time management.

[0027] II. Order Request Upload and Initial Screening The order requirements uploaded by the company are as follows: the order quantity is 60 tons, the delivery time is 10 days later (i.e., it needs to be delivered within 10 days), and the destination is Shanghai.

[0028] In the initial screening phase, companies created service topologies based on the service scope of each supply chain and the current actual service scope: the service topologies of supply chains A and C both include the Shanghai area (A's topology is a closed area centered on Shanghai, connecting 5 locations including Hangzhou; C's topology is a closed area centered on Shanghai, connecting 6 locations including Nanjing), while B's service topology does not cover Shanghai. Basic fit was assessed by combining average daily order volume and theoretical maximum output: A's theoretical maximum output is 80 tons ≥ 60 tons, and its average daily output of 50 tons is close to demand; C's theoretical maximum output is 90 tons ≥ 60 tons, and its average daily output of 60 tons is a perfect match; B's basic fit is low because its service topology does not cover Shanghai. A fit threshold of 70 was set. After evaluation, A's basic fit was 85, and C's was 80, both exceeding the threshold; B's basic fit was 55, failing to meet the standard. The initial screening results were supply chains A and C.

[0029] III. Final Fit Analysis and Correction Based on the initial screening results, the company analyzed the final fit between A and C. The calculation considered the historical average order unit price (10,000 RMB / ton), current unit price (9,500 RMB / ton for A, 10,500 RMB / ton for C), historical average loss percentage (2% for A, 3% for C), historical order delivery time deviation (A's actual delivery time was on average 1 day faster than expected, while C's actual delivery time was on average 0.5 days slower than expected), and product quantity matching (both A and C's theoretical output can meet the demand of 60 tons). After comprehensive calculation, the final fit of A was 88%, and the final fit of C was 75%.

[0030] Next, the company made corrections based on product quality information: A's recent three order loss percentages were 1%, 2%, and 1%, respectively, indicating stable quality, and the corrected fit was 85%; C's recent three order loss percentages were 3%, 2%, and 4%, respectively, showing slight fluctuations, and the corrected fit was 76%.

[0031] IV. Result Output and List Creation The company sets the output threshold to 80. Among supply chains A (corrected fit 85) and C (corrected fit 76), A meets the output threshold. In the final created supply chain list, A is listed first, with the following associated information: service area is East China, average daily order volume is 50 tons, theoretical maximum daily output is 80 tons, the percentage of loss for the three most recent orders is 1%, 2%, and 1%, and the current product unit price is 0.95 million yuan / ton.

[0032] In summary, the above method, during its implementation, accurately acquires multi-dimensional supply chain information and establishes a cleansing logic to eliminate incomplete and unsuitable historical data, ensuring the effectiveness of the analytical foundation. It constructs a topology based on service scope and actual service points, assesses basic compatibility using capacity data, and accurately selects suitable supply chains, avoiding the problem of invalid single compatibility results. The final compatibility is calculated by weighting data such as historical unit price, loss rate, and timeliness deviation, and then corrected with product quality information to improve the accuracy of compatibility analysis. Finally, the supply chain list, sorted by the corrected results and annotated with key information, intuitively presents high-quality options, helping users efficiently identify suitable supply chains, reducing cooperation risks caused by incomplete information and compatibility deviations, enhancing the scientific nature and reliability of supply chain selection, and providing precise decision support for supply chain management in the chemical and plastics industry.

[0033] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for early warning of risks in the chemical and plastics supply chain in the chemical and plastics industry, characterized in that, include: Obtain basic supply chain information and order history information, set up supply chain order history information cleaning logic, and clean the supply chain order history information based on the supply chain order history information cleaning logic; Upload order demand information, and initially screen suitable supply chains based on the order demand information; Based on historical supply chain order information and the initially selected suitable supply chains, analyze the final fit of each initially selected suitable supply chain with respect to the order demand information. The order demand information includes: order demand product quantity, order demand time, and order receiving destination. In the initial screening stage of the supply chain, a supply chain service topology is created based on the supply chain service scope and the current actual service scope of each supply chain in the basic information of each supply chain. Based on each supply chain service topology, the basic adaptability of the supply chain is evaluated in conjunction with the average daily order product quantity of each supply chain and the theoretical maximum daily product output of the supply chain. An adaptability judgment threshold is set, and all supply chains that meet the basic adaptability judgment threshold are used as the initial screening results and directed to the supply chain. The supply chain service topology is determined by defining a closed area on an electronic map based on the supply chain service range, then determining points based on the current actual service range of the supply chain, and finally determining the supply chain service topology by connecting adjacent points. The current actual service range of the supply chain is a data packet consisting of the location coordinates of several order destinations. The basic adaptability assessment operation for each supply chain is as follows: ； In the formula: For basic supply chain adaptability; This represents the average distance from the location of the supply chain in the topology corresponding to each candidate supply chain to the order receiving destination. For the supply chain The distance from its location in the corresponding topology to the order receiving destination; For the supply chain The shortest distance from the corresponding topological boundary to the order receiving destination; For the supply chain The shortest distance from each point on each path in the corresponding topology to the order receiving destination; For the supply chain The total number of paths in the corresponding topology; The destination coordinates for receiving the order; This is the i-th path; This is a decision function; if the condition inside the parentheses is true, it takes the value 1; otherwise, it takes the value 0. Here is the constraint function, and its value is: , Indicates the value of an expression within parentheses; This represents the maximum daily output of products according to supply chain theory. This refers to the average daily order volume within the supply chain. This refers to the quantity of products required for the order. Among them, based on supply chain basic adaptability Compared with the adaptation judgment threshold, the basic adaptation degree of the supply chain that exceeds the adaptation judgment threshold will be considered. The source supply chain serves as an initial screening result; The final fit analysis logic for each initially screened suitable supply chain relative to order demand information is expressed as follows: ； In the formula: For the initial screening of suitable supply chains The final fit; The average historical unit price of products across all supply chain order history information; For the supply chain The current unit price of the product; For the supply chain The historical average percentage of order losses; To define a custom minimum value and avoid a denominator of zero; For the supply chain Total historical order volume; , For the v-th historical order, the estimated delivery time and the actual delivery time are given. Configure the weight for the v-th order; ; For order demand timestamps; This is the current timestamp; For the supply chain The estimated delivery time for the order has been confirmed. Wherein, the configuration weight of the v-th order According to the supply chain The daily average order volume is determined from the order history information: , This represents the quantity of products corresponding to the v-th historical order. Indicates supply chain The daily average orders in the order history information include the total cumulative supply of products in the supply chain with a defined product quantity. The correction logic for the final fit between the adapted supply chains obtained from each initial screening and the order demand information is as follows: ； In the formula: The final result of the supply chain fit adjustment; The percentage of loss for the vth historical order. Obtain product quality information from the supply chain and revise the adaptation analysis results based on the supply chain product quality information; Set an output threshold, compare the output threshold with the corrected analysis results, and output the supply chain corresponding to the corrected analysis results that meet the output threshold. Create a supply chain list and label the associated information for each supply chain in the list.

2. The method for early warning of risks in the chemical and plastics supply chain in the chemical and plastics industry according to claim 1, characterized in that, The basic information of the supply chain includes: the service scope of the supply chain, the current actual service scope of the supply chain, the average daily order volume of the supply chain, and the theoretical maximum daily output of products of the supply chain. The historical supply chain order information includes: order product unit price, order product quantity, order origin and destination, estimated and actual delivery time, and order damage percentage. The supply chain order history information cleaning logic is used to extract order history information from the supply chain order history information that will participate in subsequent analysis steps; Among them, the maximum daily output of products in the supply chain theory is determined based on the production equipment of the supply chain products, the estimated delivery time of orders is determined based on the order dispatch time and delivery time estimated by the supply chain back-end, and the actual delivery time of orders is determined based on the actual order dispatch time and delivery time of the supply chain. The acquisition of basic supply chain information and order history information corresponds to no less than three supply chain objectives. During the acquisition of basic supply chain information, a cloud database is created simultaneously for the differentiated storage of basic supply chain information. The user terminal can manually delete, store, and modify the basic supply chain information in the cloud database in real time.

3. The method for early warning of risks in the chemical and plastics supply chain in the chemical and plastics industry according to claim 1, characterized in that, The basic supply chain information and order history information are sourced from supply chain service users. The cleansing logic for the supply chain order history information is as follows: Traverse the historical supply chain order information, identify incomplete information in the historical supply chain order information, and use the incomplete historical supply chain order information as the first target for cleaning, and delete it from all the acquired historical supply chain order information; The user client sets exclusion criteria based on one or more of the following: order product unit price, order product quantity, order origin and destination, order estimated delivery time and actual delivery time, and order damage percentage. Based on these exclusion criteria, the historical information of supply chain orders is cleaned. The criteria for determining incomplete supply chain order history information are: any one or more of the following are missing: order product unit price, order product quantity, order origin and destination, order estimated delivery time and actual delivery time, and order damage percentage.

4. The method for early warning of risks in the chemical and plastics supply chain in the chemical and plastics industry according to claim 1, characterized in that, The paths in the supply chain topology, when determined, follow the following rules: Each route has been used at least once by the supply chain distribution department, and there is no overlap between the routes; When it is determined that there is only one suitable supply chain, the current output result is deemed invalid. The matching determination threshold is continuously lowered proportionally until at least two suitable supply chains are determined. At this point, the matching determination threshold is stopped, and the preliminary screening result of the supply chain is output.

5. The method for early warning of risks in the chemical and plastics supply chain according to claim 1, characterized in that, The supply chains in the supply chain list are arranged based on their final fit correction results, with the supply chains with larger final fit correction results placed at the top of the list. The associated information for each supply chain in the supply chain list includes: basic supply chain information, the percentage of the latest three order losses in the historical information corresponding to the recent orders of the supply chain, and the unit price of the order products.

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