673 results about "Digital transformation" patented technology

The invention belongs to the technical field of air traffic control and conduction, and particularly relates to an intelligent question answering system method for air traffic control and conduction business knowledge. According to the method and the system, the refined and context-aware information retrieval capability of the air traffic control communication service knowledge and the expert-level air traffic control communication service knowledge question and answer capability are provided, the knowledge management and application efficiency is effectively improved, and powerful support is provided for digital transformation of related services. Comprising the following steps: S1, a document content extraction and storage process; s2, a content retrieval and generation process; s3, content slice optimization is carried out through extraction and similarity calculation of adjacent paragraphs or contents, complete contents are in the same slice, and the content retrieval efficiency is improved; according to the method, the label library and the business rule library are continuously iteratively optimized, so that the provided service is always in the optimal state.

The invention belongs to the technical field of artificial intelligence, and discloses a government information consultation system based on a large language model, which comprises a user interaction module, a large language model core engine, a knowledge base integration module, a multi-level authority management module, a feedback optimization mechanism and a risk control module. The comprehensive intelligent government affair service system is constructed through the six core modules, remarkable advantages are shown in government affair service digital transformation, the system innovatively adopts multi-mode interactive design, multiple input and output modes of voice, text and images are supported, an intelligent authority management mechanism is matched, and the intelligent authority management mechanism is matched with the intelligent authority management mechanism. According to the technical scheme, the accessibility and convenience of government affair services are greatly improved, precise services for different user groups are achieved, it is guaranteed that sensitive data are safe and controllable while wide spreading of government affair information is guaranteed, and a large language model of a system core is subjected to professional government affair scene optimization training and is combined with a dynamically-updated knowledge graph technology.

The embodiment of the invention provides a data processing method and system for an enterprise digital transformation platform, and belongs to the field of data processing. The method comprises the steps that structured field information from all heterogeneous data sources is acquired, and preprocessing operation is executed on the structured field information; constructing the processed structured field information into an embedded input sequence, splicing the embedded input sequence into a natural language fragment according to a preset template, and inputting the natural language fragment into a fine-tuned semantic coding model to obtain a corresponding semantic embedded vector; identifying similar field groups by adopting a clustering algorithm based on density or a hierarchical structure, and classifying each group of structured field information into a semantic cluster; and generating a corresponding standard field identifier for each semantic clustering cluster, and storing the generated standard field identifier in a standard field index database of the platform after digital transformation. According to the scheme, the field unified management and cross-system data alignment capability of the enterprise digital platform is remarkably enhanced.

The invention relates to the technical field of fault monitoring, in particular to a power transmission line fault monitoring and positioning method, system and device and a medium. The method comprises the following steps: firstly, performing digital conversion on an original current signal to obtain time sequence data, and then identifying and classifying fault events through threshold detection and a feature extraction algorithm to obtain classification labels of fault types; then, based on the classification label, establishing a traveling wave propagation model and carrying out time difference calculation, carrying out clustering analysis on a plurality of wave head data in a preset time window, and judging whether the fault is a single-point fault or a multi-point fault through a clustering result; and finally, a positioning result is transmitted to the central server for comprehensive verification and alarm management, and a final fault response is formed. By introducing a time series data analysis and clustering judgment mechanism, the fault type can be accurately identified, single-point and multi-point fault conditions can be effectively distinguished, and meanwhile, the reliability of a positioning result is improved through comprehensive verification of the central server.

The invention relates to the technical field of hydraulic fracturing, in particular to a method for evaluating effectiveness of fracture parameters of artificial fracturing of a horizontal well. The method comprises the following steps that information collection based on ground process parameters and underground dynamic parameters is conducted on the horizontal well artificial fracturing construction process, and fracturing working condition data are obtained; according to the fracturing working condition data, the fracture expansion of the horizontal well is monitored in real time, digital conversion processing is conducted, and real-time fracture monitoring data is generated; performing micro-seismic signal analysis on the real-time crack monitoring data, and performing crack network space distribution calculation to generate crack network distribution data; performing reservoir stress field dynamic evolution analysis according to the fracture network distribution data to generate stress field distribution data; and carrying out propping agent migration trajectory tracking according to the stress field distribution data to generate propping agent distribution data. According to the method, the reservoir stress field dynamic evolution analysis and the proppant migration mechanical model are combined, and the effectiveness of the fracture parameters can be evaluated more accurately.

The invention relates to the technical field of air pressure intensity adjustment, and discloses a pressure control method and device for accurately adjusting air pressure intensity, and the method comprises the steps: carrying out the digital conversion and temperature and humidity compensation of an original pressure signal collected by a pressure sensing array, and obtaining a pressure data matrix and a pressure gradient matrix; calculating a pressure distribution mass center and a pressure fluctuation frequency spectrum to obtain a pressure space distribution characteristic matrix and a pressure time domain characteristic matrix; inputting a three-state Markov model for dynamic state identification to obtain a pressure state transition probability matrix and a pressure response prediction matrix; constructing an objective function containing a pressure tracking error term and an organization safety constraint term, and solving to obtain a PID control parameter matrix and a pressure safety limit matrix; and constructing a three-stage control system comprising a basic controller, an interference compensator and a safety protector, and outputting an air pressure regulation driving signal. According to the method, high-precision pressure sensing control is realized.

The invention relates to the technical field of building engineering cost intelligent estimation, and discloses a building engineering cost intelligent estimation and checking method fusing a domain knowledge graph and a large language model, and the method comprises the following steps: S1, building a building engineering domain knowledge graph (KG), integrating a quota library, a material price library and historical project data, and carrying out the calculation of a building engineering domain knowledge graph (KG); and defining an entity relationship and a dynamic updating rule. According to the intelligent building engineering cost estimation and checking method fusing the domain knowledge graph and the large language model, a closed loop of knowledge structuring (KG) + semantic comprehension (LLM) + multi-modal reasoning is realized for the first time, engineering cost management is promoted to be transformed from experience driving to data-knowledge dual driving, a reusable technical normal form is provided for the field of intelligent construction, and the engineering cost is estimated and checked. The method solves the problems of efficiency, precision, dynamics and interpretability of traditional cost management, has technical innovation and practical value, and provides core technical support for digital transformation of constructional engineering.

The invention relates to the technical field of information, and provides a purchase management method based on an intelligent supply chain management platform, and the method comprises the steps: obtaining material demand data submitted by all departments, carrying out the standardization of the timestamp and demand of the material demand data, and forming standardized data containing an auxiliary classification dimension, a time dimension and a quantity dimension; generating an initial purchase plan table according to the real-time demand data and a preset purchase management rule, and grouping the purchase data in the initial purchase plan table according to a preset grouping rule to obtain a grouped purchase plan table; and obtaining response time prediction data, comparing the response time prediction data with a preset response time threshold value, if the response time prediction data is greater than the threshold value, optimizing the purchasing behavior by adjusting the priority and resource allocation, and determining an optimized purchasing strategy. The standardization, transparency and high efficiency of the purchasing process are realized, and the digital transformation and intelligent upgrading of enterprise purchasing are effectively promoted.

The invention discloses a multifunctional intelligent electronic ear tag device. The ear tag adopts a head hoop and an arc-shaped ear hook structure, a connecting buckle is of a magnetic attraction type, punching is not needed, and the head hoop is made of medical silica gel, so that it is ensured that the ear tag is comfortable to wear by animals and convenient to use repeatedly. The power management module guarantees power supply, and the data monitoring module can collect multi-dimensional information such as animal body surface temperature, environment and behavior data. During working, breeding areas are divided to construct a wireless network, data are acquired and then preprocessed, and the animal growth state sensing model is utilized to analyze and upload a result. The power consumption adaptive algorithm dynamically adjusts the working mode of the ear tag according to the equipment state and the like, such as adjusting the sampling frequency and the local model complexity, so that low-power-consumption edge calculation and accurate reasoning are realized. The user terminal supports data display, interaction control and remote alarm, and helps a manager adjust a breeding strategy based on an analysis result. The system has the characteristics of high comfort, low power consumption and high precision, and provides technical support for digital transformation of animal husbandry.

A system for managing digital transformation projects, consisting of: • a processing unit configured to execute a variety of instructions in real time during the lifecycle of the digital transformation project to perform risk assessment, quality control, and dynamic compromise optimization; • a storage unit coupled to the processing unit, wherein the storage unit stores project data, risk categories, predefined quality metrics and resilience indicators; • a user interface module configured to display project performance metrics, including risk levels, quality status and resilience indicators, and to allow user interactions for real-time adjustment of project parameters; • A communication module configured to synchronize project data with external systems, databases and cloud-based platforms, ensuring seamless data exchange and real-time reporting between multiple project management tools and stakeholders.

The invention relates to the technical field of digital twinning, in particular to an industrial equipment digital twinning system and an intelligent optimization method, and integrates digital twinning modeling, edge computing, cloud computing and visualization technologies. The method comprises the following steps: firstly, constructing an equipment digital twinborn body through three-dimensional modeling and a CAD drawing, and simulating and acquiring data by using a virtual sensor; and the edge calculation module synchronizes physical equipment and digital model data to realize collaborative perception, reasoning, state evaluation and early warning. And the cloud computing module further analyzes the data and optimizes the operation parameters of the equipment. The visualization module integrates multivariate data in a three-dimensional interface, visually displays the equipment state and optimization information, responds to a user instruction, realizes comprehensive, real-time and interactive equipment monitoring and management, and improves the intelligent level and operation and maintenance efficiency of industrial equipment, and the systematic method not only improves the overall efficiency of industrial equipment management, but also improves the operation and maintenance efficiency of the industrial equipment. And reliable technical support is provided for digital transformation of enterprises.

The invention discloses an ideological and political large-scale course teaching attention assessment data acquisition method based on sight tracking. The method comprises the following steps: S1, high-definition large-scene eye movement tracking photographing equipment captures eye images of students in a course teaching process in real time through an infrared camera; s2, performing pupil area detection and pupil center fitting on the eye image to obtain sight tracking data; s3, performing gaze hotspot analysis and gaze duration statistics according to the sight tracking data to quantify attention distribution and change trend of the students and visually display the attention distribution and change trend; and S4, generating a teaching quality evaluation report and teaching optimization suggestions according to the gazing hotspot analysis and gazing duration statistical results. The classroom teaching effect can be objectively evaluated in real time, subjective evaluation errors are reduced, the accuracy and efficiency of teaching feedback are improved, the method is suitable for various scenes such as traditional classrooms, online education and experiment teaching, and the method has the industrial application prospect of education digital transformation.

The invention belongs to the technical field of robot process automation optimization, and particularly relates to an RPA process intelligent optimization method based on a large model. According to the method, the process data is obtained through a convenient file import mode, and the bottleneck and the optimization point are accurately identified by means of data acquisition, preprocessing, semantic understanding and scene learning deep analysis process. And then, the large model automatically generates optimization suggestions and displays an expected adjusted process, and after confirmation by a user, the process can be automatically adjusted and a new file is generated. In the verification link, the process execution condition is strictly detected in normal and abnormal environments, and the optimization effect and stability are ensured. According to the technology, the optimization efficiency and quality are effectively improved, the process adaptability is enhanced, the labor cost is reduced, an intelligent, efficient and reliable solution is provided for RPA process optimization of enterprises, the enterprises are assisted in optimizing business processes in digital transformation, and the operation efficiency and competitiveness are improved.

The invention discloses a student high-order thinking evaluation system based on artificial intelligence, and belongs to the technical field of artificial intelligence learning evaluation. In order to solve the problems of insufficient data integration ability and incomplete evaluation of the current learning evaluation system, the invention aims to develop a student high-order thinking evaluation system based on artificial intelligence, and the system combines the latest education, psychology, learning science, cranial neuroscience and information technology theories. And a comprehensive, systematic and digital-intelligent high-order thinking evaluation system is constructed. The system monitors and analyzes the learning process and high-order thinking degree of students in real time through the artificial intelligence technology, and generates personalized feedback and suggestions. Meanwhile, the system integrates multi-source data, covers cognitive and non-cognitive factors of the students, and realizes comprehensive evaluation of abstraction, meta-cognition, criticality, anti-fact-hypothesis and creative thinking of the students. The system provides a brand new scheme for education evaluation, and promotes digital transformation of education evaluation.

The invention relates to the technical field of natural language processing, in particular to an enterprise transformation diagnosis report generation method based on a large model. Collecting corpus data by using an enterprise diagnosis questionnaire; constructing a digital transformation diagnosis knowledge base, and storing the knowledge base into a vector database; training a sample model, and constructing a diagnosis report template through fine tuning of Prompt cue words; and taking the fine-tuned cue word as input, automatically generating a diagnosis report by utilizing the trained large model, selecting different file formats by utilizing an agent, generating a diagnosis report and outputting the diagnosis report. Through questionnaires and industry characteristic analysis, diagnosis suggestions are intelligently generated, enterprise transformation pain points are identified, and the efficiency and accuracy of enterprise transformation diagnosis are improved.

The invention provides an enterprise intelligent finance and taxation system fusing supervised learning and a block chain, and solves the core technical problems of insufficient data credibility, transparent contradiction between privacy protection and supervision, AI model training data island and the like of a traditional finance and taxation system. According to the system, an innovative technical fusion scheme is adopted, bank API, OCR recognition, voice input and other multi-source financial data are integrated through a multi-modal data fusion unit, and high-quality data fusion is achieved through confidence evaluation and an intelligent conflict resolution algorithm; an intelligent classification unit based on BERT deep learning integrates a pre-training model with a business rule engine and a gradient boosting decision tree, and accurate and automatic classification of financial transactions is achieved. A complete technical solution is provided for enterprise finance and taxation digital transformation, intelligent, automatic and credible processing of finance and taxation businesses is achieved on the premise that data safety and privacy protection are guaranteed, and the method has wide market application prospects.

The invention discloses an intelligent analysis method and system for enterprise digital transformation, and relates to the technical field of enterprise digital transformation, and the method comprises the following specific steps: perception and preprocessing: employing a network data capture technology to obtain scene factor related text information from multiple channels, according to the method, key information such as policy and regulation update and market dynamic change is captured in real time by utilizing a plurality of information acquisition channels, and a knowledge graph system containing rich enterprise knowledge is constructed; according to the technical scheme of the invention, new scene factors can be deeply associated and accurately matched with knowledge such as business processes and technical architectures inside an enterprise, so that the system can provide more scientific and accurate digital transformation decision suggestions for the enterprise, the enterprise is helped to better cope with external environment changes, the internal management process is optimized, and the business operation efficiency is improved.

The invention provides a cloud computing-based narrow-linewidth 1200 nm semiconductor laser data processing system, and relates to the technical field of data processing, and the system comprises a laser transmitting module which is used for transmitting a narrow-linewidth 1200 nm laser beam by using a semiconductor laser; the data acquisition module is used for being connected with the laser emission module, acquiring state parameters, including power, wavelength, line width and working environment data, of the laser beam in real time, and preprocessing and digitally converting signals output by the sensor; and the cloud processing platform module is used for receiving and processing the data of the data acquisition module, realizing real-time analysis, anomaly detection, trend prediction and remote monitoring of the data, and obtaining an analysis result of a cloud processing platform. According to the invention, remote intelligent monitoring and automatic optimization adjustment of the laser are realized, and the data processing efficiency and the performance stability of the laser are improved.

An industrial information hub (IDH) serves as a single industrial ecosystem platform where multiple participants can deliver repeatable and standardized services relevant to their core competencies. The IIH system is centered around the development of an ecosystem that creates and delivers value to users—including industrial enterprises, OEMs, system integrators, vendors, etc.—through the aggregation of digital content and domain expertise. The IIH system serves as a trusted information broker between the ecosystem and the OT environments of plant facilities, and provides a platform for connecting assets, contextualizing asset data and providing secure access to the ecosystem. Additionally, the IIH system provides tools and support to OEMs and other subject matter experts, allowing those experts to enable their digital assets for use in the ecosystem. The IIH system reduces the cost and risks for digital transformation of industrial assets.

The invention discloses an intelligent business opportunity business processing optimization method and system, and relates to the technical field of artificial intelligence, and the method comprises the steps: collecting historical business opportunity data, and carrying out the multi-dimensional feature extraction, and obtaining business opportunity feature data; constructing a time sequence prediction network based on an attention mechanism, and performing data processing on the business opportunity feature data to obtain business opportunity conversion probability data; generating a business opportunity allocation scheme through a reinforcement learning algorithm according to the business opportunity conversion probability data in combination with sales team capability data and resource utilization data; and monitoring the execution state of the business opportunity allocation scheme, and when it is detected that a state index deviates from a preset threshold value, outputting early warning information and an intervention suggestion. The business opportunity processing efficiency and the conversion rate are improved, and reliable technical support is provided for digital transformation of enterprise sales management.

The invention discloses a power distribution network switching station on-line comprehensive monitoring method based on the Internet of Things, and aims to solve the problems that a traditional switching station is poor in monitoring real-time performance, insufficient in fault early warning capability and the like. The method is realized based on an intelligent monitoring and coping system of an Internet of Things architecture, and through cooperation of multiple modules of equipment operation state monitoring, environment monitoring, security monitoring, intelligent linkage control, alarm management, historical data analysis and the like, an alarm linkage intelligent control closed-loop cooperation algorithm and a time sequence analysis algorithm are combined. And comprehensive perception and intelligent analysis of the operation state, environmental parameters and the like of the switching station equipment are realized. The system can monitor key parameters such as cable head temperature and partial discharge in real time, supports intelligent linkage processing of abnormal scenes such as harmful gas exceeding and water immersion, and predicts the equipment trend through historical data mining. The technology improves the equipment operation safety and operation and maintenance efficiency, reduces the line loss, enhances the power supply reliability, lays a foundation for constructing a novel power system, and promotes the digital transformation of a power distribution network.

The invention discloses a student comprehensive ability evaluation system based on artificial intelligence, and belongs to the technical field of artificial intelligence student learning evaluation. Aiming at the problems of single dimension and poor evaluation effect in the existing student evaluation system, the system not only can provide personalized feedback and improvement suggestions for students and help the students to improve team cooperation, communication and problem solving capabilities, but also can provide accurate teaching evaluation and decision support for teachers and education managers, so that the students can have a better teaching effect. And intelligent upgrading of a teaching mode is promoted. By promoting digital transformation of education evaluation, the system provides an innovative solution for constructing a more scientific, fair and efficient learning evaluation system, and assists high-quality development of education.

The invention discloses a data processing system and method based on a federated architecture interface and related equipment, and relates to the technical field of computer software, in particular to a federated architecture distributed system formed based on a central coordination node and a plurality of regional autonomous nodes. The central coordination node is used for performing global strategy making, metadata block chain evidence storage, conflict detection and federated monitoring and self-healing to realize global management and control, and the regional autonomous node adapts to a physical machine heterogeneous environment to perform local strategy execution, heterogeneous protocol conversion and resource autonomous regulation and control so as to realize flexible regulation of a regional strategy. According to the scheme, through a federated and intelligent treatment system, inherent contradictions between centralized management and control and department autonomy, standardization and rapid iteration and global safety and local flexibility are solved, technical support is provided for an enterprise to construct a standardized, high-reliability and easy-to-expand API ecological system, digital transformation is assisted, and the enterprise safety is improved. And global controllability and local autonomy of enterprise-level API ecology are realized.

The invention discloses a wind turbine generator power generation capacity analysis, diagnosis and optimization method and device, and relates to the field of wind turbine generator power generation capacity monitoring, and the method comprises the steps: obtaining a plurality of groups of to-be-processed data including wind turbine generator operation data, meteorological data and wind field operation data, carrying out the preprocessing, and inputting the data into a plurality of analysis models, comprising a power curve fitting analysis model, a wind deviation analysis model, a temperature-power analysis model, a running time analysis model, a power loss analysis model, a pitch angle analysis model, a micro-siting analysis model and / or an AGC curve deviation analysis model, and obtaining multiple groups of analysis data; inputting the multiple groups of analysis data into a diagnosis model constructed based on machine learning to obtain a diagnosis result; and inputting the diagnosis result into the expert optimization suggestion model to obtain an optimization suggestion scheme. The method can improve the power generation efficiency of the wind power plant, improves the system efficiency and accuracy, reduces the operation cost, and facilitates the realization of the digital transformation of the wind power industry.

The invention relates to the technical field of engineering construction informatization, in particular to a process-level multi-dimensional coding construction file detection system and method, and the system comprises a four-dimensional dynamic coding engine, an intelligent file verification module, a block chain evidence storage and restoration module and a dynamic tracing platform. The four-dimensional dynamic coding engine generates a unique code and verifies process logic; the intelligent file verification module identifies missing files based on an engineering file template library and a weighting algorithm; the block chain evidence storage and repair module carries out cochain evidence storage on missing records and sets a time-limited completion mechanism; the dynamic tracing platform realizes bidirectional mapping and visual monitoring of the construction file and the BIM model; according to the method, through cooperation of all the modules, code generation verification, file integrity detection, missing evidence storage repair and construction whole process tracing are completed. The method solves the problems that traditional construction file management is low in efficiency, difficult in process supervision, difficult in data tracing and collaboration and the like, promotes digital transformation of project management, and improves project quality and management efficiency.

The invention discloses a traffic data security encryption and circulation system and method based on a block chain, belongs to the technical field of traffic control, and aims to solve the problems of security, privacy and trust in traffic data sharing. The system comprises an edge computing node which is deployed near a data source and is used for performing encryption or privacy enhancement processing on original traffic data; a block chain network with a smart contract is deployed, node identities are managed, verification information is recorded, an access strategy is stored, and data circulation is controlled; and the data processing unit is used for aggregating the processed data to generate a circulatory data product. The method comprises the steps of edge security processing, block chain management verification, product generation by the data processing unit and management and control circulation of the block chain according to a strategy. Through edge security processing and a block chain trust mechanism, data security privacy is guaranteed, safe, transparent and credible circulation and utilization of traffic data are realized, and reliable data support is provided for intelligent upgrading and digital transformation of the traffic industry.

The invention belongs to the technical field of enterprise digitization, and particularly relates to a rapid tracking and positioning method for enterprise digitization development maturity. Comprising the following steps: S1, establishing a digital development maturity evaluation framework; s2, index system screening is carried out based on a fuzzy Delphi method; s3, establishing an improved K-means model based on density and weight; s4, carrying out enterprise digital development grade division; s5, establishing an enterprise digital transformation mature stage correction model; according to the method, a digital development maturity evaluation framework is constructed, index system screening based on a fuzzy Delphi method is utilized, an improved K-means model based on density and weight is combined, enterprise digital development grade division and an enterprise digital transformation maturity stage correction model are combined, enterprises are helped to quickly know the current situation of own digital development, and the evaluation accuracy of the digital development maturity is improved. Problems can be found in time and targeted measures can be taken so that a problem that rapid and accurate tracking and positioning of enterprise digital development maturity are lacked in the prior art can be solved.

The invention discloses an automatic page generation method of a software construction platform based on a large language model, which comprises the following steps of: extracting a scene, a page and constraint description from a natural language demand, and generating JSON (JavaScript Object Notation) content containing a data model, a query condition, a table column and static data through the large language model; according to component type constraints and verification rules, the JSON is mapped to components and combinations of buttons, labels, texts, pictures, pull-down selection, multi-choice, single choice, tables, dates and the like of the code-free construction platform; and automatically filling a component set based on the upper and lower partition templates, and injecting static data and verification logic. Through industry knowledge adaptation, component semantic binding and dynamic constraint, it is ensured that the page conforms to field specifications and interaction logic, the learning cost is reduced, manual intervention is reduced, and the method is suitable for the fields of smart cities, natural resources, urban and rural residence construction, emergency management, enterprise digital transformation and the like.

The invention discloses an electromagnetic transient simulation and mapping method and system oriented to multi-physics field coupling, and belongs to the technical field of substation digital operation and maintenance and electromagnetic simulation. Deploying multiple types of sensors in a transformer substation, preprocessing the acquired multi-physical field data, and fusing with the three-dimensional twinborn model; a coupling algorithm is adopted to carry out multi-physical field coupling analysis, multi-physical quantity display and thermodynamic diagram superposition are realized, and scene evolution change simulation under various typical working conditions is supported; a micro-service architecture is adopted to construct a digital twin system, double closed-loop verification of simulation and actual measurement is performed through actual measurement data and simulation data of a real-model test field, model optimization is completed, and real-time mapping of electromagnetic transient dynamic simulation and a transformer substation physical entity is realized. The method improves the precision of model and entity mapping, meets the requirements of real-time tracking and response of the electromagnetic transient change of the transformer substation, adapts to the digital transformation of different transformer substations, and provides a basis for the operation and maintenance of the transformer substations.

The invention discloses a Teamcenter-based model parameter and bill of materials (BOM) management method, relates to the field of product life cycle management system application, and aims to realize efficient management of model parameters and a bill of materials (BOM) through the steps of integrated data management, automatic process, authority control, version control, intelligent assistance and the like on the basis of a Teamcenter platform. The uniform storage and integration capability of Teamcenter is utilized to ensure the consistency and integrity of model parameters and BOM data; automatic processes such as automatic consistency checking and automatic PDF generation are designed, and manual intervention is reduced; the data security is guaranteed through an authority management function; a strict version control mechanism is implemented to ensure data traceability; and intelligent assistance is provided for the user by using functions of searching, querying and the like, so that the working efficiency is improved. According to the method, the problems of data updating lagging, high error rate and untimely information sharing in a traditional management mode are effectively solved, and powerful support is provided for intelligent manufacturing and digital transformation of enterprises.