436 results about "Materials management" patented technology

The invention relates to the technical field of material management, and discloses a dynamic rule generation and self-adaptive auditing system and method for material management, and the system comprises a rule intelligent extraction module, a rule management knowledge base, an enhanced auditing engine, a man-machine cooperation calibration module and a self-adaptive execution module. The method comprises the steps of automatic rule extraction, rule storage and management, enhanced auditing and reasoning, man-machine collaborative calibration, knowledge base real-time optimization and adaptive routing execution. According to the method, the rule is automatically extracted from the unstructured document, the problem that a traditional system rule depends on manpower and is lagged in updating is solved, dynamic optimization of the rule and confidence is achieved by introducing a man-machine collaborative feedback closed loop, the accuracy and transparency of an audit decision are improved by enhancing reasoning and explainable decision technologies, and the audit efficiency is improved. And the optimal balance between auditing efficiency and risk control is realized through self-adaptive routing execution based on credibility.

The invention belongs to the technical field of medical material management, and particularly relates to a medical material intelligent supply chain management scheme and system based on multi-modal AI. According to the invention, through multi-modal data fusion, full-life-cycle and full-link tracking of materials is realized, information islands are eliminated, management transparency is improved, unexpected consumption and physical damage risks are identified in an early stage, a large amount of overstock or clinical supply interruption is avoided, operation cost is reduced, and based on a dynamic loss threshold, replenishment and cross-warehouse allocation can be realized just in need. The inventory turnover rate and the supply guarantee rate are considered, environment monitoring and validity period information are processed, it is ensured that temperature and humidity sensitive materials are stored under the optimal condition, losses caused by expiration or environment abnormity are reduced, the waste rate and the excessive stockpiling risk are comprehensively reduced, meanwhile, timely availability of key materials is clinically guaranteed, and the service life of the materials is prolonged. And the economic benefit and safety of the medical material supply chain are improved.

The invention relates to the technical field of sectional material excess material management, and discloses a sectional material excess material management method and device and electronic equipment, and the method comprises the following steps: S1, setting a minimum available length threshold value of excess materials, which is used for judging whether the minimum available length threshold value is included in an excess material management process or not; s2, the excess materials generated by cutting are recognized, information including the color, the length, the surface state and the profile structure attribute is obtained, and a unique identifier is generated for each section of excess materials; s3, storing the excess material information meeting the conditions into an excess material management database, and associating storage position information of the excess material management database; and S4, after a new order request is received, screening matched excess materials in the excess material database according to an order demand to form a candidate set. According to the method, a structural management technical scheme based on geometric contour reconstruction and matching of the excess materials is adopted, and the identifiability, traceability and reutilization of the excess materials in the machining process are achieved. The technical effects of intelligent classification and efficient scheduling of the processing residual materials are achieved.

The invention discloses a highway engineering construction remote material abnormity management method, which relates to the technical field of material management, and comprises the following steps: collecting material information parameters for analysis, obtaining an analysis result and carrying out abnormity identification, outputting an abnormity identification result, triggering a response mechanism for the abnormity identification result, and carrying out automatic early warning. By constructing a full-process digital highway engineering construction remote material anomaly management system, the problems of multiple types of traditional management are solved, multi-source data are integrated to automatically correct errors and generate accurate data, and the material anomaly management system is established by means of space-time dimension cross validation and construction process compliance analysis. A preset abnormal feature combination library is combined to capture a composite risk, a hierarchical response and a mapping table are adopted to realize differential early warning, responsibility is clarified through receiving verification and block chain evidence storage, and a closed loop is formed by combining treatment with template optimization and dual verification, so that the risk is reduced, and the management intelligence and refinement level is improved.

A metering equipment warehouse division demand prediction and scheduling method based on spatio-temporal feature fusion comprises the steps of firstly obtaining and collecting warehouse division data, then establishing a spatio-temporal feature fusion model based on the warehouse division data, and then establishing a spatio-temporal diagram convolution prediction network, the spatio-temporal diagram convolution comprises a diagram convolution layer and a time convolution layer, through extraction and fusion of the two layered features, dynamic weight fusion is obtained, joint modeling of space-time dynamics is realized, and finally, prediction and allocation decision are implemented based on the dynamic weight fusion. According to the method, the multi-modal graph structure fusing the space-time association and the replacement rule is constructed, and a space-time joint modeling architecture and a dynamic feedback mechanism are designed, so that high-precision demand prediction and global inventory optimization are realized; the method systematically solves the core problems of insufficient spatial correlation modeling, dynamic event response lagging, low efficiency in multi-source data utilization and the like of a traditional method, and provides an efficient solution for electric power material management.

The invention provides an automatic material identification and matching method and system for a three-dimensional model and a medium, and relates to the technical field of material management, and the method comprises the steps: constructing a standardized material database, and extracting and standardizing material attribute information; analyzing first material description information in the three-dimensional software model by utilizing an SQL (Structured Query Language), and matching the first material description information with the material attribute information to obtain a first material matching result; extracting second material description information in the project material document by using VBA programming, and matching the second material description information with the material attribute information to obtain a second material matching result; and data integration is carried out through PowerBI, and a project material state visual billboard is constructed. The technical problems that in the prior art, a unified standardized material database is lacked, material description formats in different sources are inconsistent, expression is not standard, a construction material list cannot be accurately generated, and informatization and intellectualization of project material management are limited are solved.

The invention discloses a purchase demand prediction method combined with PMC material management and control, and belongs to the technical field of material management and control data processing, and the method comprises the steps: obtaining a material consumption sequence and corresponding timestamp data, and employing a time sequence decomposition method to separate trend components and seasonal components, and obtaining a consumption rule feature sequence; if the fluctuation amplitude of the consumption rule feature sequence exceeds a preset threshold value, determining the consumption rule feature sequence as a basic demand predicted value sequence; obtaining a market price index sequence, and calculating a correlation coefficient between the basic demand predicted value sequence and the market price index sequence; if the absolute value exceeds a set threshold value, updating a basic demand predicted value sequence through a time sequence model; generating a purchase plan sequence according to the basic demand predicted value sequence and the inventory average value; and generating a final output report. The invention discloses a problem that a current material management and control mode cannot capture key changes in time and is difficult to balance contradictions between inventory and production.

The invention belongs to the technical field of data processing, and particularly discloses a warehouse material management method and system based on an intelligent inspection robot, and the method comprises the steps: collecting environment monitoring data through a data collection device, enabling the environment monitoring data to comprise temperature and humidity information, smoke concentration and an image sequence, and obtaining an original multi-mode signal set; a deep learning model is adopted to extract feature vectors according to the original multi-modal signal set, and multi-dimensional feature representation is obtained and used for subsequent fusion processing; performing priority ranking on anomaly detection from the multi-dimensional feature representation, and determining a high-risk signal subset to identify potential hazards; if the high-risk signal subset meets a triggering condition, image sequence analysis is carried out; the invention aims to solve the problems of complexity of multi-source data and inaccurate real-time identification of abnormal events in environmental monitoring.

The invention discloses a building material planning management system based on a BIM technology, and relates to the technical field of BIM, and the system comprises the steps: a data collection module collects the full-process multi-source data of materials from purchasing to using; the unified coding module distributes a unique electronic identification code containing a category, a supplier and a full-process traceability index to each building material; the data storage and processing module cleans and converts the data and forms a standardized full-life-cycle database; the BIM integration module establishes one-to-one correspondence between material entities and BIM model components through electronic identification codes, and full-process data tracing calling and circulation state visualization are achieved; the interaction module provides a multi-terminal interface to support cooperation of multiple participants. According to the invention, the problems of information isolated island and traceability fault of traditional material management are solved, the management and control efficiency and collaboration are improved, and cost reduction and benefit increase of the construction project are facilitated.

The invention discloses an intelligent material cabinet and a safe and accurate material distribution method. The intelligent material cabinet further comprises an anti-theft unit, a material recognition unit and a safety interlocking mechanism on the basis of a conventional cabinet body. The anti-theft unit seals a blue opening by arranging a long turning plate and a short turning plate at the blue opening of a lifting blue and is linked with a material taking turning plate of a material taking opening; the material identification unit is provided with an intelligent camera, a wide-angle camera and a pressure sensor for detecting material information; the safety interlocking mechanism is provided with a limiting switch, an electronic bolt door lock and a material taking indicator lamp, and limiting of the lifting basket, locking of a material taking opening material taking turning plate and material taking prompting are achieved. According to the method, safe and accurate material distribution is achieved through material management, material identification and safety linkage. According to the material cabinet and the method, the defects of traditional material warehouse management are overcome, the accuracy of material distribution and the anomaly detection processing capacity are improved, the vulnerability of theft is eradicated, the safety of material extraction operation is ensured, and then the adaptability, automation and intelligence of material warehouse management are improved.

The invention discloses an intelligent distribution system for welding material management and an operation method thereof, and relates to the technical field of welding material pretreatment equipment, and the intelligent distribution system structurally comprises a drying box, a feeding device and a material taking distribution device. A plurality of layers of sliding frames are arranged in the drying box, and material frames are arranged on the sliding frames and can slide out from one side. The feeding device comprises a transferring mechanism and a feeding table, and the transferring mechanism is used for transferring the material frame between the drying box and the feeding table. The material taking and distributing device comprises a mechanical arm and a grabbing mechanism and is used for grabbing and transferring the welding materials in the drying box. The operation method comprises the steps that 1, empty material frames in the drying box are taken out through the transferring mechanism and placed on the workpiece feeding table; 2, a welding material is supplemented into the material frame; 3, taking down the filled material frame through a transferring mechanism, and feeding the material frame into a drying box for drying; and 4, the welding materials are grabbed from the drying box through a material taking and distributing device and put in. By applying the scheme, the technical problems that in the prior art, the working intensity of workers is large, the environment is poor, and whole-process automation is difficult to achieve can be solved.

The invention discloses a global material intelligent management and control analysis platform based on multi-professional link data, relates to the technical field of material management, and solves the technical problems of insufficient consumption abnormality judgment accuracy and delayed inventory early warning and supply decision. According to the method, a weighted initial threshold model of historical data and business quota is innovatively constructed, a differential statistical method is adopted for periodic and non-periodic materials, meanwhile, a real-time influence factor is introduced, and a threshold is dynamically corrected through a weighting algorithm, so that the threshold can accurately adapt to business scene change, and the service scene change is accurately matched with the business scene change. The method effectively reduces the abnormal misjudgment rate and the missed judgment rate, achieves the precise monitoring of the consumption state, achieves the precise calculation of the basic remaining time, the scene-based remaining time and the safety buffer time through the scene-based consumption speed model and stock effective value measurement and calculation, achieves the scientific evaluation of the stock sufficiency through the combination with a preset threshold value, generates a purchase signal in advance, and improves the purchase efficiency. And the risks of stock overstock and material shortage are avoided.

The invention relates to a CNC machining material unified management system based on intelligent early warning and multi-dimensional fusion, and belongs to the technical field of intelligent manufacturing and industrial informatization. The invention aims to solve the technical challenges in the existing CNC processing material management. The system adopts a three-layer architecture, comprises a data layer, a business logic layer and an application layer, and realizes the functions of unified modeling, classified management, batch tracking, inventory early warning and the like of material data. Through the intelligent tool breakage prediction module, the two-stage position management module, the intelligent inventory prediction module and the like, the system can automatically identify tool breakage abnormity, optimize the storage position, predict the inventory depletion date and generate intelligent replenishment suggestions. The system improves the management efficiency, reduces the inventory cost and the stockout risk, is suitable for the fields of intelligent manufacturing and industrial informatization, and meets the requirements of digital transformation of enterprises.

The invention provides a material management method and system suitable for an offline multi-terminal environment, and relates to the technical field of material management, and the method comprises the steps: obtaining network data; obtaining material data of a plurality of terminals in an offline state; performing statistical analysis on the material data to generate a material operation statistical index; carrying out visual analysis on the material operation statistical indexes to obtain a material consumption visual chart; according to the material consumption visualization chart, predicting a material demand index through a material prediction model; determining an optimal material distribution scheme through a material distribution algorithm according to the predicted material demand indexes in combination with inventory constraints and demand constraints; and based on the optimal material distribution scheme, material distribution is carried out through an automatic material distribution process so as to realize material management. According to the invention, the efficiency and accuracy of material management can be improved, so that managers can make scientific and reasonable decisions even in a network-free environment.

The invention discloses an overstocked material automatic inventory method based on multi-element collaborative cause tracing, relates to the technical field of material management, and solves the problems that a standardized multi-factor quantitative model is not established for evaluation of market demands during external docking, the matching logic of single-category and multi-category materials is not clear, and the market demands are not evaluated. According to the method, multi-dimensional identification is carried out by combining material attributes and dynamic states, misjudgment of a single warehouse age standard is avoided, the accuracy of accumulated material identification is improved, and the accuracy of the accumulated material identification is improved by quantitatively comparing the accumulated remaining amount with a preset value and combining accurate parameter matching of required materials and defining an internal reuse boundary, so that the accuracy of the accumulated material identification is improved. The internal consumption rate of reusable materials is improved, and a weighted quantization model of purchase quantity matching degree + date of delivery collaboration degree + cooperation stability is established for single-category materials; for multiple categories of materials, the combination matching logic of the same subject demand combination score is adopted, the external demand matching precision is improved, and the disposal period is shortened.

The invention discloses a power distribution network construction material demand analysis and prediction method, which comprises the following analysis and prediction steps: S1, collecting historical material data of a power distribution network construction project, the historical material data comprising project attribute data and material usage data; s2, preprocessing the material consumption data, including data cleaning, standardization and normalization processing; s3, carrying out dimension reduction processing on the material data based on a principal component analysis method; s4, performing clustering analysis on the material project attributes based on a clustering analysis algorithm; s5, parameters of the extreme learning machine are optimized based on a particle swarm algorithm, the optimized extreme learning machine is adopted to construct a power distribution network construction material demand prediction model, and the number and amount of power distribution network construction material demands are predicted; the system can effectively improve the material management level of a power enterprise, and improves the efficiency and quality of a material demand plan.

The invention relates to an electric power storage material intelligent detection and management system based on the Internet of Things, and the system comprises a warehouse material management module which is used for storing, maintaining and carrying out the classification management of basic information of various electric power materials in a warehouse, and the basic information comprises material numbers, types, storage positions, number, warehousing time and material states; meanwhile, synchronous data updating with an upper management system can be carried out; according to the electric power storage material intelligent detection and management system based on the Internet of Things, through cooperative work of the warehouse material management module and the RFID positioning module, real-time storage, maintenance and position tracking of material information are realized, and an operator can acquire serial numbers, categories, quantity, storage positions and states of various electric power materials in a warehouse at any time; errors and omissions easily occurring in traditional manual checking are avoided, and the accuracy of warehouse management is improved.

The invention discloses a consumable management optimization method and system, and belongs to the technical field of material management. Comprising the following steps: S1, in a total warehouse, carrying out statistics on all consumables to obtain the name, the category, the model, the existing quantity and the purchase price of each consumable; s2, in the sub-warehouses, performing statistics on each department to obtain a practical affair type, a name, a category, a model, an existing quantity, a consumption quantity and a use score; s3, integrating and processing the data of S1 and S2 to obtain a stock index, a consumption index, a price index and an evaluation index; and S4, performing calculation according to the indexes in the S3 to obtain a management strategy and a current purchase list, and adjusting the number of consumables in the total warehouse and the sub-warehouses according to the management strategy.

The invention relates to the technical field of production intelligent management and control of energy enterprises such as thermal power enterprises and nuclear power enterprises, and discloses a power plant material full-life-cycle intelligent management method and related equipment.The method comprises the steps that a power plant material full-life-cycle big data center is established, and the power plant material full-life-cycle big data center integrates multi-source data through a distributed architecture; unified data standard and interface specification are carried out on the distributed architecture integrated multi-source data; respectively carrying out life management, material management and equipment maintenance management on the unified data standard and interface specification to obtain dynamic multi-service data; dynamic multi-service data are butted and fused for data association analysis, material full-process penetration management, material full-life-cycle tracing, intelligent purchase decision support, inventory dynamic optimization management, intelligent decision algorithm optimization and full-process visual monitoring. According to the invention, power plant material management is converted from passive response to active prediction and from segmented control to full-process collaboration, and the management efficiency is significantly improved.

The invention provides a cloud chain collaborative material intelligent management system for small and medium-sized enterprises, and relates to the technical field of intelligent management, material data of different enterprises are collected and stored in an isolated manner, corresponding labels are given to different materials which are scanned to be warehoused, and the collected material data and the given label data are encrypted and transmitted to a cloud chain collaborative layer; the cloud chain collaboration layer carries out structured storage on the received material data and label data, and integrates private cloud, alliance chain and differential privacy gateway technologies to realize data non-sharing collaboration; the intelligent application layer constructs a demand prediction model to predict material demands, generates a purchase list according to a demand prediction result in combination with an actual inventory condition, carries out purchase based on the purchase list, and carries out the lightweight collaborative application of edge calculation, block chains and federated learning technologies in the material management of small and medium-sized enterprises. The problems of data islands, low collaboration efficiency, high deployment cost and the like in material management are solved.

The invention discloses a low-power-consumption laser radar lorry volume and material management system and method in the technical field of volume measurement. The system comprises a central control part, a lorry counting part, a plurality of lorry volume detection parts, a plurality of cleaning parts and a plurality of driving parts. The truck volume detection part is used for scanning passing trucks based on a three-dimensional measurement technology to obtain three-dimensional point cloud data of containers and goods of the trucks; the truck counting part is used for counting the trucks subjected to the volume scanning based on a three-dimensional measurement technology; the cleaning part is used for cleaning dust on the surface of the scanning end of the truck volume detection part and synchronously cleaning dust in a volume scanning area; the driving part is used for providing driving force for the cleaning part based on truck gravity. Synchronous dust removal of the scanning end and the scanning area is achieved by driving the cleaning part through the gravity of the truck, and meanwhile accurate metering, automatic counting and data traceability of the volume of the truck are achieved by processing scanning data and associating the scanning data with counting results.

The invention provides a building material scheduling management method, and belongs to the technical field of building material scheduling, and the method comprises the following steps: collecting material basis and stock information, constructing an evaluation model, and determining a weight by taking the influence on the project progress and the market scarcity degree as indexes; constructing an engineering three-dimensional model, disassembling the total construction period as an operation section, analyzing the association strength of materials and key nodes, and determining the morning and later periods of arrival; taking the stock information and the arrival time as input, constructing a transportation and time efficiency dual-objective function, and optimizing to obtain transportation details; in combination with the storage cost and the loss rate, constructing a storage income and consumable cost dual-objective function, and optimizing to obtain storage details; and a scheduling database is constructed, information is integrated, and a material demand superposition time point is identified. The systematic scheduling management method can realize accurate evaluation of material information, deep collaboration with the project progress, consideration of transportation and storage optimization, and integration of whole project material demand information, so as to improve scientificity and high efficiency of construction project material management.

The invention discloses an electronic material intelligent management method and system, relates to the field of material management, and is based on a 12-bit production coding specification of an SPYY.XBBBVVVV format. The specification defines a device category (X), a capability value (BBB) and a main variable (VVVV) by means of a main code segment (XBBBVVVV); a device form (S), a specific package (P) and key characteristics (YY) such as precision and grade are defined through an auxiliary code segment (SPYY). And based on the rule, performing structured analysis on the target material code, and extracting candidate materials from the material library by taking the analyzed device type and packaging type as physical constraints. And then, parameterizing the candidate materials, and carrying out multi-dimensional compatibility scoring and weighted calculation on the candidate materials and the target materials to realize accurate quantitative evaluation. Finally, based on score sorting and recommendation of an optimal result, the problems of model selection and substitution caused by non-uniform coding are effectively solved, and the response efficiency and accuracy of the supply chain are remarkably improved.

The invention belongs to the technical field of material management, and discloses a photoelectric product intelligent material system charging tray which comprises a charging tray base, a secondary limiting module, a charging tray two-dimensional code, a base and a supporting rod, the charging tray base is arranged on the base, and the base provides a mounting platform for the overall structure of the charging tray; the supporting rod is connected with the tray base and the base; a through hole and a positioning hole are formed in the charging tray base, the through hole is used for inserting a standard guide piece or a power supply assembly, and the positioning hole is used for containing a to-be-assembled material and achieving preliminary positioning; the secondary limiting module comprises at least one first limiting point, at least one second limiting point and at least one limiting column, and the secondary limiting module is arranged around the positioning hole and used for conducting secondary limiting on the direction and the position of the assembly part. The charging tray two-dimensional code is arranged on the surface of the charging tray base, has a unique identification attribute, is used for carrying out information binding with the material code, and supports block chain tamper-proof tracing and ERP platform information interaction. According to the invention, the misoperation rate is low, and the production efficiency and the quality stability are greatly improved.

The invention relates to the technical field of intelligent material management, in particular to an intelligent material management system and method. Comprising an intelligent sensing and dynamic acquisition unit; a multi-source data co-processing unit; an intelligent prediction and scheduling decision unit; a block chain full life cycle traceability unit; and an intelligent abnormity early warning response unit. According to the invention, a time sequence feature extraction module obtains a material warehouse-in and warehouse-out period, an equipment capacity trend, a state mutation feature and a conversion standardization vector through a dynamic window and classification extraction; the self-adaptive prediction model module reads physical attributes of materials, calculates three types of weights into vectors, inputs feature vectors into LSTM to obtain original prediction values, and obtains a result fitting a physical rule through a fusion layer; the physical constraint scheduling module generates a scheme according to storage location load bearing and volume; and the feedback iterative optimization module calculates deviation, and parameters are adjusted by gradient descent. The problems that traditional prediction is poor in adaptation and scheduling lacks physical constraints are solved, and prediction accuracy and scheduling feasibility are improved.

The utility model discloses a metal accessory machining production line. The metal accessory machining production line comprises a stamping mechanism. The input end of the sharpening mechanism is connected with the output end of the stamping mechanism; the input end of the riveting mechanism is connected with the output end of the sharpening mechanism; the input end of the three-dimensional warehouse is connected with the output end of the riveting mechanism; and the input end of the stock mechanism is connected with the output end of the three-dimensional warehouse. According to the production line, the continuous and automatic machining process of metal accessories from raw materials to finished products is achieved by integrating the stamping mechanism, the sharpening mechanism and the riveting mechanism, the three-dimensional warehouse and the stocking mechanism are arranged, the three-dimensional warehouse is used for storing finished product materials, the material management efficiency of the production line is improved, the continuity and stability of the production process are ensured, and the production efficiency is improved. And meanwhile, the materials can be automatically arranged and stacked according to the preset arrangement through the stocking mechanism, delivery preparation before loading is completed, the production efficiency is greatly improved, manual intervention is reduced, and the error rate is reduced.

The invention provides a medical material multistage warehouse intelligent management system and method based on demand prediction, and the system comprises an intelligent recognition module which is used for achieving the quick warehouse-in and warehouse-out operation of medical materials; the stockout pre-taking module is used for receiving and recording the request application when the inventory is insufficient; the demand prediction module is used for adopting a prediction model of multi-granularity time decomposition; the dynamic priority adjustment module is used for constructing an evaluation system; the multi-target optimization distribution module is used for carrying out material distribution; the multi-stage warehouse collaborative scheduling module is used for monitoring the inventory difference of the multi-stage warehouses in real time; the real-time monitoring and early warning module is used for monitoring the storehouse in real time; and the intelligent analysis and optimization module is used for generating a visual report. The intelligent level and the operation efficiency of medical material management are comprehensively improved. According to the system, the group fairness and the resource utilization efficiency can be considered while the quick response of the emergency medical demand is ensured, and the stockout risk and the operation cost are remarkably reduced.

The invention relates to the technical field of information management, in particular to a material digital management system and method based on a cloud platform. The method comprises the following steps: acquiring material data; distributing a material storage space by using the material data; receiving an operation message of the storage space, and pushing the operation message to an inventory database; creating a circulation record table and an inventory state table; using the operation message in the inventory database to update a circulation record table, and recording circulation data; automatically updating an inventory state table according to the circulation data so as to determine the material inventory capacity; when the material inventory capacity is lower than or equal to a preset safety inventory threshold value, management early warning information is generated; and when the material inventory capacity is higher than a preset safety inventory threshold value, updating the management safety field of the inventory state table. The material inventory is monitored in real time based on the information management technology, the replenishment information is intelligently generated, inventory dynamic management is achieved, and the material management efficiency is improved.

1. Name of the design product: Graphical user interface of material management system for electronic device. 2. Use of the design product: Electronic device. 3. Design points of the design product: The graphical user interface in the screen. 4. Picture or photo best indicating the design points: Front view. 5. Use of the graphical user interface: To support the marketing staff to view, edit and forward multi-type materials, and record and count the material visitors. 6. Other circumstances needing explanation: The front view is a long picture which can slide along the longitudinal direction.

The present invention discloses a material coding method based on material attributes, which includes the following steps in sequence: S1: according to the material category and material attributes, a rule table is set to establish a mapping relationship between the material category and the rule table, wherein the rule table includes the following items: classification code name, classification code symbol, attribute segment name and attribute segment serial number; S2: the rule table is selected to establish a coding library: the material category corresponding to the material is determined, and the rule table corresponding to the material category is selected; the material code and the attribute segment name in the rule table are used as items in the coding library, and the information content corresponding to each item is input or imported to obtain several groups, and each group is given unique pseudo-material coding information; S3: whether there is a duplicate code is determined; S4: material coding information is generated; S5: saving. The present invention is applicable to coding various different materials, has a wide range of applications, and is highly practical; it can avoid the problem of duplicate codes and improve the efficiency of material management.