Supply chain material information integrated management system based on cloud platform

Abstract

The invention relates to the technical field of supply chain management, in particular to a supply chain material information integrated management system based on a cloud platform, which comprises a basic information management module, an inventory management module, a supply chain collaboration module, a data analysis and decision support module and a safety management module. According to the invention, information of each link in the supply chain is integrated, and real-time sharing and collaborative management of material data are realized; the transparency of the supply chain is improved, efficient collaboration of all links is ensured, information islands and delay phenomena are reduced, and the overall supply chain efficiency is improved; according to the invention, a data analysis and decision support module is integrated, trend prediction is carried out according to historical data, and scientific supply chain decision support is provided for enterprises; particularly, when market demands change or emergencies occur, the system can provide coping strategies in time, and the response capacity and decision accuracy of enterprises are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of supply chain management, and in particular to a supply chain material information integrated management system based on a cloud platform. Background Art

[0002] Supply chain management (SCM) technology involves coordinating and optimizing the material flow, information flow, and capital flow in the supply chain to ensure efficient use of resources in each link of the supply chain and reduce inventory backlogs and logistics costs. The supply chain information integration management system promotes the seamless connection of various links in the supply chain by sharing and updating material information in real time. Although the cloud-based supply chain material information integration management system has improved the efficiency and transparency of the supply chain in many aspects, there are still some technical challenges and problems in actual application, including the following aspects:

[0003] First, although the cloud platform can integrate data from all parties, the data formats, standards and interfaces between different suppliers, manufacturers or logistics companies are not unified, and information asymmetry still exists. Data silos are still the main bottleneck restricting the efficiency of supply chain collaboration.

[0004] Secondly, although the cloud platform has strong computing and data processing capabilities, the real-time performance and data accuracy of the system are still facing challenges when facing the real-time collection and processing of massive material information. Especially in the dynamic adjustment of material procurement, production scheduling and logistics management, how to ensure the timely update and accurate feedback of information is a difficult point in technical implementation.

[0005] Finally, in the supply chain management system, a large amount of sensitive data is involved. How to ensure the security and privacy of this data and prevent data leakage and cyber attacks is still an urgent problem to be solved. Especially when multiple parties use the cloud platform, data protection and access rights management become particularly important.

[0006] In response to the above problems, it is necessary to propose a supply chain material information integrated management system based on cloud platform. Summary of the invention

[0007] The purpose of the present invention is to solve the problems existing in the background technology and to propose a supply chain material information integrated management system based on a cloud platform.

[0008] The purpose of the present invention can be achieved through the following technical solutions:

[0009] The cloud platform-based supply chain material information integrated management system includes basic information management module, inventory management module, supply chain collaboration module, data analysis and decision support module and security management module.

[0010] The basic information management module performs material category management, material information management and supplier information management. The material category management mentioned is as follows:

[0011] Retrieve the preset material category table, which contains several material types. Each material type corresponds to several preset attribute fields, including category ID field, type name field, supplier name field, inventory field, specification field and whether to enable field.

[0012] The material information management is specifically as follows:

[0013] Map the material category table to a tree structure to manage material information in a hierarchical and classified manner.

[0014] The tree structure includes:

[0015] Top-level root node: Automobile production line materials;

[0016] The first level of classification: includes three nodes: raw materials, semi-finished products and finished products.

[0017] The second level classification includes several nodes representing the subordinate material categories of specific raw materials, semi-finished products and finished products, corresponding to:

[0018] Specific raw material categories, including metals, plastics and rubber;

[0019] Specific categories of semi-finished products include roofs, chassis, doors, sensors, controllers, seat frames, instrument panels and interior trims;

[0020] Specific finished product categories include engines, transmissions, drive shafts, clutches, brake pads and discs.

[0021] The third level of classification: specific information of each specific material, including the specifications, materials, current total inventory and historical highest inventory of each raw material category; the specifications, materials, current total inventory and historical highest inventory of each semi-finished product category; the specifications, materials, current total inventory and historical highest inventory of each finished product category.

[0022] The fourth level of classification is the inventory batch information of each material, including the material batch number, storage warehouse number, inventory quantity of the batch, initial purchase cost, operating cost, supplier name, supplier contact information, disposal cost, discount rate and material service life.

[0023] Whenever new material information v is added to the tree structure, it is verified in hierarchical depth.

[0024] By formula Calculate the classification depth D(v) of the new material information in the tree structure, that is, the number of layers to which the newly added new material information belongs in the tree structure; where u and v are the node numbers in the tree structure, and children(v) is the set of child nodes of node v. If D(v) is consistent with the numerical value of the layer depth of the newly added new material information v, it is determined that the layer depth of the new material information v is correctly allocated; otherwise, it is determined that the layer depth of the new material information v is incorrectly allocated, and the new material information v is removed from the tree structure, and then its corresponding layer depth is reallocated.

[0025] The structure tampering self-check is performed at preset time intervals, and the layer depth verification is traversed through all nodes in the tree structure, and nodes that do not meet the condition: D(v) is consistent with the value of the layer depth where the newly added new material information v is located are removed from the tree structure.

[0026] The supplier management described is specifically: managing supplier information based on designing supplier forms through SQL statements.

[0027] The supplier information includes supplier name, contact information, supplier credit rating, supply capacity index, goods quality rating and logistics cost base.

[0028] The inventory management module manages the incoming and outgoing materials.

[0029] The warehousing management includes: recording the warehousing information of materials, including the warehousing date, warehouse name, warehousing person, custodian, supplier, etc., to ensure the accuracy and traceability of the warehousing materials.

[0030] The outbound management includes: recording the outbound information of materials, including the outbound date, outbound person, outbound warehouse, outbound customer, etc., to ensure the compliance and timeliness of outbound materials.

[0031] As a preferred embodiment of the present invention, a first-in-first-out algorithm is used to manage the order in which materials are shipped out of the warehouse, thereby minimizing the backlog of expired or slow-moving materials.

[0032] Get the entry date t0, current inventory Q, maximum inventory Q_max, historical inventory Qt at time t, historical outbound quantity Vt at time t and expiration date t_max of each batch of incoming materials.

[0033] By formula Calculate the incoming time factor T, turnover factor S and expiration risk factor D of each batch of incoming materials, where λ1 and λ2 are preset weight factors.

[0034] As a preferred embodiment of the present invention, the formula Priority = Q × (e S +e T+D) Calculate the outbound priority of each batch of incoming materials. Whenever an outbound operation is performed for a certain type of material, obtain the batch with the highest outbound priority among the materials of this type and mark it as the backlog material to be outbound.

[0035] The supply chain collaboration module realizes supply chain management through the collaboration of production and logistics.

[0036] The production collaboration described is specifically: connecting with the production planning system to achieve real-time sharing and collaborative adjustment of production progress.

[0037] By formula Calculate the production progress P of material batch j at time t j (t). is the estimated consumption progress of material batch j in the production plan, where ΔP j (t) is the deviation between the actual production progress and the estimated consumption progress of material batch j; α is the production coefficient factor, which indicates the influence of inventory on production progress; Q j (t) is the inventory of material batch j at time t, is the minimum inventory threshold of material batch j.

[0038] The logistics collaboration specifically includes: connecting with the logistics system to achieve real-time tracking and collaborative management of logistics information.

[0039] By formula Calculate the actual transportation status factor L of material batch j at time t j (t), where is the expected transportation arrival time given by the logistics planning system, where ΔL j (t) is the deviation characteristic value of the logistics status, which is matched to a preset specific value according to the transportation status of the logistics batch j, and the transportation status includes delay, early arrival and transshipment.

[0040] As a preferred embodiment of the present invention, by formula Calculate the overall synergy index, the first imbalance coefficient R1(t) and the second imbalance coefficient R2(t), where β1 and β2 are preset influencing factors. When C(t) is greater than the preset threshold, the production synergy and logistics synergy are judged to be unbalanced, and the logistics batch with the largest first imbalance coefficient is retrieved to determine its production synergy abnormality; the logistics batch with the largest second imbalance coefficient is retrieved to determine its logistics synergy abnormality.

[0041] The data analysis and decision support module conducts in-depth analysis of supply chain material data to explore the patterns and trends behind the data. Based on the data analysis results, it provides enterprises with decision support in inventory management, procurement strategies, etc., including inventory status forecasting decision support and material operation decision support;

[0042] The inventory status forecast decision support is specifically:

[0043] Based on ARIMA autoregressive moving average, a material inventory fluctuation prediction model is established, and the inventory vector at time t is defined as: X t ={x1, x2, ..., xm}, where x1, x2, ..., xm are the inventory of each material category. Calculate the forecast inventory vector at time t Where μ is a constant term, and φ i is the preset autoregressive coefficient, which indicates the impact of past inventory values ​​on the predicted inventory volume; j is the moving average coefficient, which indicates the impact of past errors on the forecasted inventory quantity, where ε t-j is the error vector, representing the predicted inventory vector at time tj and the actual inventory vector X t = the error of {x1, x2, ..., xm}, specifically the difference between the predicted inventory vector and the actual inventory vector at time t. t The fluctuation range is 0 to The error random number, where The specific value of is equal to the historical error vector with the largest vector modulus divided by the total number of material categories m.

[0044] The material operation decision support is specifically:

[0045] Get the purchase quantity m and initial purchase cost C of each batch of materials initial , operating cost C in year t operation (t), final disposal cost C disposal , discount rate r and useful life n.

[0046] By formula Calculate its operating cost base OCB. Where LCC is the life cycle cost of the material, and k1 and k2 are preset weight factors.

[0047] The security management module sets different permissions for different users to ensure the security of the system and the confidentiality of data. Encryption technology and data backup strategies are used to ensure the security and reliability of data.

[0048] The users and permissions described include:

[0049] Open data modification, editing, data access, log access and data export permissions to administrator users;

[0050] Open data access, log access rights and data export rights to auditors;

[0051] Only data access permissions are granted to guest users;

[0052] Only data access permissions are open to API interface users.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] 1. The present invention integrates the information of each link in the supply chain to realize the real-time sharing and collaborative management of material data; through the basic information management module, inventory management module, supply chain collaboration module and other functional modules, the system can enable suppliers, manufacturers, warehouse managers, logistics companies, etc. to grasp the specific status, inventory situation and production progress of materials in real time, thereby improving the transparency of the supply chain, ensuring efficient collaboration of each link, reducing information islands and delays, and improving the overall supply chain efficiency;

[0055] 2. The present invention can help enterprises accurately grasp key information such as material specifications, inventory, historical maximum inventory, etc. through precise material category management and hierarchical classification structure, so as to optimize inventory management; the system tracks the inventory dynamics of materials in real time, combines production demand forecasting and supply chain collaboration modules, and automatically adjusts material procurement, inventory allocation and production plans, avoiding excessive backlog or shortage of materials, reducing inventory costs, improving material utilization, and ensuring smooth production process;

[0056] 3. The present invention integrates data analysis and decision support modules, which can conduct comprehensive analysis and prediction of various types of information in the supply chain based on real-time data; through big data analysis technology, the system can not only optimize decisions such as material procurement, production scheduling and logistics distribution, but also make trend predictions based on historical data, and provide scientific supply chain decision support for enterprises; especially when market demand changes or emergencies occur, the system can provide response strategies in a timely manner to enhance the enterprise's adaptability and the accuracy of decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings:

[0058] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0059] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] See also Figure 1 As shown, the cloud platform-based supply chain material information integrated management system includes basic information management module, inventory management module, supply chain collaboration module, data analysis and decision support module and security management module.

[0061] The basic information management module performs material category management, material information management and supplier information management. The material category management mentioned is as follows:

[0062] Retrieve the preset material category table, which contains several material types. Each material type corresponds to several preset attribute fields, including category ID field, type name field, supplier name field, inventory field, specification field and whether to enable field.

[0063] The material information management is specifically as follows:

[0064] Map the material category table to a tree structure to manage material information in a hierarchical and classified manner.

[0065] The tree structure includes:

[0066] Top-level root node: Automobile production line materials;

[0067] The first level of classification: includes three nodes: raw materials, semi-finished products and finished products.

[0068] The second level classification includes several nodes representing the subordinate material categories of specific raw materials, semi-finished products and finished products, corresponding to:

[0069] Specific raw material categories, including metals, plastics and rubber;

[0070] Specific categories of semi-finished products include roofs, chassis, doors, sensors, controllers, seat frames, instrument panels and interior trims;

[0071] Specific finished product categories include engines, transmissions, drive shafts, clutches, brake pads and discs.

[0072] The third level of classification: specific information of each specific material, including the specifications, materials, current total inventory and historical highest inventory of each raw material category; the specifications, materials, current total inventory and historical highest inventory of each semi-finished product category; the specifications, materials, current total inventory and historical highest inventory of each finished product category.

[0073] The fourth level of classification is the inventory batch information of each material, including the material batch number, storage warehouse number, inventory quantity of the batch, initial purchase cost, operating cost, supplier name, supplier contact information, disposal cost, discount rate and material service life.

[0074] Whenever new material information v is added to the tree structure, it is verified in hierarchical depth.

[0075] By formula Calculate the classification depth D(v) of the new material information in the tree structure, that is, the number of layers to which the newly added new material information belongs in the tree structure; where u and v are the node numbers in the tree structure, and children(v) is the set of child nodes of node v. If D(v) is consistent with the numerical value of the layer depth of the newly added new material information v, it is determined that the layer depth of the new material information v is correctly allocated; otherwise, it is determined that the layer depth of the new material information v is incorrectly allocated, and the new material information v is removed from the tree structure, and then its corresponding layer depth is reallocated.

[0076] The structure tampering self-check is performed at preset time intervals, and the layer depth verification is traversed through all nodes in the tree structure, and nodes that do not meet the condition: D(v) is consistent with the value of the layer depth where the newly added new material information v is located are removed from the tree structure.

[0077] The supplier management described is specifically: managing supplier information based on designing supplier forms through SQL statements.

[0078] The supplier information includes supplier name, contact information, supplier credit rating, supply capacity index, goods quality rating and logistics cost base.

[0079] The inventory management module manages the incoming and outgoing materials.

[0080] The warehousing management includes: recording the warehousing information of materials, including the warehousing date, warehouse name, warehousing person, custodian, supplier, etc., to ensure the accuracy and traceability of the warehousing materials.

[0081] The outbound management includes: recording the outbound information of materials, including the outbound date, outbound person, outbound warehouse, outbound customer, etc., to ensure the compliance and timeliness of outbound materials.

[0082] Furthermore, the first-in-first-out algorithm is used to manage the order in which materials are shipped out of the warehouse, thereby minimizing the backlog of expired or slow-moving materials.

[0083] Get the entry date t0, current inventory Q, maximum inventory Q_max, historical inventory Qt at time t, historical outbound quantity Vt at time t and expiration date t_max of each batch of incoming materials.

[0084] By formula Calculate the incoming time factor T, turnover factor S and expiration risk factor D of each batch of incoming materials, where λ1 and λ2 are preset weight factors.

[0085] Furthermore, by the formula Priority = Q × (e S +e T+D ) Calculate the outbound priority of each batch of incoming materials. Whenever an outbound operation is performed for a certain type of material, obtain the batch with the highest outbound priority among the materials of this type and mark it as the backlog material to be outbound.

[0086] The supply chain collaboration module realizes supply chain management through the collaboration of production and logistics.

[0087] The production collaboration described is specifically: connecting with the production planning system to achieve real-time sharing and collaborative adjustment of production progress.

[0088] By formula Calculate the production progress P of material batch j at time t j (t). is the estimated consumption progress of material batch j in the production plan, where ΔP j (t) is the deviation between the actual production progress and the estimated consumption progress of material batch j; α is the production coefficient factor, which indicates the influence of inventory on production progress; Q j (t) is the inventory of material batch j at time t, is the minimum inventory threshold of material batch j.

[0089] The logistics collaboration specifically includes: connecting with the logistics system to achieve real-time tracking and collaborative management of logistics information.

[0090] By formula Calculate the actual transportation status factor L of material batch j at time t j (t), where is the expected transportation arrival time given by the logistics planning system, where ΔL j (t) is the deviation characteristic value of the logistics status, which is matched to a preset specific value according to the transportation status of the logistics batch j, and the transportation status includes delay, early arrival and transshipment.

[0091] Furthermore, through the formula Calculate the overall synergy index, the first imbalance coefficient R1(t) and the second imbalance coefficient R2(t), where β1 and β2 are preset influencing factors. When C(t) is greater than the preset threshold, the production synergy and logistics synergy are judged to be unbalanced, and the logistics batch with the largest first imbalance coefficient is retrieved to determine its production synergy abnormality; the logistics batch with the largest second imbalance coefficient is retrieved to determine its logistics synergy abnormality.

[0092] The data analysis and decision support module conducts in-depth analysis of supply chain material data to explore the patterns and trends behind the data. Based on the data analysis results, it provides enterprises with decision support in inventory management, procurement strategies, etc., including inventory status forecasting decision support and material operation decision support;

[0093] The inventory status forecast decision support is specifically:

[0094] Based on ARIMA autoregressive moving average, a material inventory fluctuation prediction model is established, and the inventory vector at time t is defined as: X t ={x1, x2, ..., xm}, where x1, x2, ..., xm are the inventory of each material category. Calculate the forecast inventory vector at time t Where μ is a constant term, and φ i is the preset autoregressive coefficient, which indicates the impact of past inventory values ​​on the predicted inventory volume; j is the moving average coefficient, which indicates the impact of past errors on the forecasted inventory quantity, where ε t-j is the error vector, representing the predicted inventory vector at time tj and the actual inventory vector X t = the error of {x1, x2, ..., xm}, specifically the difference between the predicted inventory vector and the actual inventory vector at time t. t The fluctuation range is 0 to The error random number, where The specific value of is equal to the historical error vector with the largest vector modulus divided by the total number of material categories m.

[0095] The material operation decision support is specifically:

[0096] Get the purchase quantity m and initial purchase cost C of each batch of materials initial , operating cost C in year t operation (t), final disposal cost C disposal , discount rate r and useful life n.

[0097] By formula Calculate its operating cost base OCB. Where LCC is the life cycle cost of the material, and k1 and k2 are preset weight factors.

[0098] The security management module sets different permissions for different users to ensure the security of the system and the confidentiality of data. Encryption technology and data backup strategies are used to ensure the security and reliability of data.

[0099] The users and permissions described include:

[0100] Open data modification, editing, data access, log access and data export permissions to administrator users;

[0101] Open data access, log access rights and data export rights to auditors;

[0102] Only data access permissions are granted to guest users;

[0103] Only data access permissions are open to API interface users.

[0104] It should be understood that the terms “include” and “comprising” used in the specification and claims of the present disclosure indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0105] It should also be understood that the terms used in this disclosure are only for the purpose of describing specific embodiments and are not intended to limit the disclosure. As used in this disclosure and the claims, the singular forms "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise. It should also be further understood that the term "and / or" used in this disclosure and the claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations;

[0106] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A cloud-based supply chain material information integrated management system, including basic information management module, supply chain collaboration module and data analysis and decision support module, which is characterized by ； The basic information management module manages material categories, material information and supplier information, and standardizes and updates material data in real time; The supply chain collaboration module realizes supply chain management through the collaboration of production and logistics; through production collaborative management, it realizes docking with the production planning system, shares production progress data in real time, adjusts material distribution plans and production schedules, and optimizes resource allocation; through logistics collaborative management, it realizes docking with the logistics system, tracks the status and location of material transportation, ensures the visualization of the logistics process, and adjusts transportation arrangements in a timely manner; Conduct comprehensive assessment of production collaborative management and logistics collaborative management; The data analysis and decision support module conducts in-depth analysis of supply chain material data to explore the patterns and trends behind the data; based on the data analysis results, it provides enterprises with decision support in inventory management and procurement strategies, including inventory status forecasting decision support and material operation decision support.

2. The cloud platform-based supply chain material information integrated management system according to claim 1 further comprises an inventory management module and a security management module, characterized in that: The inventory management module manages the incoming and outgoing materials, monitors the inventory status of materials in real time, ensures optimal control of inventory, and avoids overstocking or material shortages; provides real-time update and dynamic management of inventory data of various materials, and performs intelligent scheduling in combination with material demand; The security management module sets different permissions for different users to ensure the security of the system and the confidentiality of data; it uses encryption technology and data backup strategies to ensure the security and reliability of data.

3. The cloud platform-based supply chain material information integrated management system according to claim 1 is characterized in that: The specific process of material category management, material information management and supplier information management is as follows: The material category management is specifically as follows: Retrieve the preset material category table, which contains several material categories. Each material category corresponds to several preset attribute fields, including category ID field, category name field, supplier name field, inventory field, specification field, and whether to enable field; The material information management is specifically as follows: Map the material category table to a tree structure to manage material information in a hierarchical and classified manner; The tree structure includes: Top-level root node: Automobile production line materials; The first level of classification: including three nodes: raw materials, semi-finished products and finished products; The second level classification includes several nodes representing the subordinate material categories of specific raw materials, semi-finished products and finished products, corresponding to: Specific raw material categories, including metals, plastics and rubber; Specific categories of semi-finished products include roofs, chassis, doors, sensors, controllers, seat frames, instrument panels and interior trims; Specific finished product categories include engines, transmissions, drive shafts, clutches, brake pads and discs; The third level of classification: specific information of each specific material, including the specifications, materials, current total inventory and historical highest inventory of each raw material category; the specifications, materials, current total inventory and historical highest inventory of each semi-finished product category; the specifications, materials, current total inventory and historical highest inventory of each finished product category; The fourth level of classification is the inventory batch information of each material, including the material batch number, storage warehouse number, inventory quantity of the batch, initial purchase cost, operating cost, supplier name, supplier contact information, disposal cost, discount rate and material service life; Whenever new material information v is added to the tree structure, it is verified in layer depth; The supplier management is specifically: managing supplier information based on designing supplier forms through SQL statements; The supplier information includes supplier name, contact information, supplier credit rating, supply capacity index, goods quality rating and logistics cost base.

4. The cloud platform-based supply chain material information integrated management system according to claim 3 is characterized in that: The specific process of layered depth verification is as follows: By formula Calculate the classification depth D(v) of the new material information in the tree structure, that is, the number of layers to which the newly added new material information belongs in the tree structure; where u and v are the node numbers in the tree structure, and children(v) is the set of child nodes of node v; if D(v) is consistent with the numerical value of the layer depth of the newly added new material information v, it is determined that the layer depth allocation of the new material information v is correct; otherwise, it is determined that the layer depth allocation of the new material information v is wrong, and the new material information v is removed from the tree structure, and then its corresponding layer depth is reallocated; The structure tampering self-check is performed at preset time intervals, the hierarchical depth verification is traversed through all nodes in the tree structure, and nodes that do not meet the condition: D(v) is consistent with the numerical value of the hierarchical depth of the newly added new material information v are removed from the tree structure.

5. The cloud platform-based supply chain material information integrated management system according to claim 1 is characterized in that: The specific process of production collaborative management is: Connect with the production planning system to achieve real-time sharing and coordinated adjustment of production progress; By formula Calculate the production progress P of material batch j at time t j (t); where is the estimated consumption progress of material batch j in the production plan, where ΔP j (t) is the deviation between the actual production progress and the estimated consumption progress of material batch j; α is the production coefficient factor, which indicates the influence of inventory on production progress; Q j (t) is the inventory of material batch j at time t, is the minimum inventory threshold of material batch j.

6. The cloud platform-based supply chain material information integrated management system according to claim 1, characterized in that: The specific process of logistics collaborative management is: By formula Calculate the actual transportation status factor L of material batch j at time t j (t), where is the expected transportation arrival time given by the logistics planning system, where ΔL j (t) is the deviation characteristic value of the logistics status, which is matched to a preset specific value according to the transportation status of the logistics batch j, and the transportation status includes delay, early arrival and transshipment.

7. The cloud platform-based supply chain material information integrated management system according to claim 5 or 6, characterized in that: The specific process of comprehensive evaluation of production collaborative management and logistics collaborative management is as follows: By formula Calculate the overall coordination index, the first imbalance coefficient R1(t) and the second imbalance coefficient R2(t), where β1 and β2 are preset influencing factors; when C(t) is greater than the preset threshold, determine that production coordination and logistics coordination are unbalanced, retrieve the logistics batch with the largest first imbalance coefficient, and determine that its production coordination is abnormal; retrieve the logistics batch with the largest second imbalance coefficient, and determine that its logistics coordination is abnormal.

8. The cloud platform-based supply chain material information integrated management system according to claim 1, characterized in that: The inventory status forecasting decision support and material operation decision support are specifically: The inventory status forecast decision support is specifically: Based on ARIMA autoregressive moving average, a material inventory fluctuation prediction model is established, and the inventory vector at time t is defined as: X t ={x1, x2, ..., xm}, where x1, x2, ..., xm are the inventory quantities of each material category; through the formula Calculate the forecast inventory vector at time t Where μ is a constant term, and φ i is the preset autoregressive coefficient, which indicates the impact of past inventory values ​​on the predicted inventory volume; j is the moving average coefficient, which indicates the impact of past errors on the forecasted inventory quantity, where ε t-j is the error vector, representing the predicted inventory vector at time tj and the actual inventory vector X t = the error of {x1, x2, ..., xm}, specifically the difference between the predicted inventory vector and the actual inventory vector at time t; where randε t The fluctuation range is 0 to The error random number, where The specific value of is equal to the historical error vector with the largest vector modulus divided by the total number of material categories m; The material operation decision support is specifically: Get the purchase quantity m and initial purchase cost C of each batch of materials initial , operating cost C in year t operation (t), final disposal cost C disposal , discount rate r and useful life n; By formula Calculate its operating cost base (OCB); Where LCC is the life cycle cost of the material, and k1 and k2 are preset weight factors.

9. The cloud platform-based supply chain material information integrated management system according to claim 2, characterized in that: Real-time monitoring of material inventory to ensure optimal inventory control is as follows: Record the incoming materials information, including the incoming date, warehouse name, incoming person, custodian and supplier, to ensure the accuracy and traceability of incoming materials; The outbound management includes: recording the outbound information of materials, including the outbound date, outbound person, outbound warehouse and outbound customer, to ensure the compliance and timeliness of outbound materials; Combine the first-in-first-out algorithm to manage the order of material outbound delivery, thereby minimizing the backlog of expired or slow-moving materials; Get the entry date t0, current inventory Q, maximum inventory Q_max, historical inventory Qt at time t, historical outbound quantity Vt at time t and expiration date t_max of each batch of incoming materials; By formula Calculate the storage time factor T, turnover factor S and expiration risk factor D of each batch of incoming materials, where λ1 and λ2 are preset weight factors; By formula Priority = Q × (e S +e T+D ) Calculate the outbound priority of each batch of incoming materials; whenever an outbound operation is performed on a certain type of material, obtain the batch with the highest outbound priority among the materials of this type and mark it as the backlog material to be outbound.

10. The cloud platform-based supply chain material information integrated management system according to claim 2, characterized in that: The users and permissions described include: Open data modification, editing, data access, log access and data export permissions to administrator users; Open data access, log access rights and data export rights to auditors; Only data access permissions are granted to guest users; Only data access permissions are open to API interface users.

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