506 results about "Management process" patented technology

The invention relates to the technical field of management and control systems, in particular to a digital intelligence system applied to collaborative management and control of water-power engineering construction participating units, which comprises a project data management module covering water-power engineering construction full life cycle management, extracting multi-source information data from various subsystems, and constructing a project view and a project management information base; the project risk analysis module is used for constructing an intelligent risk analysis model for risk analysis and generating a dynamic evaluation result, a graded early warning notification and an auxiliary decision scheme; the project collaborative management module is used for processing graded early warning notification and auxiliary decision-making schemes by using a multi-layer perceptron model, and generating finalizing service achievements and management process records; and the project document management module is used for performing compliance automatic checking and processing on the electronic documents needing to be archived, and dynamically updating and optimizing the project management information base. Through the closed-loop management and control system, the cooperative management and control efficiency of water-power engineering construction participation units is improved.

The invention relates to the technical field of consumable traceability, and discloses an SPD medical consumable intelligent monitoring and traceability management system, which comprises a consumable warehousing module for inputting information through a UDI code and updating the inventory; the receiving plan generation module is used for calculating the demand quantity of each department for different types of consumables according to the demands of clinical departments, and generating a receiving plan according to the demand quantity; according to the distribution and use module, the SPD system distributes the consumables according to the receiving plan and selects the earliest batch for distribution according to the FIFO principle or the FEFO principle; and the refund processing module is used for re-evaluating the remaining period of validity when the unused consumables are refund. According to the method, UDI coding runs through the whole consumable management process, a complete closed-loop management process of intelligently analyzing and predicting future demands, dynamically optimizing inventory, recording consumable circulation information in the whole process, generating and finally purchasing execution is introduced, an informatization means and a management optimization strategy are combined, and the SPD medical consumable management level can be effectively improved.

The invention relates to the technical field of campus management, and particularly discloses a smart campus management system based on big data, an event-driven data management architecture is used for dynamically collecting, integrating and associating multi-source heterogeneous data in a campus, and generating a standardized event stream; the dynamic resource scheduling engine is in communication connection with the event-driven data governance architecture, generates a resource allocation instruction based on event types and priorities in event streams, and dynamically deploys campus resources; the closed-loop evaluation optimization module receives a resource scheduling result of the dynamic resource scheduling engine and generates a multi-dimensional evaluation index, and the multi-dimensional evaluation index is fed back to the data governance architecture through root cause analysis so as to optimize a subsequent decision; the privacy enhancement processing unit integrates a federated learning framework and a differential privacy algorithm, performs collaborative analysis on cross-system data and ensures the anonymity of individual data; through three core technologies of dynamic data management, intelligent resource scheduling and closed-loop evaluation optimization, intelligent upgrading of the whole campus management process is realized.

An agent management platform for providing a runtime environment for the execution of agents can be used to manage process deployments. The agents can be configured to perform specific tasks on software applications within defined objectives. Using an obtained execution request, the agent management platform can associate agents with one or more nodes by comparing node constraints against agent constraints. The nodes can include computers equipped with containers that provide isolated runtime environments for agent execution. The agent management platform can instantiate agents in corresponding containers on the computers of associated nodes, and / or execute the instantiated agents to perform corresponding tasks.

The invention discloses a wire harness manufacturing management system and method based on artificial intelligence, and relates to the technical field of intelligent manufacturing, and the method comprises the steps: inputting a structured feature vector and a process constraint condition into a multi-target reinforcement learning model, and generating a process parameter instruction; the process parameter instruction is executed, the product yield is monitored in real time, and cross-process quality tracing is carried out on the abnormal product yield; historical data of abnormal batches in crimping, assembling and testing procedures are traced, the defect root cause probability of each procedure is calculated based on a Bayesian causal network, and primary and secondary root causes of quality defects are obtained and analyzed; and dynamically updating process constraint conditions according to primary and secondary root cause analysis results, adjusting a reward function of the multi-target reinforcement learning model, and re-optimizing a process parameter instruction. According to the invention, the operation state of the production equipment is accurately captured, the production process is optimized and adjusted in real time, and a closed-loop management process is formed, so that the production flexibility, efficiency and product quality are remarkably improved.

The invention provides an urban construction and traffic engineering investigation and design enterprise product quality management system and method. The system comprises a cross-project type quality data fusion module, a dynamic defect evolution prediction module, an intelligent layered spot check engine, a three-dimensional quality situation deduction module, a conference knowledge graph construction module, a result influence evaluation module and a self-adaptive file management system. All the modules are connected through a unified data bus to form a closed-loop management process of quality data acquisition, analysis, decision and feedback. According to the system, through the functions of multi-modal data fusion, defect prediction, intelligent spot check, situation deduction, knowledge precipitation, achievement evaluation, file management and the like, the whole-process intelligent management and control of the project quality are realized, and the management efficiency and the decision scientificity are improved.

The invention relates to the technical field of workflow optimization, in particular to an enterprise management process optimization method and system, and the method comprises the following steps: obtaining the length of an approval task queue, the average approval time and the number of pending tasks, calculating a task backlog rate, calling task flow fluctuation to set a node load state coefficient, and generating a load distribution state of approval nodes. According to the invention, the task circulation priority is calculated based on the time constraint and the service weight, so that the emergency task is circulated preferentially, the approval efficiency is improved, the approval path is sorted through the node processing capability and is adjusted and optimized, the task circulation adapts to the load change, the flow blocking risk is reduced, and the task state change record is screened based on the circulation path. The data screening accuracy is improved, the effectiveness of task execution data is ensured, the abnormal detection is combined with the time sequence trend and abnormal node analysis, abnormal task tracking is more efficient, problem nodes are traced accurately, and abnormal task processing is accelerated.

The invention discloses a power grid material sampling inspection management method for realizing whole-course tracing based on intelligent sample sealing, and relates to the technical field of electric power material management and intelligent perception, and the method comprises the following steps: S1, an initialization stage: executing a sample sealing coding segmentation pre-configuration process, distributing independent numbered segments to each sample sealing terminal, and the central control module synchronizes the use state of the terminal code to realize distributed isolation of code generation. According to the invention, coding uniqueness is realized through segmented pre-configuration and global duplicate checking, identity information security is guaranteed by adopting chip one-time write protection and tamper-proof technologies, and sample packet switching and data counterfeiting are effectively prevented by combining automatic acquisition and multi-round consistency comparison. Abnormal recognition and closed-loop processing ensure that abnormal events are frozen in time and responsibility is traced, and irregular samples are prevented from flowing into subsequent links. The whole-process auditing and dynamic optimization enable the management process to be self-perfected, and the intelligence, standardization and reliability of sampling inspection of the power grid materials are remarkably improved.

The invention discloses a big data-based natural gas pipeline maintenance optimization method and system, relates to the technical field of natural gas pipeline maintenance, and aims to construct a structured monitoring data set, construct a graph model of pipeline states and risk factors, establish a prediction model, introduce a memory mechanism to process low-frequency anomalies, and generate and optimize a maintenance scheduling scheme. According to the natural gas pipeline maintenance optimization method provided by the invention, the map model and the prediction model are constructed based on the multi-source monitoring data, the causal path between the pipeline operation state and the external risk factor can be identified, and the maintenance efficiency is improved. Maintenance task generation, early warning triggering and terminal linkage operation are completed through risk level evaluation and scheduling optimization, collected monitoring data are used for model training and map updating after being processed, a closed-loop management process is formed, and the method is suitable for natural gas pipeline state recognition and maintenance scheduling in various operation environments.

The invention discloses a warehouse in-out rechecking management system based on automatic visual scanning, which relates to the technical field of warehouse rechecking management, and comprises a pose acquisition unit, a visual calibration unit, a cargo reading unit, a record management unit, a warehouse-in rechecking unit and a warehouse-out rechecking unit, the pose acquisition unit is used for acquiring a color image and a depth image of a target cargo in a to-be-identified area so as to obtain pose information of the cargo, and the visual calibration unit is used for obtaining a relation matrix of a camera coordinate system and a mechanical arm coordinate system by calculating a rotation matrix and a translation matrix. And space coordinates in an image collected by the camera are converted into a mechanical arm coordinate system. The automatic visual scanning and mechanical arm technology are combined, the intelligent level in the warehouse management process can be greatly improved, the method is more suitable for actual complex warehouse scenes, the cargo warehouse-in and warehouse-out speed can be increased, and the cargo checking accuracy can also be improved.

The invention discloses a software and hardware combined data interaction method and system based on a Modbus communication component. According to the method and the system, different types of Modbus slave devices are managed through a unified communication configuration file and a point table configuration file, so that compatible access to heterogeneous devices is realized; through an optimized point table analysis mechanism, efficient and self-adaptive data acquisition of discontinuous register addresses is supported, and fine processing and conversion are performed on different data types; a graphical configuration management tool is provided, and the equipment configuration and point table management process is simplified; and a standardized command model is used, so that unified control and data interaction of an upper-layer application on Modbus equipment are facilitated. According to the invention, the flexibility, usability and data interaction efficiency of Modbus communication can be remarkably improved, the system integration and operation and maintenance cost is reduced, and an efficient and reliable Modbus communication solution is provided for the field of industrial automation.

The invention discloses a government affair department knowledge base access authority control method based on a block chain, and relates to the technical field of block chains and information security, distributed nodes jointly participate in decision making, the performance bottleneck of a single control point and the single point fault risk are effectively eliminated, and the reliability and stability of a system are remarkably improved; when a plurality of departments need to collaboratively update a strategy, the intelligent contract based on the threshold multi-signature mechanism can automatically execute voting aggregation and a strategy effective process without depending on manual operation of a central administrator, so that the efficiency and the automation level of cross-department collaboration are greatly improved, and the instantaneity and the consistency of strategy change are ensured; the inherent non-tampering and traceable characteristics of the block chain provide powerful auditing guarantee for the whole authority management process; and each policy update request, voting process, final decision and policy version switching are completely recorded on the chain to form a non-repudiated audit clue.

The present invention discloses a supply chain logistics information management system based on artificial intelligence, specifically related to the field of artificial intelligence technology, including a linear fitting module, a non-linear fitting module, a dual-mode construction module, a distribution verification module, and a management intervention module. The linear fitting module obtains linear conventional coefficients according to linear scenario information, the non-linear fitting module obtains non-linear special coefficients according to non-linear scenario information, the dual-mode construction module constructs a dual-mode management model based on the linear conventional coefficients and non-linear special coefficients and outputs a time cost delay index, the distribution verification module classifies the delay status in the supply chain logistics information management process, and the management intervention module conducts intervention management according to the classification results. This application predicts the time cost of the most time-consuming and laborious customs declaration and tax payment links in the supply chain logistics information management process, improving the management effectiveness and real-time performance of the entire logistics information management chain.

The invention provides an electromechanical equipment full-life-cycle management system, and the system comprises an obtaining module which is used for obtaining the current stage of a full life cycle of electromechanical equipment, and determining equipment variable parameters and equipment measurement parameters which need to be monitored at present; the offset module is used for acquiring the running state and the environmental parameters of the electromechanical equipment, and determining a measurement parameter offset value based on the running state and the environmental parameters; offset is carried out on the equipment measurement parameter based on the measurement parameter offset value, and an offset measurement parameter is obtained; the measurement module is used for determining corresponding parameter measurement equipment based on the equipment variable parameters; controlling parameter measurement equipment to measure equipment variable parameters of the electromechanical equipment according to the offset measurement parameters to obtain a parameter set; and the control module is used for analyzing the parameter set and controlling the operation of the electromechanical equipment based on an analysis result. According to the invention, the defects of inaccurate data measurement and resource waste in the current full life cycle management process are overcome.

The invention relates to the technical field of safety production management, and discloses a safety production hidden danger closed-loop management and control supervision system and a risk assessment early warning method, and the system comprises an environment modeling module which is used for building a digital model of a production unit and calculating a systematic instability coefficient based on historical data; the risk assessment module is used for quantifying the initial risk potential energy in combination with the coefficient and the hidden danger inherent attribute; the risk evolution module is used for dynamically updating risk potential energy according to a time and space coupling rule; the closed-loop verification module is used for judging the actual effectiveness of the intervention measure by comparing the management entropy before and after the intervention after the intervention measure is implemented; and the self-adaptive feedback module is used for automatically updating the systematic instability coefficient in the environment model according to the judgment result. According to the method, risk quantification, dynamic early warning, effect verification and model self-optimization are integrated, a complete closed-loop management process is formed, and the scientificity and foresight of safety production management are remarkably improved.

A change management task automation system reduces manual effort required for change audits and streamlines the change management process, enforcing preventative compliance with change management best practices. A plurality of automation modules provides change management task automation functionality for several processes, including software change management, database change management, key report change management, data lake change management, patch change management, and controlled version document repository management automation.

The invention discloses an airport operation and maintenance data storage method and device based on a block chain and electronic equipment, and relates to the field of airport operation and maintenance data security management.The method comprises the steps that a first hash value is calculated for collected original operation and maintenance data, and a probe private key is used for conducting double-layer digital signature, transmitting the signed operation and maintenance data packet to an intelligent operation and maintenance system by adopting a preset encryption communication channel, calling a block chain intelligent contract through the intelligent operation and maintenance system under the condition that the integrity verification of the single piece of original operation and maintenance data is passed, and verifying the legality of the double-layer digital signature; and performing structured processing on the original operation and maintenance data passing the signature verification, and storing the original operation and maintenance data to a block chain network. According to the method and the device, the technical problems that data among multi-source heterogeneous systems is insufficient in credibility in a management process of airport operation and maintenance data, the security of data transmission cannot be guaranteed, and data leakage is easily caused in related technologies are solved.

The invention discloses a digital certificate life cycle management method based on a block chain, and relates to a block chain and digital identity authentication technology, and the method comprises the steps: receiving a certificate issuing application submitted by a certificate applicant, and writing the certificate issuing application into a certificate application node of a block chain network; obtaining a historical certificate revocation record of a certificate applicant through the verification node based on the certificate revocation state query interface, and performing security evaluation on the certificate issuing application to generate an evaluation result; when the evaluation result shows that the applicant has no historical certificate revocation record, a digital certificate is generated through the certificate issuing node, and the digital certificate and the identity identification information of the certificate applicant form a certificate block; and broadcasting the certificate block to all nodes of the block chain network through the certificate issuing node, and recording state change information to form a state tracing chain. According to the invention, the whole digital certificate management process and the block chain technology are deeply fused, a complete closed-loop management system is constructed, and revolutionary upgrading of a traditional certificate management system is realized.

The invention provides a double-way buffering mechanism design method for Web services. Two buffering mechanisms based on dynamic pages and static pages perform double-way reading and writing through a database and an xml buffering file, synchronous operation is performed to trigger updated buffering mechanisms, an xml buffering module is used as a using library when a user accesses, a database in an application system is used as a standby library, and reading and writing operations of data are finished in the xml buffering file; and the design content comprises a management process, a reading process and a write-in process of a double-way buffering mechanism. The double-way buffering mechanism design method has the advantages that by means of the dynamic and static combined double-way buffering mechanism, timeliness and accuracy of a system in mass data processing can be improved to a large extent, and performances and service qualities of a Web server are improved.

The invention discloses a multi-agent-based industrial equipment abnormal event management method and device and a medium, and relates to the technical field of multi-agents, and the method comprises the steps: carrying out the equipment abnormal event recognition of industrial Internet of Things platform data, so as to determine an equipment abnormal event; based on the original knowledge base, performing multi-dimensional exception decision analysis on the equipment exception event to obtain a task execution instruction; based on the equipment automatic execution task instruction, first work order data is obtained through equipment work order completion processing; according to an operation and maintenance personnel execution task instruction, performing operation and maintenance dialogue completion processing to obtain second work order data; and performing knowledge classification distinguishing knowledge precipitation on the first work order data and the second work order data to determine updated knowledge, and uploading the updated knowledge to the original knowledge base to obtain an updated knowledge base. According to the method, the technical problem that the relevance of the abnormal event management process of the industrial equipment is poor is solved.

The invention provides an urban internal lake water pollution treatment method and system. Real-time water quality data are collected from a lake; processing the collected data; using the prediction model to predict a water quality trend and identify a pollution risk; according to the analysis result of the machine learning algorithm and the water quality model, the decision support module generates a targeted treatment strategy; according to the treatment strategy provided by the decision support module, specific treatment measures are implemented; and the intelligent management and control module is used for monitoring and managing the whole treatment process in real time. All the modules are linked to construct a whole-process and intelligent treatment system, the treatment efficiency of urban internal lakes is effectively improved, and continuous improvement of water quality and long-acting restoration of an ecological system are achieved.

The invention provides a BIM-based building construction simulation management method and system. The BIM-based building construction simulation management method comprises the steps of pre-constructing a first construction progress model as an initial design construction progress model by using a BIM system; constructing a second construction progress model based on the BIM system according to the current building construction management process, wherein the second construction progress model is obtained by scanning a building construction site and inputting the building construction site into the BIM system; comparing the second construction progress model obtained by actual scanning with the first construction progress model, judging a current project progress difference and a construction quality difference, and generating a supervision strategy; a danger warning area is generated according to the module type of the second construction progress model, video information in the danger warning area is obtained in real time, and human body information is recognized from the video information; and calculating a comprehensive quality score according to a comparison result of the second construction progress model and the first construction progress model at each progress node.

The invention provides a bulk commodity transaction whole-process collaborative management system and method, and the method comprises the steps: carrying out the structural dependence evaluation of a verification result of a state transition condition between adjacent collaborative management processes and transaction node information of each collaborative management process, and obtaining a block sequence of state dependence between the collaborative management processes; when the state change of one collaborative management process is completed, generating a digital signature for combined data of transaction node information of the current collaborative management process and a hash value of a block head corresponding to a preorder collaborative management process by using a private key of a participant responsible for the state change, and constructing a state change voucher of bulk commodity transaction; and packaging the state change voucher and the block sequence on which the state depends as transaction data to candidate blocks, and forming a distributed account book for recording bulk commodity transaction full-process state transition through a non-tampering characteristic of a block chain. Based on the scheme, credible collaborative evidence storage of bulk commodity transaction whole-process data can be realized.

The invention discloses an interface design and implementation method of a BMC (Baseboard Management Controller) remote management system based on Redfish. According to the method, a multi-module resource model conforming to Redfish specifications is constructed in a baseboard management controller (BMC), management modules including Systems, Chassis, Managers, Account Service, Session Service, TaskService, Update Service, FRU and the like are integrated, and a unified RESTful interface architecture is formed. The method supports standardized access to management functions such as a server system state, hardware assets, a user account, remote control and firmware upgrading, and meanwhile, a unified authentication mechanism and an asynchronous task mechanism are introduced, so that an efficient and safe out-of-band management process is realized. The system has the advantages of uniform interface, clear structure, safety, controllability, high expandability and the like, and is suitable for various data center and server remote management scenes.

The described techniques address issues related to compatibility and cost-effectiveness of in-vehicle networks. The described techniques may utilize security Ethernet-based protocols, for example, without the need to exchange separate key agreement messages and, consequently, meet the stringent starting time requirements for real-time control systems. Additionally, a membership tracking solution may be implemented in which each node within a membership group may request, or “challenge” other nodes with the same group to verify their online status, and this online status may be maintained over time. Finally, a transmission queue management process is described that deletes queued messages only when it is determined that every intended recipient node received the message, thereby providing atomicity. Retained queued messages may then be re-transmitted in accordance with a transmission schedule.

The invention discloses a data process management system and method based on a block chain technology, and relates to the technical field of big data analysis. The change rule of the data reading request amount, the packet loss rate and the storage capacity of each block is accurately grasped based on historical data, the traditional limitation is broken through, and the data processing perspectiveness and accuracy are improved. And meanwhile, a comprehensive risk assessment and intelligent storage strategy system is constructed, a risk value is calculated in combination with multiple factors, the data backup fragmentation storage layout is optimized, dynamic monitoring and intelligent replacement are performed on storage blocks, the data loss risk is reduced, and the data security and availability are enhanced. From data prediction to dynamic migration, all links are in close cooperation, data security and consistency are ensured through transmission encryption and index real-time updating, the management process is continuously optimized, and a complete, efficient and intelligent solution is provided for block chain data process management.

The invention provides an RAG-based equipment maintenance management knowledge base construction method and system and electronic equipment, and the method comprises the steps: S1, collecting multi-source data related to equipment maintenance, and carrying out standardized preprocessing, the data comprising a maintenance record, a fault report, an equipment manual and expert maintenance experience; s2, storing the preprocessed data into a knowledge base according to a hierarchical structure of equipment maintenance dimensions, and establishing association between maintenance knowledge and equipment features; s3, analyzing equipment maintenance query input by a user, extracting fault feature information and retrieving matched maintenance knowledge fragments; s4, fusing the retrieved maintenance knowledge to generate a structured maintenance scheme, and outputting the structured maintenance scheme after auditing; and S5, continuously updating the knowledge base based on the actual maintenance feedback and the newly added case, and optimizing the association relationship of the maintenance knowledge. By constructing a closed-loop knowledge management process of collection-storage-retrieval-generation-updating, systematic management, accurate matching and intelligent application of equipment maintenance knowledge are realized, the equipment maintenance efficiency and quality are improved, and the maintenance cost is reduced.

The invention discloses a hot patch management method in a passive optical network system, a storage medium and an electronic device, in a Linux system, a patch management process running in a user mode and a patch management unit running in a kernel mode cooperatively execute, and the method comprises the steps that after the patch management process completes loading of a patch pack, the patch pack is loaded in the user mode; acquiring a patch function address and an original function address in the patch pack to obtain a corresponding relation, and configuring the corresponding relation to a patch management unit; when the original function is called, the original function determines to execute the original function logic or jump to the address indicated by the hook parameter by judging the value of the hook parameter; and the patch management unit registers a corresponding probe for each patch function according to the corresponding relationship so as to trigger a processing function of the probe to execute an operation of modifying the value of the hook parameter into a corresponding patch function address before the original function is executed, so that an execution process is skipped to the patch function when the original function is called, and the original function is called. And managing the function-level hotfix of the kernel mode and the user mode in the same framework.

The invention relates to the technical field of network security, and provides a network security policy optimization method and system, and the method comprises the steps: obtaining a detection sensitivity adjustment record of a process of adjusting and managing a network communication mode through a self-adaptive network security system, and carrying out the optimization of a network security policy based on the detection sensitivity adjustment record; identifying a communication mode in which the detection sensitivity is continuously reduced; performing multi-dimensional risk re-assessment on the communication mode to obtain a multi-dimensional risk re-assessment result; the multi-dimensional risk re-assessment comprises the steps of performing association analysis on the communication mode and a preset abnormal behavior to obtain association analysis information; obtaining the current state and operation logic of the industrial production process; verifying the rationality of the communication mode in the industrial control system in combination with the current state and the operation logic to obtain rationality verification information; and according to a multi-dimensional risk re-assessment result, adjusting and optimizing a security policy, and generating and sending alarm information. The method has the effect of improving the network security protection level of the industrial control system.

The invention discloses a mold life cycle management method and system based on an RFID (Radio Frequency Identification) technology, relates to the field of mold management, and in particular relates to a method and system for realizing whole-process management of a mold life cycle based on data acquisition and analysis of RFID and PLC (Programmable Logic Controller) equipment collaboration. The method comprises the following management steps: step 1, initializing mold information and binding the mold information with an RFID (Radio Frequency Identification Device); step 2, RFID reader-writer deployment and station identification are carried out; 3, mold state sensing and data filtering; 4, collecting data used in the production process; 5, RFID and PLC data fusion verification is carried out; step 6, uploading the data to the cloud and a life cycle management platform; and 7, automatically judging the state of the mold and outputting management suggestions. The problems of low recognition efficiency, inaccurate state tracking, lack of life cycle management and the like in the existing mold management process are solved, and real-time sensing, automatic statistics, state judgment, visual display and intelligent decision support of the mold in the whole life cycle are realized, so that the efficiency, accuracy and intelligent level of mold management are improved.