32 results about "Production analysis" patented technology

The invention discloses a concrete production management system and method, and belongs to the technical field of concrete production. The method comprises the following steps: 1, preliminarily analyzing raw materials; step 2, production analysis; and step 3, quality detection. Therefore, errors of manual judgment are reduced, the raw materials entering the production link meet the standard, production delay and cost increase caused by raw material problems are avoided, and the risk of production accidents caused by the fact that raw material abnormity is not treated in time is reduced. According to the method, the construction proportion model of the concrete is established, the construction proportion performance index of each abnormal production task process of the concrete is evaluated, and the construction proportion is adjusted, so that the quality stability of the concrete is effectively improved, the quality problem is solved, the performance of the concrete is optimized, and the requirements of different construction scenes are met; meanwhile, data experience is accumulated by establishing a model, and data support is provided for subsequent production.

A computer-implemented method for automated decline curve and production analysis using automated production segmentation, empirical modeling, and artificial intelligence. The method includes segmenting historical production data based on a change in a central tendency of a selected segmentation parameter to generate segmented production data. The method also includes forecasting future production data from a last production segment to a terminal decline rate according to a fitted empirical model, a trained artificial intelligence model, or any combinations thereof. The method includes forecasting exponential production data to an economic limit. Further, the method includes calculating an estimated ultimate recovery by summing the historical production data, future production data, and the exponential production data.

The invention relates to the technical field of copper alloys, and particularly discloses a preparation system of a copper-chromium-zirconium alloy wire for a high-speed rail, which is used for solving the problems of boiling boundary phase locking, rewetting blocking and cooling speed banding, induction of spiral hot spots, performance discretization and monitoring misjudgment in the existing production process of the copper-chromium-zirconium alloy wire. The system comprises a production processing module, a sensing module, a spraying topology module, a phase analysis module, a boundary analysis module and a production analysis module. Through uniform time base of a partition setting table, a phase coherence characteristic table and a hydrothermal boundary characteristic table and partition fineness regulation and control driven by quantitative indexes, cooling banding caused by phase locking and rewetting blocking is inhibited, spiral hot spots and parameter discreteness are reduced, a cross-partition time sequence and a set boundary are unified, set convergence and switching consistency are improved, and the method is suitable for large-scale popularization and application. Misjudgment of low-frequency pseudo fluctuation monitoring is reduced, and control vectors are optimized in combination with performance specifications of the high-speed rail overhead line system.

This invention discloses a visualized intelligent scheduling system for SMT production lines, relating to the field of precision electronics. It solves the problem of poor scheduling performance in existing intelligent scheduling systems for production lines. The system includes a data acquisition module: analyzing production demand for target orders to be executed, obtaining the quantity of products in the target order, performing historical production quantitative analysis on the production line executing the order based on the quantity of products in the target order, and acquiring production line scheduling data based on the analysis results; a production line matching module: matching production lines for target orders to be executed, obtaining target-suitable production lines; a production analysis module: monitoring the production of sample production units included in the target-suitable production line, obtaining the overall efficiency of the unit equipment based on the monitoring results, and obtaining production scheduling analysis data; and a production scheduling module: performing real-time production scheduling for the product production units on the target-suitable production line. This invention can improve the scheduling efficiency of intelligent scheduling systems for production lines.

The invention relates to the field of shale gas well yield analysis, and particularly discloses a shale gas well yield linear and nonlinear hybrid automatic classification and prediction method, which comprises the following steps of: selecting geological and engineering factors as characteristic variables, establishing a linear and nonlinear hybrid model, and determining an influence relationship of each variable by minimizing a fitting error; unsupervised automatic classification is carried out on the samples until the number of residual samples is insufficient; and calculating the minimum value of the distance from the prediction sample to each classification, and predicting the yield according to the classification rule. According to the method, unsupervised automatic classification is realized, the prediction problem of unknown classification is solved, the yield prediction precision is improved, the geological complexity is fit, and the method can be expanded and applied.

The invention relates to an AI management and control method and system based on multi-source heterogeneous data analysis. The method comprises the following steps: performing cleaning and format standardization processing on multi-source heterogeneous data in a production full link; performing feature extraction on the standardized data, and extracting an equipment operation feature vector and a production efficiency feature vector related to a production state; inputting the feature vectors into a production analysis model based on machine learning for fusion analysis, and generating a production state evaluation result; performing optimization decision processing according to the production state evaluation result and the real-time production plan to obtain a production adjustment instruction; finally, generating a control command according to the production adjustment instruction and sending the control command to a production execution system; according to the scheme, intelligent control of the production process can be realized, so that the production efficiency and the product quality are effectively improved.

The present application relates to the technical field of pressure sensitive adhesive production monitoring, and particularly relates to a pressure sensitive adhesive online production analysis method and system based on data monitoring. The method comprises the following steps: deploying a coating data monitoring network on a coating production line; synchronously obtaining coating real-time monitoring data containing coating thickness data and coating pressure data online through the coating data monitoring network; performing horizontal and vertical decoupling analysis and pressure disturbance feature based on the coating thickness data in the coating real-time monitoring data, then determining the defect source type, and generating corresponding vertical control instructions, horizontal control instructions or step-by-step cooperative control instructions according to the defect source type, so as to realize real-time automatic control of the horizontal and vertical thickness of the wide-width pressure sensitive adhesive coating. The present application realizes accurate determination of the defect source through online correlation diagnosis of the coating thickness and process pressure data, so as to complete real-time regulation of the horizontal and vertical thickness.

The invention discloses an unconventional oil reservoir oil well development problem analysis method and device, and relates to the technical field of oil-gas field development, and the method comprises the steps: obtaining basic parameter data and fracturing construction parameter data of an unconventional oil reservoir oil well development process; determining a production analysis curve; determining the end time of the crack linear flow stage; the effective artificial fracture half length is determined; determining a well control radius; the reservoir permeability within the well control range is determined; simulating an oil well development model; determining simulation basic parameter data; determining a simulated production analysis curve according to the simulated basic parameter data; according to the production analysis curve and the simulated production analysis curve, the oil well development effect is analyzed, and an analysis result is determined. According to the method, the oil well development problem can be comprehensively, accurately and dynamically analyzed through the production data, whether the oil well production dynamic state is reasonable or not is analyzed, the input cost of problem analysis is reduced, and the oil well recovery rate can be effectively improved.

The invention provides a real-time data analysis method for an aluminum shell stamping production line, and belongs to the technical field of production analysis, and the method comprises the steps: capturing the current flow velocity of a material from a convex die fillet through optical flow velocity detection, synchronously collecting stress distribution, and obtaining the wall thickness of a flange region and the flow resistance at a draw bead; a yield strength real-time value and a male die fillet radius set value are extracted in combination with a material database, and a flow state data set is obtained through integration; according to the wall thickness of the flange area in the flow state data set and the flow resistance at the draw bead, the material accumulation amount is evaluated, the yield strength real-time value is fused to adjust the accumulation evaluation weight, and the accumulation state of the flange area is recognized; determining a coordinate range and a risk level identifier of the tension fracture risk area; whether the area proportion of the risk area exceeds an allowable limit value or not is judged through comparative analysis of the coordinate range of the tension crack risk area and a preset forming safety threshold value, and therefore it is determined that the overall forming state is overrun forming or safe forming.

The invention relates to the field of edge data transmission, in particular to a data processing system and method based on big data, and the system comprises a node monitoring module which is used for determining whether to carry out node processing analysis for each edge processing node or not according to a transmission fluctuation index and a supervision fluctuation index; the analysis and evaluation module is used for determining a processing and analysis mode according to the execution interference index and the execution duration index; the production analysis module is used for determining a change analysis strategy according to the branch change generalization coefficient and determining whether each initial analysis node is in a third node risk state or not according to the change reference interference parameter; the interference analysis module is used for determining a data redundancy coefficient according to the estimated key proportion index and the topological estimated key index; and the execution optimization module is used for determining whether to perform dynamic execution analysis on the execution analysis node according to the node execution duration coefficient. According to the invention, the transmission efficiency of big data real-time transmission in the industrial production process is improved.

The invention discloses a data processing method and device, computer equipment, a computer product and a storage medium. The method comprises the following steps: receiving M financial feature data of M data parties; wherein the financial feature data is obtained by desensitizing feature data related to financial activities of the target object; then, based on the M pieces of financial feature data, determining a financial black production analysis result; the financial black property analysis result corresponds to a financial black property analysis task participated by the M data parties, the financial black property analysis result is used for representing whether the financial activity of the target object has the risk of financial black property or not, and the financial black property analysis result is based on the financial black property feature data. Processing the financial black production analysis task through a multi-party security computing method; according to the embodiment of the invention, the financial black production analysis result is determined through multi-party security calculation, so that the financial black production analysis is more accurate while the security of the data in the data processing process is ensured.

The quality of natural products such as beer, bread, wine, etc. is determined by many parameters: process parameters that may or may not be changed, external parameters, and parameters of the raw materials. With complex processes and many process steps, it is very difficult to relate the parameters to the quality, if possible. Data on process control, values ​​of product and process related parameters, as well as values ​​that can be interpreted as indicators of quality, substances and their amounts found in the product (either final or intermediate), other parameters, or a combination thereof. Between the values ​​obtained for the parameters, relationships can be determined that can be used for process optimization. This can be performed for one or more process steps, one or more parameters in the process, and one or more quality parameters.

An integrated autonomous operation system that holistically renders the operation in digital form at multiple scales, including reservoir, surface infrastructure, workflows, processes, and the real asset. The system provides an end-to-end digital twin connecting subsurface to production. A subsurface model identifies and monitors water-producing zones for strategic decisions. The models use intelligent Al to provide optimum water injection setpoints. The models provide data to systems that automatically control the chokes and valves to meet the setpoints, thus achieving fully integrated, autonomous operations.

The application relates to the field of visual monitoring, in particular to an intelligent welding system based on machine vision, which comprises a production analysis module used for determining a production line monitoring strategy; a node monitoring module used for determining an interference analysis mode in response to an analysis setting condition; an interference analysis module used for determining a node adjustment strategy based on an abnormal reflection parameter and an abnormal reflection distribution index in response to a reflection analysis condition, and determining whether to adjust a light source distribution index based on the abnormal reflection parameter and an edge abnormal parameter in response to a quality analysis condition; a monitoring evaluation module used for determining whether to update a monitoring parameter for a monitoring execution node in response to a difference analysis condition; and a difference compensation module connected with the monitoring evaluation module and used for determining a difference compensation mode corresponding to each difference analysis node in response to a compensation setting condition. The application improves the accuracy of quality inspection results of target welding pieces.

The invention provides an enterprise production data analysis system based on multi-dimensional data acquisition, and the system comprises a multi-dimensional data acquisition module which is used for obtaining mechanical operation total factor data in real time; the data preprocessing module is connected with the multi-dimensional data acquisition module and is used for carrying out standardization processing on the acquired data; and the real-time data transmission link is connected with the data preprocessing module and is used for guaranteeing instant transmission of the processed data. By means of the technical scheme, the problems that in the prior art, the data dimension is single, the real-time performance is insufficient, and the analysis model is rigid can be effectively solved. The technical problem mainly refers to limitation of an existing system in production analysis. According to the method, multi-dimensional data are integrated, and a real-time data processing technology and a dynamic analysis model are adopted, so that the technical problems are solved, and more comprehensive, real-time and accurate production data analysis is realized.

This invention discloses a cloud-based concrete production analysis system. Based on big data on raw material usage for concrete strength grades, this system addresses issues such as untimely monitoring, incomplete monitoring information, and inaccurate problem responses in existing concrete production systems. The system specifically includes: a data acquisition unit, a cloud storage unit, a mixing data analysis unit, a concrete quality analysis unit, an early warning release unit, and a production display terminal. This method uses a cloud platform to store, integrate, calculate, analyze, and visualize concrete mixing information, reducing the manpower input cost for concrete mixing management, providing real-time responses to production exceeding standards and quality issues, and improving the risk control of concrete product quality problems, the intensity of production process monitoring, and management efficiency.

This application relates to the field of smart agriculture, providing a method and system for constructing an agricultural information platform for smart agriculture. The method includes: collecting multi-source heterogeneous agricultural data from agricultural IoT devices, remote sensing data sources, and agricultural production management systems to generate a standardized agricultural dataset; constructing a spatiotemporal dual-dimensional fusion agricultural data centralized storage system based on the standardized agricultural dataset, classifying, storing, and uniformly managing the data; performing agricultural production analysis, resource utilization analysis, and environmental change analysis on the standardized agricultural dataset to generate comprehensive analysis results; forming a modular agricultural information platform based on the comprehensive analysis results using a microservice-based decomposition approach; and using user profile-driven dynamic analysis of the comprehensive analysis results to update and display agricultural production management information, planting guidance information, risk warning information, and data service information to users, thereby improving the intelligence, precision, and collaboration of agricultural production management.

This invention discloses a low-temperature curing method and system for heterojunction solar cells, relating to the field of solar cell technology. The system includes a production monitoring module, a controller, a product testing module, a safety assessment module, and a personnel allocation module. The production monitoring module collects internal environmental data from the production equipment and sends this data to a production analysis module. The production analysis module performs a safety analysis on the received internal environmental data using a safety assessment model to determine whether adjustments to the internal environment of the production equipment are necessary to ensure the consistency of the curing environment for the heterojunction solar cells. The personnel allocation module allocates personnel to the production equipment based on the curing records of workers performing the low-temperature curing process, selecting the worker with the smallest curing deviation as the operator for that equipment. This avoids situations where employees are unfamiliar with the operation, reduces the generation of defective products, and thus improves production efficiency.

In at least one example, a method for production analysis modeling for product quality detection includes receiving an audit request for a product that includes an identified failure; identifying production analysis data associated with a production process for the product, the production analysis data including data captured during production of the product; providing the production analysis data for the product to a machine learning model used to produce the product to compare the production analysis data to a specified range of data for the product; determining data from the production analysis data that is outside of the specified range identified by the machine learning model; and identifying a cause of the identified failure during production of the product based on the determined data.

The application discloses a method for depicting remaining gas distribution based on post-pressure fracture network iterative fitting technology, and relates to the field of shale gas development.The method fully considers geological data of gas wells in a well area, well structure, fracturing construction, microseismic monitoring, gas production profile, gas well production data and fracturing interference data, uses unstable production analysis, geological modeling and numerical simulation and other methods, iteratively implements gas well reserve production conditions, depicts remaining gas distribution, is suitable for remaining gas distribution research of various types of shale gas reservoirs at home and abroad, can guide shale gas development adjustment well deployment and development technical policy making, significantly improves block recovery and gas field development benefit, and has wide popularization prospect.

The invention provides a station robot dispatching method and system, and the method comprises the steps: analyzing stations related in an industrial production and manufacturing process, determining an initial dispatching station, and determining a dispatching scheme; configuring the robot according to the dispatching scheme to obtain a station robot; a station robot is dispatched to a station for station task operation, and meanwhile, the industrial production and manufacturing process is monitored to obtain production monitoring information; performing production analysis according to the production monitoring information to judge whether a station robot needs to be adjusted to obtain an analysis and judgment result; and when the station robot needs to be adjusted, determining an adjustment target station and an adjustment target station robot, performing scheduling configuration according to the adjustment target station to determine scheduling information, performing configuration updating on the adjustment target station robot by using the scheduling information, and performing new station task operation. According to the station requirement in the industrial production and manufacturing process, the dispatching of the station robots is changed in a short time, and the dispatching flexibility of the station robots is improved.

The invention relates to the technical field of angle measurement, in particular to a sheet metal part angle measurement glove and system, and the sheet metal part angle measurement glove comprises a glove body, an angle sensing system, a data processing unit and a man-machine interaction unit. According to the sheet metal part angle measuring glove and system, by means of the flexibility of a human hand, the sheet metal part angle measuring glove and system can easily enter a narrow and complex space for measurement, the access problem of a traditional rigid measuring tool is solved, and extremely high flexibility is achieved; the operation is just like hand touch, so that the steps of repeatedly adjusting and observing the measuring tool are omitted, the detection efficiency is greatly improved, the measurement is rapid and visual, and the requirement on the proficiency of an operator is reduced; a high-linearity flexible angle sensor and a digital calibration technology are adopted, so that the parallax error of human eye reading is eliminated, and the measurement precision is high; and the measurement result can be digitally stored, wirelessly transmitted and traced, so that the quality management and the production analysis are facilitated, and the system is seamlessly integrated in a digital manufacturing system.

The application discloses an intelligent management and control system based on a large model and integrated multi-dimensional space-time data fusion, and belongs to the fields of artificial intelligence and engineering application. The system comprises a space-time large model base, an engineering object three-dimensional or four-dimensional integrated model, an intelligent agent cooperation module and an autonomous analysis, decision and control module. Based on embedding engineering field knowledge class public domain data into a large model, a space-time large model base is formed, engineering object three-dimensional or four-dimensional geometric and attribute data, monitoring and monitoring and equipment automation and other dynamic business data are fused, an integrated expression, storage and management private domain data source is constructed, autonomous analysis and decision are made by using the reasoning capability of the space-time large model, intelligent agent cooperation is dispatched to complete task planning arrangement, safety production analysis and decision support and management and control, and various engineering graphic and text reports are automatically generated. The application can solve the intelligent management and control problems in the fields of mines, factories, traffic, water conservancy, buildings and machinery, and significantly improves the practicability of the artificial intelligence system in the engineering field.

The invention relates to a multi-element coupling type surface flood full-process dynamic simulation analysis method, and belongs to the technical field of urban flood prevention and hydrological simulation. The method comprises the following steps: S1, analyzing regional topographic features; s2, analyzing space-time transfer of the earth surface cover; s3, water catchment area runoff production analysis; and S4, node flooding analysis. According to the method, deep fusion of terrain and cover data and coupling simulation of the runoff production-confluence process are realized, the problems of data splitting, simulation disjunction, fuzzy cause diagnosis and the like of a traditional method are solved, the model verification goodness of fit is high, the universality is high, the application value is high, and urban flood control and drainage planning, waterlogging emergency response and sponge city construction can be effectively supported.

The invention relates to the field of machining management, in particular to a machining process optimization and operation management system and method based on an integrated system, and the system comprises an integrated machining module, a workpiece positioning module, a production analysis module, a process scheduling module and an operation feedback module. The work piece positioning module is used for acquiring a work piece surface model and evaluating the completion rate, the production analysis module is used for generating a scheduling scheme, the process scheduling module is used for selecting the scheduling scheme, and the operation feedback module is used for checking the actual completion rate of the work piece and adjusting the scheduling scheme. And the processing sequence is reasonably distributed, so that the production cycle is shortened, the overall production efficiency is improved, the production state is predicted, a more reasonable production plan is selected, the product production is ensured to meet the requirements, and a more efficient, more flexible and more sustainable production operation process is realized.

This invention discloses a safety production analysis method oriented towards multimodal data and causal knowledge graphs, belonging to the field of industrial safety production monitoring and intelligent analysis technology. The method comprises the following steps: S1. Conducting multimodal sensing and acquisition with spatiotemporal synchronous preprocessing to output a standardized multimodal data stream; S2. Performing cross-modal self-supervised pre-training based on the results of S1 to obtain a pre-trained basic model; S3. Using a three-layer federated architecture combined with privacy protection, collaboratively training the pre-trained basic model to generate an aggregated and optimized global model; S4. Constructing and dynamically updating an industrial safety causal knowledge graph, combining it with the global model for causal reasoning, and outputting risk assessment results; S5. Calculating and classifying a comprehensive risk value based on the results of S4, matching and executing response strategies; S6. Collecting feedback data from risk responses to complete closed-loop self-optimization. Using this method, accurate early warning of industrial safety can be achieved, ensuring data security, reducing annotation costs, and enhancing system adaptability.

The invention relates to the technical field of pressure-sensitive adhesive production monitoring, in particular to a pressure-sensitive adhesive online production analysis method and system based on data monitoring. The method comprises the following steps: deploying a coating data monitoring network on a coating production line; coating real-time monitoring data including coating thickness data and coating pressure data are synchronously obtained on line through a coating data monitoring network; the method comprises the following steps of: performing transverse and longitudinal decoupling analysis and pressure disturbance characteristics on the basis of coating thickness data in coating real-time monitoring data, then judging the type of a defect source, and generating a corresponding longitudinal regulation and control instruction, a transverse regulation and control instruction or a step-by-step coordinated regulation and control instruction according to the type of the defect source; therefore, real-time automatic control of the transverse and longitudinal thicknesses of the wide pressure-sensitive adhesive coating is realized. According to the method, accurate judgment of a defect source is realized through online correlation diagnosis of the coating thickness and the process pressure data, so that real-time regulation and control of transverse and longitudinal thicknesses are completed.

The application provides a sea-sky integrated safe production method, comprising the following steps: collecting a sea operation environment to obtain sea operation environment data; transmitting the sea operation environment data through a sea-land-sky-ground integrated basic network; performing sea virtual modeling on the sea operation environment data to obtain a sea environment model; introducing production factors into the sea environment model to perform production analysis and obtain a production scheme; and adjusting and controlling production equipment according to the production scheme to complete a production process. The application provides a sea-sky integrated safe production method, an offshore oil and gas exploration production public service platform based on an industrial internet, accelerates the layout of the industrial internet in irregular and complex production environments generated under field or offshore conditions, builds a new ecology of digitally driven offshore oil and gas exploration production, and meets the requirements of lean and safe production.

The invention discloses a digital management system and method for large commodity enterprises in the clothing industry, and relates to the technical field of clothing supply chain management. Comprising a data acquisition module, an enterprise analysis module, a production analysis module, a matching and screening module, a scheme generation module and an adjustment and correction module, data of industry chain enterprises of the clothing industry are production and operation data, management data and market feedback data of the enterprises in recent N years, and the technical key points are as follows: the production and operation data, the management data and the market feedback data of existing clothing production enterprises and clothing conveying enterprises are comprehensively analyzed; according to the method, the comprehensive evaluation value for reference of the costume design enterprise is generated, so that the costume design enterprise can quickly know the conditions of related enterprises, cooperative enterprises can be screened more reasonably, the use effect is good, and the method has a good use prospect.

1. Name of the product in this design: Graphical User Interface for Industrial Furnace Production Data Analysis System for Electronic Equipment (Roller Hearth Furnace IV). 2. Intended use of this design: for use in an electronic device. 3. The key design features of this product are the interface content in the graphical user interface. 4. The image or photo that best illustrates the design points: Interface change state diagram 2. 5. Due to the conventional design of electronic devices, other views are omitted. 6. Purpose of the graphical user interface: To display information from the industrial furnace production data analysis system. 7. Description of the changing states of the graphical user interface: The main view is the graphical interface displayed when the user logs in; the interface change state diagram 1 is the graphical interface displayed when the user clicks the fifth button in the upper right corner of the main view; the interface change state diagram 2 is the graphical interface displayed when the user clicks the "Production Analysis" button in the drop-down menu below the fifth button in the upper right corner of the interface change state diagram 1.