88 results about "Process management system" patented technology

The invention relates to the technical field of medicine management, and discloses a medicine informatization whole-process management system based on big data analysis. According to the system, a drug full-life-cycle multi-dimensional data stream is captured through a distributed sensing node network, and a drug state tensor is generated after noise filtering and missing value compensation are carried out through a real-time stream processing engine. The risk identification module scans and locates an abnormal data cluster through a multi-scale mode and constructs a drug quality hypersurface model; and the data aggregation module establishes a mapping relation between a state tensor and a quality model by using a space-time diagram attention network and calculates a global consistency metric value. The intelligent decision-making module generates an optimal drug management action sequence based on the measurement value under multiple constraint conditions, the closed-loop control module executes the action sequence and monitors system state deviation in real time, data acquisition parameters are dynamically calibrated, and autonomous optimization and closed-loop management of the whole process of drugs are achieved.

The invention relates to the technical field of intelligent manufacturing and supply chain collaborative management of woven garments, in particular to a garment production process management system based on artificial intelligence, and the system comprises a production network management center which is used for obtaining a node execution entropy value; the demand dynamic analysis unit is used for carrying out feature extraction analysis on the collected unstructured design data to obtain an order complexity coefficient; the strategy game matching unit is used for obtaining a steady-state scheduling signal or a recovery scheduling signal; when a steady-state scheduling signal is generated, the collaborative scheduling execution unit is used for generating a global optimal scheduling instruction, and minimizing turnover time is taken as an optimization target; when a recovery scheduling signal is generated, the collaborative scheduling execution unit is used for generating a risk recovery scheduling instruction, taking a minimum node execution entropy value as an optimization target, and actively inhibiting pursuit of turnover time; according to the method, the problem that the hidden risk of the node cannot be sensed in the prior art is effectively solved, and an accurate quantitative basis is provided for subsequent preventive scheduling.

The invention provides a process digital collaborative management method and system based on a data unified exchange platform, and belongs to the technical field of industrial software and intelligent manufacturing, and the method comprises the steps: constructing the data unified exchange platform, so as to achieve the data exchange among a process management system, a PLM system and a production management system; in the process management system, based on the EBOM obtained from the PLM system, constructing and managing a multi-state process BOM including a basic PBOM, a trial-production PBOM and a production PBOM; and a collaboration mechanism is constructed through a data unified exchange platform, so that business collaboration based on the multi-state process BOM is realized. According to the method, the problems of data consistency and flow collaboration which troubles the manufacturing industry for a long time are solved, and key technical support is provided for enterprises to realize digital transformation and intelligent upgrading through efficiency improvement, quality guarantee, cost control and knowledge precipitation.

The invention discloses a smart agriculture whole-process management system based on environment detection and farmland inspection, and relates to the technical field of smart agriculture, and the system comprises a grid modeling module which is used for constructing a knowledge network, dividing a land block boundary into a plurality of management units, and creating scene grid nodes for each management unit in the knowledge network, the corresponding scene element information is written into scene grid nodes, and a scene knowledge grid basic graph is generated; and the patrol decision module is used for mapping patrol observation records obtained at preset patrol anchor points into patrol event nodes, associating the patrol event nodes with the corresponding periodic scene view sub-graphs and carrying out rule matching to generate a management task node set. According to the method, patrol event nodes and periodic scene view sub-graphs are associated according to scene grids and time proximity relationships, rule matching is performed through a preset scene rule template, and a trigger chain of environment state-patrol description-management tasks is explicitly described in the same knowledge network.

The invention relates to the technical field of agricultural informatization and intelligent management, in particular to a selenium-rich bio-organic fertilizer research and development and demonstration and popularization full-process management system, which comprises a raw material digital filing module, a raw material fingerprint feature vector generation module and a selenium-rich bio-organic fertilizer research and development and demonstration and popularization module, and is characterized in that the raw material digital filing module is used for executing a moving average filtering algorithm to clean data; the market demand reverse analysis module is used for extracting, calculating and generating an environment demand constraint matrix representing market differentiation demands based on a preset element circulation rule; the research and development and production scheduling intelligent decision-making module is used for starting an evolutionary resolving model, mapping raw material fingerprints to an environment constraint matrix and outputting a dynamic production management instruction list; the production execution supervision module is used for distributing an instruction to the terminal and monitoring process execution data in real time; the full-life-cycle closed-loop optimization module is used for obtaining feedback data calculation deviation and generating correction factors to update model parameters; the method solves the contradiction between the heterogeneity of the non-standard biomass raw materials and the precise nutritional requirements of functional agricultural products.

The invention belongs to the technical field of informatization management, and discloses a shared laboratory service full-process management system and method based on a micro-service architecture. Comprising the steps of performing user authentication on a laboratory user, and generating basic credit line data; the account age of the laboratory order is monitored in real time, and whether a user account is set to be in a frozen state is judged; receiving repayment state data, calculating an unfreezing waiting period, and recovering the user account to a normal state after the unfreezing waiting period is ended; when the user account is in a normal state, starting second-reading timing before the user places an order, and generating an anti-bypassing behavior log; after the second-reading timing is finished, generating comprehensive hash data, executing a digital signature, and generating signature chain data; generating an experiment detection report according to the signature chain data, and embedding a hidden watermark containing comprehensive hash data; the performance bottleneck of a traditional single framework in a high-concurrency scene can be effectively solved, and the management efficiency, the risk control capability and the service quality of the shared laboratory are improved.

This technology enables accurate detection of parent and child objects from images captured by cameras, such as wearable cameras, whose camera angle and position change. [Solution] The parent component detection unit 20 detects the parent component image region from the image captured by the wearable camera 40. The child component detection unit 30 detects the child component image region within the parent component image. The parent component detection unit 20 includes a parent component neural network 22 that has been trained on images including the parent component image region. The parent component neural network 22 sets up multiple candidate regions (bounding boxes) in the captured image and identifies the candidate region with the highest confidence score for the parent component image region. When the obtained confidence score is equal to or greater than the parent component threshold over a predetermined number of frames of the video, the parent component detection unit 20 confirms the candidate region that is equal to or greater than the parent component threshold, detected in the captured image after the predetermined number of frames, as the parent component image region.

This application discloses a power training end-to-end management system and method based on digital threads, belonging to the field of power training information management. The system uses a digital thread engine as its core hub, connecting data and business flows across modules such as training resources, information, examinations, and points. It anchors the entire lifecycle behavior trajectory of trainees through unique identifiers and timestamps, achieving dynamic mapping and real-time traceability of all elements. The digital thread engine incorporates an AI-MLP neural network and a lightweight GNN module, automatically identifying inflection points in skill development and knowledge gaps, accurately attributing them to long-term skill evolution. The examination management module employs an AI anti-cheating mechanism, enabling seamless post-exam learning. The training resource module connects to a digital twin model, supporting AR immersive practical training. This invention constructs a closed loop of "learning-practice-examination-evaluation-application," improving the accuracy and practicality of training, addressing pain points such as low efficiency in new energy operation and maintenance talent training and fragmented training management, and providing solid talent support for the new energy industry.

The invention discloses a hand plate mold detection process optimization management method and system, relates to the technical field of mold detection, and aims to solve the problems of low efficiency and quality risk when a traditional detection process management system treats a novel composite material and a complex free-form surface structure hand plate mold. The method comprises the following steps: acquiring material characteristic data and geometric characteristic data of a to-be-detected mold; inputting the material characteristic data, the geometric characteristic data and the real-time state parameters and the dynamic capability parameters of the detection equipment into a preset virtual simulation module for detection process rehearsal; according to a rehearsal result output by the virtual simulation module, identifying a potential detection risk associated with the to-be-detected mold; the potential detection risks comprise the scanning blind area proportion, the number of interference points of the measuring head and the estimated detection time consumption deviation.

The application discloses a construction organization whole-process management system, which is suitable for a railway construction process and comprises an interactive sharing platform, a preliminary management module, an execution period management module and a completion period management module, wherein the interactive sharing platform is a center for information sharing and data exchange of construction participants and is used for monitoring abnormal construction processes; the preliminary management module performs preliminary analysis according to shared data and uploads the preliminary analysis to the interactive sharing platform in real time; the execution period management module supervises progress and quality in a construction execution process, generates efficiency and quality analysis results and uploads the efficiency and quality analysis results to the interactive sharing platform; the completion period management module acquires customer internal acceptance information after completion, analyzes differences between the acceptance information, summarizes the differences, generates a project delivery report and uploads the project delivery report to the interactive sharing platform; and the tracing module is used for storing data of various construction projects in categories; the whole-process management system realizes information sharing of the railway construction process, supervision and early warning of abnormal construction, increases experiences of customer parties and railway management parties, improves project completion capability and customer satisfaction and realizes data tracing.

The invention discloses a pregnancy assisting process management system and method based on intelligent interaction, and relates to the technical field of data processing. The intelligent interaction-based pregnancy assisting process management method comprises the steps of S1, collecting pregnancy assisting stage data and historical symptom data of a pregnancy assisting process, performing preprocessing, generating semantic vectors in combination with natural language processing, and constructing a pregnancy assisting management database; s2, analyzing semantic meanings of the symptom words in different pregnancy-assisting stages through pregnancy-assisting stage data, and adjusting the matching precision of the symptoms and the pregnancy-assisting stages; s3, quantifying the context matching degree by analyzing the comprehensive semantic representation and stage semantic difference of the symptom words; and S4, fusing multi-dimensional stage semantics, feature data, evaluation symptoms and pregnancy assisting stage matching degrees to carry out stage classification analysis, and realizing stage attribution optimization and problem type classification. The problems that in the pregnancy assisting process, symptoms and different stages are difficult to accurately match, contextual understanding is insufficient, and the problem classification error is large are solved.

This application discloses a method, apparatus, device, and medium for converting process models into Extensible Markup Language (XML) files. If it is necessary to import a process model from a source process management system into a target process management system, the source XML file of the process model needs to be converted into a target XML file that the target process engine can parse. This achieves the synchronization and interaction of process models in process management systems based on different types of process engines.

The invention relates to the technical field of process control, in particular to an automatic rainwater collection and reuse process management system and method, and the system comprises a rainfall load dynamic evaluation module, a runoff drainage path optimization module, a reuse flow collaborative scheduling module, an operation energy efficiency modeling module and a reuse process feature output module. According to the method, the deposition distribution of the solid-liquid two-phase flow is deduced based on the water flow shear force and the dynamic energy dissipation rate, the runoff drainage path is optimized, the momentum peak value is captured, the flow state evolution precision under the rainfall impact is improved, the hydraulic slope fall of the gravity flow and the pressure flow is analyzed, and the water head loss sudden change section caused by pipe diameter shrinkage and the elbow is checked; the eddy current energy consumption accumulation effect caused by water pressure pulsation and turbulent flow surge is accurately mapped, the anti-scouring and anti-resonance hydraulic stable window period is extracted, the synchronous cooperative response safety of multiple valve sets of an executing mechanism is enhanced, pipe network cavitation and cavitation erosion and water hammer oscillation abrasion are reduced, and it is ensured that water pump transmission is efficient and stable.

A radiation oncology workflow management system is provided. The system may include interactive graphical interface and a particularly programmed processor, thereby to perform operations including displaying a window containing a user interface (UI) environment on a computer screen, parsing an input received from a user via the UI environment, thereby to determine which of a plurality of atomic application functions is indicated by the input, automatically interacting with an atomic application associated with the atomic application function determined to be indicated by the input, and automatically displaying information received from the atomic application via the UI environment.

Methods, systems, and computer-readable media are provided for asynchronous process automation that efficiently manages asynchronous processes based on process control metadata to keep data up-to-date at an adaptively variable type-specific cadence based on process control metadata, eliminating the need for manual engagement to maintain operational activities. An event-driven framework is provided for the asynchronous process automation that includes AI agent(s) for interactions, along with a process management system that tracks pending potential work items due to one or more changes in source data. The process management system activates an asynchronous process management process after a wait period. The process management system then determines which pending potential work items to perform in an iteration of evaluation of the pending potential work items. The process control metadata includes stored limitations on a timing for performing individual processes. The process management system prioritizes processes based on process control metadata, such as prioritizing specific ones over others, including throttling certain other processes during high impact time-sensitive activities.

The invention provides a tunnel construction process management system and method, and relates to the technical field of tunnel construction, and the system comprises an information obtaining unit which is used for obtaining process creation information; the data splitting unit is used for performing data splitting on the process creation information to obtain subitem creation process information; the energy efficiency detection unit is used for carrying out process energy efficiency detection on the process information for creating the subitem to obtain a process efficiency index; the subitem optimization unit is used for performing subitem process optimization on the process efficiency indexes to obtain corresponding optimized subitem process information; the working procedure splicing unit is used for splicing working procedures so as to fuse and generate tunnel construction working procedures; and the dynamic optimization unit is used for carrying out influence evaluation on the tunnel construction process so as to carry out dynamic management optimization on the tunnel construction process. According to the system and the method provided by the invention, site construction conditions can be better matched, the response capability of process execution parameters is improved, and effective management of tunnel construction processes is ensured.

1. Name of the product in this design: Graphical User Interface for Managing the Promotional Planning Process of Electronic Devices. 2. Intended use of this design: for use in an electronic device. 3. The key design features of this product are its graphical user interface content. 4. The image or photograph that best illustrates the design's key features: the front view. 5. Uses of the graphical user interface: for managing the workflow of advertising and promotional planning projects. 6. Human-computer interaction method of graphical user interface: The main view is the budget information maintenance interface of the publicity and planning process management system. When the user clicks the "Publicity and Planning Management" button on the left side of the main view, the user will jump to the interface change state diagram 1. The interface change state diagram 1 shows the query interface of supplier settlement summary in publicity and planning management. When the user selects the purchase date, the reimbursement date and the supplier and clicks the "Query" button, the user will jump to the interface change state diagram 2. The interface change state diagram 2 shows the query result interface of supplier settlement summary ledger query. 7. Other situations requiring explanation: Other explanation: "XXX" in the interface represents replaceable text content, and the gray blocks in the interface represent replaceable images.

The application provides an intestinal preparation quality real-time evaluation and whole-process management system based on artificial intelligence, which comprises the following functions: patient end provides intestinal preparation start time setting, laxative type selection, examination process and matters needing attention query and online consultation function; medical staff end provides patient management, progress and cleanliness score monitoring, early warning processing, data export and message interaction function, wherein the intelligent data acquisition module acquires multi-dimensional data; the artificial intelligence dynamic scoring module analyzes the data based on a deep learning model, generates a cleanliness pre-score and determines a quality grade; the active early warning and intervention module analyzes the data in real time, issues an early warning and provides intervention suggestions; the medical examination result closed-loop verification module receives the doctor's score after colonoscopy, compares and analyzes the pre-score, and optimizes the evaluation model. The application realizes the standardized guidance, active risk early warning and closed-loop optimization management of the intestinal preparation process, effectively improves the preparation quality, guarantees the safety of patients and optimizes the clinical decision-making.

A process management system includes a management unit that manages section data that defines sections in a real space and process data that indicates an expected location, from among the sections, in which a management target is to be positioned at the time of completing a work process, a first wireless device that is attached to the management target and stores first identification information, at least one reading apparatus that is capable of reading identification information from a wireless device, and a determination unit that checks a location of the management target estimated based on a result of reading of the first identification information from the first wireless device against the expected location by variable granularity depending on type information associated with the management target to determine a status of the work process regarding the management target.

The invention discloses a process management system, method and device and a storage medium, and relates to the technical field of computers. The system comprises a GS cluster, a DS cluster, at least one migration server and a database, the DS cluster comprises at least one DS carried by a game engine for supporting a game application program, and at least one DS process runs on the DS; a first migration server in the at least one migration server is used for storing running state information of a first DS process into a database through a first migration process after the first DS process in a plurality of DS processes corresponding to the DS cluster is closed under the condition that the new DS process is pulled up, and the new DS process is used for replacing the first DS process; the first migration process is stateless service; the first GS in the GS cluster is used for notifying the new DS process to read the running state information of the first DS process from the database. According to the method and the device, the online non-stop migration of the DS process under the long-period game service is supported.

The invention discloses a thermal power plant coal burning whole process management system based on AI intelligent identification, and the system comprises a sampling room AI intelligent identification system which identifies the number of people entering a sampling room, and judges whether to carry out the sampling of two persons; the sample preparation room AI intelligent identification system is used for identifying the number of personnel entering the sample preparation room, judging whether double-person sample preparation is carried out, judging whether the coal sample drying time is compliant, and analyzing and judging whether coal sample weighing data is compliant; the AI intelligent identification system for full-moisture sample preparation identifies whether a riffle is adopted for division or not in the sample preparation process by using an AI technology; and the AI intelligent identification system of the calorific value preparation chamber identifies whether an operator has the action of checking the oxygen bomb and the crucible or not when the oxygen bomb is opened after the test is finished. According to the invention, the AI intelligent identification technology is introduced into each key link of the fire coal from purchasing to burning into ash, so that automatic monitoring of sampling, sample preparation, testing and other processes is realized, the operation is ensured to accord with specifications, and the accuracy and safety of fire coal management are improved.

This system reads the characters printed on the materials used in the work as images and recognizes the identification code. This eliminates the need for physical labeling such as paper or stickers on the materials, allowing for direct reading of the characters written on the materials, thereby improving the convenience of material management. The system provides a work process management management method and program. [Solution] The work process management system 1 includes a shooting unit 301 that photographs a string of characters 10 printed on a component 6 used in the work, and a display unit 302 that recognizes the string of characters 10 photographed by the shooting unit 301 and displays pre-stored string of character candidates 20 corresponding to the recognized string of characters 10. The display unit 302 displays one or more string of character candidates 20 for the worker 5 to select from and accepts the worker 5's selection.

This invention discloses a digital full-process SaaS system and method for the disposal of non-performing personal loans based on the S2B2C model, belonging to the fields of financial technology and non-performing asset disposal technology. The system uses artificial intelligence, big data, and blockchain as core technologies, constructing five modules: NPL intelligent assessment, NPL intelligent case allocation, diversified judicial mediation, grid worker collaboration, and value-added services. It pioneers an S2B2C case source supply chain architecture, connecting upstream asset providers, midstream service providers, downstream debtors, and grid workers across the entire chain. It achieves second-level asset package breakdown and valuation, multi-dimensional accurate case allocation, batch online judicial mediation (including AI emotion recognition, electronic service of process, and blockchain evidence storage), and offline grid worker services. It also integrates debt inquiry, employment-based debt resolution, and rapid lawyer order-grabbing functions, forming a complete "assessment-case allocation-disposal-resolution-closed loop" solution. It can be widely applied to large-scale disposal scenarios of non-performing personal loans for banks, consumer finance companies, asset management companies (AMCs), law firms, and other entities.

The application discloses a leather solid waste resourceization process management system based on big data analysis, comprising: a data acquisition module for collecting and preprocessing, constructing a basic data sequence; a feature extraction module for performing kernel regression operation according to the basic data sequence to form a solid waste feature sequence; a transformation prediction module for performing inference prediction operation on the solid waste feature sequence through a Fourier neural network; a path selection module for multi-objective sorting of the prediction result and screening of a target path; a parameter matching module for constructing a process parameter set according to the target path; a resource processing module for mapping the process parameter set into an instruction execution and recording feedback data; and a feedback updating module for updating parameters of the Fourier neural network. The application combines technologies such as feedforward neural network and Fourier neural network, has the advantages of high resource transformation efficiency, strong intelligent selection capability of processing path and sustainable optimization.

The invention belongs to the technical field of silicon steel rolling, and provides a silicon steel rolling process management and control system and method, and the system comprises an early warning system construction module which is used for obtaining first cold rolling process parameter data and silicon steel performance parameter data after the first cold rolling process of oriented silicon steel is completed, and analyzing and processing the data to obtain an early warning system; constructing a collaborative mismatching early warning index system; and the risk level output module is used for inputting real-time index data of the first cold rolling and outputting the probability of collaborative mismatching after the second cold rolling based on a collaborative mismatching early warning index system and a prediction model trained by historical collaborative matching data, and dividing risk levels according to the output probability value. Therefore, the problem of risk identification lag caused by cooperative mismatching of the reduction rates of the first cold rolling and the second cold rolling in the oriented silicon steel cold rolling process is solved, the scrap of the whole coil of strip steel caused by entering the second cold rolling with the initial defect is reduced, the magnetic performance standard-reaching rate and the Gaussian structure proportion of the silicon steel are improved, and the final product quality is guaranteed.

The application discloses a project process management system fusing text analysis and progress tracking, comprising the following modules: a double-channel guidance fusion module used for respectively extracting context semantic vectors and structural intention vectors from a preprocessed text sequence and generating a fusion representation used for task element recognition; an adaptive weight module used for adjustable aggregation and comprehensive correlation calculation of multi-source semantic features; an edge weight adaptive sparsification processing module used for performing edge weight screening and structure optimization on an edge set in an initial task interconnection graph and outputting a sparsified task dependency graph; a cross-layer state perception module used for adjusting node styles and edge states to reflect global execution trends; and a path rearrangement module used for triggering key path analysis and structure reconstruction logic and forming a new path structure. The application fuses semantic analysis and graph modeling and constructs an intelligent linkage project process management system.

The present application relates to the technical field of intelligent manufacturing and supply chain collaborative management of clothing, in particular to a clothing production process management system based on artificial intelligence, comprising: a production network management center for obtaining node execution entropy; a demand dynamic analysis unit for performing feature extraction analysis on collected unstructured design data to obtain an order complexity coefficient; a strategy game matching unit for obtaining a steady-state scheduling signal or a recovery scheduling signal; when the steady-state scheduling signal is generated, a collaborative scheduling execution unit is used to generate a global optimal scheduling instruction with the optimization objective of minimizing the turnaround time; when the recovery scheduling signal is generated, the collaborative scheduling execution unit is used to generate a risk repair scheduling instruction with the optimization objective of minimizing the node execution entropy and actively suppressing the pursuit of turnaround time; the present application effectively solves the problem that the prior art cannot perceive the hidden risks of nodes, and provides accurate quantitative basis for subsequent preventive scheduling.

This invention discloses a PCB board production process management system and method based on intelligent traceability, belonging to the field of production management technology. It includes constructing a board-level traceability knowledge graph from process event data during PCB board production based on board-level traceability primary keys and traceable process chains. When an anomaly is triggered in the process event data, the system expands the association starting from the abnormal PCB board graph node to determine candidate responsibility nodes and generate an anomaly responsibility chain. Then, based on the anomaly responsibility chain, it identifies suspected anomaly sources and generates process control status by combining the graph association relationships between other in-process PCB boards and suspected anomaly sources. Based on this, it executes review or rework insertion and writes the handling results. This upgrades PCB production traceability from linear history query to graph-based responsibility chain positioning, and enables precise release, review, and freeze control based on suspected anomaly sources, thereby improving anomaly traceability efficiency, reducing the risk of excessive interception, and enhancing the closed-loop nature of production process management.