41 results about "Quality management system" patented technology

The invention discloses a full-link quality tracing method driven by batch of a process card, relates to the technical field of intelligent manufacturing and quality tracing, and aims to automatically generate a dynamic process card batch number through PDA code scanning and work reporting and realize full-process seamless association and tracing from material picking, film spraying, bag making to inspection. According to the method, a defect propagation path prediction mechanism is innovatively introduced, all associated batches are automatically locked when a certain batch is detected to be bad based on the BOM topological relation, the traditional tracing time is compressed from the hour level to the second level, and the quality problem response speed and accuracy are greatly improved. Meanwhile, the system intelligently recommends the optimal reworking path in combination with historical reworking data, the reworking time can be reduced by about 40%, and the production efficiency and the resource utilization rate are remarkably improved. According to the technology, real-time acquisition, dynamic analysis and intelligent decision support of quality data are realized, and core technical support is provided for an enterprise to construct an efficient, transparent and traceable full-link quality management system.

The invention discloses a water conservancy project construction progress and quality management system and method, and belongs to the technical field of water conservancy project construction progress and quality management, and the method comprises the steps: S1, obtaining real-time construction parameters, a design reference value and environment load data; s2, based on the real-time construction parameters and the design reference value, calculating to obtain a comprehensive construction deviation index; s3, combining the building information model data and the comprehensive construction deviation index to construct a digital twinborn model containing an initial defect; s4, based on the digital twinborn model containing the initial defect, coupling the comprehensive construction deviation index and the environmental load data, and calculating to obtain an accumulated damage factor; and S5, determining a long-term health degree score based on the accumulated damage factors, and laying an accurate mathematical foundation for subsequent full life cycle performance prediction.

The invention relates to the field of engineering management, and particularly discloses a quality management system and method for engineering construction, and the method comprises the steps: firstly carrying out the preprocessing of a BIM model, and constructing a reference frame integrating visual features and spatial geometric information; when a problem image shot by a mobile terminal at a construction site is received, a computer vision and space calculation technology is introduced, a two-dimensional field image is analyzed into an accurate pose of a shooting camera in a three-dimensional BIM space, and sight line tracing is automatically performed in a BIM digital model based on the accurate pose. And intelligently inferring and retrieving candidate components which are highly matched with the perspective of the problem. And finally, on-site unstructured problem data and the unique identifier of the BIM component are firmly bound through lightweight interaction confirmation with the user, and a standardized structured problem record is obtained. Therefore, the problems of low manual positioning efficiency and unstable association can be solved, and the whole-process intelligent closed loop of quality problem data from acquisition to structured storage is realized.

Systems and methods for improving query creation and AQM are provided. A user interface is provided that allows an analyst to generate and test queries. After the analyst provides a query, one or more subsets of previous call center interactions are selected to test the provided query using methods such as a large language model or string vectorization. Once the subsets of interactions are selected, an LLM is used to evaluate the query against the subset. The evaluations may indicate interactions which were positive and which interactions were negative and may include quotes from the interactions that support the evaluations. The evaluations are presented to the analyst for review, and the analyst may revise the query in view of the evaluations. Once the analyst is satisfied with the performance of the query, the query may be used by the LLM to perform AQM for new interactions in the call center.

The invention discloses a quality management system evaluation and authentication system based on multi-source heterogeneous data processing, and belongs to the technical field of quality management. A quality management system evaluation and authentication system based on multi-source heterogeneous data processing comprises a data acquisition module, a data preprocessing module, a data fusion module, a data analysis module, a quality management system grading model, an evaluation and authentication module and a user management and interaction module. According to the invention, the problems of single data source, need of manual acquisition of evaluation data and poor evaluation efficiency in evaluation authentication of the existing quality management system are solved. Through automatic acquisition and processing of the multi-source heterogeneous data, the comprehensiveness and accuracy of the data are remarkably improved, the labor cost is greatly reduced, the evaluation efficiency and quality are improved, and a more reliable quality management evaluation result is provided for enterprises.

The embodiment of the invention provides a quality management system authentication contract review code matching model construction and prediction method and a quality management system authentication contract review code matching model construction method. Comprising the following steps: collecting CNAS39 large-class code system data, business license operation range expression data of each industry, historical review case data and policies and regulations which are published by a supervision department and are about the consistency of an authentication range and a business license range, and constructing a professional knowledge base according to the collected data and the policies and regulations; pre-training a language model by using the professional knowledge base to obtain a pre-trained language model; and training data is constructed according to the historical review case data, the pre-training language model is finely adjusted by adjusting hyper-parameters, and a code matching model for quality management system authentication contract review is obtained.

The invention provides a quality data multi-index cross-domain NLP enhanced retrieval and computing power sharing method, which comprises the following steps of: establishing a group headquarter cross-domain quality intelligent platform as a central nervous, and configuring an intelligent retrieval service and data exchange engine basic capability unit for each hierarchical subject; secondly, the basic-level quality management system is connected to the quality intelligent service system to form hierarchical association; and finally, realizing cross-domain retrieval and computing power sharing through intelligent identification, matching functions and cross-node data transmission. According to the method, the data integration problem is solved through the quality information exchange directory, and comprehensive integration and efficient utilization of the quality data are realized; the service collaboration problem is solved through cross-domain data interaction and collaboration, and the collaboration efficiency and the product quality control precision are improved; the technical adaptation problem is solved by deploying a platform and an engine and sharing basic computing power, and stable interaction of data and deep application of the AI technology are guaranteed.

The invention discloses a construction and evaluation method for an applicant drug clinical test quality management system, and aims to solve the problems that traceable evidence chains are lacked among applicant clinical test quality system elements, evidence materials and evaluation conclusions, evaluation is difficult to quantify, and closed-loop improvement based on evaluation results is difficult. According to the method, quality system element data, evidence material data and evidence source data are obtained and standardized, and a time heterogeneous evidence graph comprising element nodes, evidence nodes, version nodes, responsibility nodes and evidence source nodes is constructed; executing graph neural network representation learning on the evidence graph to generate a relationship likelihood parameter and an evidence credibility likelihood parameter; constructing a Bayesian factor graph containing conflict factors, and executing belief propagation to obtain element compliance posterior distribution and evidence credibility posterior distribution; and further calculating a compliance score, an uncertainty score and a coverage rate score to form a three-dimensional score result, and extracting an evidence chain to generate traceable output, thereby achieving the technical effects of automatic establishment of the evidence chain, compliance quantitative evaluation, conflict evidence suppression and evaluation result driven closed-loop improvement.

The invention provides a business and quality management system, and the system comprises an acquisition monitoring module which is used for collecting quality related data in a product production process in real time, carrying out the analysis of the quality related data, and carrying out the monitoring of an abnormal event in the product production process based on an analysis result; the exception handling module is used for detecting an abnormal event under the condition that the acquisition monitoring module monitors the abnormal event, and performing exception early warning based on a detection result; the analysis and display module is used for analyzing and counting the quality related data and / or the detection result to generate a related report and displaying the report; and the quality tracking module is used for acquiring the full life cycle data of the product based on the output of the acquisition monitoring module, the exception handling module and the analysis display module so as to track the product quality. By integrating the functions of real-time monitoring, exception handling, full-life-cycle quality tracking and the like, an efficient, intelligent and comprehensive quality management system is provided for enterprises, and the product quality and the production efficiency can be improved.

A method for detecting solid content in a traditional Chinese medicine extraction quality management system is disclosed. This invention addresses the problems of existing detection methods, which not only affect extraction efficiency but also suffer from low accuracy and are prone to errors. The steps of this invention include installing two solid content detection instruments based on different principles on the extraction tank; installing a jacketed pressure gauge on the steam pipeline of the extraction tank; installing a thermometer inside the extraction tank; installing a tuning fork switch on the filter of the extraction tank; and installing a flow meter after the pump on the variable frequency delivery pump of the extraction tank. The two solid content detection instruments transmit the detected data to a central processing unit (CPU). The jacketed pressure gauge, thermometer, and flow meter transmit the collected data to the CPU. The CPU analyzes the collected data to generate a trend curve of solid content change over time. This invention belongs to the field of traditional Chinese medicine extraction technology.

The invention relates to the technical field of sponge titanium production processes, in particular to a sponge titanium production process anomaly automatic analysis and disposal method based on an MES (Manufacturing Execution System), which comprises the following steps of: firstly, integrating DCS (Distributed Control System), LIMS (Laser Information Management System) and quality management system data through the MES, and collecting key process parameters and quality data to form a complete data chain; establishing a dynamic early warning model, and combining SPC, machine learning and ARIMA models to realize abnormal real-time early warning and trend prediction; abnormal root causes are automatically analyzed by means of an AI model, a report is generated, and treatment measures are accurately pushed through a graph database knowledge base; and finally, monitoring-diagnosis-disposal-knowledge precipitation closed-loop management is formed. Advanced prevention and control of production abnormity are achieved, diagnosis accuracy and disposal efficiency are improved, repeated occurrence of quality defects and similar problems is reduced, and the intelligent level and operation efficiency of titanium sponge production are remarkably improved.

This invention presents a rapid method for detecting moisture in raw materials and fuels. Addressing the problems of low efficiency, long cycle time, large human error, and significant data feedback delays associated with existing methods using manual oven drying in centralized laboratory testing, this invention provides a systematic solution for real-time, automated moisture detection at the physical testing end. The core of this method lies in the following: after raw materials are sampled upon arrival at the plant, moisture samples and analytical samples are separated. The moisture sample is directly placed in a multi-station fully automated moisture analyzer, where weighing, drying, and calculation are automatically completed. The test results are automatically uploaded to the enterprise's quality management system in real-time via a data interface for immediate production use. Simultaneously, the analytical sample is sent to the laboratory for testing according to the original process. This invention, through a combination of equipment automation and process reconfiguration, achieves on-site, parallel, automated, and real-time moisture detection, significantly improving detection efficiency and accuracy, and providing timely and reliable data support for stable blast furnace production and cost control.

The application relates to the technical field of mold management, in particular to a mold working quality management method and a quality management system, wherein the mold working quality management method comprises the following steps: S1, adding a unique identity label to each mold, and associating relevant information corresponding to each mold to be recorded into a quality management system; S2, establishing the health life value of each mold through the relevant information of the mold, and comprehensively monitoring the mold during mold working, and updating the health life value of the corresponding mold in real time; S3, screening a plurality of matched molds according to the health life value of the mold according to a preset matching rule to perform mold forming work, so as to adjust the forming quality of the same batch of products to be within a preset range. Through the unique identity label added to the mold and the relevant information of the mold recorded and updated in real time, the digital management of the whole life cycle of the mold is realized, and the overall state, efficiency and service life of the mold are conveniently evaluated.

The invention discloses a standardized inspection method for efficient inspection of a ship, which comprises the following steps of: automatically matching a standard inspection item table and an inspection element list required by actual ship inspection of an actual ship product from a ship standard inspection knowledge base by using a quality management system, and automatically generating an inspection item data packet; the inspection item data packet is issued to the handheld terminal, an inspector inspects through the handheld terminal, information such as a three-dimensional design model, inspection items and elements of the ship product to be inspected can be looked up at any time, and meanwhile field inspection information can be written into the inspection item data packet and uploaded to the quality management and control system to be analyzed and evaluated; a traditional two-dimensional drawing inspection mode is changed, backtracking circulation and application of data are achieved, and iterative optimization of ship design and construction links is supported.

The present application belongs to the technical field of passenger car assembly tightening operation, and particularly relates to a mistake-proof tightening device and method with physical positioning; wherein an X-direction guide rail is provided with an X-direction sliding seat, the X-direction sliding seat is provided with a Y-direction linear sliding rail, the Y-direction linear sliding rail is provided with a Y-direction sliding seat, a Y-direction servo motor is fastened on the Y-direction sliding seat and cooperates with a Y-direction linear sliding rail internal gear rack through a gear; the Y-direction sliding seat is provided with a Z-direction linear sliding rail and a Z-direction jacking cylinder, and a tightening machine is matched on the Z-direction linear sliding rail through a connecting plate; an X-direction servo motor is fixed on the X-direction sliding seat and cooperates with an X-direction guide rail internal gear rack through a gear; the present application formulates a mistake-proof tightening control system architecture for a general assembly workshop with digital information collection and interconnection function, deeply researches a mistake-proof tightening control logic and a production / quality management system, builds a mistake-proof tightening digital platform, and connects various information systems to realize automatic mistake-proof tightening function under the premise of ensuring information interconnection.

The invention relates to the technical field of power equipment quality detection, and particularly discloses a power transmission line iron tower detection and quality management system. The system comprises a user authentication module, an authority management module, a detection plan management module, a sample information management module, a physical and chemical detection management module and a report generation module. Differentiated operation authorities are distributed to different user groups through an authority management module; creation, execution and state management of a detection plan are realized through a detection plan management module, and a sampling list and a detection entrance are automatically generated; complete sample data is forcibly recorded through the sample information management module so as to ensure data traceability; the detection data filling unit supports communication with external detection equipment so as to automatically collect and calculate data, supports multi-user collaborative editing and displays an editing state in real time; and finally, the report generation module automatically synthesizes various types of detection reports according to the template, so that the detection efficiency, the data accuracy and the management standardization are effectively improved.

Provided is a quality management system for an energy device that is composed of a plurality of electrode layers and an electrolyte layer, the quality management system making it possible to efficiently acquire a feature amount of an intermediate article that strongly affects the performance of the energy device without significantly reducing the operation rate of a manufacturing line in a manufacturing process of the energy device, and to manage the performance quality of the energy device at the time of shipment inspection. A quality management system for an energy device for determining the quality of an intermediate product in an energy device manufacturing process comprises: a first inspection data acquisition device that acquires first inspection data related to a material of the intermediate product; a second inspection data acquisition device that acquires second inspection data, which is a feature amount related to the intermediate product; a data storage / calculation device that calculates a performance prediction value of the energy device on the basis of correlation data that has been accumulated in the past, using the first inspection data and the second inspection data as inputs; and a data output device that outputs the first inspection data, the second inspection data, and the performance prediction value, the quality management system being characterized in that: the intermediate product is a functional sheet that functions as an electrode layer or a carrier conductive layer of the energy device, and a slurry in which a functional material, a solvent, and a binder that constitute the functional sheet are mixed; and the data storage / calculation device has a correlation database in which performance information of the energy device and manufacturing conditions and structure information of the functional sheet and the slurry are accumulated, the data storage / calculation device calculating the performance prediction value of the energy device by inputting the structure information of the intermediate product acquired from at least one of the first inspection data and the second inspection data into the correlation database, and determining the quality of the intermediate product.

The invention relates to the technical field of metal processing quality management and control, in particular to a non-ferrous metal rolling quality management system and method. The system comprises a calendaring working condition data acquisition unit used for acquiring calendaring process data and microstructure data and generating a calendaring structure data tensor; the void risk intelligent identification unit is used for constructing a void nucleation potential map and a disturbance response map, inputting the void nucleation potential map and the disturbance response map into the double-branch attention time sequence neural network model, and outputting to obtain a void risk heat map and a void risk scoring matrix; the interference fringe closed-loop regulation and control unit is used for constructing a pseudo film evolution diagram, generating a spray array response coefficient matrix and outputting the spray array response coefficient matrix to a spray cooling valve group as a control quantity; and the rolling quality grading evaluation unit constructs a multi-grade rolling quality label set and generates a rolling quality evaluation table. According to the invention, intelligent identification of the cavity risk and closed-loop quality control of the thickness of the cooling film in the metal rolling process are realized.

An RFID finished footwear quality management system includes a footwear needle detector module, configured to identify RFID tag information of each shoe or each pair of shoes, and perform metal detection to obtain a detection result and a detection time; a small package verification module, configured to read RFID tag information of a pair of shoes, tongue tag information, and inner shoe box barcode information, and bind the RFID tag information of the pair of shoes, the tongue tag information, and the inner shoe box barcode information; and a packaging box needle detector module, configured to scan an outer box code to record packaging box label information, read RFID tag information of each shoe or each pair of shoes within a packaging box.

This invention relates to the field of LED strip manufacturing technology, specifically to a method for LED strip manufacturing and quality management, and a management system using the same. The method includes the following steps: S1: Initializing the LED strip manufacturing and quality management system; S2: Evaluating the optical and electrical performance parameters of each LED bead, and outputting status information after associating the position information of each LED bead; S3: Selecting a corresponding number of matching LED beads according to preset production specifications, and outputting the LED beads sequentially according to a preset sorting order; S4: Dynamically adjusting the control parameters of each LED strip; S5: Performing a quality assessment on the LED strip. This invention enables the detection and efficient screening of large quantities of LED beads, ensuring a high degree of consistency in the optical and electrical performance parameters of the LED beads on each LED strip.

The invention relates to the technical field of quality management, and discloses an LED fluorescent material quality management system based on emission spectrum data, and the system comprises a trajectory analysis unit, a spectral analysis unit, a high temperature maintenance unit and a quality management unit. A spectral response track is generated through parameters such as a spectral intrinsic purity factor and a thermal evolution incidence matrix, the spectral drift and thermal quenching process is reduced, the spectral analysis unit carries out analysis based on the spectral response track to obtain a dynamic spectral response vector representing dynamic thermal stability, and meanwhile, the high-temperature performance maintenance index generated by the high-temperature maintenance unit is used for improving the dynamic thermal stability. The performance maintenance capability of the LED fluorescent material at a high temperature can be reflected, the instruction of the LED fluorescent material can be effectively judged through the quality management identifier generated by the quality management unit, the quality misjudgment is effectively avoided, and the quality management accuracy is improved.

The invention discloses an automobile part quality management method and device, equipment and a storage medium, and relates to the technical field of computers. The method comprises the following steps: receiving input data for performing quality management on a target automobile part based on an automobile part quality management system; calling a pre-deployed large model in the automobile part quality management system, enabling the large model to call a target analysis model based on the input data and the historical analysis data, and generating a response result based on a first analysis result of the target analysis model; the target analysis model is at least one of a plurality of analysis models pre-deployed in the automobile part quality management system; and outputting a second analysis result according with a preset format through the automobile part quality management system based on the response result of the large model. By adopting the method, the quality management efficiency of the automobile parts can be improved.

The invention discloses a product full life cycle inspection plan generation method based on quality risk prediction, and belongs to the technical field of product manufacturing quality control. The method comprises the following steps: acquiring quality risk factor data, a historical quality database and a real-time production data flow in design, manufacturing, testing and after-sales stages; constructing a dynamic quality risk prediction model based on the data by applying a machine learning algorithm, and outputting risk level data; constructing a dynamic mapping rule of the inspection frequency, the sampling scheme and the inspection strict degree according to the risk level; based on the total inspection cost constraint, the delivery cycle constraint and the available resource capacity, applying an optimization algorithm to generate a full-life-cycle optimal inspection plan; acquiring updated data in real time to trigger the model to re-output the risk level and update the inspection plan; and outputting the optimal inspection plan to a quality management system to drive resource configuration. According to the method, the technical effect of efficiently optimizing and updating the full-life-cycle inspection plan of the product in real time is achieved.

The present application relates to the technical field of metal processing quality control, in particular to a non-ferrous metal calendering quality management system and method; the system comprises: a calendering working condition data acquisition unit for acquiring calendering process data and microstructure data to generate a calendering structure data tensor; a cavity risk intelligent identification unit for constructing a cavity nucleation potential map and a disturbance response map, and inputting the cavity nucleation potential map and the disturbance response map into a double-branch attention time sequence neural network model to output a cavity risk heat map and a cavity risk score matrix; an interference stripe closed-loop regulation unit for constructing a pseudo-membrane layer evolution map, generating a spray array response coefficient matrix and outputting to a spray cooling valve group as a control quantity; and a calendering quality grading evaluation unit for constructing a multi-grade calendering quality label set and generating a calendering quality evaluation table. The present application realizes intelligent identification of cavity risk and closed-loop quality control of cooling film thickness during metal calendering.

A computer-implemented method of recording information from a quality management system digitally, e.g. using blockchain. The information retrieved from the documents is assigned a value and these val

The invention discloses a performance detection method for automobile sensor production, and relates to the technical field of sensor detection, and the method comprises the steps: reading and recognizing the type of a sensor through non-contact coding, and matching a detection template; automatic electrical connection is realized through self-adaptive clamping and visual auxiliary alignment; temperature circulation, electromagnetic interference and random vibration are synchronously applied in the temperature control cavity to form a three-field coupling stress environment; synchronously acquiring multi-channel response data at a high sampling rate, and marking and storing the multi-channel response data; performing three-dimensional comparison and abnormality diagnosis based on the standard reference model and a gradient lifting decision tree algorithm, and generating a structured report; a result is uploaded to a quality management system, a process optimization instruction is fed back, and closed-loop control is achieved. By means of the technical scheme, various sensor types can be fully automatically compatible, vehicle-mounted complex working conditions can be truly reproduced, early failure can be accurately recognized, and whole-process traceability and production line flexibility improvement are achieved.

The application discloses an AI-based multi-dimensional quality management system for inspection mode, and belongs to the technical field of inspection supervision. The system is used to solve the technical problem of poor multi-dimensional quality supervision and management effect of the inspection mode in the prior art. The system monitors and counts the inspection results of each implementation of the inspection mode, processes and classifies the inspection results of each implementation, performs inspection failure processing of abnormal inspection sets in different dimensions, obtains first inspection failure total values and second inspection failure total values corresponding to different dimensions, performs multi-dimensional quality management data processing and analysis on the first inspection failure total values and the second inspection failure total values obtained through multi-dimensional supervision processing, obtains an inspection quality value corresponding to the existing inspection mode, and optimizes the inspection content of the existing inspection mode and / or optimizes the existing inspection mode according to the analysis result of the inspection quality value.

The application provides a scientific research project quality management method, system, electronic equipment and storage medium, wherein the method comprises the following steps: acquiring a mapping relationship between quality activities in a scientific research project proposal and chapters and sections in quality management system file regulations, and determining a planned time schedule of the project quality activities; correcting the planned time schedule based on the completion time schedule of the project quality activities, the mapping relationship and the comparable completion time schedule of the quality activities of a completed project of the same type, to obtain a corrected time schedule of the project quality activities; and in response to an operation of inputting a project development cycle proportion and a stage project quality activity completion progress target value in the corrected time schedule, obtaining a quantity target value of each quality activity stage of the project, so that the quality activity law of the scientific research project can be accurately predicted, and the quality plan can be timely adjusted according to the actual working condition, and the efficiency of the scientific research project quality management is improved.

The invention relates to the technical field of underground pipeline laying of water conservancy projects, in particular to an engineering project full-life-cycle quality management system based on AI and digital twinning. The method comprises the following steps: acquiring dynamic cavity research and judgment basic information, and determining a cavity feature information set according to the dynamic cavity research and judgment basic information; initial spraying control information is obtained, based on the cavity feature information set, the spraying control information is adjusted with the purpose of suppressing the cavity expansion trend, and a basic spraying strategy is determined; based on the cavity feature information set, cavity dynamic influence features are analyzed, a current tunneling strategy is adjusted according to the cavity dynamic influence features, and a dynamic tunneling strategy is determined; based on the dynamic tunneling strategy and the cavity feature information set, cavity filling and supporting strategy analysis is conducted, a final hydraulic engineering underground pipeline laying strategy is generated and executed in combination with a basic spraying strategy, and a laying data log is output. The method effectively reduces the influence of the hole risk on the project quality, and guarantees the safety and high-efficiency promotion of the whole life cycle of the project.

This invention relates to the fields of machine vision and industrial quality inspection, specifically to an industrial product quality management system based on vision inspection, comprising: a light field modulation and acquisition unit, which controls a programmable fully polarized light source to illuminate a target object and generates a four-dimensional polarization raw data stream through a focal plane beam splitting micro-polarization array camera; a polarization space mapping unit, which converts the data stream into a polarization degree feature matrix and a polarization angle feature matrix; a polarization entropy gradient evaluation unit, which calculates the polarization angle Shannon entropy within a sliding window, generates a polarization high-entropy heatmap, and extracts polarization topological singularities by differential extraction with a baseline polarization manifold model; and a physical closed-loop and adaptive update unit, which outputs workpiece coordinates and shape classification instructions, performs physical control feedback, and extracts local Stokes vector features to update the baseline polarization manifold model.