158 results about "Virtual production" patented technology

The present invention discloses a digital production operation management method for data quality assessment and analysis, including: step 1: constructing a multi-level distributed data acquisition system; step 2: designing a multimodal data fusion framework, combining graph neural network and time series data processing technology to realize data fusion and multidimensional analysis; step 3: constructing an intelligent scheduling engine to realize dynamic adaptive scheduling strategy to cope with real-time changes in the production environment; step 4: designing a decentralized self-organizing production network to realize flexible adjustment and optimization of the production process; step 5: realizing the coordinated optimization of product design and equipment maintenance through topology optimization, multi-objective optimization and machine learning algorithms; step 6: constructing a virtual production network to realize real-time monitoring, dynamic prediction and optimization decision support of the production system. Through the present invention, enterprises can break the limitations of traditional production models, improve production efficiency, flexibly respond to changes in market demand, and optimize resource allocation.

The invention discloses an industrial automation control method and system, and relates to the technical field of data processing, and the method comprises the steps: collecting the operation data of production equipment, constructing a digital twin model, and forming a virtual production network; obtaining resource state data of each factory in the virtual production network in real time, dynamically generating an optimal cross-factory scheduling scheme, and simulating the scheduling scheme in the virtual production network for simulation verification and scheme adjustment; and deploying the scheduling scheme to a physical factory, controlling equipment to execute tasks through an automatic control system, and summarizing production data and simulation results for storage and backup. According to the method, the accuracy and efficiency of industrial automation control are remarkably improved, equipment operation data can be processed more efficiently, equipment dynamic behaviors are accurately simulated, a cross-factory optimal scheduling scheme is generated in real time, a closed-loop optimization mechanism is formed through simulation verification and feedback adjustment, the dynamic adaptability and global optimality of the scheduling scheme are achieved, and the scheduling efficiency is improved. Therefore, the resource utilization efficiency is greatly improved.

The invention discloses a modular reconfigurable production line control system integration method, which relates to the technical field of industrial automation, and comprises the following steps: establishing virtual mapping based on physical attribute parameters to form a production line digital twin basic model framework; collecting data in real time based on an on-site sensor, and establishing a digital twinborn dynamic mapping mechanism synchronous with a physical production line state; a reconstruction scheme is imported into a virtual environment, and key performance indexes are analyzed through a production line digital twin model rehearsal module combination process. A virtual production line model is constructed through a digital twin technology, a rehearsal and verification reconstruction scheme in a virtual environment is supported, trial and error time and cost required by traditional physical debugging are remarkably reduced, a reconstruction strategy is further optimized through a cloud AI algorithm, closed-loop optimization from virtual verification to physical execution is achieved in combination with edge end real-time control, and the real-time performance of the virtual production line is improved. The production line can quickly complete local or overall reconstruction according to production requirements, and the response speed and flexibility of the production line are greatly improved.

The invention relates to the technical field of industrial automation and intelligent manufacturing, in particular to a rubber tube production line monitoring method and system.The method comprises the steps that multi-mode production data of a production line is collected and preprocessed, a virtual production line model is generated through a dynamic twin model and compared with actual data, and virtual-real difference data is generated; performing anomaly detection on the virtual-real difference data based on a classification algorithm and a rule matching structure, and optimizing parameters of an anomaly detection model; generating abnormal trend prediction data by using the optimized model, and proposing a system correction suggestion according to the prediction data; and dynamically adjusting the operation parameters of the equipment through a closed-loop feedback mechanism. According to the invention, through innovative dynamic twin modeling, deep learning optimization and closed-loop control technologies, real-time monitoring and intelligent adjustment of the production line are realized, and the production efficiency and the product quality are effectively improved.

The invention relates to the technical field of script execution, and provides a multi-script execution method for a virtual controller, and the method comprises the steps: setting a script structure, a graph model structure and a graph node structure; the method comprises the following steps: performing grammar and semantic check on script data to be executed, converting the script data into a script object according to a script structure, converting the script data into a directed acyclic graph according to a graph model structure, and traversing the directed acyclic graph to obtain an execution sequence of graphs in each level of the directed acyclic graph; and scheduling the script object according to an FIFO algorithm, traversing the directed acyclic graph during scheduling to obtain graph nodes in each execution sequence, and performing interpretive execution on the script object according to an ignition rule and the graph nodes in each execution sequence. The method aims at analyzing and executing various scripts, the reliability of the virtual production line is further improved, and the use cost of the platform is reduced.

The invention discloses a metal formwork production full-process management and control system based on a cloud platform, and relates to the technical field of industrial manufacturing, and the system comprises an industrial cloud platform which is in communication connection with the following modules: a global element perception processing module, an industrial Internet-of-Things terminal used for combined deployment, and a cloud platform module. And multi-source heterogeneous data including equipment state, cutter service life information, material circulation information, personnel operation information and workpiece quality detection data are collected in real time. According to the method, the industrial Internet of Things terminal is deployed, multi-source heterogeneous data such as equipment state, cutter life and material circulation are collected in real time, a virtual production environment synchronized with a physical workshop is constructed in combination with a digital twinning technology, a production scheduling problem is converted into a path planning problem based on an ant colony algorithm, an optimal scheduling scheme is generated in real time, and the scheduling efficiency is improved. The problems that a traditional system is rigid in plan and slow in response are solved, and the flexibility and efficiency of production scheduling are remarkably improved.

The invention discloses a thermal insulation color steel sandwich composite board product quality detection system based on digital twinning, and particularly relates to the field of quality control. The system comprises a composite board full-dimension three-dimensional digital model construction module, a production digital twinborn body creation module, a total-factor real-time data acquisition module, a data preprocessing module, a twinborn data driving and model calibration module, a quality intelligent analysis decision module and an optimization execution module. The model construction module constructs a reference model and embeds a process standard and a quality threshold value; the twin creation module builds a virtual production line, standardizes a data interface and assigns an ID to a plate; the data acquisition module acquires real-time data; the preprocessing module removes abnormal values, standardizes data and associates the data; the calibration module updates the twin body, calculates the deviation and calibrates the model; the analysis module realizes compliance judgment, defect analysis and quality prediction; and the optimization module generates and executes an instruction, so that the problems of low efficiency, data splitting and no closed loop of traditional detection are solved, and the quality control precision and efficiency are improved.

The invention discloses a design method of an automobile panel mold, which relates to the technical field of mold design, and comprises the following steps: applying a load condition and a boundary condition to a three-dimensional model of the mold to obtain a working condition data report, optimizing the three-dimensional model of the mold based on the working condition data report, creating a digital twin model at the same time, and building a virtual production environment. The construction of the virtual production environment enables an engineer to carry out various simulation and debugging operations under the condition of not interfering actual production, discover potential problems in advance and carry out optimization. And more importantly, the real-time monitoring and remote maintenance functions are used, so that the running state of the production line can be mastered at any time, the forming parameters of the mold can be adjusted in time, and the stability and high efficiency of the production process are ensured. Intelligent management of the whole life cycle of the mold is achieved through the digital twinning technology, and the production efficiency and the product quality are remarkably improved.

The embodiment of the invention provides a virtual platform simulation monitoring method and device, and the method comprises the steps: carrying out the signal analysis of a received programmable logic controller signal of an actual production line through a set code analysis model, obtaining a corresponding virtual signal table, building a motion track of a simulation model in simulation software according to the virtual signal table, and carrying out the simulation monitoring of a virtual platform. A simulation event is added to the key control node; outputting a virtual production line model in a 3D model file format, and issuing the virtual production line model and the message queue connection parameters to a webpage end; after a ready state signal of the webpage end is monitored, starting to send position information and state change information of a virtual production line model to a message queue service, so that the webpage end updates a corresponding model position and a model state after receiving the position information and the state change information; according to the invention, the automation and real-time interactivity of simulation monitoring of the virtual platform can be effectively improved.

The invention relates to a digital prototype construction system for three-dimensional weaving preform equipment, the system comprises five different model construction methods and four associated construction methods among models, and the five different models are constructed by physical modeling, data modeling, motion modeling, process modeling and simulation. The four associations among the models are the association of a physical model and data, the association of a motion model, a physical three-dimensional model and a data model, the association of a process model, the motion model and the data model, and the association of a simulation result and the data model. According to the method, a virtual production process twin model is constructed, bidirectional real-time interaction with a physical production process is performed, and dynamic updating of a simulation model is driven by using multi-source data, so that the construction process of a digital prototype is standardized, real-time monitoring of the production process is realized, the utilization rate of data is improved, and closed-loop feedback and process optimization are realized.

In one aspect, a method includes determining, from among a plurality of resource processing nodes in a game scene, a downstream resource processing node corresponding to at least one resource processing node, an input resource of the corresponding downstream resource processing node being an output resource of the at least one resource processing node; respectively connecting the at least one resource processing node and the corresponding downstream resource processing node to generate a virtual production line between the at least one resource processing node and the corresponding downstream resource processing node; and displaying the virtual production line on a graphical user interface.

The invention discloses a training method, device, equipment and product for mine virtual production line simulation training, and relates to the technical field of skill talents, the method is applied to a digital mine training system, the digital mine training system comprises a data acquisition controller, a data processing module and a data processing module, the method comprises the following steps: receiving a training starting instruction of a user; responding to the training starting instruction through the data acquisition controller, and providing a digital mine training task for the user; and acquiring operation information when the user executes the digital mine training task, and evaluating the operation information in real time through a preset evaluation model to obtain an evaluation result. Therefore, the problems that the safety problem exists when the to-be-on-duty personnel are trained through a physical mine, and the training effect is poor due to the fact that no systematic score exists are solved, and the training effect is improved.

The invention discloses a production line variant scheme obtaining method for upgrading and updating of complex mechanical and electrical products. The method comprises the steps that production line parameters are obtained; constructing a complex mechanical and electrical product production line variant design platform and a digital twin platform; constructing a production line parameter association network; determining the upgrading type of the complex mechanical and electrical product; mapping the complex mechanical and electrical product upgrading knowledge to a production line parameter association network to analyze a production line parameter change starting point; the production line parameter change starting point is input into a complex mechanical and electrical product production line variant design platform, and a production line variant scheme is output; and performing virtual transformation on the complex mechanical and electrical product production line according to the production line transformation scheme in the digital twin platform, and evaluating whether the transformed virtual production line of the complex mechanical and electrical product meets the production requirements of the product, and if not, adjusting the parameter change starting point of the production line. The problem that the production line adjustment efficiency is low due to the fact that an existing production line variant scheme design method mainly depends on experience of designers and lacks systematic and standardized process support is solved.

The invention discloses an artificial intelligence-based higher engineering college engineering practical training production line courseware teaching system and method, and aims to solve the problems of equipment updating lag, poor teaching adaptability, virtual and real environment separation, evaluation feedback lag and the like existing in a traditional practical training system, a configurable virtual production line three-dimensional model is constructed through a production line digital modeling module; teaching content is dynamically optimized based on a knowledge graph by combining an intelligent courseware generation module; the student behavior analysis module integrates eye movement tracking, operation track recording and a physiological signal monitoring unit to realize multi-modal data acquisition; the virtual-real cooperative control module establishes bidirectional interaction between real equipment and a virtual terminal through a data mapping and synchronous calibration technology; and the dynamic evaluation feedback module adopts a reinforcement learning algorithm to generate a three-dimensional visual evaluation report and adjusts a teaching strategy in real time.

The present technology relates to a video displaying apparatus, a video processing system, and a video processing method by which the estimation accuracy of a position posture of a camera that shoots a video to be displayed as the background is improved. A virtual production system estimates a position posture of a camera, with use of distance measurement data acquired from a sensor. The camera shoots a video to be displayed on a video displaying unit on a background. The video displaying unit includes a plurality of pixels in each of which a light source is arranged, and absorbs light of a predetermined wavelength at a light absorbing region that is at least part of a region, other than the light source, of a light absorbing pixel that is at least part of the plurality of pixels. Then, the virtual production system generates, on the basis of a result of the estimation of the position posture, video data that associates the position of the camera in a shooting space and the position of the camera in the video with each other, and outputs the generated video data to the video displaying unit. The present technology can be applied to a virtual production system.

The embodiment of the invention provides a multi-scale digital twin system of a combustion explosive production line. Comprising the steps that a digital twin data layer represents the manufacturing process and dynamic evolution of a combustion explosive production line through production line geometric model data, production line physical model data, production line behavior model data and production line rule model data of the combustion explosive; the digital twinning communication unit is used for realizing data interaction between the digital twinning virtual production line and the physical production line and data interaction between different intelligent agents in the digital twinning analysis layer; the digital twinning analysis layer is used for completing collaborative analysis of models in the multi-scale digital twinning analysis layer by adopting a multi-agent deep reinforcement learning technology; and the digital twinning application layer is used for realizing multi-scale digital twinning application. According to the method, analysis and decision making are carried out by combining the high-risk characteristics of the combustion explosive production line and calculation of the equipment operation state and the safety risk state, and the characterization and prediction capability of the safety risk of the combustion explosive production line is improved.

The invention provides a railway vehicle production line digital twin system and method, and the system comprises a physical space layer which is used for obtaining the state information of a railway vehicle physical production line in real time; the information layer is used for performing information conversion and analysis on the state information of the railway vehicle physical production line to obtain processed railway vehicle production line information; and the virtual space layer is used for updating the railway vehicle virtual production line model based on the processed railway vehicle production line information, so that the railway vehicle virtual production line model corresponds to the railway vehicle physical production line. Through the digital twinning technology, digital transformation of the railway vehicle manufacturing industry is promoted, the production efficiency is improved, quality control is optimized, the maintenance cost is reduced, and the production flexibility is enhanced.

The intelligent production cooperative control system of the slow-release fertilizer comprises a data acquisition module which acquires multi-source production data signals from batching, granulation, coating and drying sections in real time, and the multi-source production data signals at least comprise raw material ratio and material temperature; the intelligent optimization module receives the multi-source production data signal and releases a target based on a preset nutrient; the production execution control module receives the cooperative control instruction signal and generates a process control signal according to the cooperative control instruction signal; the digital twin module is respectively connected with the data acquisition module and the intelligent optimization module, receives the multi-source production data signal to update the state of the virtual production model, and provides an analog simulation and prediction feedback signal for the intelligent optimization module; the quality tracking module is connected with the data acquisition module and the production execution control module, and receives a multi-source production data signal and a process control signal. The slow release fertilizer intelligent production cooperative control system can solve the problems that slow release fertilizer production quality is not stable, energy consumption is high, and cooperative optimization cannot be achieved.

The invention provides a textile flexible production line multi-material scheduling system, which comprises a physical execution layer and a multi-material scheduling layer, wherein the physical execution layer comprises reconfigurable textile production equipment; the intelligent sensing layer is arranged at key nodes of the physical execution layer; the central scheduling and control layer is in communication connection with the physical execution layer and the intelligent sensing layer; and the digital twin layer is a virtual mapping of the physical execution layer in an information space, and forms a closed loop with the central scheduling and control layer and the physical execution layer. According to the method, the perspectiveness and the global optimization capability of a scheduling decision are realized through a digital twinning technology, the system places an initial production scheduling scheme in a high-fidelity virtual production line model for millisecond-level concurrent simulation deduction, and potential process bottlenecks and quality risks during blending production of different materials are accurately predicted; and by taking the production efficiency, the energy consumption and the quality qualification rate as multi-target reward functions, completing iterative optimization of massive strategies in a virtual space, thereby obtaining an approximately globally optimal scheduling instruction before the physical production is put into use.

Systems, apparatus, and methods of rendering content based on a control point of a camera device are disclosed. In an example, a marker is attached to the camera device and its pose is tracked over time. Based on a camera model of the camera device, an offset between the marker and the control point is determined. The tracked pose of the marker can be translated and / or rotated according to the offset to estimate a pose of the control point. The rendering of the content is adjusted over time based on the estimated poses of the control point. Upon presentation of the content in a real-world space (e.g., on a display assembly located therein), the camera device can capture the content along with other objects of the real-world space and generate a video stream thereof.

The invention relates to the technical field of virtual simulation control, in particular to a Factory IO-based metal sorting control system, which comprises a virtual production line construction module, a hardware configuration module, a joint debugging module, a task execution module and a process optimization module. According to the invention, through comprehensive analysis of operation characteristics of the conveyor belt, distribution of detection stations and signal fluctuation, signal characteristics in a material coverage area can be identified in advance, associated extraction and dynamic cooperative adjustment of equipment layout and operation parameters are realized, and through interactive identification of equipment positions, adjustable areas and trigger conditions, the accuracy of the equipment layout is improved. Adjusting points influencing sorting precision are accurately positioned, task loads and priorities are intelligently matched in task execution, efficient allocation and resource optimization of scheduling areas are achieved, scheduling paths and time intervals are dynamically evaluated on the flow level, a continuous and adjustable operation sequence is formed, and sorting efficiency and overall operation performance are improved.

The invention provides a method and a system for calculating the processing cost of a metal product under a circulating production process. The method comprises the following steps: setting a virtual productive cost center; setting a production auxiliary cost center; tracking and collecting actual production performance formed by processing the product by the production auxiliary cost center; according to the actual production, the workload of the processed product is calculated; according to the workload, calculating the calculation weight in the processing cost generated in the production auxiliary cost center, and sharing the cost to the product; and summarizing the cost according to the cost project, and recording the cost to a virtual productive cost center. According to the method, the cost composition of the product can reflect the actual manufacturing process more accurately, the problem of tracking and statistics of related elements of product cost change in the circulating production process is simplified, and the problem that the machining cost of a unit in the circulating production cannot reflect the actual machining condition of the product on the unit practically is solved.

The invention discloses a measurement production virtual interaction method and system based on a three-dimensional industrial simulation technology, and relates to the technical field of virtual reality, and the method comprises the steps: collecting the data of a production site in real time, and integrating the collected data to a three-dimensional simulation platform through a data interface, according to the actual layout of a production site and the shape of equipment, a three-dimensional modeling technology is used for simulation, production operation data is mapped to corresponding attributes of a three-dimensional model, construction of a virtual production site environment and dynamic operation display of the equipment are carried out in a simulation platform, and automatic control and optimal scheduling of the equipment are carried out according to an algorithm. And setting an equipment operation state monitoring threshold value, performing early warning, and performing optimization adjustment on the production plan and the equipment maintenance plan. According to the invention, production field data is collected in real time, simulation is carried out by using a three-dimensional modeling technology, and automatic control and an optimization scheduling algorithm are combined, so that high efficiency, accuracy and intelligentization of virtual interaction are realized, and the management level and production efficiency of metering production are improved.

The invention discloses an automobile production line detection system based on digital twinning, and the system comprises a program connection module which is used for recognizing a program operator through a container form or network connection, and receiving and distributing a program sequence used by a production line; the vehicle registration module is used for connecting a to-be-tested vehicle through a network protocol, performing vehicle registration and generating digital twin of the vehicle; the production line station module is used for calculating and mapping the number of stations, station identifiers and station lengths of a production line according to the input data of the line body, creating to form digital stations, acquiring assembly line numbers or vehicle identification codes of vehicles on the stations of the line body by docking production line control information, and sending the assembly line numbers or the vehicle identification codes to the production line station module; mapping the virtual production line and the production line control information to generate digital station twinning of a production line physical entity; and finally, visually displaying the operation state of the digital production line. The invention also discloses an automobile production line detection method based on digital twinning. According to the invention, accurate mapping of all production links is realized.

An embodiment of the present invention provides a multi-scale digital twin system for a combustible explosive production line, comprising: a digital twin data layer that characterizes the manufacturing process and its dynamic evolution of the combustible explosive production line through geometric model data, physical model data, behavioral model data, and rule model data of the combustible explosive production line; a digital twin communication unit that enables data interaction between the digital twin virtual production line and the physical production line, as well as data interaction between different agents in the digital twin analysis layer; a digital twin analysis layer that uses multi-agent deep reinforcement learning technology to complete collaborative analysis of models in the multi-scale digital twin analysis layer; and a digital twin application layer that implements multi-scale digital twin applications. The present invention combines the high-risk characteristics of combustible explosive production lines with the calculation of equipment operating status and safety risk status for analysis and decision-making, thereby improving the ability to characterize and predict safety risks of combustible explosive production lines.

The invention discloses a method for optimizing micro saw blade production by using a genetic algorithm. The method comprises the following steps: S1, establishing a virtual simulation environment; s2, parameter optimization is carried out in the virtual simulation environment, and a plurality of virtual production schemes are generated; s3, selecting an optimal scheme through high-dimensional topology hypersurface mapping and an asymmetric singular value perturbation technology; s4, applying the optimal scheme to actual production, and analyzing monitoring data by using a Schrodinger-Newman geometric gravitational field exceeding method; s5, when the deviation exceeds a preset threshold value, triggering a self-repairing mechanism, and performing optimization iteration again; s6, actual production parameters are adjusted based on the repairing scheme; s7, updating the digital twinborn model in real time to reflect the latest production condition; s8, analyzing historical data in combination with a machine learning algorithm, and optimizing future production parameter setting; and S9, circularly executing the steps S4 to S8 to achieve the production optimization target, the precision of the micro saw blade production process is improved, and continuous optimization and stability of the production quality are ensured.

The invention provides a multi-source data fusion industrial energy-saving management system based on big data, and the system comprises a data collection and edge processing module which is used for collecting on-site multi-source heterogeneous data in parallel and executing filtering and time calibration; the industrial big data storage center is used for storing data by adopting a cold and hot data layered architecture; the spatio-temporal data deep fusion engine is configured to be used for constructing a virtual production takt axis, mapping a continuous energy consumption waveform to the axis by using a nonlinear time warping algorithm, eliminating time lag interference and generating a standard energy consumption fingerprint in combination with a thermal response model; the dynamic energy-saving decision control module is used for calculating a transient energy consumption balance index covering recovery compensation and life loss based on the fingerprint vector, and generating a control instruction when an energy-saving gain threshold value is met; and the terminal execution feedback module is used for instruction issuing and feedback. According to the method, the problem of spatial-temporal dislocation of discrete work orders and continuous energy consumption data is solved, and refined dynamic energy-saving control of equipment is realized.

The invention discloses an automatic program adaptation method and system for a multi-vehicle-type manufacturing process, electronic equipment and a storage medium, and the method comprises the steps that a group control server receives a production instruction, and the production instruction comprises a VIN code, a vehicle type code and an electric gun code of a vehicle; the group control server stores the production instruction in a queue form to obtain a virtual production queue; when the vehicle arrives at the entrance of the unmanned island, the group control server receives the trigger request signal, obtains a production instruction corresponding to the vehicle from the virtual production queue, and sends the obtained production instruction to the unmanned island; after the unmanned island receives the information, verification is successful, the unmanned island sends a command to the robot controller according to the vehicle type code, and a matched track program is called; and the unmanned island sends a command to the tightening controller according to the electric gun code and calls a matched tightening parameter program. The group control server pushes the VIN, the vehicle type and the electric gun code to the unmanned island, and double-automatic matching of a track program and a tightening program is completed in the same beat.

The application discloses a virtual production-based equipment monitoring method and device, equipment, medium and product, and relates to the technical field of virtual production. The method comprises the following steps: acquiring running state data and running video data corresponding to a plurality of hardware devices respectively; matching the running state data of the hardware devices with monitoring indexes of the device types corresponding to the hardware devices, displaying the matching results between the running state data of the hardware devices and the monitoring indexes; displaying video pictures corresponding to the running video data of the hardware devices; and performing data statistical analysis on the running performance data of the hardware devices, and displaying the statistical analysis results of the running performance data in the form of a chart. The method realizes the automation of data detection of each device in the shooting field of virtual production in the hardware aspect, improves the monitoring efficiency of the hardware devices in the shooting field of virtual production, and reduces the workload of the on-site staff.

Systems, apparatus, and methods for rendering content based on production element pose are disclosed. In an example, motion capture data of a production element is received, the production element moving from a first physical pose to a second physical pose. The motion capture data is processed to determine the coordinates of the second physical pose. A transformation of the second physical pose of the production element to a virtual pose of the production element is generated. A virtual model of the production element is updated, the virtual model comprising the virtual pose of the production element. The content is rendered based on the updated virtual model.