Accurate tracking management method for distribution network business expansion engineering material use data

Abstract

The invention relates to the field of distribution network industry material management, in particular to a distribution network industry expansion engineering material use data accurate tracking management method, which is deeply connected with an enterprise internal ERP system, construction cost structured data and a data medium table, constructs a distributed material management account book based on a block chain technology, realizes real-time query of material information and improves working efficiency. A recurrent neural network is utilized, a first supply material demand prediction model is established in combination with multi-source data, the material demand of each construction stage is accurately predicted, and resource allocation is optimized. Through coding material and project information, making a material distribution plan and approval record, establishing a two-way tracing mechanism and combining the Internet of Things technology to track materials in real time, the standardization and safety of material management are guaranteed. Meanwhile, materials are checked regularly, and the reporting process is standardized. The method effectively solves the problems of difficult material information query, inaccurate demand estimation and difficult data tracing, promotes continuous improvement and optimization of enterprise material management, and has significant economic benefits and management values.

Description

Technical Field

[0001] The present invention relates to the field of distribution network industry material management, and particularly to a method for accurately tracking and managing the usage data of materials in distribution network project expansion Background Art

[0002] In the situation of continuous social and economic development and rising electricity demand, distribution network project expansion has become a key measure to ensure power supply and meet new electricity loads. As the terminal link of power transmission, the construction and transformation projects of the distribution network are becoming increasingly frequent, involving the allocation and use of a large number of materials.

[0003] In the existing material management of distribution network project expansion, the enterprise internal ERP system, cost structured data and data center are in an independent state. This makes managers have to shuttle between multiple systems to query material information, and the work efficiency is extremely low. For the determination of material requirements, it mainly relies on experience estimation, resulting in either material shortage and project delay or material backlog and cost waste, and it is simply impossible to achieve the optimal allocation of resources. In terms of the material management of individual projects, the association between material attributes and project information is loose, the material allocation plan lacks a rigorous process, data traceability is difficult, the usage records and cost accounting are also inaccurate and incomplete, the generated reports are difficult to assist in decision-making, the management transparency is poor and the material utilization efficiency is extremely low, which greatly hinders the effective development and continuous progress of enterprise material management.

[0004] Therefore, it is necessary to propose a method for accurately tracking and managing the usage data of materials in distribution network project expansion to solve the above problems. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for accurately tracking and managing the usage data of materials in distribution network project expansion to solve the problems of time-consuming material information query, difficult estimation of material requirements and difficult traceability of material usage data.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A method for accurately tracking and managing the usage data of materials in distribution network project expansion, comprising the following steps:

[0008] S11: Deeply connect the enterprise internal ERP system, cost structured data and data center, build a material management system, and use blockchain technology to build a distributed material management ledger to achieve real-time query of material information;

[0009] S12: According to the designed quantity data of self-provided materials, combined with the project breakdown structure, map it to different individual projects, construction processes and progress, use a recurrent neural network, integrate historical project data, analyze the consumption law of self-provided materials in past projects, and establish a demand prediction model for self-provided materials;

[0010] S13: Compare the predicted demand for owner-supplied materials with the current inventory situation, calculate the shortage quantity, introduce Internet of Things technology, equip materials with intelligent sensors to collect location, quantity, status, and environmental condition information and transmit it to the system, establish an inbound and outbound registration and usage record process, and achieve real-time tracking of owner-supplied materials;

[0011] S14: Develop a monthly sampling and quarterly comprehensive material inventory plan, conduct on-site inventory of owner-supplied materials and reconcile with the system inventory data, and based on accurate prediction and tracking data, use an online approval system to standardize the submission process to ensure accurate and reasonable material submission.

[0012] Preferably, the method further includes steps for auxiliary distribution and traceability of materials for individual projects:

[0013] S21: Based on the existing multi-level data association between owner-supplied materials and individual projects, identify and code the attribute information of materials and the project information of individual projects;

[0014] S22: According to the construction schedule plan of individual projects and the predicted demand for owner-supplied materials in the structured cost data, develop a detailed material distribution plan and distribution approval and record process;

[0015] S23: Establish a two-way data traceability mechanism, develop a data traceability function in the system, and achieve forward traceability from material distribution records to individual projects and the overall project, as well as reverse traceability from the project to the details of material distribution;

[0016] S24: For each material distribution and use, record the actual usage quantity and calculate the cost and accumulate it into the accounting data of individual projects, and generate a material balance and inventory transfer report based on the accounting data;

[0017] In step S11, the ERP system realizes the query of ERP material inbound and outbound information by synchronizing the material inbound and outbound data of the data center, and realizes the query of ERP material inventory information by synchronizing the material inbound and outbound data of the data center; the ERP system obtains the designed quantity information of owner-supplied materials from the structured cost data, and ensures the consistency and accuracy of the data through the docking method of data extraction, transformation, and loading.

[0018] Preferably, in step S12, the prediction model for the demand of owner-supplied materials is as follows:

[0019] According to historical project data, let the construction progress data be X1, the project scale data be X2, the geographical environment data be X3, the market dynamics data be X4, the weather data be X5, the historical consumption rate of owner-supplied materials be X6, the predicted demand for owner-supplied materials be Y, the activation function of the hidden layer of the recurrent neural network be σ, and the weight matrices be W ih 、W hh 、W ho, the bias term is b h , b o , then the hidden layer state h t is,

[0020] h t = σ(W ih · [X 1t , X 2t , X 3t , X 4t , X 5t , X 6t + W hh · h t-1 + b h ),

[0021] The output layer is,

[0022]

[0023] where t represents time synchronization, corresponding to different construction stages.

[0024] Preferably, the regular material inventory plan is carried out in a combination of monthly and quarterly. The monthly inventory uses the sampling inventory method to conduct full inspections on key materials and high-value materials, and conducts spot checks on general materials; the quarterly inventory conducts a comprehensive inventory, generates a detailed inventory report after the inventory, including the actual quantity of materials, loss situation, analysis of inventory turnover rate indicators, and compares and analyzes with the system data to find out the reasons for the differences and make timely adjustments.

[0025] Preferably, when standardizing the submission process, an online approval system is adopted. The submission application includes detailed material requirement descriptions, usage plans, and budget estimate information; multiple approval nodes are set in the approval process, and the approval levels are determined according to the material type and amount. During the approval process, the system automatically associates inventory data and the demand prediction model for self-provided materials, providing decision-making references for the approval personnel to ensure the accuracy and rationality of the submission.

[0026] Preferably, for the coding of material attribute information, in addition to the basic name, specification, and model, it also includes the production date and batch number information of the materials, and is embedded into the overall coding using a specific time coding format.

[0027] Preferably, the data traceability function module adopts a storage architecture that combines a relational database and a graph database. The relational database is used to store the structured data of material distribution and usage, and the graph database is used to construct the complex relationship network between materials, individual projects, and projects. Through the visual graph display method, it is convenient for users to conduct forward and reverse traceability queries intuitively, improving the convenience and accuracy of data traceability.

[0028] Preferably, the data traceability function also has an abnormal data alarm mechanism. When abnormal material flow is found during the traceability process, such as when materials appear in unauthorized individual projects or the actual usage quantity seriously does not match the distribution plan, the system automatically triggers an alarm message to notify relevant management personnel to conduct investigations and handling in a timely manner, ensuring the standardization and security of material management.

[0029] Preferably, when recording the actual usage quantity of materials, for quantifiable materials, the usage data is automatically collected by devices such as electronic scales and length measuring instruments and uploaded to the system; for non-quantifiable materials, a combination of manual registration and on-site photography is used to record the usage situation, ensuring the accuracy and integrity of the usage quantity record.

[0030] Preferably, the generated material balance and inventory transfer reports adopt a standardized template format, including material balance quantity, amount, storage location, and usage efficiency information, and provide comparative analysis data with similar projects, providing data support and reference basis for subsequent material procurement and management decisions.

[0031] The technical effects and advantages of the present invention:

[0032] 1. Deeply connect with the enterprise's internal ERP system, cost structured data, and data center, establish a comprehensive material management system, and build a distributed material management ledger based on blockchain technology within the system. Management personnel can query the ERP material inbound, outbound, and inventory information in real time in a unified system without switching between multiple systems, greatly improving work efficiency.

[0033] 2. The two-way data traceability mechanism enables the accurate forward and reverse traceability of material distribution information between individual projects and the overall project. Adopting a hybrid storage architecture and visual display, it improves management transparency and controllability, facilitating the timely discovery and solution of problems.

[0034] 3. Establish a demand prediction model for owner-supplied materials to accurately predict the material requirements at each construction stage of different individual projects, make advance material reserve and allocation plans, effectively avoid project delays caused by material shortages or cost waste caused by material backlogs, and achieve the optimal allocation of resources.

[0035] 4. Introduce the Internet of Things technology to equip materials with intelligent sensors to collect information such as material location, quantity, status, and environmental conditions in real time, and use geographic information system (GIS) technology to intuitively display the material distribution and flow on a map, realizing the real-time tracking and monitoring of materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a structure diagram of the method for accurately tracking and managing material usage data in the distribution network service expansion project of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0038] The present invention provides a method for accurately tracking and managing the material usage data of the distribution network business expansion project as Figure 1 shown, including the following steps:

[0039] S11: Deeply connect to the enterprise internal ERP system, cost structured data, and data center, build a material management system, and use blockchain technology to build a distributed material management ledger to achieve real-time query of material information;

[0040] This ledger utilizes the immutable and decentralized characteristics of the blockchain to ensure the authenticity and integrity of material data, while facilitating managers to query material information in real time. Automatically execute the rules and processes in material management through smart contracts, such as inbound and outbound approvals, material distribution, etc.

[0041] Managers can query the ERP material inbound, outbound, and inventory information in real time in a unified material management system without switching between multiple systems, greatly improving work efficiency.

[0042] S12: According to the designed quantity data of the owner-supplied materials, combined with the project breakdown structure, map it to different individual projects, construction processes, and progress, use a recurrent neural network, integrate historical project data, analyze the consumption rules of the owner-supplied materials in past projects, and establish an owner-supplied material demand prediction model. This model can automatically learn and adapt to the changes in different project scenarios, and adjust the prediction results in real time to accurately predict the material requirements at each construction stage of different individual projects;

[0043] Collect historical data of at least 30 similar distribution network business expansion projects in the past, and use data mining algorithms to analyze these data to find frequent item sets and association rules of the consumption of owner-supplied materials in different construction stages, such as foundation construction, tower erection, line erection, etc. Combining with the project breakdown structure WBS, finely associate the designed quantity of owner-supplied materials with specific individual projects, such as Substation A, Line B, etc. and their construction processes, such as substation foundation pouring, excavation process in tower erection, and progress. Using machine learning algorithms, with factors such as construction progress, project scale, geographical environment, etc. as input variables and the demand for owner-supplied materials as the output variable, establish a prediction model for the demand of owner-supplied materials, and continuously optimize the model parameters through cross-validation and error analysis. This prediction model based on big data analysis and project structure association can accurately predict the demand for owner-supplied materials of different individual projects in each construction stage, and make good preparations for material reserve and allocation plans in advance. Compared with the traditional empirical estimation method, it greatly improves the timeliness and accuracy of material supply, and avoids project delays caused by material shortages or cost waste caused by material backlogs.

[0044] S13: Compare the predicted demand for owner-supplied materials with the current inventory situation, calculate the shortage quantity, introduce Internet of Things technology, equip the materials with intelligent sensors to collect location, quantity, status, and environmental condition information and transmit it to the system, establish an inbound and outbound registration and usage record process, and achieve real-time tracking of owner-supplied materials;

[0045] Intelligent sensors can be selected such as RFID tags, Bluetooth beacons, environmental sensors, etc. Through the sensors, real-time collect information such as the location, quantity, status, and environmental conditions of the materials, such as temperature, humidity, light, etc., and transmit these data to the material management system. Using geographic information system GIS technology, visually display the distribution and flow of materials on the map, and achieve real-time tracking and monitoring of materials. When abnormal situations occur to the materials, such as loss, damage, and non-compliance of environmental conditions, the system automatically issues an alarm.

[0046] S14: Formulate a monthly sampling and quarterly comprehensive material inventory plan, conduct on-site inventory of owner-supplied materials and reconcile with the system inventory data. Based on accurate prediction and tracking data, use an online approval system to standardize the submission process to ensure accurate and reasonable material submission;

[0047] Using drones equipped with high-definition cameras and image recognition technology to quickly inventory and collect data on warehouse materials. At the same time, introduce robot-assisted inventory to improve the accuracy and efficiency of inventory. After inventory, generate a detailed report, compare and analyze it with the system data, automatically identify differences and make adjustments. Based on accurate prediction and tracking data, adopt an online approval system to standardize the submission process. The submission application contains detailed information, and the approval process determines the level according to the material type and amount. The system automatically associates relevant data to assist in approval. Use natural language processing technology to realize the functions of intelligent question answering and automatic document review during the approval process.

[0048] Regular inventory plans combined with detailed report analysis help to timely discover problems in material management, such as inventory backlogs, abnormal losses, etc., and take targeted measures for adjustment. The standardized submission process and intelligent approval system ensure the rationality and accuracy of material requirements, avoid over-purchasing or under-purchasing, improve the efficiency and effectiveness of material procurement, and at the same time strengthen the internal process management and internal control of the enterprise.

[0049] In an embodiment of the present invention, first, organize a professional technical team to deeply connect the enterprise's internal ERP system, cost structured data, and data center using tools such as data interfaces and middleware to ensure stable and efficient data transmission between systems; select a suitable blockchain platform, build a distributed material management ledger in the material management system, write intelligent contract code, define material management rules and processes, including logic such as inbound and outbound approvals and material distribution, and deploy it to the blockchain network so that related operations can be automatically executed and cannot be tampered with.

[0050] Collect detailed data of at least 30 past similar distribution network business expansion projects from channels such as the enterprise database and historical project documents, specifically including information such as the designed quantity of owner-supplied materials, the actual consumption of materials in each construction stage, construction progress, project scale, geographical environment, market dynamics, weather data, etc. After data preprocessing, build a framework for the owner-supplied material demand prediction model based on the recurrent neural network (RNN). Use the construction progress, project scale, geographical environment, market dynamics, and weather data as input variables, and the owner-supplied material demand as the output variable. Train the model with the preprocessed data and evaluate the trained model with the test data set, and calculate indicators such as prediction accuracy and error rate.

[0051] According to the material characteristics and management requirements, select appropriate intelligent sensors, install RFID tags for metal materials for positioning and quantity monitoring, equip environmental sensors for materials sensitive to the environment to monitor temperature and humidity, build a sensor data transmission network, and use Bluetooth or Wi-Fi technology to transmit the information such as the location, quantity, status, and environmental conditions of the materials collected by the sensors to the material management system in real time; develop a data access interface to enable the system to receive and process sensor data, and integrate it with GIS technology to visually display the distribution and flow of materials on a map.

[0052] Set rules for judging material anomalies in the material management system. When the material location has not changed for a long time, the quantity exceeds a reasonable range, or the environmental conditions exceed the threshold, the alarm mechanism is automatically triggered, and relevant management personnel are notified in time through text messages, system pop-ups, etc. for handling.

[0053] During the monthly inventory, staff use handheld terminal devices to read RFID tags or check the status of materials for sample inventory; during the quarterly inventory, use drones equipped with high-definition cameras to take panoramic photos of the warehouse materials, automatically identify the quantity and status of materials through image recognition technology, and at the same time arrange robots to assist manual workers for detailed inventory to ensure the accuracy of inventory data; compare the actual material data obtained from the inventory with the inventory data in the system to generate a detailed inventory report.

[0054] Build an online approval system on the material management system, design a submission application template, and require applicants to fill in detailed information such as material demand descriptions, usage plans, and budget estimates. Set different approval levels and approval nodes according to the material type and amount. During the approval process, the system automatically associates inventory data and the demand prediction model for owner-supplied materials, provides decision-making references for approvers, approvers perform approval operations through the system, the system uses natural language processing technology to automatically review application documents, and conducts intelligent question and answer for doubtful points.

[0055] It also includes the steps of assisting in the distribution and traceability of materials for individual projects:

[0056] S21: Based on the existing multi-level data association between owner-supplied materials and individual projects, identify and code the attribute information of materials and the project information of individual projects;

[0057] S22: According to the construction progress plan of individual projects and the demand prediction of owner-supplied materials in the structured cost data, formulate a detailed material distribution plan and distribution approval and recording process;

[0058] S23: Establish a two-way data traceability mechanism, develop a data traceability function in the system, and realize the forward traceability from material distribution records to individual projects and the overall project, as well as the reverse traceability from project engineering to material distribution details;

[0059] S24: For each material allocation and usage, record the actual usage amount and calculate the cost, which is accumulated into the accounting data of the individual project. Generate a material balance and transfer report based on the accounting data.

[0060] In an embodiment of the present invention, based on the actual requirements of enterprise material management, a coding rule including the core information of materials and projects is formulated. The material attributes are coded in the form of "material category code + production date + batch number + serial number", and the individual project information is coded as "project area code + project type code + project serial number + construction stage code" to ensure the uniqueness, systematicness and expandability of the coding. With the help of professional coding software, codes are generated for materials and individual projects in batches according to the established rules and verified regularly.

[0061] Construct a multi-level approval process, set approval authorities according to the value and scarcity of materials, ensure the standardization and transparency of the approval process, and record in detail each link of the formulation and approval of the material allocation plan, including the applicant, approver, approval time, approval opinions, etc. At the same time, the adjustment situation of the allocation plan is also recorded completely for easy traceability and responsibility definition.

[0062] Select a relational database to store the structured data of material allocation and usage, create data tables such as material allocation records, individual project information, and overall project information, and establish an association relationship through primary keys and foreign keys. Use a graph database to construct a complex relationship network among materials, individual projects, and projects, intuitively display their associations, and develop a data traceability function module. When tracing forward, the user inputs the material allocation record number, and the system displays the corresponding individual project and the overall project information to which the allocation belongs according to the association relationship between the relational database and the graph database. When tracing backward, starting from the project or individual project, all the details of the material allocations involved are displayed.

[0063] For quantifiable materials, install electronic scales and flow meters at the construction site to collect usage data in real time and automatically upload it to the material management system. For non-quantifiable materials, the construction personnel shall fill in the usage quantity and purpose information in a timely manner after use and upload on-site photos as a supplement. A cost calculation model is preset in the material management system. According to the material purchase unit price, transportation cost, loss rate information, and combined with the actual usage amount, the cost of each material usage is automatically calculated and accumulated into the accounting data of the individual project. Regularly update the cost-related data to ensure the accuracy of cost calculation.

[0064] Develop a report generation function in the system according to the standardized template. At the end of each month or quarter, the system automatically generates a material balance and inventory transfer report based on the accounting data, including the quantity, amount, storage location, usage efficiency, etc. of the material balance. By comparing and analyzing the data with that of similar projects, explore the space for cost control and material management optimization, and provide strong support for subsequent material procurement and management decisions.

[0065] Furthermore, the ERP system realizes the query of ERP material receipt and issue information by synchronizing the material receipt and issue data of the data middle platform, and realizes the query of ERP material inventory information by synchronizing the material receipt and issue data of the data middle platform; the ERP system obtains the designed quantity information of owner-supplied materials from the structured cost data, and ensures the consistency and accuracy of the data through the docking method of data extraction, transformation and loading. When performing data synchronization and integration, clean the extracted data to remove duplicate, incorrect or incomplete data records.

[0066] Furthermore, in step S12, the owner-supplied material demand prediction model is as follows:

[0067] According to historical project data, let the construction progress data be X1, the project scale data be X2, the geographical environment data be X3, the market dynamics data be X4, the weather data be X5, the past consumption rate of owner-supplied materials be X6, the predicted demand for owner-supplied materials be Y, the activation function of the hidden layer of the recurrent neural network be σ, and the weight matrices be W ih 、W hh 、W ho , the bias term is b h 、b o , then the hidden layer state h t is,

[0068] h t =σ(W ih ·[X 1t ,X 2t ,X 3t ,X 4t ,X 5t ,X 6t +W hh ·h t-1 +b h ),

[0069] The output layer is,

[0070]

[0071] Among them, t represents time synchronization, corresponding to different construction stages.

[0072] In the demand forecasting model for owner-supplied materials, the output layer receives the information output by the hidden layer, calculates based on the set weight matrix and bias term, and finally outputs the predicted demand for owner-supplied materials. The weight matrix and bias term are learned and optimized through training data, enabling the model to accurately fit the relationship between the demand for owner-supplied materials and various influencing factors.

[0073] Furthermore, the regular material inventory plan is carried out in a combination of monthly and quarterly. The monthly inventory uses the sampling inventory method, with key materials and high-value materials inspected in full and general materials inspected by sampling; the quarterly inventory conducts a comprehensive inventory, generating a detailed inventory report after the inventory, including the actual quantity of materials, loss situation, analysis of inventory turnover rate indicators, and comparing and analyzing with the system data to find the reasons for the differences and make timely adjustments.

[0074] Furthermore, when standardizing the submission process, an online approval system is adopted. The submission application includes detailed material demand descriptions, usage plans, and budget estimate information; multiple approval nodes are set in the approval process, and the approval levels are determined according to the material type and amount. During the approval process, the system automatically associates inventory data and the demand forecasting model for owner-supplied materials, providing decision-making references for the approval personnel to ensure the accuracy and rationality of the submission.

[0075] Furthermore, for the coding of material attribute information, in addition to the basic name, specification, and model, it also includes the production date and batch number information of the materials, which are embedded in the overall coding using a specific time coding format.

[0076] Furthermore, the data traceability function module adopts a storage architecture that combines a relational database and a graph database. The relational database is used to store the structured data of material allocation and usage, and the graph database is used to construct the complex relationship network among materials, individual projects, and projects. Through a visual graph display method, it is convenient for users to intuitively conduct forward and reverse traceability queries, improving the convenience and accuracy of data traceability;

[0077] The data traceability function also has an abnormal data alarm mechanism. When abnormal material flows are found during the traceability process, such as materials appearing in unauthorized individual projects or the actual usage quantity seriously not matching the allocation plan, the system automatically triggers alarm information to notify relevant management personnel to conduct investigations and handling in a timely manner, ensuring the standardization and security of material management.

[0078] Furthermore, when recording the actual usage quantity of materials, for quantifiable materials, the usage data is automatically collected by devices such as electronic scales and length measuring instruments and uploaded to the system; for non-quantifiable materials, a combination of manual registration and on-site photography is used to record the usage situation, ensuring the accuracy and integrity of the usage quantity record.

[0079] Furthermore, the generated material balance and inventory transfer reports adopt a standardized template format, including material balance quantity, amount, storage location and usage efficiency information, and provide comparative analysis data with similar projects, providing data support and reference basis for subsequent material procurement and management decisions.

[0080] The above-mentioned method for accurately tracking and managing the material usage data of distribution network expansion projects can achieve the following beneficial effects:

[0081] Deeply connect with the enterprise's internal ERP system, cost structured data and data middle platform to establish a comprehensive material management system, and build a distributed material management ledger based on blockchain technology within the system. Managers can query ERP material inbound and outbound and inventory information in real time in a unified system without having to switch between multiple systems, which greatly improves work efficiency; based on past engineering data mining and analysis and project decomposition structure associations, a recurrent neural network is used in combination with historical engineering data, market dynamics, weather data, etc. to establish a forecast model for supply-side material demand. This model can accurately predict the material requirements of different single projects at each construction stage, make material reserves and allocation plans in advance, effectively avoid project delays due to material shortages or cost waste due to material backlogs, and achieve optimal resource allocation; encode material and project information, enhance data association recognition, formulate distribution plans and approval and record processes based on the single project construction schedule and material demand forecast, so that material distribution is scientific and reasonable, and responsibilities are clear. The two-way data traceability mechanism adopts a hybrid storage architecture and visual display, which improves the transparency and controllability of management, facilitates the timely discovery and resolution of problems, calculates the usage and cost of materials and generates reports to assist in decision-making, and comprehensively improves the efficiency, accuracy and scientificity of single project material management to ensure efficient use of materials; the introduction of Internet of Things technology equips materials with smart sensors to collect real-time information such as material location, quantity, status, and environmental conditions, and uses geographic information system GIS technology to intuitively display the distribution and flow of materials on the map, realizing real-time tracking and monitoring of materials. When abnormal conditions occur in materials, the system automatically issues an alarm. At the same time, the data traceability function has The abnormal data alarm mechanism notifies relevant management personnel to deal with abnormal material flows in a timely manner, ensuring the standardization and safety of material management; regularly conducts material inventory, uses drones and robots to assist in inventory to improve accuracy and efficiency, generates detailed reports after inventory and compares and analyzes them with system data, standardizes the submission process, adopts an online approval system and uses natural language processing technology to assist in approval, records the actual usage of materials and generates standardized material balance and inventory transfer reports, provides comparative analysis data with similar projects, provides strong data support and reference basis for subsequent material procurement and management decisions, and promotes continuous improvement and optimization of enterprise material management.

[0082] The foregoing has shown and described the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments, and what is described in the above embodiments and the specification is only the principle of the present invention. Without departing from the spirit and scope of the present invention, various changes and improvements will occur to the present invention, and all these changes and improvements fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A precise tracking and management method for material usage data in distribution network business expansion projects, characterized in that, The following steps are involved: S11: Deeply connect the company's internal ERP system, cost structured data and data center, build a material management system, and use blockchain technology to build a distributed material management ledger to achieve real-time query of material information; S12: Based on the design quantity data of the supplied materials, combined with the project breakdown structure, it is mapped to different individual projects and construction processes and schedules. Using a recurrent neural network and integrating historical project data, the consumption patterns of the supplied materials in past projects are analyzed to establish a supply material demand forecasting model. S13: Compare the predicted demand for Supplied A's materials with the current inventory situation, calculate the shortage, introduce IoT technology, equip materials with smart sensors to collect location, quantity, status, and environmental condition information and transmit it to the system. Establish a process for registering inbound and outbound inventory and recording usage to achieve real-time tracking of Supplied A's materials. S14: Develop monthly sampling and quarterly comprehensive material inventory plans, conduct on-site inventory of materials supplied by Party A and verify them with the system inventory data. Based on accurate forecasting and tracking data, use the online approval system to standardize the submission process to ensure that material submissions are accurate and reasonable.

2. The method for accurately tracking and managing the material usage data of the distribution network business expansion project according to claim 1, characterized in that It also includes auxiliary distribution and traceability steps for single project materials: S21: Based on the existing multi-level data association between the materials supplied by Party A and the individual projects, identification coding is performed for the attribute information of the materials and the project information of the individual projects; S22: Based on the construction schedule of the individual project and the forecast of the supply material demand in the cost structured data, formulate a detailed material allocation plan and allocation approval and record process; S23: Establish a two-way data traceability mechanism and develop data traceability functions in the system to achieve forward tracing of material distribution records to individual projects and the entire project, and reverse tracing from project to material distribution details; S24: For each material distribution and use, the actual usage is recorded and the cost is calculated and accumulated into the accounting data of the individual project. Based on the accounting data, a material balance and inventory transfer report is generated; In step S11, the ERP system realizes ERP material inbound and outbound information query by synchronizing the material inbound and outbound data of the data center, and realizes ERP material inventory information query by synchronizing the material inbound and outbound data of the data center; The ERP system obtains the design quantity information of materials supplied by the client from the structured cost data, and ensures the consistency and accuracy of the data through the docking method of data extraction, conversion and loading.

3. The method for accurately tracking and managing the material usage data of the distribution network business expansion project according to claim 1, wherein, In step S12, the material demand forecasting model for Party A is as follows: According to historical engineering data, let the construction progress data be X1, the project scale data be X2, the geographical environment data be X3, the market dynamics data be X4, the weather data be X5, the past consumption rate of owner-supplied materials be X6, the predicted demand for owner-supplied materials be Y, the activation function of the hidden layer of the recurrent neural network be σ, and the weight matrices be W ih 、W hh 、W ho , and the bias terms be b h 、b o , then the hidden layer state h t is h t = σ(W ih · [X 1t , X 2t , X 3t , X 4t , X 5t , X 6t + W hh · h t-1 + b h ) The output layer is, Among them, t represents time synchronization, corresponding to different construction stages.

4. The method for accurately tracking and managing the material usage data of the distribution network business expansion project according to claim 1, wherein: Regular material inventory plans are conducted on a monthly and quarterly basis. Monthly inventory uses a sampling method to conduct full inspections of key and high-value materials, and random inspections of general materials. Quarterly inventory is a comprehensive inventory, and a detailed inventory report is generated after the inventory, including the actual quantity of materials, loss situation, and inventory turnover rate indicator analysis. It is also compared with system data to identify the causes of differences and make timely adjustments.

5. The accurate tracking and management method for the material usage data of the distribution network business expansion project according to claim 1, wherein: When standardizing the submission process, an online approval system is adopted. The submission application includes detailed material requirement descriptions, usage plans, and budget estimate information. Multiple approval nodes are set in the approval process, and the approval levels are determined according to the material type and amount. During the approval process, the system automatically correlates inventory data and the prediction model of materials provided by the employer, providing decision-making references for the approval personnel to ensure the accuracy and rationality of the submission.

6. The method for accurately tracking and managing the material usage data of the distribution network business expansion project according to claim 1, wherein: For the coding of material attribute information, in addition to the basic name, specification, and model, it also includes the production date and batch number information of the materials, which are embedded in the overall coding using a specific time coding format.

7. The method for accurately tracking and managing the material usage data of the distribution network business expansion project according to claim 1, wherein: The data traceability function module adopts a storage architecture that combines a relational database and a graph database. The relational database is used to store the structured data of material allocation and usage, while the graph database is used to construct the complex relationship network among materials, individual projects, and projects. Through a visual graph display method, it is convenient for users to directly conduct forward and reverse traceability queries, improving the convenience and accuracy of data traceability.

8. The accurate tracking and management method for the material usage data of the distribution network project expansion according to claim 7, characterized in that: The data traceability function also has an abnormal data alarm mechanism. When abnormal material flows are found during the traceability process, such as materials appearing in unauthorized individual projects or the actual usage amount seriously deviating from the allocation plan, the system automatically triggers an alarm message to notify relevant management personnel to conduct investigations and handle them in a timely manner, ensuring the standardization and security of material management.

9. The method for accurately tracking and managing the material usage data of the distribution network project expansion according to claim 1, wherein: When recording the actual usage amount of materials, for quantifiable materials, the usage data is automatically collected by devices such as electronic scales and length measuring instruments and uploaded to the system; for non-quantifiable materials, a combination of manual registration and on-site photography is used to record the usage situation to ensure the accuracy and integrity of the usage amount record.

10. The method for accurately tracking and managing the material usage data of the distribution network business expansion project according to claim 1, wherein: The generated material balance and inventory transfer report adopts a standardized template format, including the material balance quantity, amount, storage location, and usage efficiency information, and provides comparative analysis data with similar projects, providing data support and reference basis for subsequent material procurement and management decisions.

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